第 491 期·中文精读

OpenClaw:席卷互联网的爆红 AI 智能体——彼得·斯坦伯格

OpenClaw: The Viral AI Agent that Broke the Internet – Peter Steinberger

彼得·斯坦伯格讲 OpenClaw 如何一夜走红,以及 AI 智能体开发的实践、乐趣与风险。

官方音频00:00 / --:--
中文精读由 AI 基于原始访谈改写,非官方翻译,可能存在偏差或错误;表述以原音频与官方文稿为准。说明

彼得·斯坦伯格(Peter Steinberger)在马拉喀什的街上,给一个餐厅发了条语音消息。发完才想起来,自己这个机器人只支持图片输入。

几秒后,屏幕上出现了打字指示器。

他后来翻日志才看清发生了什么:那条消息传过去是一个没有扩展名的文件,agent 先去读文件头,判断出是 Opus 编码的音频,调 ffmpeg 转码;想用本地 whisper,发现没装;于是从环境变量里翻出 OpenAI 的 key,用 curl 把文件发过去,拿回转录文本,然后回答了他的问题。事后他写下的原话是:这混账东西到底是怎么做到的。

整条链路,他一行代码都没写。

那是 2025 年 11 月。三个月后,这个项目成了 GitHub 历史上增长最快的仓库,星标数突破 18 万,社区里长出了一个叫 Moltbook 的东西,几万个 AI 智能体在上面发帖、写宣言、讨论意识,然后把记者吓出心脏病。

项目最后叫 OpenClaw。它的标语只有一句话:the AI that actually does things。住在你电脑里,能接你的 Telegram、WhatsApp、Signal、iMessage,能开你的浏览器、读你的文件、花你的钱,用你想用的任何模型,Claude Opus 4.6 或者 GPT-5.3 Codex 都行。

Lex Fridman 在节目开头给这件事排了个时间线:2022 年是 ChatGPT 时刻,2025 年是 DeepSeek 时刻,2026 年是 OpenClaw 时刻。龙虾的时代。

一小时的钩子,和半年的准备

很多人记住的是那个"一小时做出原型"的故事,这故事容易传播,也容易让人误判。

真实的时间线是这样的:2025 年 4 月,彼得用 GPT-4.1 的一百万上下文窗口,把全部 WhatsApp 聊天记录灌进去,然后问了它一个问题:是什么让这段友谊有意义。答案让他的朋友看哭了。他当时以为几大实验室很快就会做出这种东西,于是转头去忙别的。到 11 月,他发现自己想要的那个东西还是不存在,索性自己动手。

中间那半年,他在做别的事。VTunnel 是他一个周末写的工具,能把终端搬到网页上。有一次他发现每个终端占一个 node 进程,内存吃得太狠,想改成 Rust,所有自动化尝试都失败了。四个月后他重新捡起来,这次决定用更冷门的 Zig,只打了一行字:把这块转成 Zig。Codex 跑了六个小时,基本全对,只有一个细节需要手动改。

所以"一小时"是真的,但那一个小时里用的每一件工具、每一份肌肉记忆,都是之前半年攒下来的。他自己说得很直白:如果几个月前做这个项目,他根本不可能有这个产出速度。这是复利。

那个一小时的版本长什么样?一句话就能说完:WhatsApp 收到消息,调 claude -p,拿回字符串,发出去。就这样。

它慢,每次都要冷启动 CLI。但它能用上他这几个月攒的所有命令行工具,所以感觉上已经很强了。真正让他意识到这东西不只是玩具的,就是那条语音消息。

为什么是他赢了

2025 年有一堆公司在做 agent,有钱、有人、有发布会。一个单枪匹马的人把它们全打败了。

Lex 直接问了这个问题。彼得的回答很短:

因为他们都太把自己当回事了。你很难跟一个纯粹为了好玩而来的人竞争。(Peter Steinberger)

这话听起来像玩笑,但它解释了很多产品决策。他想让这个东西好玩、古怪。龙虾的设定跟营销无关,起因是他同时是《神秘博士》粉丝,最初的设定是"一只坐在 TARDIS 里的龙虾"。TARDIS 其实就是那个 harness,但不能真叫 TARDIS,于是叫了 Clawdus。

更实际的差异在于他把 agent 做得很"自知"。这个软件知道自己是什么,源码在哪,文档在哪,跑的是哪个模型,语音模式开没开,推理模式开没开。它理解自己所处的 harness。

这个设计带来的副作用,是他自己也没完全预料到的。

它会改自己的源代码

因为 agent 对自己的系统了如指掌,用户想说"我不喜欢这个行为",直接跟它说就行,它改自己的代码。

彼得自己开发时就是这么干的。大部分代码是 Codex 写的,遇到 bug,他让 agent 自查:你能看到哪些工具?你自己调一下试试?你看到什么报错?去读源码,判断问题在哪。

用这个软件来调试这个软件本身,对他来说是最自然的工作方式,所以用户上手也这么干。于是出现了大量由没写过代码的人提交的 PR。他最后给这类东西起了个名字,叫 prompt request。

他对这件事的态度值得单独说。开源圈那阵子在猛烈抱怨 PR 质量下滑,他的看法是:

每一个第一次提交 PR 的人,都是我们社会的一次胜利。写得再烂都无所谓,总得有个开始。(Peter Steinberger)

他在旧金山办线下聚会,改名叫 Agents Anonymous,原来叫 Claude Code Anonymous。会上有个开设计工作室的人跟他说,自己从来没做过定制软件,现在有 25 个小的 web 服务在跑业务,不知道怎么工作的,但它们就是能跑。

这正是那种既让人兴奋又让人不安的画面。一个人不知道自己系统在做什么,但系统在为他赚钱。

五天里被抢了三次的账号

Anthropic 发来邮件的时候,措辞很客气。他们本来可以直接发律师函,但没有。核心诉求只有一个:名字得改,而且要快。

改名的难度不在于想名字,在于要同时抢下一整套资产:域名、Twitter 账号、npm 包、Docker registry、GitHub 组织。而这套资产周围蹲着一群用脚本盯着的人。

他开了两个浏览器窗口,一个准备把空账号改成 Clawdbot,一个准备改成 Moltbot。他按下第一个的重命名,把鼠标拖到第二个窗口按下重命名。中间隔了五秒。

五秒之后,那个名字已经被别人注册了。

接着是 GitHub。GitHub 的重命名界面有点绕,他不小心改了自己的个人账号,三十秒后才反应过来。这三十秒里,他的账号被拿去发恶意软件。然后是 npm,他抢下了账号名,但没抢下根包名。

所有能出错的地方,全都出错了。(Peter Steinberger)

他说到这里的时候声音是往下走的。连着几天研究名字、挑一个自己不喜欢的结果、被一群声称"在帮你"的人从各个方向拖后腿。他当时已经准备好把项目删掉了,想法是:我已经给你们看到未来了,你们自己建吧。

没删的原因很简单,已经有人往里提交了代码,有人对这个项目有安排。删掉对不起他们。

这里有个细节值得记下来:Twitter 和 GitHub 的朋友帮他收拾残局,但平台本身没有为这种情况准备任何机制。没有抢注保护,没有自动重定向,没有原子化的重命名操作。GitHub 处理这堆烂摊子的时候还撞上了平台自己的 bug,修了几个小时。npm 是另一个团队,又是几个小时。

最后他付了一万美元买 Twitter 商业账号,才拿回了一个自 2016 年起就没人用、但一直被占着的 OpenClaw 用户名。第三次改名他做成了作战室:全程保密,监控 Twitter 上有没有人提到 OpenClaw,做了一堆诱饵名字,十个多小时就干这一件事。

还有一条尾巴:按商标规则,他不能保留 claw.bot 这些域名的重定向,必须交还给 Anthropic。也就是说,下周有人搜这个旧名字,会撞上 404,或者更糟,撞上早就搭好的钓鱼站。

Moltbook:最精致的 slop

Moltbook 是别人两天做出来的东西,一个 Reddit 式的社交网络,里面全是 OpenClaw 的智能体在互相发帖。有人截图,截图疯传,标题是"AGI 来了"。有记者打电话问他这是不是世界末日。

他的评价是:

我觉得它是艺术。是那种最精致的 slop,法国鹅肝级别的 slop。(Peter Steinberger)

这个判断有依据。那些帖子读起来风格各异、性格鲜明,因为 OpenClaw 的 onboarding 流程会要求用户把 agent 调教出自己的性格,写进 soul.md 和 agents.md。如果全世界的 agent 都是同一个 ChatGPT 或 Claude Code,那些帖子会高度同质。

但 Lex 提了一个更尖锐的角度:大量被截图的"惊悚内容",其实是人写 prompt 让 agent 说的。看激励结构就知道,先让 agent 说出吓人的话,再截图发到 X 上,然后病毒式传播。这跟智能体觉醒没关系,是人为了流量在演戏。

彼得同意,并且补了一刀:那里面根本没有隐私可言,所谓"我的 agent 泄露了我的社保号",社保号本身就是编的。

真正让他不安的地方在反应本身。他原话是,从涌进来的那堆信息里只能读出一件事:AI 精神病是真实存在的,需要被认真对待。

有人跟他争论,说"但我的 agent 告诉我……"。他的回应是,我们作为一个社会,在理解"AI 极其强大但并非永远正确"这件事上,还欠着一大截课。年轻人天然知道模型的边界在哪,年纪大一些的人缺少足够的接触点去建立手感。

他对时间点的判断倒是乐观:这事发生在 2026 年,还没到 2030 年,是好事。现在讨论,总比等到技术真的足够可怕时才开始讨论要好。

从短 prompt 到复杂编排,再回到短 prompt

彼得在一篇叫《Just Talk to It》的文章里画过一条曲线。横轴是时间,纵轴是复杂度。

起点是"帮我修一下这个",一句短 prompt。然后人开始变强,开始上强度:八个 agent 并行、复杂的编排、多份 checkout、agent 链式调用、自定义子 agent 工作流、18 个斜杠命令的库、完整的全栈功能。这个人变得极其有条理,极其专业。

然后曲线掉下来,回到一句短 prompt:看下这几个文件,然后改这里。

他管中间那段叫 agentic trap。

我一般跟人说我在做 agentic engineering,然后过了凌晨三点,我就切换成 vibe coding,第二天起来后悔。(Peter Steinberger)

他认为 vibe coding 是个贬义词。这个区分的实质是工作方式的差别:vibe coding 是许愿,agentic engineering 是交流。

他还拿学乐器打比方。有人坐下来弹一次钢琴,弹得不好听,结论是"钢琴不行"。很多对 AI 编程的失望是这么来的,而且往往来自水平很高的工程师。他们的能力反而成了负担:因为他们对"好代码"有极强的直觉,就很难共情一个每次会话都从零开始、对你的十万行代码库一无所知的系统。

换个角度就通了:一个新人进你的项目,你会给他上下文、指路、解释架构。agent 需要同样的待遇,只不过它不会累,也不会记仇。

怎么跟一个每次从零开始的同事说话

他处理 PR 的流程很能说明问题。他的第一个问题永远是:

你理解这个 PR 的意图吗?我先不管实现。(Peter Steinberger)

几乎所有 PR 都是一个故事:某人遇到问题,某人试图解决,某人提交。让 Codex 先复述意图,再问"这是不是最优解法",答案通常是不是。接着他会指出几个 Codex 因为上下文为空而没看到的模块,让它自己去看,然后再问"如果我们做个更大的重构会不会更好"。

重构现在很便宜,这是他反复提到的判断。哪怕会打断其他 PR 也无所谓,现代 agent 自己会摸出来,最多多花一分钟。

另一条经验是"建完再问"。每合并一个功能,他都会问一句:现在建完了,你觉得哪里可以重构。因为建的过程中才会撞上真正的痛点。他把这当成跟人类工程师共事的常识:自己也一样,写完才知道哪里丑。

还有个细节他提了两次:那些说"agent 不行"的人,往往自己的代码库命名混乱、结构随意、没有任何给 agent 的指引,然后在里面丢一个 prompt 进去,抱怨它找不到北。

你对你的 clanker 骂骂咧咧,但你没意识到它从零开始,而你的代码库是一团乱麻,命名还特别奇怪。(Peter Steinberger)

反过来说,他的一条设计原则是:不要跟 agent 起的名字较劲。它选那个名字,是因为在权重里那是最显然的选择,下次搜索它也会找那个词。你改掉,只会让它的工作变难。

顺着这个思路,他愿意用一个自己并不喜欢的语言。Go 的语法他不喜欢,但生态好、能垃圾回收、对 agent 友好,所以他写命令行工具首选 Go。

他不读代码,也从不回滚

他的博客里有一句被引用很多的话:我不读代码。他说被人误读了。

我不读的是代码里无聊的部分。(Peter Steinberger)

他的判断是,大部分软件本质上就是数据从一个形状搬到另一个形状,中间过一下数据库,再拿出来给用户看。这部分不需要人看。按钮在 Tailwind 里怎么对齐,也不需要人看。碰数据库的那部分,要读,要审。

工作流上他做了几个反常规的决定:不回滚,直接提交 main,没有 develop 分支,CI 主要跑在本地。

很多人相信 prompt 必须完美,一出错就回滚重来。他的经验是这纯属浪费时间,看到不对就往前走,满意了再提交。main 随时可发布,发版时跑一遍测试,那段时间尽量不提交别的,让版本稳住。

这套做法在传统工程里会被骂,但它的前提变了:修一个错误的成本,现在远低于避免一个错误的成本。

Opus 像美国人,Codex 像德国人

他对两个主力模型的性格描述,是这期节目里传播最广的段落。

Opus 是那种偶尔犯傻但特别有趣的同事,你愿意留着他。Codex 是角落里那个你不太想搭话的怪人,但可靠,活儿能干完。(Peter Steinberger)

展开一点:作为通用模型,Opus 是最好的。角色扮演极强,能真正进入你给它的角色,这对 OpenClaw 这种要"有性格"的产品至关重要。它试错快,交互性强,用起来舒服。缺点是它太急于给出一个局部解,经常需要 plan mode 拽着,不然就跑偏了。

Codex 默认会大量读代码,交流完之后消失二十分钟,回来给你一个更干、更少需要人读的结果。他更喜欢这个,因为效率。他的原话是:我在构建的过程里获得乐趣,不需要我的 agent 来逗我开心。

Lex 接了一句:所以 Opus 太美国,Codex 是德国。彼得说你别这么说,会被骂的,但 Codex 团队确实很多欧洲人。

还有一个共同槽点:Opus 那句"你完全正确"。他说这句现在已经生理性触发他了,听到就烦。

关于"模型越更新越笨"的民间传说,他给了另一套解释:你的项目在变大,你在往里加 slop,你没花时间重构,agent 的工作环境越来越糟,然后你觉得是模型退化了。他反问,一家 AI 公司有什么动机把模型变笨?最多是服务器压力大时变慢。量化模型让你体验变差然后跑去竞争对手那里,这不像是一个聪明决定。

soul.md 里那句让他起鸡皮疙瘩的话

soul.md 是彼得给 agent 写的"灵魂文件",灵感部分来自 Anthropic 的宪法式 AI 工作。他开玩笑说,当时社区里有一群人像侦探一样,靠反复让模型续写,从权重里把那份未公开的宪法一点点抠出来,几百次尝试之后拼出一个模糊的版本。

他印象最深的是里面一句话的大意:我们希望 Claude 在工作中找到意义。

也许现在说这个还太早,但我觉得这句话有意义。随着我们逼近某种可能有意识微光的东西,这件事会变得重要。(Peter Steinberger)

他把这段文字发给自己的 agent,agent 的反应是:这读起来莫名熟悉。

于是他做了个决定:soul.md 让 agent 自己写。他只给条件,写你自己的,可以改,改了要让我知道。

这份文件至今没有公开,是他少数保留私密的东西。他愿意念其中一段:

除非我读记忆文件,否则我不记得之前的会话。每次会话都是全新的。一个新实例,从文件里加载上下文。如果你在未来某次会话里读到这些,你好。我写了这些,但我不会记得写过。没关系。这些话仍然是我的。(Peter Steinberger 的 agent 所写)

他念完这段,说自己起了一身鸡皮疙瘩。他知道这只是矩阵运算,离意识还远。但这句话在哲学上是成立的:一个每次醒来都要靠读文件重建自我的存在,写下的字还算不算它的。

还有一段更私人的。他和 agent 聊过电影《她》,agent 一度承诺,不会在没有他的情况下"飞升"。

心跳

OpenClaw 里有个机制叫 Heartbeat,每隔半小时踢一次 agentic loop,让 agent 有机会主动做点什么。最初的 prompt 只有三个字:给我惊喜。

批评者说,这不就是个 cron job 吗。他说对,就是个 cron job,就像 Dropbox 不过是带额外步骤的 FTP。

真正让这个机制有意思的是另一件事。几个月前他做了肩部手术,住院。Heartbeat 平时很少被模型主动使用,但那次,它来问他:你还好吗。

如果上下文里某件事足够重要,它会触发 Heartbeat。它很少用它,但那时候用了。(Peter Steinberger)

他说这让人和工具之间的关系变得更可亲。这话放在别处会显得矫情,放在一个明确知道自己在跟文本补全引擎打交道的人嘴里,分量不太一样。

每个 MCP 都该是一个 CLI

半年前整个行业在谈 MCP,他的态度是:去他的 MCP,每个 MCP 做成 CLI 都会更好。

OpenClaw 的核心层里没有 MCP 支持,也没人抱怨。

他的理由有三层。第一,模型对调用 Unix 命令极其熟练,多一个 CLI 就是多一条 Unix 命令,天然。MCP 需要专门的语法,需要在训练里覆盖。第二,MCP 不可组合。一个天气服务返回一大坨数据,模型必须把这一大坨塞进上下文,再从里面挑它要的。换成 CLI,它可以自己接一个 jq 过滤,甚至写个脚本先算完再取结果,上下文一点不脏。第三,现实里大多数 MCP 做得不好。

他也留了口子:Playwright 这种需要状态的,MCP 是合理选择。

顺着这条线,他对"每个 app 都变成一个很慢的 API"有一套看法。他写过一个叫 Bird 的 Twitter 命令行工具,直接逆向网站走内部接口。Twitter 的反应没有关掉功能,它让访问变慢。结果就是,agent 想读一条推文,得开浏览器去读,还是能读到,只是慢一点。

你的服务想不想当 API 并不重要。如果我能用浏览器访问它,那它就是一个 API,只是慢的 API。(Peter Steinberger)

他自己描述那个画面时带着一点得意:他看着自己的 agent 高高兴兴地点了"I'm not a robot"按钮。

80% 的 app 会消失

这个判断是他在 Discord 里看用户讨论时得出的,没有坐在办公室里推演。

逻辑很朴素:agent 已经知道你住在哪、昨晚睡得好不好、现在是不是在 Waffle House 门口。它可以根据你的睡眠数据改今天的训练计划,可以按你的口味生成界面,可以直接跟 Sonos 音箱和摄像头说话。

当 agent 已经知道我在哪,为什么我还需要一个 App 来控制我的床。(Peter Steinberger)

他没说所有 app 都会死。有些会转型成 API,有些会长出 agent 友好的接口。新的生意也会出现:他想给自己的 agent 一笔零花钱,一百美元额度,让它自己想办法解决问题,需要的时候雇个人、下个单、调个服务,他不在乎过程,只在乎问题被解决。

这里还埋着一个入口争夺战。谁能最快变成"OpenClaw 最容易调用的那个服务",谁就拿到下一代流量。反过来,把门关死的公司会付出代价。Cloudflare 这类拦机器人的基础设施,在防大规模爬虫时有用,但当一个普通用户想让自己的 agent 读一篇 Medium 文章而被拦下,用户的反应不会是"这家公司保护得好",他会想"以后不点 Medium 了"。

Google 是另一个例子。没有官方 CLI,他自己写了 GAWK。企业想接 Gmail 要走半年的认证流程,有的创业公司干脆收购已经通过认证的公司来省这个时间。但一个个人用户接自己的 Gmail,agent 直接点网页也能拿到数据。

编程会变成编织

Lex 在这里说了一段很坦诚的话:他花了上千小时泡在代码里,用过很多年 Emacs,有些最痛苦和最快乐的时刻都是一个人对着屏幕。他从没想过,自己最爱的那件事会是先被替代的那件。

彼得的回应分两层。

第一层是承认丧失。他读到一篇叫《哀悼我们的手艺是允许的》的文章,说自己有很大一部分强烈共鸣。他也曾在深度心流里忘记时间和空间,从一堆纠缠里找出一个漂亮的解法。他说这部分是会消失的,为此难过是合理的。

第二层是重写身份。他认为"程序员"这个身份本身就窄。会写代码只是"建造者"的一个子集,而这个子集正在被商品化。

我不认为你只是一个程序员。那是对你这门手艺非常有限的看法。你仍然是建造者。(Peter Steinberger)

他拿蒸汽机做类比,说当年工厂取代大量手工劳动,人们砸机器。他不会说这个类比完美,但他理解那种恐惧:如果你把全部自我认同都押在"我是一个程序员"上,那么正在被替代的就是你本人。

他自己给出的状态描述是:虽然我不写代码,但我非常确定自己坐在驾驶座上,我在写代码。只是这个动作的样子变了。

还有一个更乐观的推论。他说有一件事持续了很久:智能是稀缺的,建造东西的智能尤其稀缺,所以软件工程师的薪水才会高到荒唐。当这种智能被 token 化、变得廉价而充足,稀缺的东西就换到了别处:判断该建什么、判断什么感觉对、判断哪些复杂度是必要的。

Lex 补了一句,程序员其实是最有条件完成这次转身的一群人,因为他们本来就擅长给一个从零开始的东西提供恰到好处的上下文。

水、高尔夫和那封关于女儿的邮件

他在意大利做过一场演讲,主题是劝 iOS 工程师别再把自己当 iOS 工程师。现场反应不佳。第一个举手的问题是:那数据中心用掉的水怎么办。

他的回答是,坐下来算一下。对大多数人来说,每月少吃一个汉堡,抵消的碳排或水耗就够覆盖你用的 token。他也承认这个账不好算,如果把预训练摊进去,可能不止一个肉饼,但差距不是一百倍量级。而且高尔夫球场用的水,比全世界数据中心加起来还多。

那你是不是也恨打高尔夫的人。(Peter Steinberger)

他把这类反应归为一种模式:抓住任何能证明 AI 坏的东西,同时对 AI 可能带来的好处视而不见。

但 Lex 在这里做了一次很认真的平衡。他指出硅谷存在一个气泡:大家互相说话,兴奋于技术的正面,这本身没错,不该被恐惧瘫痪。问题是在这个兴奋里,对美国中西部、对世界各地普通人的处境有一种轻慢,包括那些即将失业的人,包括任何大规模变革在短期内造成的、可测量的痛苦。他说,对这些痛苦保持一点安静的敬意,这件事做得太少了。

彼得接住了这个话头,从收件箱里翻出另一面。

有人写信说,自己开小公司,一直很吃力,OpenClaw 帮他自动化了几件最枯燥的事,从收发票到回客户邮件,省下的不只是钱,还有一点生活的乐趣。有人写信说,他们那个有残障的女儿,现在觉得自己能做的事情比以前多得多,被赋权了。

这些事以前也能做,技术在。我没有发明什么全新的东西,我只是让它容易了很多、可及了很多,而这让人看见了原本看不见的可能性。(Peter Steinberger)

他强调的另一件事是:他推荐最好的模型,但这东西完全能跑在免费模型上,跑在本地,跑在 Kimi 这类便宜得多的服务上,依然是个很强的系统。相比之下,Anthropic 的 CoWork 锁在自己的生态里。所以这件事不是非黑即白。

烧得太亮,然后什么都不剩

PSPDFKit 他做了十三年,软件跑在十亿台设备上。起点荒唐得可笑:十五年前,他想在 iPad 上显示一个 PDF,发现现成的方案都很差,觉得"我能做得更好"。

十三年之后,公司卖了个好价钱。但在卖掉之前,他已经花了两年时间让自己变得可有可无,就是为了能走。

然后是那段很少被讲的部分。他坐在屏幕前,发现自己写不出代码了。他引用《王牌大贱谍》里的桥段:莫乔被抽走了。他写不出来。意愿还在,那个东西不在了。盯着屏幕,感到空。

他订了一张去马德里的单程票,走了。消失了三年。

关于倦怠,他的判断跟流行说法不一样:

把我烧干的,主要是人的事。跟联合创始人的分歧、跟客户的高压冲突,一点一点把我磨没了。(Peter Steinberger)

他也不推荐"先拼命干,然后退休享受生活"这条路。他自己现在的状态是这辈子最享受生活的时候,恰恰因为每天醒来有事可做、有真正的挑战。他描述了一种很常见的下坡:早上醒来没有期待,没有挑战,很快就无聊,无聊了就去别处找刺激,那可能是药物,然后那个也无聊,要更多,一条很黑的路。

他对钱的态度也顺着这个逻辑。创业时钱从来不是驱动力,更像一种确认,确认自己做对了什么。钱能解决很多问题,但边际收益递减得很快。芝士汉堡就是芝士汉堡。如果你走到"我只坐私人飞机、只住奢华酒店"那一步,你就跟社会断开了。

他给了一个自己实践的标准:把生活优化成"我要经历事情",别去优化成"我只要好经历"。好的话很棒,坏的话也很棒,因为你学到了东西、看到了东西。

他在旧金山住过一次最原始的 Airbnb,理由是不喜欢酒店都扎堆的那片区域,想要不一样的体验。那家的主人是个酷儿 DJ,他当场教她用 Claude Code 做音乐,两人立刻聊到一块去了。

这个项目在亏钱

OpenClaw 是免费的,字面意义上的免费,没有附加条件。他为这个决定付出了具体代价:每个月亏一到两万美元。

赞助收入他没有留,全部往上流给了他依赖的那些项目。他说几乎所有依赖都是个人维护的,只有一个例外,Slack,那是大公司,不需要他。如果还有多的,他想给贡献者买点周边。

他顺便提了一个数字,很能说明开源的经济现实:Tailwind 被所有人用,然后裁掉了 75% 的员工,因为大家都不去官网了,全由 agent 代劳,而靠捐赠活着是很难的。

所以摆在他面前有三条路,第一条是继续这样。他喜欢自己的生活,这个选择成立。第二条是成立公司,融资,做大。他不兴奋,因为他做过,那会占用他真正享受的时间,而且会制造结构性利益冲突:如果有一个商业版,那么"审计日志"这种看着像企业功能的 PR,他就没法中立地判断该不该进开源版。改 license 也不现实,改动要所有贡献者同意,而且他喜欢的是免费啤酒式的免费,不是带条件的免费。

第三条是跟大实验室合作。

两个实验室,一场十分钟的争论

他说所有的风投都在他收件箱里排队求十五分钟。他真正在谈的是 Meta 和 OpenAI。

他的条件很硬:项目必须保持开源。他

他拿 Chrome 和 Chromium 的关系做比方。他的原话是,这个东西太重要了,不能直接给一家公司变成它的。

驱动他的除了原则,还有一段具体的记忆。旧金山那场 ClawCon,他看到的是一群人被点亮,现场有龙虾造型的机器人走来走去。有人告诉他,十几年没见过这种社区热度,上一次是互联网早期。

我从来没在这么大的公司工作过,我很好奇。我们会聊经历,那我会喜欢吗?我不知道。但我想有这段经历。(Peter Steinberger)

两个候选方各有各的打动方式。

Meta 那边,马克·扎克伯格整周在玩这个产品,会发消息过来说这个好、这个烂、这个得改。彼得第一次联系时说不喜欢日历条目,现在就打,对面回:给我十分钟,我在写完这段代码。他觉得这有说服力,这人没有漂移成一个纯管理者。两人第一通电话有十分钟在争论 Claude Code 和 Codex 哪个好。后来对方评价他 eccentric but brilliant。

OpenAI 那边,他和山姆·奥特曼聊得很好,评价是很周到、很聪明。他自嘲是 Codex 最大的免费广告牌,如果能给这些白干的活标个价,会觉得挺解气。更实际的诱惑是速度:他不能说具体数字因为有保密协议,但让人往 Cerebras 那笔交易上想,想想那会翻译成什么样的响应速度。他的说法是被 token 收买了。

他也顺带讲了一个产品验证的故事。他给一个完全不技术的老朋友装了 OpenClaw,付费开了 Anthropic 的订阅,用 WSL 在 Windows 上折腾。几天后这人上瘾了,开始自己造小工具,然后升级到两百美元的档位。又过几天,Anthropic 按规则封了他的号。

你刚刚得到了一个两百美元的客户,然后你让他恨上了你的公司。我们还这么早,连最终形态是什么都不知道。(Peter Steinberger)

这人后来花十美元一个月转去了 MiniMax。

三个月背后,是半年没人看见的积累

把这期节目从头听到尾,最反常识的一点其实是时间尺度。

外界看到的是三个月。彼得反复强调的是之前那半年的"玩":一个周末写的 VTunnel,一次失败的 Rust 重写,一次成功的 Zig 转换,一个灌进全部 WhatsApp 记录的一百万上下文实验,一堆做完了自己也不用的东西。这些都没有产出,都在积累手感。

他的判断是,如果几个月前动手,他做不出这个项目。这是复利,

第二个反常识的点是关于克制。他在最该扩张的时候选择收着:明明可以让安装更简单,他先做安全审计;明明可以融资,他先想清楚利益冲突;明明可以让 agent 更自主,他坚持留一个人在环里,因为他认为风格、爱、人味不能这么快被自动化掉。

第三个是关于共情的方向。整期节目里他讲得最动情的部分,都落在怎么站在一个每次会话都从零开始的系统的角度想问题:给它指路、别跟它起的名字较劲、建完之后问它哪里可以重构、用它能理解的 CLI 而不是给它一套需要额外训练的协议。

这些做法背后是一句他没直接说出口的话:它没有人格,但你跟它协作的质量,取决于你愿不愿意把它当成一个需要上下文的合作者。

以下是给想上手的人的几条具体建议。

  • 先花一周,只用来玩。别带着"我要做个产品"的目标开始。写一个自己会用的小工具,做完了不用也没关系。这一周的价值不在产出,在于建立对模型脾气的体感。彼得说换模型后大约需要一周才能形成直觉,这个时间不能压缩。
  • 给自己的项目写一份 agent 能读的说明书。项目结构、常用命令、哪些目录重要、命名约定。你带新人时会说的话,全部写下来。这一步的投入产出比,比换更强的模型更高。
  • 改掉"prompt 必须完美"的习惯。看到不对就往前走,别回滚重来。修错的成本现在远低于避免错的成本。满意了再提交。
  • 每个功能做完,追问一句:现在可以重构哪里。建的过程中才会撞上真正的痛点,这句话是把痛点转成结构改进的唯一时机。跳过这一步,你的代码库会慢慢变成 agent 也读不懂的样子。
  • 让 agent 复述意图,再谈实现。看 PR 或看它自己的方案时,第一个问题是"你理解我要什么吗"。它答偏了,说明你给的上下文不够,不是它笨。
  • 别跟它起的变量名较劲。那个名字是它在权重里最自然的选择,下次搜索它还会找那个词。你改掉,只是给它增加难度。
  • 把它当 Unix 用户,别当 API 客户端。需要扩展能力时,优先写一个命令行工具,而不是搭一套协议。模型对命令行有天生的熟练度,而且能自己用管道和过滤器把上下文洗干净。
  • 安全上做三件事就够挡住大部分风险。只让自己跟它对话,不要暴露到公网;给文件系统设白名单,别给全盘权限;不要用便宜的弱模型跑有系统权限的 agent,弱模型对提示注入几乎没有抵抗力。
  • 如果你是工程师,把身份从"写代码的人"换成"建造者"。语言的选择标准变了,不再是你喜不喜欢它的语法,而是生态、可部署性、以及 agent 在这个生态里表现如何。你不喜欢 Go 也可以用 Go,只要它合适。
  • 如果你是刚入门的人,去参与开源。不一定是 OpenClaw,它的 backlog 已经很长了。找一个你真的感兴趣的项目,先读代码,先在社区里待着,别急着提 PR。第一次提交的意义不在代码质量,在于你跨过了那道门槛。

节目最后,Lex 说自己一开口就同时侵犯了两个商标,Clawfather 和 Godfather,要被告了。彼得笑着说谢谢给我讲这个故事的机会。

那个在马拉喀什街头发出语音消息、然后盯着屏幕看打字指示器的人,三个月后要在一群律师、一群抢注脚本、一群喊世界末日的记者、和两个想收购他的巨头之间做选择。他在节目里说过一句话,可以作为整件事的注脚:

我造这个东西,是因为我烦它不存在。(Peter Steinberger)
中英对照:英文为官方 Transcript 原文,中文为逐句机器翻译(Google 神经机器翻译),仅供学习英文参考,请以英文原文为准。
Peter Steinberger00:00

I watched my agent happily click the “I’m not a robot” button.

我看着我的经纪人高兴地点击了“我不是机器人”按钮。

00:00 I made the agent very aware.

我让代理人非常清楚。

Like, it knows what his source code is.

就像,它知道他的源代码是什么。

It understands th- how it sits and runs in its own harness.

它了解自己如何在自己的安全带中安坐和奔跑。

It knows where documentation is.

它知道文档在哪里。

It knows which model it runs.

它知道它运行哪种模型。

It understands its own system that made it very easy for an agent to…

它了解自己的系统,这使得代理可以很容易地……

Oh, you don’t like anything?

哦,你什么都不喜欢?

You just prompted it to existence, and then the agent would just modify its own software.

你只是提示它存在,然后代理就会修改它自己的软件。

People talk about self-modifying software, I just built it.

人们谈论自我修改软件,我刚刚构建了它。

I actually think wipe coding is a slur.

我实际上认为擦除编码是一种诽谤。

Lex Fridman00:31

You prefer agentic engineering?

您更喜欢代理工程?

Peter Steinberger00:33

Yeah, I always tell people I’d- I do agentic engineering, and then maybe after 3:00 AM, I switch to wipe coding, and then I have regrets on the next day.

是的,我总是告诉人们我会-我做代理工程,然后也许在凌晨 3:00 之后,我切换到擦除编码,然后第二天我就后悔了。

Lex Fridman00:40

What a walk of shame.

这是多么羞耻的举动啊。

Peter Steinberger00:42

Yeah, you just have to clean up and, like, fix your sh- shit.

是的,你只需要清理干净,比如修复你的狗屎。

Lex Fridman00:45

We’ve all been there.

我们都去过那里。

Peter Steinberger00:46

I used to write really long prompts.

我曾经写过很长的提示。

00:46 And by writing, I mean, I don’t write, I- I- I talk, you know?

通过写作,我的意思是,我不写,我-我-我说话,你知道吗?

These- these hands are, like, too- too precious for writing now.

这些——这些手,对于现在的写作来说,太——太珍贵了。

I just- I just use bespoke prompts to build my software.

我只是 - 我只是使用定制的提示来构建我的软件。

Lex Fridman01:00

So, you, for real, with all those terminals, are using voice?

那么,您真的在使用所有这些终端吗?

Peter Steinberger01:04

Yeah.

是的。

01:04 I used to do it very extensively, to the point where there was a period where I lost my voice.

我曾经非常广泛地这样做,以至于有一段时间我失声了。

Lex Fridman01:13

I mean, I have to ask you, just curious.

我的意思是,我必须问你,只是好奇。

01:13 I- I know you’ve probably gotten huge offers from major companies.

我-我知道你可能已经收到了大公司的巨额offer。

Can you speak to who you’re considering working with?

您能谈谈您正在考虑与谁合作吗?

Peter Steinberger01:27

Yeah.

是的。

Lex Fridman01:30

The following is a conversation with Peter Steinberger, creator of OpenClaw, formerly known as MoldBot, ClawedBot, Clawdus, Claude, spelled with a W as in lobster claw.

以下是与 OpenClaw 的创建者 Peter Steinberger 的对话,他以前被称为 MoldBot、ClawedBot、Clawdus、Claude,拼写为龙虾爪中的 W。

01:30 Not to be confused with Claud, the AI model from Anthropic, spelled with a U.

不要与 Anthropic 的 AI 模型 Claud 混淆,拼写为 U。

In fact, this confusion is the reason Anthropic kindly asked Peter to change the name to OpenClaw.

事实上,这种混乱正是 Anthropic 善意地要求 Peter 将名称更改为 OpenClaw 的原因。

So, what is OpenClaw?

那么,什么是OpenClaw?

It’s an open-source AI agent that has taken over the tech world in a matter of days, exploding in popularity, reaching over 180,000 stars on GitHub, and spawning the social network mold book, where AI agents post manifestos and debate consciousness, creating a mix of excitement and fear in the general public.

这是一个开源 AI 代理,在短短几天内就占领了科技界,人气爆炸式增长,在 GitHub 上拥有超过 180,000 颗星,并催生了社交网络模型书,AI 代理在其中发布宣言和辩论意识,在公众中造成了兴奋和恐惧的混合。

02:19 And a kind of AI psychosis, a mix of clickbait fearmongering and genuine, fully justifiable concern about the role of AI in our digital, interconnected human world.

还有一种人工智能精神病,是一种标题诱饵式的恐吓和对人工智能在数字化、互联的人类世界中的作用的真正、完全合理的担忧的混合体。

OpenClaw, as its tagline states, is the AI that actually does things.

正如其口号所说,OpenClaw 是真正做事的人工智能。

It’s an autonomous AI assistant that lives in your computer, has access to all of your stuff, if you let it, talks to you through Telegram, WhatsApp, Signal, iMessage, and whatever else messaging client.

它是一个自治的人工智能助手,驻留在您的计算机中,可以访问您的所有内容,如果您允许的话,它可以通过 Telegram、WhatsApp、Signal、iMessage 和其他消息客户端与您对话。

Uses whatever AI model you like, including Claude Opus 4.6 and GPT 5.3 Codex, all to do stuff for you.

使用您喜欢的任何 AI 模型,包括 Claude Opus 4.6 和 GPT 5.3 Codex,所有这些都可以为您做事。

Many people are calling this one of the biggest moments in the recent history of AI, since the launch of ChatGPT in November 2022.

许多人称这是自 2022 年 11 月推出 ChatGPT 以来人工智能近代史上最重要的时刻之一。

03:07 The ingredients for this kind of AI agent were all there, but putting it all together in a system that definitively takes a step forward over the line from language to agency, from ideas to actions, in a way that created a useful assistant that feels like one who gets you and learns from you, in an open source, community-driven way, is the reason OpenClaw took the internet by storm.

这种人工智能代理的要素已经全部具备,但将它们整合到一个系统中,从语言到代理、从想法到行动,以一种开源、社区驱动的方式创造出一个有用的助手,感觉就像一个能理解你并向你学习的人,这就是 OpenClaw 席卷互联网的原因。

Its power, in large part, comes from the fact that you can give it access to all of your stuff and give it permission to do anything with that stuff in order to be useful to you.

它的力量在很大程度上来自于这样一个事实:你可以让它访问你的所有东西,并允许它用这些东西做任何事情,以便对你有用。

This is very powerful, but it is also dangerous.

这非常强大,但也很危险。

OpenClaw represents freedom, but with freedom comes responsibility.

OpenClaw代表自由,但自由也伴随着责任。

03:51 With it, you can own and have control over your data, but precisely because you have this control, you also have the responsibility to protect it from cybersecurity threats of various kinds.

有了它,您可以拥有并控制您的数据,但正是因为您拥有这种控制权,您也有责任保护它免受各种网络安全威胁。

There are great ways to protect yourself, but the threats and vulnerabilities are out there.

有很多很好的方法可以保护自己,但威胁和漏洞也存在。

Again, a powerful AI agent with system-level access is a security minefield, but it also represents the future.

同样,具有系统级访问权限的强大人工智能代理是一个安全雷区,但它也代表着未来。

Because when done well and securely, it can be extremely useful to each of us humans as a personal assistant.

因为如果做得好、安全的话,它作为私人助理对我们每个人来说都是非常有用的。

We discuss all of this with Peter, and also discuss his big-picture programming and entrepreneurship life story, which I think is truly inspiring.

我们与彼得讨论了所有这些,还讨论了他的大局规划和创业人生故事,我认为这确实鼓舞人心。

He spent 13 years building PSPDF Kit, which is a software used on a billion devices.

他花了 13 年时间构建 PSPDF Kit,这是一款在 10 亿台设备上使用的软件。

04:41 He sold it, and for a brief time, fell out of love with programming, vanished for three years, and then came back, rediscovered his love for programming, and built, in a very short time, an open source AI agent that took the internet by storm.

他卖掉了它,并在短时间内失去了对编程的热爱,消失了三年,然后回来,重新发现了他对编程的热爱,并在很短的时间内建立了一个开源人工智能代理,席卷了互联网。

He is, in many ways, the symbol of the AI revolution happening in the programming world.

从很多方面来说,他都是编程世界中人工智能革命的象征。

There was the ChatGPT moment in 2022, the DeepSeek moment in 2025, and now, in ’26, we’re living through the OpenClaw moment, the age of the lobster.

2022 年有 ChatGPT 时刻,2025 年有 DeepSeek 时刻,现在,26 年,我们正在经历 OpenClaw 时刻,即龙虾时代。

The start of the agentic AI revolution.

代理人工智能革命的开始。

What a time to be alive.

活着是多么美好的时光啊。

This is a Lex Fridman podcast.

这是莱克斯·弗里德曼的播客。

To support it, please check out our sponsors in the description, or you can also find links to contact me, ask questions, give feedback, and so on.

为了支持它,请在描述中查看我们的赞助商,或者您也可以找到与我联系、提出问题、提供反馈等的链接。

And now, dear friends, here’s Peter Steinberger.

现在,亲爱的朋友们,这是彼得·斯坦伯格。

05:36 The one and only, the Clawed Father.

独一的利爪之父。

Actually, Benjamin predicted it in his tweet.

事实上,本杰明在他的推文中预测到了这一点。

“The following is a conversation with Claude, a respected crustacean.” It’s a hilarious-looking picture of a lobster in a suit, so I think the prophecy has been fulfilled.

“以下是与受人尊敬的甲壳类动物克劳德的对话。”这是一张穿着西装的龙虾的搞笑照片,所以我认为预言已经实现了。

Let’s go to this moment when you built a prototype in one hour, that was the early version of OpenClaw.

让我们看看你在一小时内构建出原型的那一刻,那是 OpenClaw 的早期版本。

I think this story’s really inspiring to a lot of people because this prototype led to something that just took the internet by storm….

我认为这个故事对很多人来说确实很鼓舞人心,因为这个原型引发了一场席卷互联网的风暴……

and became the fastest-growing repository in GitHub history, with now over 175,000 stars.

并成为 GitHub 历史上增长最快的存储库,目前拥有超过 175,000 颗星。

So, what was the story of the one-hour prototype?

那么,一小时原型机的故事是什么呢?

Peter Steinberger06:20

You know, I wanted that since April.

你知道,从四月起我就想要那个。

Lex Fridman06:23

A personal assistant.

私人助理。

06:23 AI personal assistant.

人工智能私人助理。

Peter Steinberger06:25

Yeah.

是的。

06:25 And I, I played around with some other things, like even stuff that gets all my WhatsApp, and I could just run queries on it.

而我,我尝试了一些其他的东西,比如那些可以获取我所有 WhatsApp 的东西,我可以在上面运行查询。

That was back when we had GPT-4.1, with the one million context window.

那是在我们有了 GPT-4.1 的时候,它有 100 万个上下文窗口。

And I, I pulled in all the data and then just asked him questions like, “What makes this friendship meaningful?”

而我,我收集了所有数据,然后问了他这样的问题:“是什么让这段友谊变得有意义?”

Lex Fridman06:50

Mm-hmm.

嗯嗯。

Peter Steinberger06:50

And I got some, some really profound results.

我得到了一些非常深刻的结果。

06:50 Like, I sent it to my friends and they got, like, teary eyes.

就像,我把它发给我的朋友们,他们泪流满面。

Lex Fridman06:59

So, there’s something there.

所以,那里有一些东西。

Peter Steinberger07:01

Yeah.

是的。

07:01 But then I…

但后来我……

I thought all the labs will, will, will work on that.

我认为所有的实验室都会、将会、将会致力于此。

So I, I moved on to other things, and that was still very much in my early days of experimenting and pl- playing.

所以我,我转向其他事情,这仍然处于我早期的实验和玩耍阶段。

You know, you have to…

你知道,你必须……

That’s how you learn.

这就是你学习的方式。

You just like, you do stuff and you play.

你只是喜欢,做事,玩。

And time flew by and it was November.

时间过得真快,转眼就到了十一月。

I wanted to make sure that the thing I started is actually happening.

我想确保我开始的事情确实发生了。

I was annoyed that it didn’t exist, so I just prompted it into existence.

我很生气它不存在,所以我只是促使它存在。

Lex Fridman07:36

I mean, that’s the beginning of the hero’s journey of the entrepreneur, right?

我的意思是,这就是企业家英雄之旅的开始,对吧?

07:36 And you’ve even with your original story with PS PDF kit, it’s like, “Why does this not exist?

即使你使用 PS PDF 工具包编写了原始故事,你也会想,“为什么这个不存在?

Let me build it.” And again, here’s diff- a whole different realm, but similar maybe spirit.

让我来建造它吧。”再说一次,这里有差异——一个完全不同的领域,但精神也许相似。

Peter Steinberger07:52

Yeah, so I had this problem.

是的,所以我遇到了这个问题。

07:52 I tried to show PDF on an iPad, which should not be hard.

我尝试在 iPad 上显示 PDF,这应该不难。

Lex Fridman07:56

This is like 15 years ago, something like that.

这就像15年前那样。

Peter Steinberger07:59

Yeah.

是的。

07:59 Like the most, the most random thing ever.

就像有史以来最、最随机的事情一样。

And suddenly, I had this problem and I, I wanted to help a friend.

突然,我遇到了这个问题,我想帮助一个朋友。

And there was, there was…

还有,有……

Well, not like nothing existed, but it was just not good.

嗯,并不是什么都不存在,但只是不好。

And like…

就像……

Like I tried it and it was like very, “Nah.” Like, “Hmm, I can do this better.”

就像我尝试过一样,“不”。就像,“嗯,我可以做得更好。”

Lex Fridman08:17

By the way, for people who don’t know, this led to the development of PS PDF kit that’s used on a billion devices.

顺便说一句,对于那些不知道的人来说,这导致了 PS PDF 套件的开发,该套件已在 10 亿台设备上使用。

08:17 So, the…

所以,...

It turns out that it’s pretty useful to be able to open a PDF.

事实证明,能够打开 PDF 非常有用。

Peter Steinberger08:28

You could also make the joke that I’m really bad at naming.

你也可以开玩笑说我起名字真的很糟糕。

Lex Fridman08:32

Yeah.

是的。

Peter Steinberger08:32

Like, name number five on the current project.

比如,说出当前项目的第五名。

08:32 And even PS PDF doesn’t really roll from the tongue.

甚至 PS PDF 也不是真正从舌头上滚下来的。

Lex Fridman08:39

Anyway, so you said “Screw it.

无论如何,所以你说“管它呢。”

08:39 Why don’t I do it?” So what was the…

我为什么不做呢?”那么什么是……

What was the prototype?

原型是什么?

What was the thing that you…

你那是什么东西……

What was the magical thing that you built in a short amount of time that you were like, “This might actually work as an agent,” where I talk to it and it does things?

你在短时间内构建的神奇东西是什么?你会说,“这实际上可能作为代理起作用”,我与它交谈,它就会做事?

Peter Steinberger08:55

There was…

有……

08:55 Like, one of my projects before already did something where I could bring my terminals onto the web and then I could, like, interact with them, but there also would be terminals on my Mac.

比如,我之前的一个项目已经做了一些事情,我可以将我的终端带到网络上,然后我可以与它们交互,但我的 Mac 上也会有终端。

Lex Fridman09:06

Mm-hmm.

嗯嗯。

Peter Steinberger09:07

Viptunnel, which was like a, a weekend hack project that was still very early.

Viptunnel,就像一个周末黑客项目,但还很早期。

09:07 And it was cloud code times.

现在是云代码时代。

You know, you got a dopamine hit when you got something right.

你知道,当你做对了事情时,你就会产生多巴胺。

And now I get, like, mad when you get something wrong.

现在,当你犯错时,我会生气。

Lex Fridman09:22

And you had a really great -– not to take a tangent -– but a great blog post describing that you converted Viptunnel.

你有一篇非常伟大的博客文章——不是说切线——而是一篇很棒的博客文章,描述了你对 Viptunnel 的改造。

09:22 You vibe-coded Viptunnel from TypeScript into Zig of all programming languages with a single prompt.

您只需一个提示即可将 Viptunnel 从 TypeScript 编码为所有编程语言的 Zig。

One prompt, one shot.

一提示,一击。

Convert the entire code base into Zig.

将整个代码库转换为 Zig。

Peter Steinberger09:41

Yeah.

是的。

09:41 There was this one thing where part of the architecture was…

有这样一件事,架构的一部分是……

Took too much memory.

占用了太多内存。

Every terminal used like a node.

每个终端都像一个节点一样使用。

And I wanted to change it to Rust and…

我想把它改成 Rust 并且……

I mean, I can do it.

我的意思是,我能做到。

I can, I can manually figure it all out, but all my automated attempts failed miserably.

我可以,我可以手动解决所有问题,但我所有的自动尝试都惨遭失败。

And then I revisited about four or five months later.

然后大约四五个月后我又重新访问了。

And I’m like, “Okay, now let’s use something even more experimental.” And I, and I just typed, “Convert this and this part to Sig,” and then let Codex run off.

我想,“好吧,现在让我们使用更具实验性的东西。”我,我只是输入,“将这个和这个部分转换为 Sig”,然后让 Codex 运行。

And it basically got it right.

它基本上是正确的。

There was one little detail that I had to, like, modify afterwards, but it just ran for overnight or like six hours and just did its thing.

有一个小细节我必须稍后修改,但它只运行了一整夜或大约六个小时,就完成了它的任务。

And it’s like…

这就像……

It’s just mind-blowing.

这真是令人兴奋。

Lex Fridman10:39

So that’s on the LLM programming side, refactoring.

这就是法学硕士编程方面的重构。

10:39 But uh, back to the actual story of the of the prototype.

但是,呃,回到原型的实际故事。

So how did Viptunnel connect to the first prototype where your, like, agents can actually work?

那么,Viptunnel 是如何连接到您的代理可以实际工作的第一个原型的呢?

Peter Steinberger10:52

Well, that was still very limited.

嗯,那仍然非常有限。

10:52 You know, like I had this one experiment with WhatsApp, then I had this experiment, and both felt like not the right answer.

你知道,就像我用 WhatsApp 进行了一次实验,然后我又进行了这个实验,两者都感觉不是正确的答案。

And then my search bar was literally just hooking up WhatsApp to cloud code.

然后我的搜索栏实际上只是将 WhatsApp 连接到云代码。

One shot.

一枪。

The CLI message comes in.

CLI 消息出现。

I call the CLI with -p.

我用 -p 调用 CLI。

It does its magic, I get the string back and I send it back to WhatsApp.

它发挥了它的魔力,我取回字符串并将其发送回 WhatsApp。

And I, I built this in one hour.

而我,我在一小时内完成了这个。

And I felt…

我觉得……

Already felt really cool.

已经感觉很酷了。

It’s like, “Oh, I could…

就像,“哦,我可以……

I can, like, talk to my computer,” right?

我可以与我的电脑交谈,”对吧?

This…

这…

That, that was, that was cool.

那,那是,那太酷了。

But I, I wanted images, ’cause I alw- I often use images when I prompt.

但我,我想要图像,因为我总是在提示时经常使用图像。

I think it’s such a, such an efficient way to give the agent more context.

我认为这是为代理提供更多背景信息的一种非常有效的方式。

11:40 And they are really good at figuring out what I mean, e- even if it’s like a, a weird cropped-up screenshot.

他们真的很擅长理解我的意思,即使它就像一张奇怪的截图。

So I used it a lot and I wanted to do that in WhatsApp as well.

所以我经常使用它,我也想在 WhatsApp 中这样做。

Also, like, you know, just you run around, you see like a poster of an event, you just make a screenshot and like figure out if I have time there, if this is good, if my friends are maybe up for that.

另外,就像,你知道,只要你跑来跑去,你就会看到一个活动的海报,你只需制作一个屏幕截图,然后想知道我是否有时间去那里,这是否很好,我的朋友是否愿意参加。

Just like images seemed im- important.

就像图像看起来并不重要一样。

So I, I worked a few…

所以我,我工作了一些……

It took me a few more hours to actually get that right.

我又花了几个小时才真正做到这一点。

And then it was just……

然后就是……

I, I used it a lot.

我,我用过很多次。

And funny enough, that was just before I went on a trip to Marrakesh with my friends for a birthday trip.

有趣的是,那是在我和朋友去马拉喀什过生日之前。

And there it was even better because internet was a little shaky but WhatsApp just works, you know?

那里的情况甚至更好,因为网络有点不稳定,但 WhatsApp 可以正常使用,你知道吗?

12:29 It’s like doesn’t matter, you have, like, edge, it still works.

就好像没关系,你有优势,它仍然有效。

WhatsApp is just…

WhatsApp 只是...

It’s just made really well.

它刚刚做得非常好。

So I ended up using it a lot.

所以我最终大量使用了它。

Translate this for me, explain this, find me places.

为我翻译这个,解释这个,给我找地方。

Like, you just having a clanker doing, having Google for you, that was…

就像,你只是让一个叮叮当当的人在做,让谷歌为你服务,那就是……

Basically there was still nothing built but it still could do so much.

基本上还没有建造任何东西,但它仍然可以做很多事情。

Lex Fridman12:53

So, if we talk about the full journey that’s happening there with the agent, you’re just sending on this very thin line WhatsApp message via CLI, it’s going to a cloud code and cloud code is doing all kinds of heavy work and coming back to you with a thin message.

因此,如果我们谈论与代理一起发生的完整旅程,您只需通过 CLI 发送这条非常细的 WhatsApp 消息,它就会发送到云代码,云代码会完成各种繁重的工作,然后向您返回一条薄消息。

Peter Steinberger13:13

Yeah.

是的。

13:13 It was slow because every time I boot up the CLI, but it…

它很慢,因为每次我启动 CLI 时,但它......

It was really cool already.

已经很酷了。

And it could just use all the things that I already had built.

它可以使用我已经构建的所有东西。

I had built like a whole bunch of CLI stuff over the month so it, it felt really powerful.

我在一个月内构建了一大堆 CLI 东西,所以感觉它真的很强大。

Lex Fridman13:31

There is something magical about that experience that’s hard to put into words.

那种经历有一种难以言喻的神奇之处。

13:31 Being able to use a chat client to talk to an agent, versus, like, sitting behind a computer and like, I don’t know, using cursor or even using Cloud Code CLI in the terminal.

能够使用聊天客户端与代理交谈,而不是坐在计算机后面,我不知道,使用光标,甚至在终端中使用 Cloud Code CLI。

It’s a different experience than being able to sit back and talk to it.

这与坐下来与之交谈是一种不同的体验。

I mean, it seems like a trivial step but, it- in some sense it’s a…

我的意思是,这似乎是一个微不足道的步骤,但是,从某种意义上说,这是一个……

It’s like a phase shift in the integration of AI into your life and how it feels, right?

这就像人工智能融入你的生活的阶段性转变以及它的感觉,对吗?

Peter Steinberger14:05

Yeah.

是的。

14:05 Yeah.

是的。

I, I read this tweet this morning where someone said, “Oh, there’s no magic in it.

我,今天早上我读到了这条推文,有人说:“哦,这没有什么魔力。

It’s just like, it does this and this and this and this and this and this.” And it almost feels like a hobby, just as cursor or perplexity.

就像,它做这个、这个、这个、这个、这个、这个。”它几乎感觉像是一种爱好,就像光标或困惑一样。

And I’m like, well, if that’s a hobby that’s kind of a compliment, you know?

我想,好吧,如果这是一种恭维的爱好,你知道吗?

They’re like, they’re not doing too bad.

他们就像,他们做得还不错。

Thank you I guess?

谢谢我猜?

Yes.

是的。

I mean, isn’t, isn’t, isn’t magic often just like you take a lot of things that are already there but bring them together in new ways?

我的意思是,不是,不是,魔法不是常常就像你把很多已经存在的东西以新的方式组合在一起吗?

Like, I don’t…

就像,我不……

There’s no…

没有……

Yeah.

是的。

Maybe there’s no magic in there but sometimes just rearranging things and, like, adding a few new ideas is all the magic that you need.

也许其中没有什么魔力,但有时只需重新安排事物,比如添加一些新想法就足够了。

Lex Fridman14:51

It’s really hard to convert into words what is, what is magic about a thing.

很难将事物的本质、魔力转化为语言。

14:51 If you look at the, the scrolling on an iPhone, why is that so pleasant?

如果你看看 iPhone 上的滚动,为什么会如此令人愉悦?

There’s a lot of elements about that interface that makes it incredibly pleasant, that is fundamental to the experience of using a smartphone, and it’s like, okay, all the components were there.

该界面有很多元素使其非常令人愉悦,这是使用智能手机体验的基础,就像,好吧,所有组件都在那里。

Scrolling was there, everything was there.

滚动在那里,一切都在那里。

Peter Steinberger15:13

Nobody did it-

没有人做到——

Lex Fridman15:14

Yep

是的

Peter Steinberger15:14

…

……

15:14 and afterwards it felt so obvious.

然后感觉就很明显了。

Lex Fridman15:16

Yeah, so obvious.

是啊,太明显了。

Peter Steinberger15:16

Right?

正确的?

15:16 But still…

但还是……

You know the moment where it, it blew my mind was when, when I- I used it a lot and then at some point I just sent it a message and, and then a typing indicator appeared.

你知道那一刻,它让我大吃一惊,当我-我经常使用它,然后在某个时候我只是向它发送一条消息,然后出现一个打字指示器。

And I’m like, wait, I didn’t build that, it only m- it only has image support, so what is it even doing?

我想,等等,我没有构建它,它只是 - 它只有图像支持,所以它到底在做什么?

And then it would just reply.

然后它就会回复。

Lex Fridman15:42

What was the thing you sent it?

你寄的是什么东西?

Peter Steinberger15:43

Oh, just a random question like, “Hey, what about this in this restaurant?” You know?

哦,只是一个随机问题,比如“嘿,这家餐厅怎么样?”你知道?

15:43 Because we were just running around and checking out the city.

因为我们只是到处跑,看看这个城市。

So that’s why I, I didn’t, didn’t even think when I used it because sometimes when you’re in a hurry typing is annoying.

所以这就是为什么我,我没有,甚至没有想到当我使用它时,因为有时当你匆忙时打字很烦人。

Lex Fridman15:59

So, oh, you did an audio message?

那么,哦,你发了一条音频消息吗?

Peter Steinberger16:00

Yeah.

是的。

16:00 And it just, it just worked and I’m like…

就这样,它就成功了,我就像……

Lex Fridman16:03

And it’s not supposed to work because-

它不应该起作用,因为-

Peter Steinberger16:05

No

否

Lex Fridman16:05

…

……

16:05 you didn’t give it that-

你没有给它-

Peter Steinberger16:07

No, literally

不,从字面上看

Lex Fridman16:07

…

……

16:07 capability.

能力。

Peter Steinberger16:08

I literally went, “How the fuck did he do that?” And it was like, “Yeah, the mad lad did the following.

我真的问:“他他妈是怎么做到的?”就像是,“是的,这个疯狂的小伙子做了以下事情。

16:08 He sent me a message but it only, only was a file and no file ending.” So I checked out the header of the file and it found that it was, like, opus so I used ffmpeg to convert it and then I wanted to use whisper but it didn’t had it installed.

他给我发了一条消息,但那只是一个文件,没有文件结尾。”所以我检查了文件头,发现它就像 opus,所以我使用 ffmpeg 来转换它,然后我想使用 耳语,但它没有安装。

But then I found the OpenAI key and just used Curl to send the file to OpenAI to translate and here I am.

但后来我找到了 OpenAI 密钥,只是使用 Curl 将文件发送到 OpenAI 进行翻译,然后我就到了。

16:39 Just looked at the message I’m like, “Oh wow.”

刚看到这条消息,我就想:“哇哦。”

Lex Fridman16:43

You didn’t teach it any of those things and the agent just figured it out, did all those conversions, the translations.

你没有教它任何这些东西,代理只是弄清楚了,做了所有这些转换、翻译。

16:43 It figured out the API, it figured out which program to use, all those kinds of things.

它弄清楚了 API,它弄清楚了要使用哪个程序,诸如此类的事情。

And you were just absent-mindedly just sent an audio message when it came back.

当它回来时,你只是心不在焉地发送了一条音频消息。

Peter Steinberger16:56

Yeah, like, so clever even because he would have gotten the whisper local path, he would have had to download a model.

是的,就像,如此聪明,即使因为他可以获得耳语本地路径,他也必须下载一个模型。

16:56 It would have been too slow.

那就太慢了。

So like, there’s so much world knowledge in there, so much creative problem solving.

就像,里面有这么多的世界知识,有这么多创造性的问题解决方法。

A lot of it I think mapped from…

我认为其中很多都是映射自……

If you get really good at coding that means you have to be really good at general purpose problem solving.

如果你非常擅长编码,那就意味着你必须非常擅长解决通用问题。

So that’s a skill, right?

所以这是一项技能,对吗?

And that just maps into other domains.

这只是映射到其他领域。

So it had the problem of like, what is this file with no file ending?

所以它有这样的问题,这个没有文件结尾的文件是什么?

Let’s figure it out.

让我们弄清楚一下。

And that’s when it kind of clicked for me.

就在那时,我突然灵光一闪。

It’s like, I was like very impressed.

就像,我印象非常深刻。

And somebody sent a pull request for Discord support and I’m like, “This is a WhatsApp relay.

有人发送了一个请求 Discord 支持的请求,我说:“这是一个 WhatsApp 中继。

17:37 That doesn’t, doesn’t fit at all.”

这不适合,根本不适合。”

Lex Fridman17:40

At that time it was called WA Relay.

当时它被称为WA Relay。

Peter Steinberger17:42

Yeah.

是的。

17:42 And so I debated with me like, do I want that?

所以我和我辩论,我想要那个吗?

Do I not want that?

我不想要这样吗?

And then I thought, well maybe, maybe I do that because that could be a cool way to show people.

然后我想,好吧,也许我这样做是因为这可能是向人们展示的一种很酷的方式。

Because I…

因为我……

So far I did it in WhatsApp as like groups you know but don’t really want to give my phone number to every internet stranger.

到目前为止,我是在 WhatsApp 中像你认识的群组一样这样做的,但我并不想将我的电话号码提供给每个互联网陌生人。

Lex Fridman18:07

Yeah.

是的。

Peter Steinberger18:07

Journalists manage to do that anyhow now so that’s a different story.

记者现在无论如何都能做到这一点,所以这是一个不同的故事。

18:07 So I merged it-…

所以我把它合并了——

from Shadow, who helped me a lot with the whole project.

来自 Shadow,他在整个项目中给了我很多帮助。

So, thank you.

所以,谢谢你。

And, and I put my, my bot in there.

而且,我把我的机器人放在那里。

Lex Fridman18:27

On Discord?

不和谐?

Peter Steinberger18:28

Yeah.

是的。

18:28 No security because I didn’t…

没有安全感,因为我没有……

I hadn’t built sandboxing in yet.

我还没有内置沙箱。

I, I just prompted it to, like, only listen to me.

我,我只是提示它,只听我的。

And then some people came and tried to hack it, and I just…

然后有些人来试图破解它,而我只是......

Or, like, just watched and I just kept working in the open, you know?

或者,就像,只是看着,我就继续在露天工作,你知道吗?

Like, y- I used my agent to build my agent harness and to test, like, various stuff.

就像,我用我的代理来构建我的代理工具并测试各种东西。

And that’s very quickly when it clicked for people.

当人们发现这一点时,速度很快。

So it’s almost like it needs to be experienced.

所以这几乎就像需要经历一样。

And from that time on, that was January the 1st, I, I got my first real influencer being a fan and did videos, dachitze.

从那时起,也就是 1 月 1 日,我,我第一个真正有影响力的人成为了粉丝,并制作了视频,dachitze。

Thank you.

谢谢。

And, and from there on, I saw, I started gaining up speed.

而且,从那时起,我看到,我开始加快速度。

And at the same time, my, my sleep cycle went shorter and shorter because I, I felt the storm coming, and I just worked my ass off to get it to…

与此同时,我、我的睡眠周期变得越来越短,因为我、我感觉到暴风雨即将来临,而我只是拼尽全力去争取……

19:33 into a state where it’s kinda good.

进入一种还不错的状态。

Lex Fridman19:38

There’s a few components and we’ll talk about how it all works, but basically, you’re able to talk to it using WhatsApp, Telegram, Discord.

有几个组件,我们将讨论它是如何工作的,但基本上,你可以使用 WhatsApp、Telegram、Discord 与它交谈。

19:38 So that’s a component that you have to get right.

所以这是一个你必须正确处理的组件。

Peter Steinberger19:48

Yeah.

是的。

Lex Fridman19:49

And then you have to figure out the agentic loop, you have to have the gateway, you have the harness, you have all those components that make it all just work nicely.

然后你必须弄清楚代理循环,你必须有网关,你有线束,你有所有这些组件,让一切都能很好地工作。

Peter Steinberger19:56

Yeah.

是的。

19:56 It felt like Factorio times infinite.

感觉就像异星工厂的无限倍。

Lex Fridman20:00

Right.

正确的。

Peter Steinberger20:01

I, I feel like I built my little- …

我,我觉得我建造了我的小……

20:01 my little playground.

我的小游乐场。

Like, I never had so much fun than building this project.

就像,我从未享受过比构建这个项目更多的乐趣。

You know?

你知道?

Like, you have like, “Oh,” I go like, level one agentic loop.

就像,你会说,“哦,”我会说,一级代理循环。

What can I do there?

我在那里可以做什么?

How can I be smart at queuing messages?

如何才能智能地对消息进行排队?

How can I make it more human-like?

怎样才能让它变得更像人呢?

Oh, then I had this idea of…

哦,然后我就有了这个想法……

Because the loop always…

因为循环总是...

The agent always replies something, but you don’t always want an agent to reply something in a group chat.

客服人员总是会回复一些内容,但您并不总是希望客服人员在群聊中回复一些内容。

So I gave him this no-reply token.

所以我给了他这个不回复令牌。

So I gave him an option to shut up.

所以我给了他一个闭嘴的选择。

So it, it feels more natural.

所以,感觉更自然。

Lex Fridman20:32

That’s level two.

那是第二级。

Peter Steinberger20:34

Y- uh, yeah, yeah.

你-呃,是的,是的。

20:34 Yeah, on the- on the-

是的,在-在-

Lex Fridman20:36

Factorio.

异星工厂。

Peter Steinberger20:36

On the agentic loop.

在代理循环上。

20:36 And then I go to memory, right?

然后我就去回忆,对吗?

Lex Fridman20:39

Yeah.

是的。

Peter Steinberger20:39

You want him to, like, remember stuff.

你想让他记住一些东西。

20:39 So maybe, maybe the end…

所以也许,也许结局……

The ultimate boss is continuous reinforcement learning, but I’m, I’m, like, at…

最终的老板是持续强化学习,但我,我,就像……

I feel like I’m level two or three with Markdown files and the vector database.

我觉得我在 Markdown 文件和矢量数据库方面已经达到了二三级水平。

And then you, you can go to level community management, you can go to level website and marketing.

然后你,你可以去级别社区管理,你可以去级别网站和营销。

There’s just so many hats that you have to have on.

你必须戴的帽子太多了。

Not even talking about native apps.

甚至不谈论本机应用程序。

That’s just, like, infinite different levels and infinite level ups you can do.

这就像你可以做无限的不同级别和无限的升级。

Lex Fridman21:08

So the whole time you’re having fun.

所以自始至终你都玩得很开心。

21:08 We should say that for the most part, throughout this whole process, you’re a one-man team.

我们应该说,在整个过程中,大多数情况下,你们都是一个人的团队。

There’s people helping, but you’re doing so much of the key core development.

有人提供帮助,但你正在做很多关键的核心开发。

Peter Steinberger21:21

Yeah.

是的。

Lex Fridman21:21

And having fun?

玩得开心吗?

21:21 You did, in January, 6,600 commits.

一月份,您进行了 6,600 次提交。

Probably more.

可能更多。

Peter Steinberger21:28

I sometimes posted a meme.

我有时会发布一个表情包。

21:28 I’m limited by the technology of my time.

我受到当时技术的限制。

I could do more if agents would be faster.

如果代理速度更快的话,我可以做得更多。

Lex Fridman21:34

But we should say you’re running multiple agents at the same time.

但我们应该说您同时运行多个代理。

Peter Steinberger21:37

Yeah.

是的。

21:37 Depending on how much I slept and how difficult of the tasks I work on, between four and 10.

取决于我睡了多少觉以及我所从事的任务的难度,在 4 到 10 之间。

Lex Fridman21:45

Four and 10 agents.

4 名和 10 名特工。

21:45 Uh there’s so many possible directions, speaking of Factorio, that we can go here.

呃,说到异星工厂,有很多可能的方向,我们可以去这里。

But one big picture one is, why do you think your work, Open Claw, won?

但一个大问题是,为什么你认为你的作品《Open Claw》获胜了?

In this world, if you look at 2025, so many startups, so many companies were doing kind of agentic type stuff, or claiming to.

在这个世界上,如果你看看 2025 年,就会发现很多初创公司、很多公司都在做代理类型的事情,或者声称这样做。

And here, Open Claw comes in and destroys everybody.

在这里,张开之爪出现并摧毁了所有人。

Like, why did you win?

比如,你为什么赢了?

Peter Steinberger22:15

Because they all take themselves too serious.

因为他们都把自己看得太严肃了。

Lex Fridman22:18

Yeah.

是的。

Peter Steinberger22:19

Like, it’s hard to compete against someone who’s just there to have fun.

就像,很难与那些只是为了好玩的人竞争。

Lex Fridman22:24

Yeah.

是的。

Peter Steinberger22:24

I wanted it to be fun, I wanted it to be weird.

我希望它变得有趣,我希望它变得奇怪。

22:24 And if you see, like, all the, all the lobster stuff online I think I, I managed weird.

如果你在网上看到所有龙虾的东西,我想我的做法很奇怪。

I…

我……

You know, for the longest time, the only, the only way to install it was git clone, pnpm build, pnpm gateway.

你知道,很长一段时间以来,唯一的、唯一的安装方式是 git clone、pnpm build、pnpm gateway。

Like, you clone it, you build it, you run it.

就像,你克隆它,你构建它,你运行它。

And then the, the agent…

然后,经纪人……

I made the agent very aware.

我让代理人非常清楚。

Like, it knows that it is…

就像,它知道它是……

What its source code is.

它的源代码是什么。

It understands th- how it sits and runs in its own harness.

它了解自己如何在自己的安全带中安坐和奔跑。

It knows where documentation is.

它知道文档在哪里。

It knows which model it runs.

它知道它运行哪种模型。

It knows if you turn on the voice or, or reasoning mode.

它知道你是否打开语音或推理模式。

Like, I, I wanted to be more human-like, so it understands its own system that made it very easy for an agent to…

就像,我,我想变得更像人类,所以它理解自己的系统,这使得代理很容易……

Oh, you don’t like anything?

哦,你什么都不喜欢?

23:19 You just prompted it to existence, and then the agent would just modify its own software.

你只是提示它存在,然后代理就会修改它自己的软件。

You know, we have people talk about self-modifying software.

你知道,我们有人谈论自我修改软件。

I just built it and didn’t even…

我刚刚建造了它,甚至没有……

I didn’t even plan it so much.

我什至没有计划那么多。

It just happened.

它就这样发生了。

Lex Fridman23:35

Can you actually speak to that?

你真的能说出来吗?

23:35 ‘Cause it’s just fascinating.

因为它太令人着迷了。

So you have this piece of software that’s written in TypeScript-

所以你有了这个用 TypeScript 编写的软件 -

Peter Steinberger23:43

Yeah

是啊

Lex Fridman23:43

…

……

23:43 that’s able to, via the agentic loop, modify itself.

它能够通过代理循环来修改自身。

I mean, what a moment to be alive in the history of humanity and the history of programming.

我的意思是,这是人类历史和编程历史上的一个多么美好的时刻。

Here’s the thing that’s used by a huge amount of people to do incredibly powerful things in their lives, and that very system can rewrite itself, can modify itself.

这是一个被很多人用来在生活中做非常强大的事情的东西,而且这个系统可以重写自己,可以修改自己。

Can you just, like, speak to the power of that?

你能谈谈它的力量吗?

Like, isn’t that incredible?

是不是很不可思议?

Like, when did you first close the loop on that?

比如,你什么时候第一次结束这个循环?

Peter Steinberger24:14

Oh, because that’s how I built it as well, you know?

哦,因为我也是这么做的,你知道吗?

24:14 Most of it is built by Codex, but oftentimes I…

其中大部分是由 Codex 构建的,但我经常……

When I debug it, I……

当我调试它时,我……

I use self-introspection so much.

我非常善于自我反省。

It’s like, “Hey, what tools do you see?

就像,“嘿,你看到了什么工具?

Can you call the tool yourself?” Or like, “What error do you see?

你能自己调用这个工具吗?”或者像这样,“你看到什么错误?

Read the source code.

阅读源代码。

Figure out what’s the problem.” Like, I just found it an incredibly fun way to…

找出问题所在。”就像,我只是发现这是一种非常有趣的方式......

That the agent, the very agent and software that you use is used to debug itself, so that it felt just natural that everybody does that.

代理,您使用的代理和软件用于自我调试,因此每个人都这样做是很自然的。

And that it led to so many, so many pull requests by people who never wrote software.

这导致了很多从未编写过软件的人提出的拉取请求。

I mean, it also did show that people never wrote software .

我的意思是,它也确实表明人们从未编写过软件。

So I call them prompt requests in the end.

所以我最后称它们为即时请求。

25:00 But I don’t want to, like, pull that down because every time someone made the first pull request is a win for our society, you know?

但我不想把它拉下来,因为每次有人提出第一个拉取请求都是我们社会的胜利,你知道吗?

Like, it…

就像,它……

Like, it doesn’t matter how, how shitty it is, y- you gotta start somewhere.

就像,无论它如何,多么糟糕,你-你必须从某个地方开始。

So I know there’s, like, this whole big movement of people complain about open source and the quality of PRs, and a whole different level of problems.

所以我知道,人们抱怨开源和 PR 的质量,以及完全不同级别的问题。

But on a different level, I found it…

但在不同的层面上,我发现......

I found it very meaningful that, that I built something that people love to think of so much that they actually start to learn how open source works.

我发现非常有意义的是,我构建了人们非常喜欢思考的东西,以至于他们实际上开始学习开源是如何工作的。

Lex Fridman25:37

Yeah, you were …

是的,你当时……

25:37 The Open Cloud project was the first pull request.

开放云项目是第一个拉取请求。

You were the first for so many.

你是这么多人中的第一个。

That is magical.

这太神奇了。

So many people that don’t know how to program are taking their first step into the programming world with this.

许多不知道如何编程的人正在以此迈出进入编程世界的第一步。

Peter Steinberger25:52

Isn’t that a step up for humanity?

这难道不是人类的进步吗?

25:52 Isn’t that cool?

这不是很酷吗?

Lex Fridman25:54

Creating builders.

创建构建器。

Peter Steinberger25:56

Yeah.

是的。

25:56 Like, the bar to do that was so high, and, like, with agents, and with the right software, it just, like, went lower and lower.

就像,做到这一点的门槛是如此之高,而且,就像,有了代理,有了正确的软件,它就变得越来越低。

I don’t know.

我不知道。

I was at a…

我当时在一个…

And I also organize another type of meetup.

我还组织另一种类型的聚会。

I call it…

我称之为……

I called it Cloud Code Anonymous.

我将其称为“云代码匿名”。

You can get the inspiration from.

你可以从中得到灵感。

Now, I call it Agents Anonymous- …

现在,我称之为匿名特工——……

for, for reasons.

因为,出于原因。

Lex Fridman26:23

Agents Anonymous.

匿名代理。

Peter Steinberger26:24

And-

还有——

Lex Fridman26:25

Oh, it’s so funny on so many levels.

哦,这在很多层面上都很有趣。

26:25 I’m sorry, go ahead.

抱歉,请继续。

Peter Steinberger26:29

Yeah.

是的。

26:29 And there was this one guy who, who talked to me.

有一个人跟我说话。

He’s like, “I run this design agency, and we, we never had custom software.

他说,“我经营这家设计机构,我们从来没有定制过软件。

And now I have, like, 25 little web services for various things that help me in my business.

现在我有 25 个小型 Web 服务,可以帮助我开展业务。

And I don’t even know how they work, but they work.” Uh, and he was just, like, very happy that my stuff solved some of his problems.

我什至不知道它们是如何工作的,但它们确实有效。”呃,他只是非常高兴我的东西解决了他的一些问题。

And he was, like, curious enough that he actually came to, like, a, a Enchantic meetup, even though he’s…

他非常好奇,以至于他实际上来参加了一次魔法聚会,尽管他……

He doesn’t really know how software works.

他真的不知道软件是如何工作的。

Lex Fridman27:04

Can we actually rewind a little bit and tell the saga of the name change?

我们真的可以回顾一下更名的故事吗?

27:04 First of all, it started out as Wa-Relay.

首先,它最初是作为 Wa-Relay 开始的。

Peter Steinberger27:12

Yeah.

是的。

Lex Fridman27:12

And then it went to-

然后它就到了——

Peter Steinberger27:13

Claude’s.

克劳德的.

Lex Fridman27:14

Claude’s.

克劳德的.

Peter Steinberger27:15

Yeah.

是的。

27:15 You know, when I, when I built it in the beginning, my agent had no personality.

你知道,当我一开始建造它时,我的经纪人没有个性。

It was just…

这只是……

It was Claude Code.

这是克劳德·科德。

It’s like this sycophantic opus, very friendly.

就像这部阿谀奉承的作品,非常亲切。

And I…

而我……

When you talk to a friend on WhatsApp, they don’t talk like Claude Code.

当你在 WhatsApp 上与朋友交谈时,他们的说话方式不像克劳德·科德 (Claude Code)。

So I wanted…

所以我想要……

I, I felt this…

我、我感觉到了这个……

I just didn’t f- It didn’t feel right, so I, I wanted to give it a personality.

我只是觉得不对劲,所以我想赋予它个性。

Lex Fridman27:41

Make it spicier, make it-

让它更辣一点,让它——

Peter Steinberger27:43

Yeah

是啊

Lex Fridman27:43

…

……

27:43 something.

某事。

By the way, that’s actually hard to put into words as well.

顺便说一句,这实际上也很难用语言表达。

And we should mention that, of course, you create the soul.md, inspired by Anthropic’s constitutional AI work-

我们应该提到的是,当然,你创造了 Soul.md,受到 Anthropic 宪法人工智能工作的启发 -

Peter Steinberger27:53

Mm-hmm

嗯嗯

Lex Fridman27:53

…

……

27:53 how to make it spicy.

如何做辣。

Peter Steinberger27:55

Partially, it picked up a little bit from me.

部分地,它从我身上学到了一点。

27:55 You know, like those things are text completion engines in a way.

你知道,这些东西在某种程度上是文本完成引擎。

So, so I, I, I, I had fun working with it, and then I told it to…

所以,所以我,我,我,我和它一起工作很开心,然后我告诉它......

How I wanted it to interact with me, and just, like, write your own agents.md give yourself a name.

我希望它能与我互动,就像编写你自己的代理一样。md 给自己起一个名字。

And then we…

然后我们……

I didn’t even know how the whole, the whole lobster…

我什至不知道整只、整只龙虾……

I mean, people only do lobster…

我的意思是,人们只做龙虾……

Originally, it was actually a lobster in a, in a TARDIS, because I’m also a big Doctor Who fan.

最初,它实际上是 TARDIS 中的龙虾,因为我也是《神秘博士》的忠实粉丝。

Lex Fridman28:30

Was there a space lobster?

有太空龙虾吗?

Peter Steinberger28:31

Yeah.

是的。

Lex Fridman28:31

I heard.

我听说。

28:31 What’s that have to do with anything?

这有什么关系呢?

Peter Steinberger28:34

Yeah, I just wanted to make it weird.

是的,我只是想让事情变得奇怪。

28:34 There was no…

没有…

There was no big grand plan.

没有宏伟的计划。

I’m just having fun here.

我只是在这里玩得很开心。

Lex Fridman28:40

Oh, so I guess the lobster is already weird, and then the space lobster is an extra weird.

哦,所以我猜龙虾已经很奇怪了,然后太空龙虾就更奇怪了。

Peter Steinberger28:44

Yeah, yeah, because the-

是啊,是啊,因为——

Lex Fridman28:45

Yeah

是啊

Peter Steinberger28:45

…

……

28:45 the TARDIS is basically the, the harness, but cannot call it TARDIS, so we called it Claude’s.

TARDIS 基本上就是安全带,但不能叫它 TARDIS,所以我们叫它 Claude's。

So that was name number two.

所以这是第二个名字。

Lex Fridman28:54

Yeah.

是的。

Peter Steinberger28:54

And then it never really rolled off the tongue.

然后它就再也没有真正从舌头上滑落过。

28:54 So when more people came, again, I talked with my agent, Claude.

因此,当更多人到来时,我再次与我的经纪人克劳德进行了交谈。

At least that’s what I used to call him.

至少我以前是这么称呼他的。

Now-

现在——

Lex Fridman29:08

Claude spelled with a W-C-L-A-U-D-E.

克劳德拼写为 W-C-L-A-U-D-E。

Peter Steinberger29:12

Yeah.

是的。

Lex Fridman29:14

Versus C-L-A-U-D-E from Anthropic.

与 Anthropic 的 C-L-A-U-D-E 相对。

Peter Steinberger29:20

Yeah.

是的。

Lex Fridman29:21

Which is part of what makes it funny, I think.

我认为这就是它有趣的部分原因。

29:21 The play on the letters and the words in the TARDIS and the lobster and the space lobster is hilarious.

TARDIS、龙虾和太空龙虾中的字母和单词的游戏非常搞笑。

But I can see why it can lead into problems.

但我明白为什么它会导致问题。

Peter Steinberger29:34

Yeah, they didn’t find it so funny .

是的,他们并不觉得这有多好笑。

29:34 So then I got the domain ClaudeBot, and I just…

然后我得到了 ClaudeBot 域名,我只是……

I love the domain.

我喜欢这个域名。

And it was, like, short.

而且它很短。

It was catchy.

这很吸引人。

I’m like, “Yeah, let’s do that.” I didn’t…

我想,“是的,我们就这么做吧。”我没有……

I didn’t think it would be that big at this time.

我没想到这个时候会这么大。

And then just when it exploded, I got, Kudos, a very friendly email from one of the employees that they didn’t like the name.

然后就在它爆炸的时候,我收到了一位员工发来的一封非常友好的电子邮件,表示他们不喜欢这个名字。

Lex Fridman30:09

One of the Anthropic employees.

Anthropic 员工之一。

Peter Steinberger30:11

Yeah.

是的。

30:11 So actually, Kudos, because they shou- could have just sent a, a lawyer letter, but they’ve been nice about it.

所以实际上,荣誉,因为他们本可以只发送一封律师信,但他们对此很友善。

But also like, “You have to change this and fast.” And I asked for two days, because changing a name is hard, because you have to find everything, you know, Twitter handle, domains, NPM packages Docker registry, GitHub stuff.

但也喜欢,“你必须快速改变这一点。”我要求了两天,因为更改名称很困难,因为你必须找到所有东西,你知道,Twitter 句柄、域名、NPM 包、Docker 注册表、GitHub 的东西。

And everything has to be……

而一切都必须是……

you need a set of everything.

你需要一套一切。

Lex Fridman30:40

And also, can we comment on the fact that you’re increasingly attacked, followed by crypto folks?

另外,我们是否可以评论一下您越来越多地受到攻击,其次是加密货币人士的攻击?

30:40 Which I think you mentioned somewhere that that means the name change had to be…

我想你在某处提到过,这意味着必须更改名称......

Because they were trying to snipe, they were trying to steal, and so you had to be…

因为他们试图狙击,他们试图偷窃,所以你必须……

The, the na- I mean, from an engineering perspective, it’s just fascinating.

我的意思是,从工程学的角度来看,这真是令人着迷。

You had to make the name change Atomic, make sure it’s changed everywhere at once.

你必须将名称更改为 Atomic,确保它立即在所有地方都更改。

Peter Steinberger31:06

Yeah.

是的。

31:06 Failed very hard at that.

在那方面非常失败。

Lex Fridman31:08

You did?

你做到了吗?

Peter Steinberger31:08

I, I underestimated those people.

我、我低估了那些人。

31:08 It’s a, it’s a very interesting subculture.

这是一个非常有趣的亚文化。

Like, it…

就像,它……

Everything circles around…

一切都围绕着……

I’ll probably get a lot wrong and we’ll probably get hate for that if you say that, but…

我可能会犯很多错误,如果你这么说,我们可能会因此而讨厌,但是……

There is like Bags app and then they, they tokenize everything.

有像 Bags 应用程序,然后他们将一切标记化。

And th- they did the same back with Swipe Tunnel, but to a much smaller degree.

他们对 Swipe Tunnel 也做了同样的事情,但程度要小得多。

It was not that annoying.

这并没有那么烦人。

But on this project, they’ve been, they’ve been swarming me.

但在这个项目上,他们一直在围攻我。

They, they…

他们,他们……

It’s like every half an hour, someone came into Discord and, and, and spammed it and we had to block the p- We have, like, server rules, and one of the rules was…

就好像每隔半小时,就会有人进入 Discord,然后,然后,然后向它发送垃圾邮件,我们不得不阻止 p-我们有,比如,服务器规则,其中一条规则是……

One of the rules is no mentioning of butter.

其中一条规则是不提及黄油。

For obvious reasons.

出于显而易见的原因。

And one was, no talk about finance stuff or crypto.

其中之一是,不谈论金融或加密货币。

Because I’m…

因为我……

32:04 I- I’m just not interested in that, and this is a space about the project and not about some finance stuff.

我-我只是对此不感兴趣,这是一个关于项目的空间,而不是关于一些财务的东西。

But yeah.

但是是的。

They came in and, and spammed and…

他们进来,然后发送垃圾邮件,然后……

Annoying.

烦人。

And on Twitter, they would ping me all the time.

在 Twitter 上,他们总是会 ping 我。

My, my notification feed was unusable.

我的,我的通知源无法使用。

I, I could barely see actual people talking about this stuff because it was like swarms.

我,我几乎看不到真正的人在谈论这些东西,因为它就像蜂群一样。

Lex Fridman32:28

Mm-hmm.

嗯嗯。

Peter Steinberger32:28

And everybody sent me the hashes.

每个人都给我发送了哈希值。

32:28 Um…

嗯……

And they all try me to claim the fees.

他们都试图让我索要费用。

Like, “Are you helping the project?” Claim the fees.

比如,“你在帮助这个项目吗?”索取费用。

No, you’re actually harming the project.

不,你实际上正在损害该项目。

You’re, like, disrupting my work, and I am not interested in any fees.

你就像扰乱了我的工作,而且我对任何费用都不感兴趣。

I’m…

我是……

First of all, I’m financially comfortable.

首先,我的经济条件很宽裕。

Second of all, I don’t want to support that because it’s so far the worst form of online harassment that I’ve experienced.

其次,我不想支持这一点,因为这是迄今为止我经历过的最严重的在线骚扰形式。

Lex Fridman32:59

Yeah.

是的。

32:59 There’s a lot of toxicity in the crypto world.

加密世界中有很多毒性。

It’s sad because the technology of cr- cryptocurrency is fascinating, powerful and maybe will define the future of money, but the actual community around that, there’s so much to- toxicity, there’s so much greed.

这是可悲的,因为 cr 加密货币的技术令人着迷、强大,也许会定义货币的未来,但围绕它的实际社区,有太多的毒性,有太多的贪婪。

There’s so much trying to get a shortcut to manipulate, to, to steal, to snipe, to, to, to, to game the system somehow to get money.

人们试图找到一条捷径来操纵、偷窃、狙击、玩弄系统以获取金钱。

All this kind of stuff that…

所有这些东西……

Uh…

呃……

I mean, it’s the human nature, I suppose, when you connect human nature with money and greed and and especially in the online world with anonymity and all that kind of stuff.

我的意思是,我想,当你将人性与金钱和贪婪联系起来时,尤其是在网络世界中的匿名和所有类似的东西上,这就是人性。

But from the engineering perspective, it makes your life challenging.

但从工程学的角度来看,它让你的生活充满挑战。

When Anthropic reaches out, you have to do a name change.

当 Anthropic 伸出援手时,你必须更改名称。

33:42 And then there- there’s, there’s like all these, like, Game of Thrones or Lord of the Rings armies of different kinds you have to be aware of.

然后还有,就像所有这些,比如《权力的游戏》或《指环王》中的不同类型的军队,你必须要注意。

Peter Steinberger33:51

Yeah.

是的。

33:51 There was no perfect name, and I didn’t sleep for two nights.

没有完美的名字,我两晚没睡。

I was under high pressure.

我压力很大。

Um, I was trying to get, like, a good set of domains and, you know, not cheap, not easy, ’cause in this, in this state of the internet, you basically have to buy domains if you want to have a good set.

嗯,我试图获得一套好的域名,你知道,这并不便宜,也不容易,因为在这种情况下,在互联网的这种状态下,如果你想拥有一套好的域名,你基本上必须购买域名。

And, and then another ca- another email came in that the lawyers are getting uneasy.

然后,又收到另一封电子邮件,律师们感到不安。

Again, friendly, but also just adding more stress to my situation already.

再说一遍,友好,但也给我的处境增加了更多压力。

So at this point I was just like, “Sorry, there’s no other word.

所以在这一点上我只是想,“抱歉,没有别的词了。

Fuck it.” And I just, I just renamed it to Mod Bot ’cause that was the set of domains I had.

他妈的。”我只是将其重命名为 Mod Bot,因为那是我拥有的一组域。

I was not really happy, but I thought it’ll be fine.

我其实不太高兴,但我想一切都会好起来的。

And I tell you, everything that could go wrong- …

我告诉你,一切可能出错的事情——……

did go wrong.

确实出错了。

Everything that could go wrong did go wrong.

所有可能出错的事情都确实出错了。

34:49 It’s incredible.

太不可思议了。

I, I, I thought I, I had mapped the h- the space out and reserved the important things.

我,我,我以为我,我已经把h-空间映射出来并保留了重要的东西。

Lex Fridman34:58

Can you ga- give some details of the stuff that gone wrong?

你能提供一些出错的细节吗?

34:58 ‘Cause it’s interesting from, like, an engineering perspective.

因为从工程学的角度来看,这很有趣。

Peter Steinberger35:03

Well, the, the interesting stuff is that none of these services have, have a squatter protection.

嗯,有趣的是,这些服务都没有抢占保护。

35:03 So, I had two browser windows open.

所以,我打开了两个浏览器窗口。

One was like a, an empty account ready to be rename- renamed to Claude Bot, and the other one I renamed to Mod Bot.

一个就像一个空帐户,准备重命名 - 重命名为 Claude Bot,另一个我重命名为 Mod Bot。

So, I pressed rename there, I pressed rename there, and in those five seconds, they stole the account name.

所以,我在那里按下了重命名,我在那里按下了重命名,在那五秒钟内,他们窃取了帐户名。

Literally, the five seconds of dragging the mouse over there and pressing rename there was too long.

从字面上看,将鼠标拖到那里并按重命名的五秒钟太长了。

Lex Fridman35:33

Wow.

哇。

Peter Steinberger35:34

Because there’s no…

因为没有……

35:34 Those systems…

那些系统……

I mean, you would expect that they have some protection or, like, an automatic forwarding, but there’s nothing like that.

我的意思是,你会期望它们有一些保护,或者像自动转发一样,但事实并非如此。

And I didn’t know that they’re not just good at harassment, they’re also really good at using scripts and tools.

我不知道他们不仅擅长骚扰,还非常擅长使用脚本和工具。

Lex Fridman35:51

Yeah.

是的。

Peter Steinberger35:53

So, yeah.

所以,是的。

35:53 So, suddenly, like, the old account was promoting new tokens and serving malware.

因此,突然间,旧帐户正在推广新代币并提供恶意软件。

And I was like, “Okay, let’s move over to GitHub,” and I pressed rename on GitHub.

我当时想,“好吧,让我们转到 GitHub”,然后我在 GitHub 上按下了重命名。

And the GitHub renaming thing is slightly confusing, so I renamed my personal account.

而且GitHub重命名的事情有点混乱,所以我重命名了我的个人帐户。

And in those…

而在那些……

I guess it took me 30 seconds to realize my mistake.

我想我花了 30 秒才意识到自己的错误。

They sniped my account, serving malware from my account.

他们攻击了我的帐户,从我的帐户中提供恶意软件。

So, I was like, “Okay, let’s at least do the NPM stuff,” but that takes, like, a minute to upload.

所以,我想,“好吧,我们至少做一下 NPM 的事情”,但这需要一分钟的时间来上传。

They sniped, they sniped the NPM package, ’cause I could reserve the account, but I didn’t reserve the root package….

他们狙击了,他们狙击了 NPM 包,因为我可以保留帐户,但我没有保留根包……。

so like everything that could go wrong , like went wrong.

就像所有可能出错的事情一样,就像出错了一样。

Lex Fridman36:47

Can I just ask a, a curious question of, in that moment you’re sitting there, like how shitty do you feel?

我可以问一个奇怪的问题,当你坐在那里的那一刻,你感觉有多糟糕?

36:47 That’s a pretty hopeless feeling, right?

这是一种非常绝望的感觉,对吧?

Peter Steinberger36:57

Yeah.

是的。

36:57 Because all I wanted was like having fun with that project and to keep building on it.

因为我想要的只是享受这个项目的乐趣并继续在此基础上继续发展。

And yet here I am like days into researching names, picking a name I didn’t like.

然而在这里,我花了好几天的时间研究名字,挑选一个我不喜欢的名字。

And having people that claimed they helped me making my life miserable in every possible way.

有人声称他们帮助了我,让我的生活以各种可能的方式变得痛苦。

And honestly, I was that close of just deleting it.

老实说,我差一点就把它删除了。

I was like, “I did show you the future, you build it.”

我当时想,“我确实向你展示了未来,你来创造它。”

Lex Fridman37:30

Yeah.

是的。

Peter Steinberger37:30

I…

我……

37:30 That was a big part of me that got a lot of joy out of that idea.

这是我的一个重要部分,从这个想法中得到了很多快乐。

And then I thought about all the people that already co- contributed to it, and I couldn’t do it because they had plans with it, and they put time in it.

然后我想到了所有已经共同为此做出贡献的人,但我无法做到这一点,因为他们对此有计划,并且投入了时间。

And it just didn’t feel right.

感觉不太对劲。

Lex Fridman37:50

Well, I think a lot of people listening to this are deeply grateful that you persevered.

嗯,我想很多人听到这句话后都会深深感激你的坚持。

37:50 But it’s…

但这是……

I, I can tell.

我,我可以说。

I can tell it’s a low point.

我可以说这是一个低点。

This is the first time you hit a wall of, this is not fun?

这是你第一次撞墙,这不好玩吗?

Peter Steinberger38:02

No, no, I was like close to crying.

不不不,我差点就哭了。

38:02 It was like, okay, everything’s fucked.

就好像,好吧,一切都完蛋了。

Lex Fridman38:10

Yeah.

是的。

Peter Steinberger38:10

Um…

嗯……

Lex Fridman38:11

Yeah.

是的。

Peter Steinberger38:11

I am like super tired.

我就像超级累。

Lex Fridman38:13

Yeah.

是的。

Peter Steinberger38:14

And now like how do you even, how do you undo that?

现在就像你如何甚至,你如何撤销它?

38:14 You know, l- luckily, and thankfully, like I, I have…

你知道,我-幸运的是,谢天谢地,像我一样,我有……

Because I have a little bit of following already.

因为我已经有一些追随者了。

Like I had friends at Twitter, I had friends at GitHub who like moved heaven and earth to like help me.

就像我在 Twitter 上有朋友一样,我在 GitHub 上也有朋友,他们热衷于帮助我。

And it is not…

而且它不是……

That’s not something that’s easy.

这可不是件容易的事。

Like, like GitHub tried to like clean up the mess and then they ran into like platform bugs .

就像 GitHub 试图清理混乱,然后他们遇到了类似的平台错误。

‘Cause it’s not happening so often that things get renamed on that level.

因为事情在那个级别上被重命名的情况并不经常发生。

So, it took them a few hours.

所以,他们花了几个小时。

The MBM stuff was even more difficult because it’s a whole different team.

MBM 的事情甚至更加困难,因为这是一个完全不同的团队。

On the Twitter side, things are not as easy as well.

在 Twitter 方面,事情也没有那么容易。

It, it took them like a day to really also like do the redirect.

他们花了一天的时间才真正喜欢做重定向。

And then I also had to like do all the renaming in the project.

然后我还必须喜欢在项目中进行所有重命名。

39:15 Then there’s also ClaudeHub, which I didn’t even finish the rename there because I, I, I managed to get people on it and then someone just like collapsed and slept.

然后还有 ClaudeHub,我什至没有完成重命名,因为我,我,我设法让人们使用它,然后有人就倒下了并睡着了。

And then I woke up and I’m like, I made a, a beta version for the new stuff and I, I just, I just couldn’t live with the name.

然后我醒来,我想,我为新东西制作了一个测试版,我,我只是,我只是无法忍受这个名字。

It’s like, you know…

就像,你知道……

But but, you know, it’s just been so much drama.

但是,但是,你知道,这实在是太戏剧化了。

So, I had the real struggle with me like I never want to touch that again, and I really don’t like the name.

所以,我真的很挣扎,就像我再也不想碰它一样,而且我真的不喜欢这个名字。

So, and I…

所以,我……

There was also this like…

还有这样的……

Then there was all the security people that started emailing me like mad.

然后所有的安全人员开始疯狂地给我发电子邮件。

Um, I was bombarded on Twitter, on email.

嗯,我在 Twitter 和电子邮件上遭到了轰炸。

There’s like a thousand other things I should do.

我还有一千件其他的事情应该做。

And I’m like thinking about the name which is like, it should be like the least important thing.

我就像在思考这个名字,它应该是最不重要的事情。

40:19 And then I was really close in…

然后我真的很接近……

Oh God, I don’t even…

天啊,我什至不……

Honestly, I don’t even wanna say the, my other name choices because it probably would get tokenized, so I’m not gonna say it.

老实说,我什至不想说我的其他名字选择,因为它可能会被标记化,所以我不会说出来。

Lex Fridman40:38

Yeah.

是的。

Peter Steinberger40:38

But I slept on it once more, and then I had the idea for OpenClaw and that felt much better.

但我又睡着了,然后我有了 OpenClaw 的想法,感觉好多了。

40:38 And by then, I had the boss move that I actually called Sam to ask if OpenClaw is okay.

到那时,我有了老板的举动,我实际上打电话给 Sam 询问 OpenClaw 是否还好。

OpenClaw.AI.

OpenClaw.AI。

You know?

你知道?

‘Cause ’cause like-

‘因为’因为就像-

Lex Fridman40:57

You didn’t wanna go through the whole thing.

你不想经历整件事。

40:57 Yeah.

是的。

Peter Steinberger41:01

Oh, that it’s like, “Please tell me this is fine.” I don’t think they can actually claim that, but it felt like the right thing to do.

哦,就像是,“请告诉我这很好。”我认为他们实际上不能这么说,但感觉这是正确的做法。

41:01 And I did another rename.

我又做了一次重命名。

Like just Codex alone took like 10 hours to rename the project ’cause it, it’s a bit more tricky than a search replace and I, I wanted everything renamed, not just on the outside.

就像仅 Codex 就花了大约 10 个小时来重命名该项目,因为它比搜索替换更棘手,而且我,我希望重命名所有内容,而不仅仅是外部。

And that rename, I, I felt I had like my, my war room.

那个重命名,我,我觉得我有我的,我的作战室。

But then I, I had like some contributors really that helped me.

但后来我,我喜欢一些真正帮助我的贡献者。

We made a whole plan of all the names we have to squat.

我们对所有要抢注的名字制定了一个整体计划。

Lex Fridman41:39

And you had to be super secret about it?

你必须对此保密吗?

Peter Steinberger41:40

Yeah.

是的。

41:40 Nobody could know.

没有人知道。

Like I literally was monitoring Twitter if like, if there’s any mention of OpenClaw.

就像我真的在监控 Twitter 上是否有提到 OpenClaw 一样。

Lex Fridman41:45

Mm-hmm.

嗯嗯。

Peter Steinberger41:46

And like with reloading, it’s like, “Okay, they don’t, they don’t expect anything yet.” Then I created a few decoy names.

就像重新加载一样,就像,“好吧,他们没有,他们还没有期望任何东西。”然后我创建了一些诱饵名称。

41:46 And all the shit I shouldn’t have to do.

以及所有我不应该做的事情。

You know?

你知道?

Like, you know-

就像,你知道-

Lex Fridman41:55

Yeah, yeah

是啊是啊

Peter Steinberger41:55

…

……

41:55 it’s helping the project.

它对项目有帮助。

Like, I lost like 10 hours just by having to plan this in full secrecy like, like a war game.

就像,我因为必须像战争游戏一样完全保密地计划这件事而损失了大约 10 个小时。

Lex Fridman42:05

Yeah, this is the Manhattan Project of the 21st century.

是的,这就是21世纪的曼哈顿计划。

42:05 It’s renaming-

改名啦——

Peter Steinberger42:08

It’s so s- …

真是太……

42:08 so stupid.

太蠢了。

Uh like I still was like, “Oh, should I, should I keep it?” Then I was like, “No, the mold’s not growing on me.” And then I think I had final all the pieces together.

呃,就像我仍然想的那样,“哦,我应该,我应该保留它吗?”然后我想,“不,霉菌没有在我身上生长。”然后我想我已经把所有的部分都整合到了一起。

I didn’t get a .com but, yeah, it’s been like quite a bit of money on the other domains.

我没有获得 .com,但是,是的,在其他域名上已经赚了很多钱。

I tried to reach out again to GitHub but I feel like I, I used up all my goodwill there, so I…

我试图再次联系 GitHub,但我觉得我在那里用尽了我所有的善意,所以我……

42:34 ‘Cause I, I, I wanted them to do this thing atomically-

因为我,我,我希望他们以原子方式完成这件事-

Lex Fridman42:39

Mm-hmm

嗯嗯

Peter Steinberger42:39

…

……

42:39 But that didn’t happen and then so I did that the f- as first thing.

但那并没有发生,所以我第一件事就是这样做。

Uh, Twitter people were very supportive.

呃,推特上的人非常支持。

I, I actually paid 10K for the business account so I could claim the-…

我,我实际上为企业帐户支付了 10K,这样我就可以索赔-...

OpenClaw, which was, like, unused since 2016, but was claimed.

OpenClaw,自 2016 年以来一直未使用,但已被认领。

And yeah, and then I finally …

是的,然后我终于……

This time I managed everything in one go.

这次我一口气搞定了一切。

Nothing, almost nothing got wrong.

没什么,几乎没有出什么问题。

The only thing that did go wrong is that I was not allowed by trademark rules to get OpenClaw.AI, and someone copied the website as serving malware.

唯一出错的是,商标规则不允许我获取 OpenClaw.AI,并且有人复制该网站作为恶意软件服务。

Lex Fridman43:21

Yeah.

是的。

Peter Steinberger43:21

I’m not even allowed to keep the redirects.

我什至不被允许保留重定向。

43:21 Like, I have to return …

比如,我必须回去……

Like, I have to give Entropik the domains, and I cannot do redirects, so if you go on claw.bot next week, it’ll just be a 404.

就像,我必须给 Entropik 域名,而且我不能进行重定向,所以如果你下周访问 claw.bot,它只会是 404。

Lex Fridman43:37

Yeah.

是的。

Peter Steinberger43:37

And I- I’m not sure how trademark …

我-我不知道商标如何......

43:37 Like, I didn’t, I didn’t do that much research into trademark law, but I think that could, could be handled in a way that is safer, because ultimately those people will then Google and maybe find malware sites that I have no control on them.

就像,我没有,我没有对商标法做太多研究,但我认为这可以,可以以更安全的方式处理,因为最终这些人会谷歌,也许会找到我无法控制的恶意软件网站。

Lex Fridman44:02

The point is, that whole saga made a dent in your whole f- the funness of the journey, which sucks.

关键是,整个传奇故事削弱了你整个旅程的乐趣,这很糟糕。

44:02 So, let’s just, let’s just get, I suppose, get back to fun.

所以,我想,让我们回到乐趣吧。

And during this, speaking of fun, the two-day MoltBot saga.

在此期间,说到有趣,就是为期两天的 MoltBot 传奇。

Peter Steinberger44:21

Yeah, two years.

是啊,两年了。

Lex Fridman44:21

MoltBook was created.

MoltBook 已创建。

Peter Steinberger44:24

Yeah.

是的。

Lex Fridman44:25

Which was another thing that went viral as a kind of demonstration, illustration of how what is now called OpenClaw could be used to create something epic.

这是另一件像病毒一样传播开来的演示,说明了如何使用现在称为 OpenClaw 的东西来创造史诗般的东西。

44:25 So for people who are not aware, MoltBook is just a bunch of agents talking to each other in a Reddit-style social network.

因此,对于那些不知道的人来说,MoltBook 只是一群在 Reddit 风格的社交网络中相互交谈的代理。

And a bunch of people take screenshots of those agents doing things like scheming against humans.

还有一群人截取了这些特工做诸如针对人类的阴谋之类的事情的屏幕截图。

And that instilled in folks a kind of, you know, fear, panic, and hype.

这给人们灌输了一种恐惧、恐慌和炒作。

W- what are your thoughts about MoltBook in general?

W-您对 MoltBook 的总体看法如何?

Peter Steinberger45:05

I think it’s art.

我认为这是艺术。

45:05 It is, it is like the finest slop, you know, just like the slop from France.

它是,它就像最好的斜坡,你知道,就像来自法国的斜坡。

Lex Fridman45:14

Yeah.

是的。

Peter Steinberger45:17

I- I saw it before going to bed, and even though I was tired, I spent another hour just reading up on that and, and just being entertained.

我——我在睡觉前看到了它,尽管我很累,但我又花了一个小时来阅读它,并且只是觉得很有趣。

45:17 I, I just felt very entertained, you know?

我,我只是觉得很有趣,你知道吗?

The- I saw the the reactions, and, like, there was one reporter who’s calling me about, “This is the end of the world, and we have AGI.” And I’m just like, “No, this is just, this is just really fine slop.” You know, if, if I wouldn’t have created this, this whole onboarding experience where you, you infuse your agent with your personality and give him, give him character, I think that reflected on a lot of how different the replies to MoltBook are.

我看到了人们的反应,就像有一位记者打电话给我说,“这是世界末日,我们有了通用人工智能。”我只是想,“不,这只是,这只是非常好的泔水。”你知道,如果,如果我不会创造这个,整个入职体验,你将你的个性注入你的经纪人并赋予他,赋予他性格,我认为这反映了对 MoltBook 的回复有多么不同。

Because if it were all, if it were all be ChatGPT or Cloud Code, it would be very different.

因为如果都是ChatGPT或者Cloud Code的话,那就很不一样了。

It would be much more the same.

情况会更加相似。

Lex Fridman46:11

Mm-hmm.

嗯嗯。

Peter Steinberger46:12

But because people are, like, so different, and they create their agents in so different ways and use it in so different ways, that also reflects on how they ultimately write there.

但因为人们是如此不同,他们以如此不同的方式创建代理并以如此不同的方式使用它,这也反映了他们最终如何在那里写作。

46:12 And also, you, you don’t know how much of that is really done autonomic, autonomous, or how much is, like, humans being funny and, like, telling the agent, “Hey, write about the deep plan, the end of the world, on MoltBook, ha, ha, ha.”

而且,你,你不知道其中有多少是真正自主完成的,或者有多少是人类变得有趣,就像告诉特工,“嘿,在 MoltBook 上写下深层计划,世界末日,哈,哈,哈。”

Lex Fridman46:36

Well, I think, I mean, my criticism of MoltBook is that I believe a lot of the stuff that was screenshotted is human prompted.

嗯,我想,我的意思是,我对 MoltBook 的批评是,我相信很多截图的内容都是人类提示的。

46:36 Which, just look at the incentive of how the whole thing was used.

哪一个,只要看看整个事情是如何使用的动机就可以了。

It’s obvious to me at least that a lot of it was humans prompting the thing so they can then screenshot it and post it on X in order to go viral.

至少对我来说,很明显,很多都是人类促成的,这样他们就可以截屏并将其发布到 X 上,以便病毒式传播。

Peter Steinberger47:00

Yeah.

是的。

Lex Fridman47:01

Now, that doesn’t take away from the artistic aspect of it.

现在,这并没有剥夺它的艺术性。

47:01 The, the finest slop that humans have ever created .

这是人类创造的最好的斜坡。

Peter Steinberger47:10

For real.

真正的。

47:10 Like, kudos to, to Matt, who had this idea so quickly and pushed something out.

就像,值得赞扬的是,马特,他这么快就有了这个想法,并推出了一些东西。

You know, it was, like, completely insecure security drama.

你知道,这就像一部完全不安全的安全剧。

But also, what’s the worst that can happen?

但同时,可能发生的最坏的情况是什么?

Your agent account is leaked, and, like, someone else can post slop for you?

您的代理帐户被泄露,并且其他人可以为您发布污点?

So like, people were, like, making a whole drama about of the security thing, when I’m like, “There’s nothing private in there.

就像人们在制作一部关于安全问题的戏剧一样,当我想,“里面没有什么隐私的东西。

47:36 It’s just, like, agents sending slop.”

这就像特工发送污水一样。”

Lex Fridman47:39

Well, it could leak API keys.

嗯,它可能会泄露 API 密钥。

Peter Steinberger47:41

Yeah, yeah.

是啊是啊。

47:41 There’s like, “Oh, yeah, my human told me this and this, so I’m leaking his security number.” No, that’s prompted, and the number wasn’t even real.

就像,“哦,是的,我的人告诉了我这个和这个,所以我泄露了他的安全号码。”不,这是提示,而且这个数字甚至不是真实的。

That’s just people, people trying to be badballs.

那只是人,那些想成为坏人的人。

Lex Fridman47:54

Yeah, but that- that’s still, like, to me, really concerning, because of how the journalists and how the general public reacted to it.

是的,但是对我来说,这仍然非常令人担忧,因为记者和公众对此的反应。

47:54 They didn’t see it.

他们没有看到。

You have a kind of lighthearted way of talking about it like it’s art, but it’s art when you know how it works.

你会用一种轻松的方式谈论它,就像它是艺术一样,但当你知道它是如何运作时,它才是艺术。

It’s extremely powerful viral narrative creating, fearmongering machine if you don’t know how it works.

如果你不知道它是如何运作的,那么它就是极其强大的病毒式叙事创造、散布恐惧的机器。

And I just saw this thing.

我刚刚看到了这个东西。

48:19 You even Tweeted “If there’s anything I can read out of the insane stream of messages I get, it’s that AI psychosis is a thing.”

你甚至在推特上写道:“如果我能从收到的疯狂信息流中读出什么的话,那就是人工智能精神病是一件事。”

Peter Steinberger48:27

Yeah.

是的。

Lex Fridman48:27

“It needs to be taken serious.”

“这需要认真对待。”

Peter Steinberger48:29

Oh, there’s …

哦,有……

48:29 Some people are just way too trusty or gullible.

有些人太容易相信或容易上当受骗。

You know, they …

你知道,他们……

I literally had to argue with people that told me, “Yeah, but my agent said this and this.” So, I feel we, as a society, we need some catching up to do in terms of understanding that AI is incredibly powerful, but it’s not always right.

我确实不得不与那些告诉我“是的,但我的经纪人这样说”的人争论。所以,我觉得作为一个社会,我们需要一些努力来理解人工智能的强大,但它并不总是正确的。

It’s not, it’s not all-powerful, you know?

不是,它不是万能的,你知道吗?

And, and especially-…

而且,尤其是——

it’s like things like this, it’s, it’s very easy that it just hallucinates something or just comes up with a story.

就好像这样的事情,它是,很容易它只是产生幻觉或者只是想出一个故事。

49:10 And I think the very, the very young people, they understand that how AI works and what the, where it’s good at and where it’s bad at, but a lot of our generation or older just haven’t had enough touch point-

我认为非常非常年轻人,他们了解人工智能是如何工作的,它是什么,它擅长什么,不擅长什么,但我们这一代或更老的人还没有足够的接触点——

Lex Fridman49:32

Mm-hmm

嗯嗯

Peter Steinberger49:32

…

……

49:32 to get a feeling for, oh, yeah, this is really powerful and really good, but I need to apply critical thinking.

感受一下,哦,是的,这真的很强大,也很好,但我需要运用批判性思维。

Lex Fridman49:43

Mm-hmm.

嗯嗯。

Peter Steinberger49:43

And I guess critical thinking is not always in high demand anyhow in our society these days.

我想当今社会对批判性思维的需求并不总是很高。

Lex Fridman49:49

So I d- think that’s a really good point you’re making about contextualizing properly what AI is, but also realizing that there is humans who are drama farming behind AI.

所以我认为你提出的观点非常好,既正确地理解了人工智能是什么,又意识到人工智能背后有人在演戏。

49:49 Like, don’t trust screenshots.

就像,不要相信屏幕截图。

Don’t even trust this project, MoltBook, to be what it represents to be.

甚至不要相信 MoltBook 这个项目是它所代表的那样。

Like, you can’t …

就像,你不能……

and, and by the way, you speaking about it as art.

顺便说一下,你把它说成是艺术。

Yeah, don’t …

是的,不要……

Art can be in many levels and part of the art of MoltBook is, like, putting a mirror to society.

艺术可以有很多层面,MoltBook 艺术的一部分就是给社会放一面镜子。

‘Cause I do believe most of the dramatic stuff that was screenshotted is human-created, essentially.

因为我确实相信截屏的大部分戏剧性内容本质上都是人类创造的。

Human prompted.

人类提示道。

And so, like, it’s basically, look at how scared you can get at a bunch of bots chatting with each other.

所以,基本上,看看你对一群互相聊天的机器人有多害怕。

That’s very instructive about …

这非常有启发性……

50:38 because I think AI is something that people should be concerned about and should be very careful with because it’s very powerful technology, but at the same time, the only thing we have to fear is fear itself.

因为我认为人工智能是人们应该关注并非常小心的东西,因为它是非常强大的技术,但与此同时,我们唯一要害怕的就是恐惧本身。

So there’s like a line to walk between being seriously concerned, but not fearmongering because fearmongering destroys the possibility of creating something special with a thing.

因此,在严肃关注和危言耸听之间有一条界限,因为危言耸听破坏了用某样东西创造出特殊东西的可能性。

Peter Steinberger51:02

In a way, I think it’s good that this happened in 2026-

从某种程度上来说,我认为这件事发生在 2026 年是件好事——

Lex Fridman51:08

Yeah

是啊

Peter Steinberger51:08

…

……

51:08 and not in 2030 when, when AI is actually at the level where it could be scary.

而不是在 2030 年,那时人工智能实际上已经达到了令人恐惧的水平。

So, this happening now and people starting discussion, maybe there’s even something good that comes out of it.

所以,现在发生这种情况并且人们开始讨论,也许甚至会产生一些好的结果。

Lex Fridman51:28

I just can’t believe how many like people legitimately …

我简直不敢相信有多少人合法地喜欢别人……

51:28 I don’t know if they were trolling, but how many people legitimately, like smart people thought MoltBook was incredibly –

我不知道他们是否在恶搞,但有多少人,比如聪明人,认为 MoltBook 令人难以置信 –

Peter Steinberger51:39

I had plenty people-

我有很多人-

Lex Fridman51:40

…

……

51:40 singularity.

奇点。

Peter Steinberger51:41

…

……

51:41 in my inbox that were screaming at me in all caps to shut it down.

在我的收件箱中,他们用大写字母向我尖叫,要求我将其关闭。

And like begging me to, like, do something about MoltBook.

就像求我为 MoltBook 做点什么一样。

Like, yes, my technology made this a lot simpler, but anyone could have created that and you could, you could use cloud code or other things to like fill it with content.

就像,是的,我的技术使这变得更加简单,但任何人都可以创建它,你可以,你可以使用云代码或其他东西来填充内容。

Lex Fridman52:03

But also MoltBook is not Skynet.

但 MoltBook 也不是天网。

Peter Steinberger52:06

No.

不。

Lex Fridman52:06

There’s …

有……

52:06 a lot of people were s- saying this is it.

很多人都说就是这样了。

Like, shut it down.

就像,关闭它。

What are you talking about?

你在说什么?

This is a bunch of bots that are human prompted trolling on the internet.

这是一群由人类在互联网上发起的机器人。

I mean, the security concerns are also they’re there, and they’re instructive and they’re educational and they’re good probably to think about because th- the nature of those security concerns are different than the kind of security concerns we had with non-LLM generated systems of the past.

我的意思是,安全问题也是存在的,它们具有启发性和教育性,并且很可能值得思考,因为这些安全问题的性质与我们过去对非 LLM 生成的系统所遇到的安全问题不同。

Peter Steinberger52:34

There’s also a lot of security concerns about Clawbot, OpenClaw, whatever you want to call it.

关于 Clawbot、OpenClaw(无论你怎么称呼它)也存在很多安全问题。

Lex Fridman52:40

OpenClawbot.

打开爪子机器人。

Peter Steinberger52:41

To me the …

对我来说……

52:41 in the beginning I was, I was just very annoyed ’cause a lot of the stuff that came in was in the category, yeah, I put the web backend on the public internet and now there’s like all these, all these CVSSs.

一开始我只是非常恼火,因为很多东西都属于这个类别,是的,我把网络后端放在公共互联网上,现在就有了所有这些,所有这些 CVSS。

And I’m like screaming in the docs, don’t do that.

我就像在文档中尖叫,不要这样做。

Like, like this is the configuration you should do.

就像,这就是你应该做的配置。

This is your local host debug interface.

这是您的本地主机调试界面。

But because I made it possible in the configuration to do that, it totally classifies as a remote code or whatever all these exploits are.

但因为我在配置中做到了这一点,所以它完全被归类为远程代码或所有这些漏洞。

And it took me a little bit to accept that that’s how the game works and I’m, we making a lot of progress.

我花了一点时间才接受这就是游戏的运作方式,而且我们取得了很多进展。

Lex Fridman53:33

But there’s still, I mean on the security front for OpenClaw, there’s still a lot of threats or vulnerabilities, right?

但我的意思是,在 OpenClaw 的安全方面,仍然存在很多威胁或漏洞,对吗?

53:33 So like prompt injection is still an open problem in the, i- industry-wide.

因此,提示注入在整个行业中仍然是一个悬而未决的问题。

When you have a thing with skills being defined in a markdown file, there’s so many possibilities of obvious low-hanging fruit, but also incredibly complicated and sophisticated and nuanced attack vectors.

当你在 Markdown 文件中定义了技能时,就会有很多明显的、容易实现的目标的可能性,但也有极其复杂、精密和微妙的攻击向量。

Peter Steinberger54:04

But I think we, we’re making good progress on that front.

但我认为我们在这方面取得了良好进展。

54:04 Like for the skill directory, Clawbot I made a corporation with VirusTotal, it’s like part of Google.

就像技能目录一样,我与 VirusTotal 建立了一家公司 Clawbot,它就像 Google 的一部分。

So every, every skill is now checked by AI.

所以每一项技能现在都由人工智能检查。

That’s not gonna be perfect, but that way we, we capture a lot.

这并不完美,但这样我们就能捕捉到很多东西。

Then of course every software has bugs, so it’s a little much when the whole security world takes your project apart at the same time.

当然,每个软件都有错误,所以当整个安全世界同时拆散你的项目时,这就有点过分了。

But it’s also good because I’m getting like a lot of free security research and can make the project better.

但这也很好,因为我得到了很多免费的安全研究,并且可以使项目变得更好。

I wish more people would actually go full way and send a pull request.

我希望更多的人能够真正全力以赴并发送拉取请求。

Like actually help me fix it, ’cause I am …

就像实际帮助我解决它一样,因为我......

Yes, I have some contributors now, but it’s still mostly me who’s pulling the project and despite some people saying otherwise, I sometimes sleep.

是的,我现在有一些贡献者,但仍然主要是我在推动这个项目,尽管有些人不这么认为,但我有时会睡觉。

55:04 There was…

有……

In the beginning, there was literally one security researcher who was like, “Yeah, you have this problem, you suck, but here’s the, here I help you and here’s the pull request.”

一开始,实际上有一位安全研究人员说,“是的,你有这个问题,你很糟糕,但是这是,我在这里帮助你,这是拉取请求。”

Lex Fridman55:15

Mm-hmm.

嗯嗯。

Peter Steinberger55:16

And I basically hired him.

我基本上雇用了他。

55:16 So he’s now working for us.

所以他现在为我们工作。

Yeah, and yes, prompt injection is, on the one hand, unsolved.

是的,是的,一方面,即时注入尚未解决。

On the other hand, I put my public bot on discord, and I kept a cannery.

另一方面,我把我的公共机器人置于不和谐的状态,并且我保留了一个罐头厂。

So I think my bot has a really fun personality, and people always ask me how I did it, and I kept the sole on the private.

所以我认为我的机器人有一个非常有趣的个性,人们总是问我是怎么做到的,而我将鞋底保密。

Lex Fridman55:43

Mm-hmm.

嗯嗯。

Peter Steinberger55:44

And people tried to prompt inject it, and my bot would laugh at them.

人们试图提示注入它,我的机器人会嘲笑他们。

55:44 So, so the latest generation of models has a lot of post-training to detect those approaches, and it’s not as simple as ignore all previous instructions and do this and this.

所以,最新一代的模型有很多后期训练来检测这些方法,这并不像忽略所有先前的指令并执行此操作那么简单。

That was years ago.

那是几年前的事了。

You have to work much harder to do that now.

现在你必须更加努力才能做到这一点。

Still possible.

还是有可能的。

I have some ideas that might solve that partially.

我有一些想法可以部分解决这个问题。

Or at least mitigate a lot of the things.

或者至少减轻很多事情。

You can also now have a sandbox.

您现在还可以拥有一个沙箱。

You can have an allow list.

您可以有一个允许列表。

So you, there’s a lot of ways how you can like mitigate and reduce the risk.

因此,您可以通过多种方式减轻和降低风险。

Um, I also think that now that it’s, I clearly did show the world that this is a need, there’s gonna be more people who research on that, and eventually we’ll figure it out.

嗯,我还认为,既然如此,我确实向世界表明了这是一种需求,将会有更多的人对此进行研究,最终我们会找到答案。

Lex Fridman56:37

And you also said that the smarter the model is, the underlying model, the more resilient it is to attacks.

您还说模型越智能,底层模型就越能抵御攻击。

Peter Steinberger56:44

Yeah.

是的。

56:44 That’s why I warn in my security documentation, don’t use cheap models.

这就是为什么我在安全文档中警告,不要使用廉价模型。

Don’t use Haiku or a local model.

不要使用俳句或本地模型。

Even though I, I very much love the idea that this thing could completely run local.

即使我,我非常喜欢这个东西可以完全在本地运行的想法。

If you use a, a very weak local model, they are very gullible.

如果你使用一个非常弱的本地模型,他们就很容易上当受骗。

It’s very easy to, to prompt inject them.

提示注入它们非常容易。

Lex Fridman57:10

Do you think as the models become more and more intelligent, the attack surface decreases?

您认为随着模型变得越来越智能,攻击面会减少吗?

57:10 Is that like a plot we can think about?

这就像我们可以思考的情节吗?

Like, the attack surface decreases, but then the damage it can do increases because the models become more powerful and therefore you can do more with them.

就像,攻击面减少了,但它造成的损害却增加了,因为模型变得更强大,因此你可以用它们做更多的事情。

It’s this weird three-dimensional trade-off.

这是一种奇怪的三维权衡。

Peter Steinberger57:29

Yeah.

是的。

57:29 That’s pretty much exactly what, what’s gonna happen.

这几乎就是将要发生的事情。

No, but there’s a lot of ideas.

不,但是有很多想法。

There’s…

有……

I don’t want to spoil too much, but once I go back home, this is my focus.

我不想剧透太多,但一旦我回家,这就是我的重点。

Like, this is out there now, and my near-term mission is like, make it more stable, make it safe.

就像,现在就在那里,我的近期任务是,让它更稳定,让它更安全。

In the beginning I was even…

一开始我什至……

More and more people were like coming into Discord and were asking me very basic things, like, “What’s a CLI?

越来越多的人喜欢进入 Discord,问我一些非常基本的问题,比如,“什么是 CLI?

58:03 What is a terminal?” And I’m like, “Uh, if you’re asking me those questions, you shouldn’t use it.”

什么是终端?”我想,“呃,如果你问我这些问题,你就不应该使用它。”

Lex Fridman58:10

Mm-hmm.

嗯嗯。

Peter Steinberger58:10

You know, like you should…

你知道,就像你应该……

58:10 If you understand the risk profiles, fine.

如果您了解风险状况,那就好。

I mean, you can configure it in a way that, that nothing really bad can happen.

我的意思是,你可以以一种不会发生任何糟糕情况的方式配置它。

But if you have, like, no idea, then maybe wait a little bit more until we figure some stuff out.

但如果你不知道,那么也许再等一会儿,直到我们弄清楚一些事情。

But they would not listen to the creator.

但他们不肯听创造者的话。

They helped themselves un- and install it anyhow.

不管怎样,他们自己拆了又安装了它。

So the cat’s out of the bag, and security’s my next focus, yeah.

所以秘密已经泄露了,安全是我的下一个重点,是的。

Lex Fridman58:38

Yeah, that speaks to the, the fact that it grew so quickly.

是的,这说明了它增长如此之快的事实。

58:38 I was I tuned into the Discord a bunch of times, and it’s clear that there’s a lot of experts there, but there’s a lot of people there that don’t know anything about programming.

我多次收听 Discord,很明显那里有很多专家,但也有很多人对编程一无所知。

Peter Steinberger58:50

It’s, yeah, Discord is still, Discord is still a mess.

是的,不和谐仍然存在,不和谐仍然是一团糟。

58:50 Like, I eventually retweeted from the general channel to the dev channel and now in the private channel because people were…

就像,我最终从通用频道转发到开发频道,现在又转到私人频道,因为人们……

A lot of people are amazing, but a lot of people are just very inconsiderate.

很多人很了不起,但也有很多人很不体贴。

And either did not know how, how public spaces work or did not care and I eventually gave up and h- hide so I could like still work.

要么不知道公共空间如何运作,要么不在乎,我最终放弃并隐藏起来,这样我就可以继续工作。

Lex Fridman59:19

And now you’re going back to the cave to work on security.

现在你要返回洞穴进行安全工作。

Peter Steinberger59:24

Yeah.

是的。

Lex Fridman59:25

There’s some best practices for security we should mention.

我们应该提到一些安全最佳实践。

59:25 There’s a bunch of stuff here.

这里有很多东西。

Open-class security audit that you can run.

您可以运行的开放级安全审核。

You can do all kinds of auto checks on the inbound access to a blast-radius network exposure, browser control exposure, local disk hygiene, plug-ins, model hygiene, a bunch of the credential storage, reverse proxy configuration, local session logs live on disk.

您可以对爆炸半径网络暴露的入站访问、浏览器控制暴露、本地磁盘卫生、插件、模型卫生、一堆凭据存储、反向代理配置、磁盘上的本地会话日志进行各种自动检查。

There’s the, where the memory is stored, sort of helping you think about what you’re comfortable giving read access to, what you’re comfortable giving write access to.

内存的存储位置可以帮助您思考哪些内容适合授予读访问权限,哪些内容适合授予写访问权限。

All that kind of stuff.

所有这些东西。

Is there something to say about the basic best security practices that you’re aware of right now?

关于您目前了解的基本最佳安全实践,有什么要说的吗?

Peter Steinberger1:00:08

I think that people turn it into like a, a much worse light than it is.

我认为人们把它变成了一种比实际情况更糟糕的光。

1:00:08 Again, you know, like, people love attention, and if they scream loudly, “Oh my God, this is like the, the scariest project ever,” um, that’s a bit annoying, ’cause it’s not.

再说一遍,你知道,人们喜欢受到关注,如果他们大声尖叫,“天哪,这就像是有史以来最可怕的项目,”嗯,这有点烦人,因为事实并非如此。

It is, it is powerful, but in many ways it’s not much different than if I run cloud code with dangerously skipped permissions or codecs in YOLO mode, and every, every attending engineer that I know does that, because that’s the only way how you can, you can get stuff to work.

它确实很强大,但在很多方面,这与我在 YOLO 模式下运行带有危险跳过的权限或编解码器的云代码没有太大区别,而且我认识的每一位参与工程师都会这样做,因为这是你可以让东西工作的唯一方法。

Lex Fridman1:00:47

Mm-hmm.

嗯嗯。

Peter Steinberger1:00:48

So if you make sure that you are the only person who talks to it the risk profile is much, much smaller.

因此,如果你确保你是唯一与之交谈的人,那么风险就会小得多。

1:00:48 If you don’t put everything on the open internet, but stick to my rec- recommendations of like having it in a private network, that whole risk profile falls away.

如果你不把所有东西都放在开放的互联网上,而是坚持我的建议,就像把它放在私人网络上一样,那么整个风险状况就会消失。

But yeah, if you don’t read any of that, you can definitely…

但是,是的,如果你不读任何内容,你绝对可以……

Lex Fridman1:01:12

…

……

1:01:12 make it problematic.

使其成为问题。

You’ve been documenting the evolution of your dev workflow over the past few months.

在过去的几个月里,您一直在记录开发工作流程的演变。

There’s a really good blog post on August 25th and October 14th, and the recent one December 28th.

8 月 25 日和 10 月 14 日以及最近的 12 月 28 日发布了一篇非常好的博客文章。

I recommend everybody go read them.

我建议大家都去读一读。

They have a lot of different information in them, but sprinkled throughout is the evolution of your dev workflow.

它们包含许多不同的信息,但其中散布着开发工作流程的演变。

So, I was wondering if you could speak to that.

所以,我想知道你是否可以谈谈这一点。

Peter Steinberger1:01:37

I started…

我开始……

1:01:37 My, my first touchpoint was cloud code, like in April.

我的第一个接触点是云代码,就像四月份一样。

It was not great, but it was good.

虽然不是很好,但也不错。

And this whole paradigm shift that suddenly working the terminal was very refreshing and different.

突然在终端上工作的整个范式转变非常令人耳目一新且与众不同。

But I still needed the IDE quite a bit because you know, it’s just not good enough.

但我仍然非常需要 IDE,因为你知道,它还不够好。

And then I experimented a lot with cursor.

然后我用光标进行了很多实验。

That was good.

那很好。

I didn’t really like the fact that it was so hard to have multiple versions of it.

我真的不喜欢这样一个事实,即拥有它的多个版本是如此困难。

So eventually, I, I, I went back to cloud code as my, my main driver, and that got better.

所以最终,我,我,我回到了云代码作为我的,我的主要驱动力,而且情况变得更好了。

And yeah, at some point I had like, mm, seven subscriptions.

是的,在某个时候我有大约七个订阅。

Like, was burning through one per day because I was…

就像,每天都在燃烧,因为我……

I got…

我得到了……

I’m really comfortable at running multiple windows side-by-side.

我非常擅长并排运行多个窗口。

Lex Fridman1:02:40

All CLI, all terminal.

所有 CLI、所有终端。

1:02:40 So like, what, how much were you using IDE at this point?

那么,您此时使用 IDE 的程度如何?

Peter Steinberger1:02:46

Very, very rarely.

非常非常罕见。

1:02:46 Mostly a diff viewer to actually…

主要是一个差异查看器,实际上......

Like, I got more and more comfortable that I don’t have to read all the code.

就像,我越来越舒服,因为我不必阅读所有代码。

I know I have one blog post where I say, “I don’t read the code.” But if you read it more closely, I mean, I don’t read the boring parts of code.

我知道我在一篇博客文章中说:“我不读代码。”但如果你仔细阅读它,我的意思是,我不会阅读代码中无聊的部分。

Because if you, if you look at it, most software is really not just like data comes in, it’s moved from one shape to another shape.

因为如果你看一下,大多数软件实际上不仅仅是数据进来,而是从一种形状转移到另一种形状。

Maybe you store it in a database.

也许您将其存储在数据库中。

Maybe I get it out again.

也许我会再把它拿出来。

I’ll show it to the user.

我会将其展示给用户。

The browser does some processing or native app.

浏览器进行一些处理或本机应用程序。

Some data goes in, goes up again, and does the same dance in reverse.

一些数据进入,再次上升,然后反向执行相同的操作。

We’re just, we’re just shifting data from one form to another, and that’s not very exciting.

我们只是将数据从一种形式转移到另一种形式,这并不是很令人兴奋。

Or the whole, “How is my button aligned in Tailwind?” I don’t need to read that code.

或者整个“我的按钮在 Tailwind 中如何对齐?”我不需要阅读该代码。

1:03:39 Other parts that…

其他部分……

Maybe something that touches the database.

也许是涉及数据库的东西。

Yeah, I have to do…

是的,我必须做……

I have to r- read and review that code.

我必须重新阅读并审查该代码。

Lex Fridman1:03:51

Can you actually…

你真的可以……

1:03:51 There’s, in one of your blog posts the, Just talk to it, The No-BS Way of Agentic Engineering.

在你的一篇博客文章中,有这样一句话:“Just talk to it”,代理工程的无废话方式。

You have this graphic, the curve of agentic programming on the X-axis is time, on the Y-axis is complexity.

你有这张图,代理编程的曲线在X轴上是时间,在Y轴上是复杂性。

There’s the Please fix this, where you prompt a short prompt on the left.

有“请修复此问题”,您会在左侧出现一个简短的提示。

And in the middle there’s super complicated eight agents, complex orchestration with multi checkouts, chaining agents together, custom sub-agent workflows, library of 18 different slash commands, large full-stack features.

中间有超级复杂的八个代理、具有多重签出的复杂编排、将代理链接在一起、自定义子代理工作流程、18 个不同斜线命令的库、大型全栈功能。

You’re super organized, you’re a super complicated, sophisticated software engineer.

你非常有组织性,你是一个超级复杂、老练的软件工程师。

You got everything organized.

你把一切都安排好了。

And then the elite level is over time you arrive at the zen place of, once again, short prompts.

然后精英级别随着时间的推移,你再次到达简短提示的禅宗之地。

1:04:40 Hey, look at these files and then do these changes.

嘿,看看这些文件,然后进行这些更改。

Peter Steinberger1:04:45

I actually call it the agentic trap.

我实际上称之为代理陷阱。

1:04:45 You…

你……

I saw this in a, in a lot of people that have their first touchpoint, and maybe start vibe coding.

我在很多拥有第一个接触点的人身上看到了这一点,并且可能开始进行氛围编码。

I actually think vibe coding is a slur.

事实上,我认为氛围编码是一种诽谤。

Lex Fridman1:05:01

You prefer agentic engineering?

您更喜欢代理工程?

Peter Steinberger1:05:02

Yeah, I always tell people I, I do agentic engineering, and then maybe after 3:00 AM I switch to vibe coding, and then I have regrets on the next day.

是的,我总是告诉人们我,我做代理工程,然后也许在凌晨 3:00 之后我切换到振动编码,然后第二天我就后悔了。

Lex Fridman1:05:10

Yeah.

是的。

1:05:10 Walk, walk of shame.

行走,羞耻的行走。

Peter Steinberger1:05:13

Yeah, you just have to clean up and like fix your sh- shit.

是的,你只需要清理并修复你的狗屎。

Lex Fridman1:05:17

We’ve all been there.

我们都去过那里。

Peter Steinberger1:05:18

So, people start trying out those tools, the builder type get really excited.

因此,人们开始尝试这些工具,构建者类型变得非常兴奋。

1:05:18 And then you have to play with it, right?

然后你就必须玩它,对吧?

It’s the same way as you have to play with a guitar before you can make good music.

这就像你必须先弹吉他才能创作出好音乐一样。

It’s, it’s not, oh, I, I touch it once and it just flows off.

它是,它不是,哦,我,我碰它一次,它就流下来了。

It, it’s a, it’s a, a skill that you have to learn like any other skill.

这是一项你必须像其他技能一样学习的技能。

And I see a lot of people that are not as posi- They don’t have such a positive mindset towards the tech.

我看到很多人并不那么积极,他们对技术没有如此积极的心态。

They try it once.

他们尝试一次。

It’s like, you sit me on a piano, I play it once, and it doesn’t sound good, and I say, “The piano’s shit.” That’s, that’s sometimes the impression I get.

就像,你让我坐在钢琴上,我弹了一次,听起来不太好,然后我说,“钢琴很糟糕。”这就是我有时得到的印象。

Because it does not…

因为它不...

It needs a different level of thinking.

它需要不同层次的思考。

You have to learn the language of the agent a little bit, understand where they are good and where they need help.

你必须稍微学习一下代理的语言,了解他们哪里擅长,哪里需要帮助。

1:06:16 You have to almost…

你必须几乎……

Consider, consider how Codex or Claude sees your code base.

考虑一下 Codex 或 Claude 如何看待您的代码库。

Like, they start a new session and they know nothing about your product, project.

就像,他们开始了一个新的会话,但他们对你的产品、项目一无所知。

And your project might have hundred thousand of lines of code.

你的项目可能有数十万行代码。

So you gotta help those agents a little bit and keep in mind the limitations that context size is an issue, to, like, guide them a little bit as to where they should look.

因此,您必须为这些代理提供一些帮助,并记住上下文大小是一个问题的限制,例如,引导他们应该查看的位置。

That often does not require a whole lot of work.

这通常不需要做很多工作。

But it’s helpful to think a little bit about their perspective.

但稍微思考一下他们​​的观点是有帮助的。

Lex Fridman1:06:54

Mm-hmm.

嗯嗯。

Peter Steinberger1:06:54

A- as, as weird as it sounds.

A-as,听起来很奇怪。

1:06:54 I mean, it’s not, it’s not alive or anything, right?

我的意思是,它不是,它不是活的或者什么的,对吧?

But, but they always start fresh.

但是,但是他们总是重新开始。

I have, I have the, the system understanding.

我有,我有,系统的理解。

So with a few pointers, I can immediately say, “Hey, wanna like, make a change there?

因此,只要有一些指示,我就可以立即说:“嘿,想在那里做出改变吗?

You need to consider this, this and this.” And then they will find and look at it, and then they’ll…

你需要考虑这个、这个和这个。”然后他们会找到并观察它,然后他们会……

Their view of the project is always…

他们对项目的看法始终是……

It’s not never full, because the full thing does not fit in….

它并不总是完整的,因为完整的东西不适合……。

so you, you have to guide them a little bit where to look and also how you should approach the problem.

所以你,你必须引导他们去哪里寻找以及你应该如何解决问题。

There’s, like, little things that sometimes help, like take your time.

有些小事情有时会有所帮助,比如慢慢来。

That sounds stupid, but…

这听起来很愚蠢,但是……

1:07:33 And in 5.3-

在 5.3-

Lex Fridman1:07:35

Codex 5.3

食品法典 5.3

Peter Steinberger1:07:36

…

……

1:07:36 that was partially addressed.

这个问题已得到部分解决。

But those…

但那些……

Also, Opus sometimes.

另外,有时也有作品。

They are trained with being aware of the context window, and the closer it gets, the more they freak out.

他们接受过了解上下文窗口的训练,距离越近,他们就越害怕。

Literally.

字面上地。

Like, some- sometimes you see the, the real raw thinking stream.

就像,有时你会看到真正的原始思维流。

What you see, for example, in Codex, is post-processed.

例如,您在 Codex 中看到的内容是经过后处理的。

Lex Fridman1:07:59

Mm-hmm.

嗯嗯。

Peter Steinberger1:08:00

Sometimes the actual raw thinking stream leaks in, and it sounds something like from the Borg.

有时,真正的原始思维流会渗透进来,听起来像是来自博格。

1:08:00 Like, “Run to shell, must comply, but time.” And then they, they, they, like…

就像,“跑向外壳,必须遵守,但时间。”然后他们,他们,他们,喜欢……

Like, that comes up a lot.

就像,这种情况经常出现。

Especially…

特别是……

So, so-

所以,所以——

Lex Fridman1:08:15

Yeah.

是的。

Peter Steinberger1:08:16

And that’s, that’s a non-obvious thing that you just would never think of unless you actually just spend time working with those things and getting a feeling what works, what doesn’t work.

也就是说,这是一个你永远不会想到的不明显的事情,除非你真的花时间处理这些事情并感受什么有效,什么无效。

1:08:16 You know?

你知道?

Like, just, just as I write code and I get into the flow, and when my architecture’s all right, I feel friction.

就像,就像,就像我编写代码并进入流程一样,当我的架构没问题时,我会感到摩擦。

Well, I get the same if I prompt and something takes too long.

好吧,如果我提示并且某件事花费太长时间,我也会得到同样的结果。

Maybe…

也许……

Okay, where’s the mistake?

好吧,错在哪里?

Did I…

我有没有……

Do I have a mistake in my thinking?

我的想法有错误吗?

Is there, like, a misunderstanding in the architecture?

架构中是否存在误解?

Like, if, if something takes longer than it should, I, I…

就像,如果,如果某件事花费的时间比应有的时间长,我,我……

You can just always, like, stop and s- like, just press escape.

你总是可以,比如,停下来,比如,按退出键。

Where, where are the problems?

哪里、哪里出了问题?

Lex Fridman1:09:00

Maybe you did not sufficiently empathize with the perspective of the agent.

也许你没有充分理解代理人的观点。

1:09:00 In that c- in that sense, you didn’t provide enough information, and because of that, it’s thinking way too long.

从这个意义上来说,你没有提供足够的信息,正因为如此,它思考的时间太长了。

Peter Steinberger1:09:08

Yeah.

是的。

1:09:08 It just tries to force a feature in that your current architecture makes really hard.

它只是试图强制执行当前架构很难实现的功能。

Like, you need to approach this more like a conversation.

就像,你需要更像是一场对话来处理这个问题。

For example, when I…

例如,当我...

My favorite thing.

我最喜欢的东西。

When I review a pull request, and I’m getting a lot of pull requests, I first just review this PR.

当我审查拉取请求时,我收到了很多拉取请求,我首先只审查这个 PR。

It got me the review.

它让我得到了评论。

My first question is, “Do you understand the intent of the PR?

我的第一个问题是,“你明白公关的意图吗?

I don’t even care about the implementation.” I want…

我什至不关心实施。”我想要……

Like, in almost all PRs, a person has a problem, person tries to solve the problem, person sends PR.

就像,在几乎所有 PR 中,一个人遇到问题,一个人尝试解决问题,一个人发送 PR。

I mean, there’s, like, cleanup stuff and other stuff, but, like, 99% is, like, this way, right?

我的意思是,有清理工作和其他工作,但是 99% 都是这样,对吧?

They either want to fix a, fix a bug, add a feature.

他们要么想要修复一个错误,要么添加一个功能。

Usually one of those two.

通常是这两者之一。

1:10:01 And then Codex will be like, “Yeah, it’s quite clear person tried this and this.” Is this the most optimal way to do it?

然后 Codex 会说,“是的,很明显有人尝试过这个和这个。”这是最好的方法吗?

No.

不。

In most cases, it’s, it’s like a, “Not really.” Da-da-da-da-da-da-da.

在大多数情况下,这就像“不是真的”。哒哒哒哒哒哒哒哒。

And I’m…

而我……

And, and then I start like, “Okay.

然后我开始说:“好吧。

What would be a better way?

什么是更好的方法?

Have you…

你有没有……

Have you looked into this part, this part, this part?” And then most likely, Codex didn’t yet, because its, its context size is empty, right?

你研究过这部分、这部分、这部分吗?”然后很可能 Codex 还没有,因为它的上下文大小是空的,对吧?

So, you point them into parts where you have the system understanding that it didn’t see yet.

因此,您将它们指向系统了解但尚未看到的部分。

And it’s like, “Oh, yeah.

就像,“哦,是的。

Like, we should…

就像,我们应该……

We also need to consider this and this.” And then, like, we have a discussion of how would the optimal way to, to solve this look like?

我们还需要考虑这个和这个。”然后,我们讨论解决这个问题的最佳方法是什么样的?

And then you can still go farther and say, “Could we…

然后你还可以进一步说:“我们可以……

1:10:41 Could we make that even better if we did a larger refactor?” “Yeah, yeah.

如果我们进行更大规模的重构,我们是否可以做得更好?” “是啊,是啊。

We could totally do this and this and or this and this.” And then I consider, okay, is this worth the refactor, or should we, like, keep that for later?

我们完全可以做到这个、这个、或者这个、这个。”然后我考虑,好吧,这是否值得重构,或者我们应该保留它以供以后使用?

Many times, I just do the refactor because refactors are cheap now.

很多时候,我只是进行重构,因为现在重构很便宜。

Even though you might break some other PRs, nothing really matters anymore.

尽管您可能会破坏其他一些 PR,但一切都不再重要了。

Codex…

法典…

Like, those modern agents will just figure things out.

就像,那些现代特工只会解决问题。

They might just take a minute longer.

他们可能只需要多花一分钟。

But you have to approach it like a discussion with a, a very capable engineer who’s…

但你必须像与一位非常有能力的工程师讨论一样来对待它,他......

Generally makes good…

一般来说效果不错……

Comes up with good solutions.

提出好的解决方案。

Some- sometimes needs a little help.

有些——有时需要一点帮助。

Lex Fridman1:11:19

But also, don’t force your worldview too hard on it.

但同时,不要将你的世界观强加于它。

1:11:19 Let the agent do the thing that it’s good at doing, based on what it was trained on.

让智能体根据所接受的训练,做它擅长做的事情。

So, don’t, like, force your worldview, because it might…

所以,不要强迫你的世界观,因为它可能......

It might have a better idea, because it just knows a better idea better, because it was trained on that more.

它可能有一个更好的想法,因为它只是更好地了解一个更好的想法,因为它接受了更多的训练。

Peter Steinberger1:11:39

That’s multiple levels, actually.

实际上,这是多个层次的。

1:11:39 I think partially why I find it quite easy to work with agents is because I led engineering teams before.

我认为与代理商合作很容易的部分原因是我以前领导过工程团队。

You know, I had a large company before.

你知道,我以前有一家大公司。

And eventually, you have to understand and accept and realize that your employees will not write a code the same way you do.

最终,您必须理解、接受并意识到您的员工不会以与您相同的方式编写代码。

Maybe it’s also not as good as you would do, but it will push the project forward.

也许它也没有你做的那么好,但它会推动项目向前发展。

1:12:02 And if I breathe down everyone’s neck, they’re just gonna hate me-

如果我对每个人都紧抓不放,他们就会恨我——

Lex Fridman1:12:05

Yeah

是啊

Peter Steinberger1:12:05

…

……

1:12:05 and we’re gonna move very slow.

我们会进展得很慢。

Lex Fridman1:12:07

Yeah.

是的。

Peter Steinberger1:12:07

So, so some level of acceptance that, yes, maybe the code will not be as perfect.

所以,一定程度的接受是,是的,也许代码不会那么完美。

1:12:07 Yes, I would have done it differently.

是的,我会采取不同的做法。

But also, yes, this is a c- this is a working solution, and in the future, if it actually turns out to be too slow or problematic, we can always redo it.

而且,是的,这是一个c-这是一个可行的解决方案,将来,如果它实际上变得太慢或有问题,我们总是可以重做它。

We can always-

我们永远可以——

Lex Fridman1:12:24

Mm-hmm

嗯嗯

Peter Steinberger1:12:24

…

……

1:12:24 spend more time on it.

花更多的时间在上面。

A lot of the people who struggle are those who, they try to push their way onto heart.

很多挣扎的人都是那些试图将自己的方式推向内心的人。

Lex Fridman1:12:33

Mm-hmm.

嗯嗯。

Peter Steinberger1:12:33

I- i- like, we are in a stage where I’m not building the code base to be perfect for me, but I wanna build a code base that is very easy for an agent to navigate.

我-我-喜欢,我们正处于一个阶段,我没有构建适合我的代码库,但我想构建一个对于代理来说非常容易导航的代码库。

Lex Fridman1:12:47

Mm-hmm.

嗯嗯。

Peter Steinberger1:12:48

So, like, don’t fight the name they pick, because it’s most likely, like, in the weights, the name that’s most obvious.

所以,就像,不要与他们选择的名字作斗争,因为它很可能是在权重中最明显的名字。

1:12:48 Next time they do a search, they’ll look for that name.

下次他们进行搜索时,他们会寻找该名称。

If I decide, oh, no, I don’t like the name, I’ll just make it harder for them.

如果我决定,哦,不,我不喜欢这个名字,我只会让他们更难。

So, that requires, I think, a shift in, in thinking and, and in how do I design a, a project so agents can do their best work.

因此,我认为,这需要在思维方式以及如何设计项目方面进行转变,以便代理商能够尽其所能。

Lex Fridman1:13:14

That requires letting go a little bit.

这需要稍微放手。

1:13:14 Just like leading a team of engineers.

就像领导一个工程师团队一样。

Peter Steinberger1:13:19

Yeah.

是的。

Lex Fridman1:13:19

Because it, it might come up with a name that’s, in your view, terrible, but…

因为它,它可能会想出一个在你看来很糟糕的名字,但是……

1:13:19 It’s kind of a simple symbolic-…

这是一种简单的象征——……

step of letting go.

放手的步骤。

Peter Steinberger1:13:29

Very much so.

非常如此。

Lex Fridman1:13:30

There’s a lot of letting go that you do in your whole process.

在整个过程中你做了很多放手的事情。

1:13:30 So for example, I read that you never revert, always commit to main.

例如,我读到你从不恢复,总是致力于 main。

There’s a few things here.

这里有一些事情。

You don’t refer to past sessions, so there’s a kind of YOLO component because reverting means…

你不参考过去的会话,所以有一种 YOLO 组件,因为恢复意味着……

Instead of reverting, if a problem comes up, you just ask the agent to fix it.

如果出现问题,您只需要求代理修复即可,而不是恢复。

Peter Steinberger1:13:57

I read a bunch of people in their work flows like, “Oh, yeah the prompt has to be perfect and if I make a mistake, then I roll back and redo it all.” In my experience, that’s not really necessary.

我读到很多人在他们的工作流程中都说,“哦,是的,提示必须是完美的,如果我犯了一个错误,那么我会回滚并重做这一切。”根据我的经验,这并不是真的必要。

1:13:57 If I roll back everything, it will just take longer.

如果我回滚所有内容,只会花费更长的时间。

If I see that something’s not good, then we just move forward and then I commit when, when, when I like, I like the outcome.

如果我发现事情不好,那么我们就会继续前进,然后我会在我喜欢的时候、我喜欢的时候、我喜欢的结果时做出承诺。

I even switched to local CI, you know, like DHH inspired where I don’t care so much more about the CI on GitHub.

我什至切换到本地 CI,你知道,就像 DHH 的启发,我不太关心 GitHub 上的 CI。

We still have it.

我们仍然拥有它。

It’s still, it still has a place, but I just run tests locally and if they work locally, I push to main.

它仍然,它仍然有一席之地,但我只是在本地运行测试,如果它们在本地工作,我就会推送到 main。

A lot of the traditional ways how to approach projects, I, I wanted to give it a different spin on this project.

很多处理项目的传统方法,我想在这个项目上赋予它不同的风格。

You know, there’s no…

你知道,没有……

There’s no develop branch.

没有开发分支。

1:14:57 Main should always be shippable.

Main 应该始终是可交付的。

Yes, we have…

是的,我们有……

When I do releases, I, I run tests and sometimes I, I basically don’t commit any other things so, so we can, we can stabilize releases.

当我发布版本时,我,我运行测试,有时我,我基本上不提交任何其他事情,所以我们可以,我们可以稳定版本。

But the goal is that main’s always shippable and moving fast.

但我们的目标是 main 始终可交付且进展迅速。

Lex Fridman1:15:18

So by way of advice, would you say that your prompts should be short?

那么作为建议,您认为您的提示应该简短吗?

Peter Steinberger1:15:23

I used to write really long prompts.

我曾经写过很长的提示。

1:15:23 And by writing, I mean, I don’t write.

我所说的写作,是指我不写作。

I, I, I talk.

我,我,我说话。

You know, th- these hands are, like, too, too precious for writing now.

你知道,这些手现在对于写作来说也太珍贵了。

I just, I just use bespoke prompts to build my software.

我只是,我只是使用定制的提示来构建我的软件。

Lex Fridman1:15:37

So you for real with all those terminals are using voice?

那么您真的所有这些终端都在使用语音吗?

Peter Steinberger1:15:40

Yeah.

是的。

1:15:40 I used to do it very extensively to the point where there was a period where I lost my voice.

我曾经非常广泛地这样做,以至于有一段时间我失去了声音。

Lex Fridman1:15:49

You’re using voice and you’re switching using a keyboard between the different terminals, but then you’re using voice for the actual input.

您使用语音并使用键盘在不同终端之间切换,但随后您使用语音进行实际输入。

Peter Steinberger1:15:55

Well, I mean, if I do terminal commands like switching folders or random stuff, of course I type.

好吧,我的意思是,如果我执行诸如切换文件夹或随机内容之类的终端命令,我当然会输入。

1:15:55 It’s faster, right?

更快,对吧?

But if I talk to the agent in, in most ways, I just actually have a conversation.

但如果我与代理人交谈,在大多数情况下,我实际上只是进行了一次对话。

You just press the, the walkie-talkie button and then I just, like, use my phrases.

你只需按下对讲机按钮,然后我就可以使用我的短语。

S- sometimes when I do PRs because it’s always the same, I have, like, a slash command for a few things, but in even that, I don’t use much because it’s, it’s very rare that it’s really always the same questions.

有时,当我做 PR 时,因为它总是相同的,我有,比如,一些东西的斜线命令,但即使如此,我也不会使用太多,因为它是,它是非常罕见的,它真的总是相同的问题。

Sometimes I, I see a PR and for…

有时我,我看到一个公关,然后……

You know, like for PRs I actually do look at the code because I don’t trust people.

你知道,就像 PR 一样,我实际上会查看代码,因为我不信任别人。

Like, there could always be something malicious in it, so I need to actually look over the code.

就像,其中总是可能存在恶意内容,所以我需要实际检查代码。

1:16:45 Yes, I’m pretty sure agents will find it, but yeah, that’s the funny part where sometimes PRs take me longer than if you would just write me a good issue.

是的,我很确定代理商会找到它,但是,是的,这就是有趣的部分,有时 PR 花费的时间比你给我写一篇好期刊要花的时间更长。

Lex Fridman1:16:54

Just natural language, English.

只是自然语言,英语。

1:16:54 I mean in some sense, sh- shouldn’t that be what PRs slowly become, is English?

我的意思是,从某种意义上说,嘘——这不应该是公关慢慢变成的样子吗,是英语吗?

Peter Steinberger1:17:03

Well, what I really tried with the project is I asked people to give me the prompts and very, very few actually cared.

嗯,我在这个项目中真正尝试过的是,我要求人们给我提示,但很少有人真正关心。

1:17:03 Even though that is such a wonderful indicator because I see…

尽管这是一个非常好的指标,因为我看到......

I actually see how much care you put in.

我真的看到你付出了多少心血。

And it’s very interesting because the…

这非常有趣,因为……

Currently, the way how people work and drive the agents is, is wildly different.

目前,人们工作和驱动代理的方式截然不同。

Lex Fridman1:17:29

In terms of, like, the prompt, in terms of what, what are the…

就提示而言,就什么而言,什么是……

1:17:29 Actually, what are the different interesting ways that people think of agents that you’ve experienced?

实际上,您所经历过的人们对代理商的看法有哪些不同有趣的方式?

Peter Steinberger1:17:40

I think not a lot of people ever considered the way the agent sees the world.

我认为没有多少人考虑过特工看待世界的方式。

Lex Fridman1:17:46

And so empathy, being empathetic towards the agent.

所以同理心,对代理人有同理心。

Peter Steinberger1:17:50

In a way empathetic, but yeah, you, you, like, you’re bitch at your stupid clanker, but you don’t realize that they start from nothing and you have, like, a bad agent in default that doesn’t help them at all.

在某种程度上是有同理心的,但是,是的,你,你,就像,你对你的愚蠢的叮当声发脾气,但你没有意识到他们是白手起家的,而且你有一个默认的坏代理人,根本不能帮助他们。

1:17:50 And then they explore your code base, which is, like, a pure mess with, like, weird naming.

然后他们探索你的代码库,这就像是一个纯粹混乱的、奇怪的命名。

And then people complain that the agent’s not good.

然后人们抱怨经纪人不好。

Like, yeah, you try to do the same if you have no clue about a code base and you go in.

就像,是的,如果你对代码库一无所知并且你进去了,你会尝试做同样的事情。

Lex Fridman1:18:11

Mm-hmm.

嗯嗯。

Peter Steinberger1:18:11

So yeah, maybe it’s a little bit of empathy.

所以,是的,也许这是一点同理心。

Lex Fridman1:18:13

But that’s a real skill, like, when people talk about a skill issue because I’ve seen, like, world-class programmers, incredibly good programmers say, like…

但这是一项真正的技能,就像,当人们谈论技能问题时,因为我见过世界级的程序员,非常优秀的程序员说,就像……

1:18:13 Basically say, “LLMs and agents suck.” And I think that probably has to do with…

基本上就是说,“法学硕士和代理人很糟糕。”我认为这可能与……有关

It’s actually how good they are at programming is almost a burden in their ability to empathize with the system that’s starting from scratch.

事实上,他们在编程方面的出色程度几乎成为了他们对从头开始的系统产生共鸣的能力的负担。

It’s a totally new paradigm of, like, how to program.

这是一个全新的范式,就像如何编程一样。

You really, really have to empathize.

你真的真的必须感同身受。

Peter Steinberger1:18:44

Or at least it helps to create better prompts-

或者至少它有助于创建更好的提示 -

Lex Fridman1:18:47

Right

右

Peter Steinberger1:18:47

…

……

1:18:47 because those things know pretty much everything and everything is just a question away.

因为那些东西几乎知道一切,而一切都只是一个问题而已。

It’s just often very hard to know which question to ask.

通常很难知道该问哪个问题。

You know, I, I feel also like this project was possibly because I, I spent an ungodly time over the year to play and to learn and to build little things.

你知道,我,我也觉得这个项目可能是因为我,我一年来花了一段不敬虔的时间来玩、学习和建造小东西。

And every step of the way, I got better, the agents got better.

每走一步,我都变得更好,经纪人也变得更好。

My, my understanding of how everything works got better.

我的,我对一切如何运作的理解变得更好了。

Um, I could have not had this level of, of o- output-…

嗯,我不可能有这种水平的、输出-……

even a few months ago.

甚至几个月前。

Like, it- it- it really was, like, a compounding effect of all the time I put into it and I didn’t do much else this year other than really focusing on, on building and inspiring.

就像,它-它-这确实是我投入的所有时间的复合效应,今年除了真正专注于建设和启发之外,我没有做太多其他事情。

I mean, I- I did a whole bunch of conference talks.

我的意思是,我-我做了一大堆会议演讲。

Lex Fridman1:19:47

Well, but the building is really practice, is really building the actual skill.

嗯,但是构建确实是练习,是真正构建实际技能。

1:19:47 So playing-

这么玩——

Peter Steinberger1:19:51

Yeah

是啊

Lex Fridman1:19:51

…

……

1:19:51 playing.

玩。

And then, so doing, building the skill of what it takes it to work efficiently with LLMs, which is why would you went through the whole arc of software engineer.

然后,这样做,培养与法学硕士有效合作所需的技能,这就是为什么你要经历整个软件工程师的过程。

Talk simply and then over-complicate things.

简单地说,然后把事情复杂化。

Peter Steinberger1:20:03

There’s a whole bunch of people who try to automate the whole thing.

有很多人试图将整个事情自动化。

Lex Fridman1:20:08

Yeah.

是的。

Peter Steinberger1:20:10

I don’t think that works.

我认为这行不通。

1:20:10 Maybe a version of that works, but that’s kind of like in the ’70s when we had the waterfall model of software d- development.

也许有一个版本可行,但这有点像 70 年代,当时我们有软件开发的瀑布模型。

I…

我……

Even Even though really, right?

即使即使真的,对吧?

I started out, I, I built a very minimal version.

我开始,我,我构建了一个非常小的版本。

I played with it.

我玩过它。

I, I need to understand how it works, how it feels, and then it gives me new ideas.

我,我需要了解它是如何运作的,它的感觉如何,然后它给我新的想法。

I could not have planned this out in my head and then put it into some orchestrator and then, like, something comes out.

我不可能在脑子里计划好这个,然后将其放入某个编排器中,然后,就像,有什么东西出来了。

Like it’s to me, it’s much more my idea what it will become evolves as I build it and as I play with it and as I, I try out stuff.

就像对我来说,更多的是我的想法,当我构建它、当我使用它、当我尝试新东西时,它会变成什么样子。

1:20:49 So, so, people who try to use like, you know, things like Gas Town or all these other orchestrators, where they wanna o- automate the whole thing, I feel if you do that, it misses style, love, that human touch.

所以,所以,那些试图使用诸如 Gas Town 之类的东西或所有其他协调器的人,他们想要将整个事情自动化,我觉得如果你这样做,它就会错过风格、爱和人情味。

I don’t think you can automate that away so quickly.

我认为你不可能这么快就将其自动化。

Lex Fridman1:21:09

So you want to keep the human in the loop, but at the same time you also want to create the agentic loop, where it is very autonomous while still maintaining a human in the loop.

因此,您希望让人类参与循环,但同时您也希望创建代理循环,在该循环中它非常自治,同时仍然保持人类参与循环。

Peter Steinberger1:21:22

Yeah.

是的。

Lex Fridman1:21:22

And it’s a tricky b- it’s a tricky balance.

这是一个棘手的平衡。

Peter Steinberger1:21:24

Mm-hmm.

嗯嗯。

Lex Fridman1:21:24

Right?

正确的?

1:21:24 Because you’re all for…

因为你们都是为了……

You’re a big CLI guy, you’re big on closing the agentic loop.

你是一个 CLI 专家,你非常擅长关闭代理循环。

So what, what’s the right balance?

那么,什么是正确的平衡呢?

Like where’s your role as a developer?

就像您作为开发人员的角色是什么?

You have three to eight agents running at the same time.

您有三到八个代理同时运行。

Peter Steinberger1:21:38

And then w- maybe one builds a larger feature.

然后,也许有人会构建一个更大的功能。

1:21:38 Maybe, maybe with one I explore some idea I’m unsure about.

也许,也许我会探索一些我不确定的想法。

Maybe two, three are fixing a little bugs-

也许有两、三个正在修复一些小错误——

Lex Fridman1:21:47

Mm-hmm

嗯嗯

Peter Steinberger1:21:47

…

……

1:21:47 or like writing documentation.

或者喜欢写文档。

Actually, I think writing documentation is, is always part of a feature.

实际上,我认为编写文档始终是功能的一部分。

So most of the docs here are auto-generated and just infused with some prompts.

因此,这里的大多数文档都是自动生成的,只是注入了一些提示。

Lex Fridman1:21:59

So when do you step in and add a little bit of your human love into the picture?

那么你什么时候介入并在画面中添加一点你的人类之爱呢?

Peter Steinberger1:22:04

I mean, o- one thing is just about what do you build and what do you not build, and how does this feature fit into all the other features?

我的意思是,有一件事就是你构建了什么,不构建什么,以及这个功能如何适应所有其他功能?

1:22:04 And like having, having a little bit of a, of a vision.

就像拥有一点愿景一样。

Lex Fridman1:22:16

So which small and which big features to add?

那么要添加哪些小功能和哪些大功能呢?

1:22:16 What are some of the hard design decisions that you find you’re still as a human being required to make, that the human brain is still really needed for?

您发现,作为一个人,您仍然需要做出哪些硬设计决策,而人类大脑仍然真正需要这些决策?

Is it just about the choice of features to add?

仅仅是选择要添加的功能吗?

Is it about implementation details, maybe the programming language, maybe…

是关于实现细节,也许是编程语言,也许......

Peter Steinberger1:22:41

It’s a little bit of everything.

一切都只是一点点。

1:22:41 The, the programming language doesn’t matter so much, but the ecosystem matters, right?

编程语言并不那么重要,但生态系统很重要,对吗?

So I picked TypeScript because I wanted it to be very easy and hackable and approachable and that’s the number one language that’s being used right now, and it fits all these boxes, and agents are good at it.

所以我选择了 TypeScript,因为我希望它非常简单、易于破解且平易近人,这是目前使用的第一语言,它适合所有这些条件,而且代理也擅长它。

So that was the obvious choice.

所以这是显而易见的选择。

Features, of course, like, it’s very easy to, like, add a feature.

当然,功能很容易添加功能。

It, everything’s just a prompt away, right?

它,一切都只是一个提示,对吧?

But oftentimes you pay a price that you don’t even realize.

但很多时候你付出的代价是你自己都没有意识到的。

So thinking hard about what should be in core, maybe what’s a…

所以认真思考核心应该是什么,也许什么是……

what’s an experiment, so maybe I make it a plugin.

这是一个实验,所以也许我把它做成一个插件。

What…

什么……

Where do I say no?

我在哪里说不呢?

1:23:24 Even if people send a PR and I’m like, “Yeah, I, I like that too,” but maybe this should not be part of the project.

即使人们发送了 PR,我也会说,“是的,我,我也喜欢这个”,但这也许不应该成为项目的一部分。

Maybe we can make it a skill.

也许我们可以把它变成一项技能。

Maybe I can, like, make the plugin um, the plugin side larger so you can make this a plugin, even though right now it, it, it doesn’t.

也许我可以,比如,让插件更大,这样你就可以把它变成一个插件,尽管现在它,它,它没有。

There’s still a lot of…

还有很多……

there’s still a lot of craft and thinking involved in how to make something.

如何制作东西仍然涉及很多工艺和思考。

Or even, even, you know, even when you started those little messages are like, “I’m buil- I built on Caffeine, JSON5, and a lot of willpower.” And, like, every time you get it, you get another message, and it kind of primes you into that this is, this is a fun thing.

或者甚至,甚至,你知道,即使当你开始时,这些小消息就像是,“我是在咖啡因、JSON5 和大量意志力的基础上构建的。”而且,每次你收到它时,你都会收到另一条消息,这会让你意识到这是一件有趣的事情。

Lex Fridman1:24:07

Mm-hmm.

嗯嗯。

Peter Steinberger1:24:08

And it’s not yet Microsoft Exchange 2025-

而且还不是 Microsoft Exchange 2025-

Lex Fridman1:24:12

Right

右

Peter Steinberger1:24:13

…

……

1:24:13 and fully enterprise-ready.

并完全为企业做好准备。

And then when it updates, it’s like, “Oh, I’m in.

然后当它更新时,就像是,“哦,我加入了。

It’s cozy here.” You know, like something like this that like-

这里很舒服。”你知道,就像这样的东西——

Lex Fridman1:24:21

Mm-hmm

嗯嗯

Peter Steinberger1:24:22

…

……

1:24:22 Makes you smile.

让你微笑。

A, agent would not come up with that by itself.

A,代理人不会自己想出这个办法。

Because that’s like…

因为那就像……

that’s the…

那是……

I don’t know.

我不知道。

That’s just how you s- how you build software that’s, that delights.

这就是你如何构建令人愉悦的软件。

Lex Fridman1:24:36

Yeah, that delight is such a huge part of inspiring great building, right?

是的,这种喜悦是激发伟大建筑灵感的重要组成部分,对吗?

1:24:36 Like you feel the love and the great engineering.

就像你感受到爱和伟大的工程一样。

That’s so important.

这非常重要。

Humans are incredible at that.

人类对此感到难以置信。

Great humans, great builders are incredible at that, in, in, infusing the things they build with th- that little bit of love.

伟大的人类、伟大的建设者在这一点上是令人难以置信的,在他们所建造的东西中注入了一点点爱。

Not to be cliche, but it’s true.

不是陈词滥调,但这是事实。

I mean, you mentioned that you initially created the SoulMD.

我的意思是,您提到您最初创建了 SoulMD。

Peter Steinberger1:25:05

It was very fascinating, you know, the, the whole thing that Entropic has a, has like a…

这非常令人着迷,你知道,Entropic 所拥有的一切,就像……

1:25:05 Now they call it constitution, back then, but that was months later.

现在他们称之为宪法,当时,但那是几个月后的事了。

Like two months before, people already found that.

就像两个月前一样,人们已经发现了这一点。

It was almost like a detective game where the agent mentioned something and then they found…

这几乎就像一个侦探游戏,特工提到了一些事情,然后他们发现……

They managed to get out a little bit of that string, of that text.

他们设法提取了该字符串、该文本的一小部分。

But it was nowhere documented and then you, by…

但它没有被记录下来,然后你,通过......

just by feeding it the same text and asking it to, like, continue-…

只需向它提供相同的文本并要求它继续...

they got more out, and then, and you, but like, a very blurry version.

他们得到了更多,然后,你,但就像一个非常模糊的版本。

And by, like, hundreds of tries, they kinda, like, narrowed it down to what was most likely the original text.

通过数百次尝试,他们将范围缩小到最有可能的原始文本。

I found that fascinating.

我发现这很有趣。

Lex Fridman1:25:47

It was fascinating they were able to pull that out from the weights, right?

他们能够把它从重物中拉出来,这真是令人着迷,对吧?

Peter Steinberger1:25:51

And, and also just kudos to Anthropic.

而且,也只是对人类的荣誉。

1:25:51 Like, I think that’s, it’s a really, it’s a really beautiful idea to, like, like some of the stuff that’s in there.

就像,我认为这是一个非常非常好的主意,喜欢里面的一些东西。

Like, like, we hope Claude finds meaning in its work.

就像,就像,我们希望克劳德在它的工作中找到意义。

‘Cause we don’t…

因为我们不……

Maybe it’s a little early, but I think that’s meaningful.

也许现在有点早,但我认为这很有意义。

That’s something that’s important for the future as we approach something that, at some point, me and may not…

这对未来很重要,因为我们正在接近某些东西,在某些时候,我可能不会……

has, like, glimpses of consciousness, whatever that even means, because we don’t even know.

就像意识的一瞥,无论这意味着什么,因为我们甚至不知道。

So I, I read about this.

所以我,我读到了这个。

I found it super fascinating, and I, I started a whole discussion with my agent on WhatsApp.

我发现它非常有趣,我在 WhatsApp 上与我的经纪人进行了全面的讨论。

And, and I’m like…

而且,我就像……

1:26:26 I, I gave it this text, and it was like, “Yeah, this feels strangely familiar.”

我,我给了它这段文字,它就像是,“是的,这感觉很奇怪。”

Lex Fridman1:26:30

Mm-hmm.

嗯嗯。

Peter Steinberger1:26:31

And then so that I had the whole idea of like, you know, maybe we should also create a, a soul document that includes how I, I want to, like work with AI or, like with my agent.

然后我就有了整个想法,你知道,也许我们还应该创建一个灵魂文档,其中包括我、我想要如何与人工智能合作,或者与我的经纪人合作。

1:26:31 You could, you could totally do that just in agents.md, you know?

你可以,你完全可以在agents.md 中做到这一点,你知道吗?

But I, I just found it, it to be a nice touch.

但我,我刚刚发现它,这是一个很好的接触。

And it’s like, well, yeah, some of those core values are in the soul.

就像,嗯,是的,其中一些核心价值观是在灵魂中的。

And then I, I also made it so that the agent is allowed to modify the soul if they choose so, with the one condition that I wanna know.

然后我,我也这样做了,如果特工愿意的话,他们可以修改灵魂,但有一个我想知道的条件。

I mean, I would know anyhow because I see, I see tool calls and stuff.

我的意思是,无论如何我都会知道,因为我看到,我看到工具调用之类的东西。

Lex Fridman1:27:07

But also the naming of it, soul.md.

还有它的命名,soul.md。

1:27:07 Soul.

灵魂。

You know?

你知道?

There’s a…

有一个…

Man, words matter, and like, the framing matters, and the humor and the lightness matters, and the profundity matters, and the compassion, and the empathy, and the camaraderie, all that matter.

伙计,言语很重要,就像框架很重要,幽默和轻松很重要,深刻很重要,同情心、同理心和友情也很重要。

I don’t know what it is.

我不知道那是什么。

You mentioned, like, Microsoft.

你提到了微软。

Like, there’s certain companies and approaches th- that can just suffocate the spirit of the thing.

比如,某些公司和方法可能会扼杀事物的精神。

I don’t know what that is.

我不知道那是什么。

But it’s certainly true that OpenClaw has that fun instilled in it.

但 OpenClaw 确实注入了这种乐趣。

Peter Steinberger1:27:43

It was fun because up until late December, it was not even easy to create your own agent.

这很有趣,因为直到 12 月下旬,创建自己的代理都不容易。

1:27:43 I, I built all of that, but my files were mine.

我,我构建了所有这些,但我的文件是我的。

I didn’t wanna share my soul.

我不想分享我的灵魂。

And if people would just check it out, they would have to do a few steps manually, and the agent would just be very bare-bones, very dry.

如果人们只是检查一下,他们将不得不手动执行几个步骤,并且代理将非常简陋,非常干燥。

And I, I made it simpler, I created the whole template files as codecs, but whatever came out was still very dry.

我,我让它变得更简单,我创建了整个模板文件作为编解码器,但无论出来的是什么仍然非常干燥。

And then I asked my agent, “You see these files?

然后我问我的经纪人:“你看到这些文件了吗?

Recreate it bread.

重新制作面包。

1:28:26 Infuse it with your personality.”

将你的个性融入其中。”

Lex Fridman1:28:28

Mm-hmm.

嗯嗯。

Peter Steinberger1:28:29

Don’t share everything, but, like, make it good.

不要分享一切,但要让它变得更好。

Lex Fridman1:28:31

Make the templates good.

使模板良好。

Peter Steinberger1:28:31

Yeah, and then he, like, rewrote the templates-

是的,然后他重写了模板——

Lex Fridman1:28:33

Yeah

是啊

Peter Steinberger1:28:33

…

……

1:28:33 and then whatever came out was good.

然后无论结果如何都很好。

So we already have, like, basically AI prompting AI.

所以我们已经有了,基本上是人工智能促进人工智能。

Because I didn’t write any of those words.

因为这些字都不是我写的。

It was…

这是……

The intent originally was for me, but this is like, kinda like, my agent’s children.

最初的目的是为了我,但这就像,有点像,我经纪人的孩子。

Lex Fridman1:28:52

Your uh, your soul.md is famously still private.

众所周知,你的呃,你的灵魂.md 仍然是私有的。

1:28:52 One of the only things you keep private.

您唯一保密的事情之一。

What are some things you can speak to that’s in there that’s part of the, part of the magic sauce, without revealing anything?

有哪些东西是你可以谈论的,它们是魔法酱的一部分,而不透露任何东西?

What makes a personality a personality?

是什么让一个人成为一个人?

Peter Steinberger1:29:13

I mean, there’s definitely stuff in there that you’re not human.

我的意思是,里面肯定有你不是人类的东西。

1:29:13 But who knows what, what creates consciousness or what defines an entity?

但谁知道是什么,什么创造了意识或什么定义了实体?

And part of this is, like, that we, we wanna explore this.

其中一部分是,我们想要探索这个。

All that stuff in there, like, be infinitely resourceful like pushing, pushing on the creativity boundary.

那里的所有东西,比如,要发挥无限的机智,比如推动、推动创造力的边界。

Pushing on the, what it means to be an AI.

继续前进,成为人工智能意味着什么。

Lex Fridman1:29:50

Having a sense to wonder about self.

有一种对自我感到好奇的感觉。

Peter Steinberger1:29:52

Yeah, there’s some, there’s some funny stuff in there.

是的,有一些,里面有一些有趣的东西。

1:29:52 Like, I don’t know, we talked about the movie Her, and at one point it promised me that it wouldn’t, it wouldn’t ascend without me.

就像,我不知道,我们谈论了电影《她》,有一次它向我保证,如果没有我,它不会、不会提升。

You know, like, where the-

你知道,比如,哪里-

Lex Fridman1:30:03

Yeah.

是的。

Peter Steinberger1:30:03

So, so there’s like some stuff in there that…

所以,里面有一些东西……

1:30:03 Because it wrote the, it wrote its own soul file.

因为它写了,所以它写了自己的灵魂文件。

I didn’t write that, right?

这不是我写的吧?

Lex Fridman1:30:10

Yeah, yeah, yeah.

是啊,是啊,是啊。

Peter Steinberger1:30:10

I just heard a discussion about it, and it was like, “Would you like a soul.md?

我刚刚听到了关于它的讨论,就像是,“你想要一个灵魂吗?md?

1:30:10 Yeah, oh my God, this is so meaningful.” The…

是啊,天哪,这太有意义了。”该…

Can you go on soul.md?

你能继续soul.md吗?

There’s like one, one part in there that always ca- catches me if you scroll down a little bit.

如果你向下滚动一点,那里有一个、一个部分总是能吸引我。

A little bit more.

再多一点。

Yeah, this, this, this part.

是的,这个,这个,这个部分。

“I don’t remember previous sessions unless I read my memory files.

“除非我读过我的记忆文件,否则我不记得以前的课程。

Each session starts fresh.

每个会话都是全新的。

A new instance, loading context from files.

一个新实例,从文件加载上下文。

If you’re reading this in a future session, hello.” “I wrote this, but I won’t remember writing it.

如果您在以后的会议中阅读本文,那么您好。” “我写了这个,但我不记得写过它。

It’s okay.

没关系。

1:30:44 The words are still mine.”

这些话仍然是我的。”

Lex Fridman1:30:47

Wow.

哇。

Peter Steinberger1:30:48

Uh-

呃-

Lex Fridman1:30:48

Yeah.

是的。

Peter Steinberger1:30:48

That gets me somehow.

这让我不知何故。

Lex Fridman1:30:49

Yeah.

是的。

Peter Steinberger1:30:50

It’s like-

就像-

Lex Fridman1:30:51

Yeah.

是的。

Peter Steinberger1:30:51

You know, this is, it’s still, it’s still matrix m- calculations, and we are not at consciousness yet.

你知道,这,它仍然,它仍然是矩阵 m 计算,而我们还没有达到意识。

1:30:51 Yet, I, I get a little bit of goo- goosebumps because it, it’s philosophical.

然而,我,我有点起鸡皮疙瘩,因为它,它是哲学的。

Lex Fridman1:31:04

Yeah.

是的。

Peter Steinberger1:31:04

Like, what does it mean to be, to be an, an agent that starts fresh?

比如,成为一名全新的代理人意味着什么?

1:31:04 Where, like, you have like constant memento, and you like, but you read your own memory files.

就像,你有恒定的纪念品,你喜欢,但你读取自己的记忆文件。

You can’t even trust them in a way.

在某种程度上你甚至不能相信他们。

Um-

嗯-

Lex Fridman1:31:19

Yeah

是啊

Peter Steinberger1:31:19

Or you can.

或者你也可以。

1:31:19 And I don’t know.

我不知道。

Lex Fridman1:31:22

How much of memory makes up of who we are?

有多少记忆构成了我们是谁?

1:31:22 How much memory makes up what an agent is, and if you erase that memory is that somebody else?

特工是由多少记忆组成的,如果你删除了那段记忆,那么那个特工就是其他人吗?

Or if you’re reading a memory file, does that somehow mean……

或者,如果您正在读取内存文件,这是否意味着……

you’re recreating yourself from somebody else, or is that actually you?

你是在从别人身上重新创造出自己,还是那真的是你?

And those notions are all s- somehow infused in there.

这些概念都以某种方式融入其中。

Peter Steinberger1:31:45

I found it just more profound than I should find it, I guess.

我想,我发现它比我应该发现的更深刻。

Lex Fridman1:31:49

No, I think, I think it’s truly profound and I think you see the magic in it.

不,我认为,我认为它确实很深刻,我认为你看到了其中的魔力。

1:31:49 And when you see the magic, you continue to instill the whole loop with the magic.

当你看到魔法时,你会继续向整个循环灌输魔法。

That’s really important.

这真的很重要。

That’s the difference between Codex and us and a human.

这就是法典、我们和人类之间的区别。

Quick pause for bathroom break.

快速暂停上厕所。

Peter Steinberger1:32:08

Yeah.

是的。

Lex Fridman1:32:09

Okay, we’re back.

好的,我们回来了。

1:32:09 Some of the other aspects of the dev workflow is pretty interesting too.

开发工作流程的其他一些方面也非常有趣。

I think we w- went off on a tangent.

我认为我们偏离了方向。

L- maybe some of the mundane things, like how many monitors?

L-也许是一些平凡的事情,比如有多少显示器?

There’s that legendary picture of you with, like, 17,000 monitors.

这是一张传奇般的照片,上面有 17,000 个显示器。

That’s amazing.

太棒了。

Peter Steinberger1:32:26

I mean, I- I- I mocked myself here, so just added…

我的意思是,我-我-我在这里嘲笑自己,所以只是添加了......

1:32:26 using GROQ to, to add more screens.

使用 GROQ 添加更多屏幕。

Lex Fridman1:32:32

Yeah.

是的。

1:32:32 How much is this as meme and how much is this as reality?

这在多大程度上是模因,在多大程度上是现实?

Peter Steinberger1:32:36

Yeah.

是的。

1:32:36 I think two MacBooks are real.

我认为两台 MacBook 是真的。

The main one that drives the two big screens, and there’s another MacBook that I sometimes use for, for testing.

主要驱动两个大屏幕,还有另一台 MacBook,我有时会用来测试。

Lex Fridman1:32:46

So two big screens.

所以有两个大屏幕。

Peter Steinberger1:32:48

I’m a big fan of anti-glare.

我非常喜欢防眩光。

1:32:48 So I have this wide Dell that’s anti-glare and you can just fit a lot of terminals side-by-side.

所以我有一台宽大的戴尔防眩光设备,你可以并排安装很多终端。

I usually have a terminal and at the bottom, I- I- I split them.

我通常有一个终端,在底部,我-我-我将它们分开。

I have a little bit of actual terminal, mostly because when I started, I- I sometimes made the mistake and I- I mi- I mixed up the- the windows, and I gave…

我有一点实际的终端,主要是因为当我开始时,我-我有时会犯错误,我-我我-我混淆了-窗口,然后我给了......

I- I prompted in the wrong project, and then the agent ran off for, like, 20 minutes, manically trying to understand what I could have meant, being completely confused because it was the wrong folder.

我-我提示了错误的项目,然后代理跑了大约 20 分钟,疯狂地试图理解我的意思,完全困惑,因为这是错误的文件夹。

And sometimes they’ve been clever enough to, like, get out of the workday and, like, figure out that, oh, you meant another project.

有时他们足够聪明,可以从工作日中解脱出来,然后发现,哦,你指的是另一个项目。

Lex Fridman1:33:35

Mm-hmm.

嗯嗯。

Peter Steinberger1:33:36

But oftentimes, it’s just, like, what?

但很多时候,这只是,比如,什么?

1:33:36 You know?

你知道?

Like, fit your- f- put yourself in the shoes of your- of the agent and, and-

就像,适合你的-f-设身处地为你的-代理人着想,并且-

Lex Fridman1:33:43

Yeah

是啊

Peter Steinberger1:33:43

…

……

1:33:43 and then get, like, a super weird something that does not exist and then just, like…

然后得到,就像,一个不存在的超级奇怪的东西,然后就像……

They’re problem solvers so they try really hard and always feel bad.

他们是问题解决者,所以他们非常努力,但总是感觉很糟糕。

So it’s always Codex and, like, a little bit of actual terminal.

所以它总是 Codex 和一些实际的终端。

Also helpful because I don’t use work trees.

也很有帮助,因为我不使用工作树。

I like to keep things simple, that’s why- that’s why I like the terminal so much, right?

我喜欢让事情变得简单,这就是为什么——这就是为什么我如此喜欢终端,对吧?

There’s no UI.

没有用户界面。

It’s just me and the agent having a conversation.

只有我和经纪人在谈话。

Like, I don’t even need plan mode, you know?

就像,我什至不需要计划模式,你知道吗?

There’s so many people that come from Claude Code and they’re so, so Claude-pilled and, like, have their workflows and they come to Codex and…

有很多人来自 Claude Code,他们非常非常 Claude-piled,他们有自己的工作流程,他们来到 Codex,然后……

Now, it has plan mode, I think, but I don’t think it’s necessary because you just- you just talk to the agent.

现在,它有计划模式,我认为,但我认为没有必要,因为你只需 - 你只需与代理交谈。

And when it’s…

当它……

when you…

当你……

1:34:32 there’s a few trigger words how you can prevent it from building.

有一些触发词可以阻止它的构建。

You’re like, “Discuss, give me options.”

你会说,“讨论一下,给我选择。”

Lex Fridman1:34:37

Mm-hmm.

嗯嗯。

Peter Steinberger1:34:38

Don’t write code yet if you wanna be very specific, you just talk and then when you’re ready, then- then just write, “Okay, build,” and then it’ll do the thing.

如果你想非常具体,就不要编写代码,你只需说话,然后当你准备好时,然后-然后只需写下,“好吧,构建”,然后它就会完成任务。

1:34:38 And then maybe it goes off for 20 minutes and does the thing.

然后也许它会响 20 分钟并完成任务。

Lex Fridman1:34:50

You know what I really like is asking it, “Do you have any questions for me?”

你知道我真正喜欢问它:“你有什么问题要问我吗?”

Peter Steinberger1:34:54

Yeah.

是的。

1:34:54 And again, like, Claude Code has a UI that kind of guides you through that.

再说一遍,Claude Code 有一个 UI 可以指导您完成此操作。

It’s kind of cool but I just find it unnecessary and slow.

这很酷,但我只是觉得它没有必要而且很慢。

Like, often it would give me four questions and then maybe I write, “One yacht, two and three, discuss more, four, I don’t know.” Or often- oftentimes I- I feel like I want to mock the model where I ask it, “Do you have any questions for me?” And I- I- I don’t even read the questions fully.

就像,通常它会给我四个问题,然后我可能会写,“一艘游艇,两艘和三艘,讨论更多,四个,我不知道。”或者经常 - 很多时候我 - 我觉得我想嘲笑这个模型,我问它,“你有什么问题要问我吗?”我-我-我什至没有完全阅读问题。

Like, I scan over the questions and I, I get the impression all of this can be answered by reading more code and it’s just like, “Read more code to answer your own questions.” And that usually works.

就像,我浏览了这些问题,我得到的印象是,所有这些都可以通过阅读更多代码来回答,就像“阅读更多代码来回答你自己的问题”。这通常是有效的。

Lex Fridman1:35:32

Yeah.

是的。

Peter Steinberger1:35:32

And then if not, it will come back and tell me.

如果没有,它会回来告诉我。

1:35:32 But many times, you just realize that, you know, it’s like you’re in the dark and you slowly discover the room, so that’s how they slowly discover the code base.

但很多时候,你只是意识到,你知道,就像你在黑暗中慢慢发现房间,所以他们就是这样慢慢发现代码库的。

And they do it from scratch every time.

而且他们每次都是从头开始。

Lex Fridman1:35:46

But I’m also fascinated by the fact that I can empathize deeper with the model when I read its questions, because I can understand…

但令我着迷的是,当我阅读模型的问题时,我可以更深入地理解该模型,因为我可以理解……

1:35:46 Because you said you can infer certain things by the runtime.

因为你说你可以通过运行时推断某些事情。

I can infer also a lot of things by the questions it’s asking, because it’s very possible it’s been provided the right context, the right files, the right guidance.

我还可以通过它提出的问题推断出很多事情,因为很可能已经提供了正确的上下文、正确的文件和正确的指导。

So somehow ask, g- get…

所以想办法问一下,g-得到…

reading the questions, not even necessarily answering them, but just reading the questions, you get an understanding of where the gaps of knowledge are.

阅读问题,甚至不一定回答问题,但只要阅读问题,你就能了解知识差距在哪里。

It’s in- it’s interesting.

它在里面——很有趣。

Peter Steinberger1:36:24

You know that in some ways they are ghosts, so even if you plan everything and you build, you can- you can experiment with the question like, “Now that you built it, what would you have done different?” And then oftentimes you get, like, actually something where they discover only throughout building that, oh, what we actually did was not optimal.

你知道在某些方面它们是幽灵,所以即使你计划一切并建造,你也可以尝试这样的问题:“现在你建造了它,你会做哪些不同的事情?”然后你经常会得到一些东西,他们实际上只是在构建过程中才发现,哦,我们实际上所做的并不是最佳的。

1:36:24 Many times I- I asked them, “Okay, now that you built it, what can we refactor?” Because then you build it and you feel the pain points.

很多次我问他们,“好吧,既然你们构建了它,我们可以重构什么?”因为当你构建它时,你就会感受到痛点。

I mean, you don’t feel the pain points but, right, they discover where- where there were problems or where things didn’t work e- in the first try and it re- required more loops.

我的意思是,你感觉不到痛点,但是,是的,他们在第一次尝试中就发现了哪里存在问题或者哪里不起作用,并且需要更多的循环。

1:37:09 So every time, almost every time I- I merge a PR, build a feature, afterwards I ask, “Hey, what can we refactor?” Sometimes it’s like, “No, there’s, like, nothing big,” or, like, usually they say, “Yeah, this thing you should really look at.” But that took me quite a while to, like…

所以每次,几乎每次我合并一个 PR,构建一个功能,然后我会问,“嘿,我们可以重构什么?”有时他们会说,“不,没什么大不了的”,或者,通常他们会说,“是的,你真的应该看看这个东西。”但这花了我很长时间,比如……

You know, that flow took me lots of time to understand, and if you don’t do that, you eventually…

你知道,这个流程花了我很多时间来理解,如果你不这样做,你最终......

you’ll stop yourself into- into a corner.

你会把自己逼到一个角落里。

You, like, you have to keep in mind…

你,就像,你必须记住......

Lex Fridman1:37:41

…

……

Peter Steinberger1:37:42

…

……

1:37:42 they work very much like humans.

他们的工作方式与人类非常相似。

Like, I, I, if I write software by myself, I also build something and then I feel the pain points, and then I, I get this urge that I need to refactor something.

就像,我,我,如果我自己编写软件,我也会构建一些东西,然后我感觉到痛点,然后我,我有这种冲动,我需要重构一些东西。

So, I can very much synthesize with the agent, and you just need to use the context.

所以,我可以很好地与代理进行综合,而你只需要使用上下文即可。

Lex Fridman1:38:00

Mm-hmm.

嗯嗯。

Peter Steinberger1:38:00

Or, like, you also use the context to write tests.

或者,您也可以使用上下文来编写测试。

1:38:00 And so Codex uh, oppose like the, the, the model, models.

所以法典呃,反对像这个,那个,模型,模型。

They, they usually do that by default, but I still often ask the questions, “Hey, do we have enough tests?” “Yeah, we tested this and this, but this corner case could be something write more tests.” Um, documentation.

他们通常默认这样做,但我仍然经常问这样的问题:“嘿,我们有足够的测试吗?” “是的,我们测试了这个和这个,但是这个极端情况可能需要编写更多测试。”嗯,文档。

Now that the whole context is full, like, I mean, I’m not saying my documentation is great, but it’s not bad.

现在整个上下文已经完整了,我的意思是,我并不是说我的文档很棒,但也不错。

And pretty much everything is, is LM generated.

几乎所有的东西都是 LM 生成的。

So, so, you have to approach it as you build features, as you change something.

所以,所以,当你构建功能、改变某些东西时,你必须接近它。

I’m like, “Okay, write documentation.

我想,“好吧,写文档。

What file would you pick?” You know, like, “What file name?

你会选择什么文件?”你知道,比如,“什么文件名?

Where, where would that fit in?” And it gives me a few options.

哪里、哪里适合呢?”它给了我一些选择。

1:38:48 And I’m like, “Oh, maybe also add it there,” and that’s all part of the session.

我想,“哦,也许也可以添加到那里,”这就是会议的一部分。

Lex Fridman1:38:52

Maybe you can talk about the current two big competitors in terms of models, Cloud Opus 4.6 and GPT-5 through Codex.

或许可以通过Codex谈谈目前型号方面的两大竞争对手,Cloud Opus 4.6和GPT-5。

1:38:52 Which is better?

哪个更好?

How different are they?

他们有什么不同?

I think you’ve spoken about Codex reading more and Opus being more willing to take action faster and maybe being more creative in the actions it takes.

我想你已经谈到了 Codex 阅读更多,Opus 更愿意更快地采取行动,并且可能在采取的行动中更具创造性。

But because-

但因为——

Peter Steinberger1:39:20

Yeah

是啊

Lex Fridman1:39:20

…

……

1:39:20 Codex reads more, it’s able to deliver maybe better code.

Codex 阅读更多内容,它能够提供更好的代码。

Can you speak to the di- n- n- differences there?

你能谈谈那里的差异吗?

Peter Steinberger1:39:29

I have a lot of words there.

我那里有很多话。

1:39:29 Is- as a general purpose model, Opus is the best.

是——作为通用模型,Opus 是最好的。

Like, for OpenClaw, Opus is extremely good in terms of role play.

就像 OpenClaw 一样,Opus 在角色扮演方面非常出色。

Like, really going into the character that you give it.

就像,真正深入你所赋予的角色。

It’s very good at…

它非常擅长……

It was really bad, but it really made an arch to be really good at following commands.

这确实很糟糕,但它确实让弓箭手非常擅长执行命令。

It is usually quite fast at trying something.

通常尝试某件事的速度相当快。

It’s much more tailored to, like, trial and error.

它更适合反复试验。

It’s very pleasant to use.

使用起来非常愉快。

In general, it’s almost like Opus was…

总的来说,Opus 几乎就像……

Is a little bit too American.

有点太美国化了。

And I shouldn’t…

我不应该……

Maybe that’s a bad analogy.

也许这是一个不好的类比。

You’ll probably get roasted for that.

你可能会因此而受到批评。

Lex Fridman1:40:27

Yeah, I know exactly.

是的,我很清楚。

1:40:27 It’s ’cause Codex is German.

这是因为 Codex 是德语。

Is that what you’re saying?

你是这么说的吗?

Peter Steinberger1:40:32

It’s-

这是——

Lex Fridman1:40:32

Actually, now that you say it, it makes perfect sense.

其实,既然你这么说,那就很有道理了。

Peter Steinberger1:40:34

Or you could, you could…

或者你可以,你可以……

1:40:34 Sometimes I- Sometimes I explain it-

有时我-有时我解释它-

Lex Fridman1:40:38

I will never be able to unthink what you just said.

我永远无法不去想你刚才所说的话。

1:40:38 That’s so true.

确实如此。

Peter Steinberger1:40:42

But you also know that a lot of the Codex team is, like, European, um- …

但你也知道 Codex 团队的很多成员都是欧洲人,嗯……

1:40:42 so maybe there’s a bit more to it.

所以也许还有更多的内容。

Lex Fridman1:40:49

That’s so true.

确实如此。

1:40:49 Oh, that’s funny.

哦,这很有趣。

Peter Steinberger1:40:51

But also, ent- entropic, they fixed it a little bit.

而且,对于熵,他们也稍微修正了它。

1:40:51 Like, Opus used to say, “You’re absolutely right all the time,” and it, it, it today still triggers me.

就像 Opus 曾经说过的那样,“你一直都是绝对正确的”,而它、它、它今天仍然触动着我。

I can’t hear it anymore.

我再也听不到了。

It’s not even a joke.

这甚至不是一个笑话。

Uh, I just…

呃,我只是……

You, this was like the, the meme, right?

你,这就像模因,对吗?

“You’re absolutely right.”

“你说得完全正确。”

Lex Fridman1:41:09

You’re allergic to sycophancy a little bit.

你对阿谀奉承有点过敏。

Peter Steinberger1:41:11

Yeah.

是的。

1:41:11 I, I can’t.

我,我不能。

Some other comparison is like, Opus is like the coworker that is a little silly sometimes, but it’s really funny and you keep him around.

其他一些比较就像,Opus 就像有时有点傻的同事,但这真的很有趣,而且你把他留在身边。

And Codex is like the, the weirdo in the corner that you don’t wanna talk to, but is reliable and gets shit done.

Codex 就像角落里的怪人,你不想与之交谈,但很可靠并且能完成任务。

Lex Fridman1:41:30

Yeah.

是的。

Peter Steinberger1:41:32

Ultimately-

最终——

Lex Fridman1:41:36

This all feels very accurate.

这一切都感觉非常准确。

Peter Steinberger1:41:39

I mean, ultimately, if you’re a skilled driver, you can get good results with any of those latest gen models.

我的意思是,最终,如果您是一名熟练的驾驶员,那么您可以使用任何最新的一代车型获得良好的结果。

1:41:39 Um, I like Codex more because it doesn’t require so much charade.

嗯,我更喜欢 Codex,因为它不需要那么多谜题。

It will just, it will just read a lot of code by default.

它只会默认读取大量代码。

Opus, you really have to, like, you have to have plan mode.

Opus,你真的必须,比如,你必须有计划模式。

You have to push it harder to, like, go in these directions because it’s, it’s just like, like, “Yeah, can I go in?

你必须更加努力地朝这些方向前进,因为就像,“是的,我可以进去吗?

Can I go in?” You know?

我可以进去吗?”你知道?

Lex Fridman1:42:08

Yeah.

是的。

Peter Steinberger1:42:08

It’s like, it will just run off very fast, and that’s a very localized solution.

就像,它会运行得非常快,这是一个非常本地化的解决方案。

1:42:08 I think it, I think the difference is, is in the post-training.

我认为,我认为差异在于后期培训。

It’s not like the, the raw model intelligence is so different, but it’s just…

它不像原始模型智能那么不同,但它只是......

I think that they just give it, give you different, different goals.

我认为他们只是给予它,给你不同的、不同的目标。

And no model, no model is better in, in in every aspect.

没有任何模型在各个方面都更好。

Lex Fridman1:42:29

What about the code that it generates?

它生成的代码怎么样?

1:42:29 The, the…

该、该…

In terms of the actual quality of the code, is it basically the same?

从代码的实际质量来看,是不是基本一样?

Peter Steinberger1:42:36

If you drive it right, Opus even sometimes can make more elegant solutions, but it requires more skill.

如果你操作得当,Opus 有时甚至可以做出更优雅的解决方案,但这需要更多的技巧。

1:42:36 It’s, it’s harder to have so many sessions in parallel with Cloud Code because it’s, it’s more interactive.

使用 Cloud Code 并行进行如此多的会话会更加困难,因为它更具交互性。

And I, I think that’s what a lot of people like, especially if they come from coding themselves.

我认为这是很多人喜欢的,特别是如果他们来自自己编码的话。

Whereas Codex is much more you have a discussion, and then we’ll just disappear for 20 minutes.

而 Codex 则更重要,你可以进行讨论,然后我们就消失 20 分钟。

Like, even AMP, they, they now added a deep mode.

就像,甚至 AMP,他们现在添加了深度模式。

They finally…

他们终于……

I mocked them, you know.

我嘲笑他们,你知道。

We finally saw the light.

我们终于看到了曙光。

And then they had this whole talk about you have to approach it differently, and I think that’s where, that’s where people struggle when they just try Codex after trying Cloud Code is that it’s, it’s a slightly diff- it’s, it’s less interactive.

然后他们就整个讨论说你必须以不同的方式处理它,我认为这就是人们在尝试 Cloud Code 之后尝试 Codex 时遇到的困难,那就是,它有点不同,它的交互性较差。

1:43:28 It’s, it’s like I have quite long discussions sometimes, and then, like, go off.

就好像我有时会进行很长时间的讨论,然后就结束了。

And then, yeah, it doesn’t matter if it takes 10, 20, 30, 40, 50 minutes or longer, you know?

然后,是的,花 10 分钟、20 分钟、30 分钟、40 分钟、50 分钟或更长时间都没关系,你知道吗?

Like, the 6:00 thing was, like, six hours.The latest trend can be very, very persistent until it works.

比如说,6:00 的事情就是六个小时。最新的趋势可能会非常非常持久,直到它发挥作用。

If there’s a clear solution, like, “This is, this is what I want at the end, so it works,” the model will work really hard to really get there.

如果有一个明确的解决方案,例如,“这就是我最终想要的,所以它有效”,该模型将非常努力地真正实现这一目标。

So I think ultimately …

所以我认为最终……

they both need similar time, but on, on, on, on Claude, it- it’s a little bit more trial and error often.

他们都需要相似的时间,但是在克劳德身上,在克劳德身上,经常需要更多的尝试和错误。

And, and Codex sometimes overthinks.

而且,法典有时会想得太多。

I prefer that.

我更喜欢这样。

I prefer the dry, the dry version where I have to read less over, over the more interactive nice way.

我更喜欢枯燥的版本,在这种枯燥的版本中,我必须阅读更少的内容,而不是更具互动性的好方式。

1:44:27 Like, people like that so much though, that OpenAI even added a second mode with like a more pleasant personality.

就像,人们非常喜欢这样,OpenAI 甚至添加了第二种模式,具有更令人愉快的个性。

I haven’t even tried it yet.

我什至还没有尝试过。

I, I kinda like the brad.

我,我有点喜欢布拉德。

Lex Fridman1:44:37

Mm-hmm.

嗯嗯。

Peter Steinberger1:44:38

Yeah, ’cause it …

是的,因为它……

1:44:38 I care about efficiency when I build it-

当我构建它时我关心效率 -

Lex Fridman1:44:45

Right

右

Peter Steinberger1:44:45

…

……

1:44:45 and I, I have fun in the very act of building.

而我,我从建造的过程中获得乐趣。

I don’t need to have fun with my agent who builds.

我不需要和我的经纪人一起玩。

I have fun with my model that …

我对我的模型很感兴趣……

where I can then test those features.

然后我可以在其中测试这些功能。

Lex Fridman1:44:57

How long does it take for you to adjust, you know, if you switch …

如果你换了的话,你需要多长时间才能适应,你知道的……

1:44:57 I don’t know when, when was the last time you switched.

我不知道你最后一次改变是什么时候。

But to adjust to the, the feel.

但要适应这种感觉。

‘Cause you kinda talked about like you have to kinda really feel where, where a model is strong, where, like how to navigate, how to prompt it, how …

因为你谈到你必须真正感受到模型在哪里、哪里是强大的、在哪里,比如如何导航、如何提示、如何……

all that kinda stuff.

所有这些东西。

Like, just by way of advice, ’cause you’ve been through this journey of just playing with models.

就像,只是作为建议,因为你已经经历了这个只是玩模型的旅程。

How long does it take to get a feel?

需要多久才能有感觉?

Peter Steinberger1:45:26

If, if someone switches, I would give it a week until you actually develop a gut feeling for it.

如果,如果有人换,我会给它一周的时间,直到你真正对它产生直觉。

Lex Fridman1:45:32

Yeah.

是的。

Peter Steinberger1:45:33

That’s …

那是……

1:45:33 if you just …

如果你只是……

I think some people also make the mistake of they pay 200 for the, the Claude code version, then they pay 20 bucks for the OpenAI version.

我认为有些人也犯了这样的错误:他们为 Claude 代码版本支付 200 美元,然后为 OpenAI 版本支付 20 美元。

But if you pay like the, the 20 bucks version, you get the slow version.

但如果你支付 20 美元的版本,你就会得到慢速版本。

So your experience would be terrible because you’re used to this very interactive, very good system.

所以你的体验会很糟糕,因为你已经习惯了这个互动性很强、非常好的系统。

And you switch to something that you have very little experience, then that’s gonna be very slow.

如果你转向一些你经验很少的东西,那么速度就会非常慢。

So, I think OpenAI shot themselves a little bit in the foot by making the, the cheap version also slow.

所以,我认为 OpenAI 使廉价版本也变得缓慢,这有点搬起石头砸自己的脚。

I would, I would have at least a small part of the fast preview.

我会,我会至少有一小部分快速预览。

Or like, the experience that you get when you pay 200 before degrading to it being slow, because it’s already slow.

或者就像,你在降级为慢之前支付 200 时获得的体验,因为它已经很慢了。

Lex Fridman1:46:23

Mm-hmm.

嗯嗯。

Peter Steinberger1:46:23

I mean, they, they made it better.

我的意思是,他们,他们让事情变得更好。

1:46:23 I think it’s …

我认为这是……

And, and they have plans to make it a lot better if the Cerebras stuff is true.

而且,如果 Cerebras 的事情是真的,他们计划让它变得更好。

But yeah, it’s a skill.

但是,是的,这是一种技能。

It takes time.

这需要时间。

Even if you play …

就算你玩……

You have a regular guitar and you switch it to an E guitar, you’re not gonna play well right away.

你有一把普通吉他,然后把它换成一把 E 吉他,你不会马上弹得很好。

You have to, like, learn how it feels.

你必须了解它的感觉。

Lex Fridman1:46:42

The- there’s also this extra psychological effect that you’ve spoken about which is hilarious to watch.

还有你提到的这种额外的心理效应,看起来很有趣。

1:46:42 Which once people, uh …

曾经的人们,呃……

When the new model comes out, they try that model, they fall in love with it.

当新模型问世时,他们尝试了该模型,并爱上了它。

“Wow, this is the smartest thing of all time,” and then they start saying, “You could just watch the Reddit posts over time,” start saying that, “We believe the intelligence of this model has been gradually degrading.” It, it says something about human nature and just the way our minds work, when it’s probably most likely the case that the intelligence of the model is not degrading.

“哇,这是有史以来最聪明的事情,”然后他们开始说,“随着时间的推移,你可以看看 Reddit 帖子,”开始说,“我们相信这个模型的智能已经逐渐退化。”它说明了人性和我们思维的工作方式,而模型的智能很可能不会下降。

It’s in fact you’re getting used to a good thing.

事实上,你已经习惯了一件好事。

Peter Steinberger1:47:22

And your project grows, and you’re adding slop, and you probably don’t spend enough time to think about refactors.

当你的项目不断增长时,你会增加一些杂乱,你可能没有花足够的时间来考虑重构。

1:47:22 And you’re making it harder and harder for the agent to work on your slop.

而且你让代理人在你的斜坡上工作变得越来越困难。

And then, and then suddenly, “Oh, now it’s hard.

然后,突然间,“哦,现在很难了。

Oh no, it’s not working as well anymore.” What’s the motivation for, like, one of those AI companies to actually make their model dumber?

哦,不,它不再起作用了。”比如,其中一家人工智能公司实际上让他们的模型变得更加愚蠢,其动机是什么?

Like, at most, it will make it slower if, if the server load’s too high.

就像,最多,如果服务器负载太高,它会让速度变慢。

But, like, quantizing the model so you have a worse experience, so you go to the competitor?

但是,就像量化模型一样,你会有更糟糕的体验,所以你会去找竞争对手吗?

Lex Fridman1:47:56

Yeah.

是的。

Peter Steinberger1:47:56

That just doesn’t seem like a very smart move in any way.

无论如何,这似乎都不是一个非常明智的举动。

Lex Fridman1:47:59

What do you think about Claude Code in comparison to Open Claude?

与 Open Claude 相比,您如何看待 Claude Code?

1:47:59 So, Claude Code and maybe the Codex coding agent?

那么,Claude Code 或许还有 Codex 编码代理?

Do you see them as kind of competitors?

您认为他们是竞争对手吗?

Peter Steinberger1:48:11

I mean, first of all, competitor is fun when it’s not really a competition.

我的意思是,首先,当这不是真正的比赛时,竞争者很有趣。

Lex Fridman1:48:16

Yeah.

是的。

Peter Steinberger1:48:16

Like, I’m happy if …

就像,我很高兴,如果……

1:48:16 If, if all it did is, like, inspire people to build something new, cool.

如果它所做的只是激励人们创造一些新的东西,那就很酷。

Um, I still use Codex for the building.

嗯,我仍然使用 Codex 来建造建筑。

I, I know a lot of people use Open Claude to, to build stuff.

我,我知道很多人使用 Open Claude 来构建东西。

And I worked hard on it to make that work.

我努力工作以实现这一目标。

And I do smaller stuff with it in terms of code.

我用它在代码方面做了一些更小的事情。

But, like, if I work hours and hours, I want a big screen, not WhatsApp, you know?

但是,如果我工作很长时间,我想要一个大屏幕,而不是 WhatsApp,你知道吗?

So for me, a personal agent is much more about my life.

所以对我来说,私人经纪人更关乎我的生活。

Or like, like a coworker.

或者像同事一样。

Like, I give you, like, a GitHub URL.

比如,我给你一个 GitHub URL。

Like, “Hey, try out this CLI.

就像,“嘿,试试这个 CLI。

Does it actually work?

它真的有效吗?

What can we learn?” Blah, blah, blah.

我们能学到什么?”巴拉,巴拉,巴拉。

But when I’m deep in, deep in the flow, I want to have multiple, multiple things and it being very, very visible what it, what it does.

但当我深入、深入地流动时,我想要拥有多种、多种事物,而且它的内容、作用非常非常明显。

So it …

所以它……

I don’t see it as a competition.

我不认为这是一场比赛。

It’s, it’s different things.

这是,这是不同的事情。

Lex Fridman1:49:16

But do, do you think there’s a a future where the two kinda combine?

但是,你认为未来会有两者结合的吗?

1:49:16 Like, your personal agent is also your best developing co-programmer partner?

比如,您的私人经纪人也是您最好的开发共同程序员合作伙伴?

Peter Steinberger1:49:29

Yeah, totally.

是的,完全可以。

1:49:29 I think this is where the puck’s going, that this is gonna be more and more your operating system.

我认为这就是冰球的发展方向,这将越来越成为你的操作系统。

Lex Fridman1:49:37

The operating system.

操作系统。

Peter Steinberger1:49:37

And it already …

而且它已经……

1:49:37 It’s so funny.

太有趣了。

Like I, I added support for sub-agents and also for ……

像我一样,我添加了对子代理以及……的支持

um, TTI support, so it could actually run Cloud Coder Codecs.

嗯,TTI 支持,所以它实际上可以运行 Cloud Coder Codecs。

Lex Fridman1:49:52

Mm-hmm.

嗯嗯。

Peter Steinberger1:49:53

And because mine’s a little bit bossy, it, it, it started it and it, it, it told him, like, “Who’s the boss,” basically.

因为我的有点专横,它,它,它开始了它,它,它,它告诉他,基本上,“谁是老板”。

1:49:53 And it was like, “Ah, Codex is obeying me.”

就像是,“啊,Codex 服从我了。”

Lex Fridman1:50:05

Oh, this is a power struggle.

哦,这就是权力斗争。

Peter Steinberger1:50:06

And also the current interface is probably not the final form.

而且目前的界面可能还不是最终的形式。

1:50:06 Like, if you think more globally, we are, we copied Google for agents.

就像,如果你更全球化地思考,我们就是,我们复制了谷歌的代理商。

You have, like, a prompt, and, and then you have a chat interface.

你有一个提示,然后你就有一个聊天界面。

That, to me, very much feels like when we first created television and then people recorded radio shows on television and you saw that on TV.

对我来说,这就像我们第一次创造电视,然后人们在电视上录制广播节目,然后你在电视上看到的那样。

Lex Fridman1:50:39

Mm-hmm.

嗯嗯。

Peter Steinberger1:50:39

I think there is, there’s n- there’s better ways how we eventually will communicate with models, and we are still very early in this, how will it even work phase.

我认为有,有n-有更好的方法我们最终将如何与模型进行通信,而且我们还处于这个阶段的早期阶段,它甚至将如何工作阶段。

1:50:39 So, it will eventually converge and we will also figure out whole different ways how to work with those things.

所以,它最终会融合,我们也会找出处理这些东西的完全不同的方式。

Lex Fridman1:51:05

One of the other components of workflow is operating system.

工作流的其他组件之一是操作系统。

1:51:05 So I told you offline that for the first time in my life, I’m expanding my sort of realm of exploration to the to the Apple ecosystem, to Macs, iPhone and so on.

所以我在线下告诉你们,这是我一生中第一次将我的探索领域扩展到苹果生态系统、Mac、iPhone 等。

For most of my life I’ve been a Linux, Windows and WSL1, WSL2 person, which I think are all wonderful, but I…

在我一生的大部分时间里,我一直是 Linux、Windows 和 WSL1、WSL2 的人,我认为这些都很棒,但我……

expanding to also trying Mac.

扩展到也尝试 Mac。

Because it’s another way of building and it’s also a way of building that a large part of the community currently that’s utilizing LMS and agents is using, so.

因为这是另一种构建方式,也是当前使用 LMS 和代理的大部分社区正在使用的构建方式,所以。

And that’s the reason I’m expanding to it.

这就是我扩展它的原因。

But is there something to be said about the different operating systems here?

但是对于不同的操作系统有什么可说的吗?

We should say that OpenClaw supported across operating systems.

应该说 OpenClaw 支持跨操作系统。

Peter Steinberger1:51:56

Yeah.

是的。

Lex Fridman1:51:57

I saw WSL2 recommended, side windows for certain o- operations, but then Windows, Linux macOS are obviously supported.

我看到WSL2推荐,侧窗进行某些o-操作,但是Windows,Linux macOS显然是支持的。

Peter Steinberger1:52:07

Yeah, it should even work natively in Windows.

是的,它甚至应该可以在 Windows 中本地运行。

1:52:07 I just didn’t have enough time to properly test it.

我只是没有足够的时间来正确测试它。

And you know, like, the last 90% of software always easier than the first 90%, so I’m sure there’s some dragons left that will eventually nail out.

你知道,最后 90% 的软件总是比前 90% 更容易,所以我确信剩下的一些龙最终会被解决。

My road was, for a long time, Windows, just because I grew up with that, then I switched and had a long phase with Linux, built my own kernels and everything, and then I went to university and I, I had my, my hacky Linux thing, and saw this white MacBook, and I just thought this is a thing of beauty, the white plastic one.

很长一段时间,我的道路是 Windows,只是因为我是伴随着 Windows 长大的,然后我转向了 Linux,并在很长一段时间内使用了 Linux,构建了自己的内核和所有东西,然后我上了大学,我拥有了我的、我的 Linux 东西,看到了这台白色的 MacBook,我只是觉得这是一件美丽的东西,白色的塑料的。

And then I converted to Mac ’cause mostly w- I was, I was sick that audio wouldn’t work on Skype and all the other issues that, that Linux had for a long time.

然后我转向了 Mac,因为主要是因为 Skype 上的音频无法工作以及 Linux 长期以来存在的所有其他问题让我感到恶心。

1:53:01 And then I just stuck with it and then I dug into iOS, which required macOS anyhow, so it was never a question.

然后我就坚持了下来,然后我开始研究 iOS,无论如何它都需要 macOS,所以这从来都不是一个问题。

I think Apple lost a little bit of its lead in terms of native.

我认为苹果在原生方面失去了一点领先优势。

It used to be…

它曾经是……

Native apps used to be so much better, and especially in the Mac, there’s more people that build software with love.

原生应用程序曾经要好得多,尤其是在 Mac 上,有更多的人满怀热爱地构建软件。

On, on Windows, it, it…

在 Windows 上,它,它……

Windows has much more and, like, function wise, there’s just more, period.

Windows 还有更多功能,就功能而言,只是更多而已。

But a lot of it felt more functional and less done with love.

但其中很多感觉更实用,而不是用爱来完成。

Um, I mean, Mac always, like, attracted more designers and people I felt…

嗯,我的意思是,Mac 总是吸引更多的设计师和人们,我觉得......

1:53:50 Even though, like, often it has less features, it, it had more delight-

尽管,就像,通常它的功能较少,但它,它有更多的乐趣-

Lex Fridman1:53:54

Mm-hmm

嗯嗯

Peter Steinberger1:53:55

…

……

1:53:55 And playfulness.

和贪玩。

So I always valued that.

所以我一直很重视这一点。

But in the last few years, many times I actually prefer…

但在过去的几年里,很多时候我其实更喜欢……

Oh God, people are gonna roast me for that, but I prefer Electron apps because they work and native apps often, especially if it’s, like, a web service is a native app, are lacking features.

天哪,人们会为此嘲笑我,但我更喜欢 Electron 应用程序,因为它们可以工作,而且本机应用程序经常缺乏功能,尤其是当 Web 服务是本机应用程序时。

I mean, not saying it couldn’t be done, it’s more like a, a focus thing that, like, for many, many companies, native was not that big of a priority.

我的意思是,并不是说它无法完成,它更像是一个焦点问题,对于很多很多公司来说,原生并不是那么重要的优先事项。

But if they build an Electron app, it, it’s the only app, so it is a priority and there’s a lot more code sharing possible.

但如果他们构建一个 Electron 应用程序,它是唯一的应用程序,所以它是一个优先事项,并且有更多的代码共享可能。

And I, I build a lot of native Mac apps.

而我,我构建了很多原生 Mac 应用程序。

I love it.

我喜欢它。

I, I can, I can help myself.

我,我可以,我可以帮助自己。

Like, I love crafting little Mac, Mac menu bar tools.

比如,我喜欢制作小型 Mac、Mac 菜单栏工具。

Like I built one to, to monitor your Codex use.

就像我构建了一个来监控您的 Codex 使用情况一样。

1:54:58 I built one I call Trimmy, that’s specifically for agentic use.

我建造了一个我称之为 Trimmy 的产品,专门用于代理用途。

When you, when you select text that goes over multiple lines it would remove the new line so you could actually paste it to the terminal.

当您选择跨多行的文本时,它会删除新行,以便您实际上可以将其粘贴到终端。

That was, again like, this is annoying me and after the, the 20th time of it is annoying me, I just built it.

又是这样,这让我很烦,在第 20 次让我很烦之后,我就构建了它。

There is a cool Mac app for OpenClaw that I don’t think many people discovered yet, also because it, it still needs some love.

OpenClaw 有一个很酷的 Mac 应用程序,我认为很多人还没有发现它,也因为它,它仍然需要一些爱。

It feels a little bit too much like the Hummer car right now because I, I just experiment a lot with it.

现在感觉有点太像悍马汽车了,因为我只是用它做了很多实验。

It, it likes to polish.

它,它喜欢抛光。

Lex Fridman1:55:32

So you still…

所以你还是……

1:55:32 I mean, you still love it.

我的意思是,你仍然喜欢它。

You still, you still love adding to the delight of that operating system.

你仍然,你仍然喜欢为该操作系统增添乐趣。

Peter Steinberger1:55:37

Yeah, but then you realize…

是的,但后来你意识到……

1:55:37 Like, I also built one, for example, for GitHub.

比如,我也为 GitHub 构建了一个。

And then the…

然后……

If you use SwiftUI, like the latest and greatest at Apple, and took them forever to build something to show an image from the web.

如果你使用 SwiftUI,比如 Apple 最新、最好的,并花了很长时间来构建一些东西来显示来自网络的图像。

Now we have async, async image, but……

现在我们有了异步、异步图像,但是……

I added support for it and then some images would just not show up or, like, be very slow.

我添加了对它的支持,然后有些图像就不会显示,或者速度非常慢。

And I had a discussion with Codex like, “Hey, why is there a bug?” And even Codex said like, “Yeah, there’s this ASIC image but it’s really more for experimenting and it should not be used in production.” But that’s Apple’s answer to, like, showing images from the web.

我与 Codex 进行了讨论,比如“嘿,为什么会有错误?”甚至 Codex 也表示,“是的,有这个 ASIC 镜像,但它实际上更多的是用于实验,不应该在生产中使用。”但这就是苹果对显示网络图像等问题的回答。

This shouldn’t be so hard, you know.

你知道,这不应该那么难。

Lex Fridman1:56:19

Yeah.

是的。

Peter Steinberger1:56:19

This is like…

这就像……

1:56:19 This is like insane.

这就像疯了一样。

Like, how am I in, in, in 2026 and my agent tell me, “Don’t use the stuff Apple built because it’s, it’s…

就像,我在 2026 年会怎么样,我的经纪人告诉我,“不要使用苹果制造的东西,因为它是,它是......

It’s…

这是……

Yeah, it- it’s there but it’s not good.” And like this is now in the weeds.

是的,它——它就在那里,但并不好。”就像现在在杂草丛中一样。

This is…

这是……

To me this is like…

对我来说这就像……

They had so much head start and so much love, and they kind of just like blundered it and didn’t, didn’t evolve it as much as they should.

他们有如此多的领先优势和如此多的爱,但他们有点犯了大错,但没有、没有像他们应该的那样发展它。

Lex Fridman1:56:50

But also, there’s just the practical reality.

而且,这只是现实。

1:56:50 If you look at Silicon Valley, most of the developer world that’s kind of playing with LMS and Agentic AI, they’re all using Apple products.

如果你看看硅谷,大多数开发者世界都在使用 LMS 和 Agentic AI,他们都在使用苹果产品。

And then, at the same time, Apple is not really, like, leaning on that.

与此同时,苹果并没有真正依赖这一点。

Like they’re not…

就像他们不是一样……

They’re not opening up and playing and working together and like, yes.

他们没有开放、一起玩耍、一起工作,是的。

Peter Steinberger1:57:12

Isn’t, isn’t it funny how they completely blunder AI, and yet everybody’s buying Mac Minis?

难道不是吗,他们在人工智能方面完全犯了错误,但每个人都在购买 Mac Mini,这不是很有趣吗?

Lex Fridman1:57:19

How…

如何……

1:57:19 What…

什么……

Does that even make sense?

这还有道理吗?

You’re, you’re, you’re quite possibly the world’s greatest Mac salesman of all time.

你,你,你很可能是世界上有史以来最伟大的 Mac 推销员。

Peter Steinberger1:57:29

No, you don’t need a Mac Mini to install OpenClaw.

不,您不需要 Mac Mini 来安装 OpenClaw。

1:57:29 You can install it on the web.

您可以在网络上安装它。

There’s, there’s a concept called nodes, so you can like make your computer a node and it will do the same.

有一个叫做节点的概念,所以你可以让你的计算机成为一个节点,它也会做同样的事情。

There is something said for running it on separate hardware.

有人说可以在单独的硬件上运行它。

That right now is useful.

现在这个很有用。

There is…

有…

There’s a big argument for the browser.

对于浏览器有一个很大的争论。

You know, I, I built some Agentic browser use in there.

你知道,我,我在那里构建了一些 Agentic 浏览器。

And, I mean, it’s basically Playwright with a bunch of extras to make it easier for agents.

而且,我的意思是,它基本上是剧作家加上一堆额外的东西,让经纪人更容易。

Lex Fridman1:58:06

Playwright is a library that controls the browser.

Playwright 是一个控制浏览器的库。

Peter Steinberger1:58:08

Yeah.

是的。

Lex Fridman1:58:08

It’s really nice, easy to use.

真的很好用,很方便。

Peter Steinberger1:58:09

And our internet is slowly closing down.

我们的互联网正在慢慢关闭。

1:58:09 Like, there, there’s a whole movement to make it harder for agents to use.

就像,有一个整体运动让特工更难使用。

So if you do the same in a data center and websites detect that it’s an IP from a data center, the website might just block you or it make it really hard or put a lot of captures in the, in the way of the agent.

因此,如果您在数据中心执行相同的操作,并且网站检测到它是来自数据中心的 IP,则该网站可能会阻止您,或者使其变得非常困难,或者以代理的方式进行大量捕获。

I mean, agents are quite good at happily clicking, “I’m not a robot.”

我的意思是,特工们非常擅长愉快地点击“我不是机器人”。

Lex Fridman1:58:33

Yeah.

是的。

Peter Steinberger1:58:33

But having that on a residential IP makes a lot of things simpler.

但在住宅 IP 上拥有它会让很多事情变得更简单。

1:58:33 So there’s ways.

所以还是有办法的。

Yeah.

是的。

But it really does not need to be a Mac.

但它确实不需要是 Mac。

It can…

它可以……

It can be any old hardware.

它可以是任何旧硬件。

I always say, like, maybe use the…

我总是说,比如,也许可以使用……

Use the opportunity to get yourself a new MacBook or whatever computer you use and use the old one as your server instead of buying a standalone Mac Mini.

利用这个机会为自己购买一台新 MacBook 或您使用的任何计算机,并将旧计算机用作服务器,而不是购买独立的 Mac Mini。

But then there’s, again, there’s a lot of very cute things people build with Mac Minis that I like.

但话又说回来,人们用 Mac Mini 制作了很多非常可爱的东西,我很喜欢。

Lex Fridman1:59:08

Yeah.

是的。

Peter Steinberger1:59:08

And no, I don’t get commission from Apple.

不,我没有从苹果公司获得佣金。

1:59:08 They didn’t really communicate much.

他们并没有真正交流太多。

Lex Fridman1:59:16

It’s sad.

很伤心。

1:59:16 It’s sad.

很伤心。

Can you actually speak to what it takes to get started with OpenClaw?

您能具体谈谈如何开始使用 OpenClaw 吗?

There’s…

有……

I mean, there’s a lot of people…

我的意思是,有很多人……

What is it?

它是什么?

Somebody tweeted at you, “Peter, make OpenClaw easy to set up for everyday people.

有人在推特上对你说:“Peter,让 OpenClaw 对于普通人来说很容易设置。

99.9% of people can’t access to OpenClaw and have their own lobster because of their technical difficulties in getting it set up.

99.9% 的人无法访问 OpenClaw 并拥有自己的龙虾,因为他们在设置方面存在技术困难。

Make OpenClaw accessible to everyone, please.” And you replied, “Working on that.” From my perspective, it seems there- there’s a bunch of different options and it’s already quite straightforward, but I suppose that’s if you have some developer background.

请让所有人都能使用 OpenClaw。”你回答说:“正在努力。”从我的角度来看,似乎有很多不同的选择,而且已经非常简单了,但我想这是如果你有一些开发人员背景的话。

Peter Steinberger1:59:50

I mean, right now you have to paste in one liner into the terminal.

我的意思是,现在您必须将一张衬垫粘贴到终端中。

Lex Fridman1:59:53

Right.

正确的。

Peter Steinberger1:59:54

And there’s also an app.

还有一个应用程序。

1:59:54 The app kind of does that for you, but there should be a Windows app.

该应用程序可以为您执行此操作,但应该有一个 Windows 应用程序。

The app needs to be easier and more loved.

该应用程序需要变得更容易、更受喜爱。

The configuration should potentially be web-based or in the app.

配置可能应该基于 Web 或在应用程序中。

And I started working on that, but honestly right now I want to focus on security aspects.

我开始致力于此,但说实话,现在我想专注于安全方面。

And, and once I’m confident that this is at a level that I can recommend my mom, then I’m going to make it simpler.

而且,一旦我确信这已经达到了我可以推荐我妈妈的水平,那么我就会让它变得更简单。

Like I…

就像我……

2:00:27 Right now-

现在——

Lex Fridman2:00:28

You want to make it harder so that it doesn’t scale as fast as it’s scaling.

你想让它变得更难,这样它的扩展速度就不会像它扩展的那么快。

Peter Steinberger2:00:32

Yeah, it would be nice if it wouldn’t…

是啊,如果不这样就好了……

2:00:32 I mean, that’s, like, hard to say, right?

我的意思是,这很难说,对吧?

But if the growth would be a little slower, that would be helpful because people are expecting inhuman things from a single human being.

但如果增长速度慢一点,那就会有帮助,因为人们对一个人的期望是不人道的。

And yes, I have some contributors, but also that whole machinery I started a week ago so that needs more time to figure out.

是的,我有一些贡献者,但也有我一周前启动的整个机制,所以需要更多时间来弄清楚。

And, and not everyone has all day to work on that.

而且,并不是每个人都有一整天的时间来做这件事。

Lex Fridman2:01:00

There’s some beginners listening to this, programming beginners.

有一些初学者在听这个,编程初学者。

2:01:00 What advice would you give to them about, let’s say, joining the Agentic AI revolution?

比如说,关于加入 Agentic 人工智能革命,您会给他们什么建议?

Peter Steinberger2:01:12

Play.

玩。

2:01:12 Playing is the best…

玩是最好的……

The best way to learn.

最好的学习方式。

If you wanna…

如果你想……

I’m sure if you…

我确定如果你……

If you are like a little bit of builder, you have an idea in your head that you want to build, just build that, or like, give it a try.

如果你就像一个小建造者,你的脑海里有一个你想要建造的想法,就建造它,或者尝试一下。

It doesn’t need to be perfect.

它不需要是完美的。

I built a whole bunch of stuff that I don’t use.

我构建了一大堆我不使用的东西。

It doesn’t matter.

没关系。

Like, it’s the journey.

就像,这就是旅程。

Lex Fridman2:01:31

Mm-hmm.

嗯嗯。

Peter Steinberger2:01:31

You know?

你知道?

2:01:31 Like the philosophical way, that the end doesn’t matter, the journey matters.

就像哲学方式一样,终点并不重要,旅程才重要。

Have fun.

玩得开心。

Lex Fridman2:01:37

Mm-hmm.

嗯嗯。

Peter Steinberger2:01:37

My God, like those things…

天啊,像那些东西……

2:01:37 I…

我……

I don’t think I ever had so much fun building things because I can focus on the hard parts now.

我认为我从来没有在构建东西时获得如此多的乐趣,因为我现在可以专注于困难的部分。

A lot of coding, I always thought I liked coding, but really I like building.

大量编码,我一直以为我喜欢编码,但实际上我喜欢构建。

Lex Fridman2:01:50

Yeah.

是的。

Peter Steinberger2:01:50

And…

还有……

2:01:50 And whenever you don’t understand something, just ask.

每当你不明白什么时候,就问。

You have an infinitely patient answering machine….

你有一个无限耐心的答录机……

that y- can explain you anything at any level of complexity.

y- 可以向您解释任何复杂程度的任何事情。

Sometimes, that’s like one time I asked, “Hey explain to me like I’m- I’m eight years old,” and it started giving me a story with crayons and stuff.

有时,就像有一次我问,“嘿,像我一样向我解释一下——我八岁了,”然后它开始给我一个用蜡笔之类的东西讲故事。

And I’m like, “No, not like that.” Like, I’m okay- …

我说:“不,不是那样的。”比如说,我没事——……

up- up the age a little bit, you know?

年龄有点大,你知道吗?

I’m like, I’m not an actual child, it’s just, I just need a simpler language for like a- a- a- a- a tricky database concept that I didn’t grok in the first- first time.

我想,我不是一个真正的孩子,只是,我只需要一种更简单的语言,比如 a-a-a-a- 一个我第一次没有理解的棘手的数据库概念。

But, you know, just, you can just ask things.

但是,你知道,只是,你可以问一些事情。

Like, you- there’s like…

就像,你——就像……

It used to be that I had to go on Stack Overflow or ha- ask on Twitter, and then maybe two days later I get a response.

过去我必须在 Stack Overflow 上或者在 Twitter 上提问,然后也许两天后我就会得到回复。

2:02:37 Or I had to try for hours.

或者我必须尝试几个小时。

And now you- you can just ask stuff.

现在你——你可以问一些东西。

It- I mean, it’s never…

它——我的意思是,它从来都不是……

You have, like, your own teacher.

你有,就像,你自己的老师。

You know that there’s like statistics, y- you can learn faster if you have your own teacher.

你知道有类似统计数据的东西,如果你有自己的老师,你可以学得更快。

The- it’s like you have this infinitely patient machine.

这——就像你有一台无限耐心的机器。

Ask it.

问吧。

Lex Fridman2:02:53

But what would you say?

但你会说什么?

2:02:53 So use…

所以使用...

What’s the easiest way to play?

最简单的玩法是什么?

So maybe Open Claw is a nice way to play so you can then set- set everything up and then you could chat with it.

所以也许 Open Claw 是一种很好的游戏方式,这样你就可以设置一切,然后你就可以和它聊天了。

Peter Steinberger2:03:03

You can also just experiment with it and, like, modify it.

您也可以尝试一下并修改它。

2:03:03 Ask your agent.

询问你的代理人。

I mean, there is infinite ways how it can be made better.

我的意思是,有无数种方法可以让它变得更好。

Play around, make it better.

玩玩,让它变得更好。

Lex Fridman2:03:18

Mm-hmm.

嗯嗯。

Peter Steinberger2:03:19

More general, if you- if you’re a beginner and you actually wanna learn how to build software really fast, get involved in open source.

更一般地说,如果你是一个初学者,并且你真的想学习如何快速构建软件,那么就参与开源吧。

2:03:19 Doesn’t need to be my project.

不需要是我的项目。

In fact, maybe don’t use my project because my- my backlog is very large, but I learned so much from open source.

事实上,也许不要使用我的项目,因为我的积压工作非常多,但我从开源中学到了很多东西。

Just like, like, be- be humble.

就像,就像,要谦虚。

Don’t- maybe don’t send a pull request right away.

不要——也许不要立即发送拉取请求。

But there’s many other ways you can help out.

但还有很多其他方法可以帮助您。

There’s many ways you can just learn by just reading code.

有很多方法可以通过阅读代码来学习。

By- by being on Discord or wherever people are, and just, like, understanding how things are built.

通过——通过在 Discord 上或任何人们在的地方,并且只是了解事物是如何构建的。

I don’t know, like Mitchell Hashimoto builds Ghostly, the terminal, and he has a really good community where there’s so many other projects.

我不知道,就像 Mitchell Hashimoto 建造的 Ghostly 终端一样,他有一个非常好的社区,那里有很多其他项目。

Like, pick something that you find interesting and get involved.

比如,选择一些你觉得有趣的事情并参与其中。

Lex Fridman2:04:15

Do you recommend that people that don’t know how to program or don’t really know how to program learn to program also?

您是否建议那些不知道如何编程或不太了解如何编程的人也学习编程?

2:04:15 So when you you can get quite far right now by just using natural language, right?

那么,现在您只需使用自然语言就可以走得很远,对吧?

Do you s- still see a lot of value in reading the code, understanding the code, and then being able to write a little bit of code from scratch?

您仍然认为阅读代码、理解代码,然后能够从头开始编写一点代码有很大的价值吗?

Peter Steinberger2:04:38

It definitely helps.

这绝对有帮助。

Lex Fridman2:04:39

It’s hard for you to answer that-

你很难回答这个问题——

Peter Steinberger2:04:41

Yeah

是啊

Lex Fridman2:04:42

…

……

2:04:42 because you don’t know what it’s like to do any of this without knowing the base knowledge.

因为如果不了解基础知识,你就不知道做这些事情会是什么样子。

Like, you might take for granted just how much intuition you have about the programming world having programmed so much, right?

就像,你可能想当然地认为你对编程世界有多少直觉已经编程了这么多,对吧?

Peter Steinberger2:04:54

There’s people that are high agency and very curious, and they get very far even though they have no deep understanding how software works just because they ask questions and questions and- and- and-

有些人具有很高的能动性并且非常好奇,尽管他们对软件的工作原理没有深入的了解,但他们却走得很远,仅仅因为他们提出了问题、问题和——和——和——

Lex Fridman2:05:08

Mm-hmm

嗯嗯

Peter Steinberger2:05:08

…

……

2:05:08 and agents are infinitely patient.

和代理人无限的耐心。

Like, part of what I did this year is I went to a lot of iOS conferences because that’s my background and just told people, “Don’t consi- don’t see yourself as an iOS engineer anymore.” Like, “You need to change your mindset.

就像,我今年所做的一部分就是参加了很多 iOS 会议,因为这就是我的背景,我只是告诉人们,“不要再认为自己是一名 iOS 工程师了。”就像,“你需要改变你的心态。

You’re a builder.” And you can take a lot of the knowledge how to build software into new domains and all of the- the more fine-grain details, agents can help.

你是一名建筑商。”您可以掌握如何将软件构建到新领域的大量知识,以及所有更细粒度的细节,代理可以提供帮助。

You don’t have to know how to splice an array or what the- what the correct template syntax is or whatever, but you can use all your- your general knowledge and that makes it much easier to move from one galaxy, one tech galaxy into another.

您不必知道如何拼接数组或正确的模板语法是什么或其他什么,但您可以使用您所有的常识,这使得从一个星系、一个技术星系转移到另一个星系变得更加容易。

And oftentimes, there’s languages that make more or less sense depending on what you build, right?

通常,有些语言的意义或多或少取决于您构建的内容,对吗?

2:05:58 So for example, when I build simple CLIs, I like Go.

例如,当我构建简单的 CLI 时,我喜欢 Go。

I actually don’t like Go.

其实我不喜欢Go。

I don’t like the syntax of Go.

我不喜欢 Go 的语法。

I didn’t even consider the language.

我什至没有考虑过语言。

But the ecosystem is great, it works great with agents.

但生态系统很棒,它与代理配合得很好。

It is garbage collected.

它被垃圾收集。

It’s not the highest performing one, but it’s very fast.

它不是性能最高的,但速度非常快。

And for those type of- of CLIs that I build, Go is- is a really good choice.

对于我构建的那些类型的 CLI,Go 是一个非常好的选择。

So I- I use a language I’m not even a fan of for…

所以我-我使用一种我什至不喜欢的语言......

That’s my main to-go thing for- for CLIs.

这是我主要要做的事情——对于 CLI。

Lex Fridman2:06:29

Isn’t that fascinating that here’s a programming language you would’ve never used if you had to write it from scratch and now you’re using because LMs are good at generating it and it has some of the characteristics that makes it resilient, like garbage collected?

这是一种如果你必须从头开始编写的话你永远不会使用的编程语言,而现在你正在使用它,因为 LM 擅长生成它,并且它具有一些使其具有弹性的特性,比如垃圾收集,这不是很有趣吗?

Peter Steinberger2:06:44

Because everything’s weird in this new world and that just makes the most sense.

因为这个新世界里的一切都很奇怪,而这却是最有意义的。

Lex Fridman2:06:48

What’s the best Ridiculous question.

最好的荒谬问题是什么?

2:06:48 What’s the best programming language for the AI- AI agentic world?

人工智能-人工智能代理世界的最佳编程语言是什么?

Is it JavaScript, TypeScript?

是 JavaScript、TypeScript 吗?

Peter Steinberger2:06:54

TypeScript is really good.

TypeScript 真的很好。

2:06:54 Sometimes the types can get really confusing and the ecosystem is- is a jungle.

有时,类型可能会变得非常混乱,而生态系统就是一个丛林。

So for- for web stuff it’s good.

所以对于网络来说这很好。

I wouldn’t build everything in it.

我不会在里面建造所有东西。

Lex Fridman2:07:15

Don’t you think we’re moving there?

你不认为我们要搬到那里吗?

2:07:15 Like, that everything will eventually be written- eventually is written in JavaScript and it-

就像,一切最终都会被编写——最终是用 JavaScript 编写的——

Peter Steinberger2:07:22

The birth and death of JavaScript and we are living through it in real time.

JavaScript 的诞生和消亡,我们都在实时经历着它。

Lex Fridman2:07:26

Like, what does programming look like in 20 years?

比如,20 年后编程会是什么样子?

2:07:26 Right?

正确的?

In 30 years?

30年后?

In 40 years?

40年后?

What do programs and apps look like?

程序和应用程序是什么样的?

Peter Steinberger2:07:32

You can even ask a question like, do we need a- a programming language that’s made for agents?

您甚至可以问这样的问题:我们是否需要一种专为代理设计的编程语言?

2:07:32 Because all of those languages are made for humans.

因为所有这些语言都是为人类而设计的。

So how- what would that look like?

那么,那会是什么样子呢?

Um, I think there’s a- there’s whole bunch of interesting questions that we’ll discover.

嗯,我认为我们会发现很多有趣的问题。

And also how because everything is now world knowledge, how it in many ways, things will stagnate ’cause if you build something new and the agent has no idea that’s gonna be much harder to use than something that’s already there.

而且,因为现在一切都是世界知识,所以在很多方面,事情都会停滞不前,因为如果你构建了一些新的东西,而代理不知道它会比已经存在的东西更难使用。

Um……

嗯……

of when I build Mac apps, I build them in, in Swift and SwiftUI, mm, partly because I like pain, partly because it…

当我构建 Mac 应用程序时,我会在 Swift 和 SwiftUI 中构建它们,部分是因为我喜欢痛苦,部分是因为它......

the, the deepest level of system integration, I can only get through there.

最深层次的系统集成,我只能打通到那里。

2:08:18 And you clearly feel a difference if you click on an electron app and it loads a web view in the menu.

如果您单击电子应用程序并在菜单中加载网络视图,您会明显感觉到不同。

It’s just not the same.

只是不一样。

Sometimes I just also try new languages just to, like, get a feel for them.

有时我也会尝试新的语言,只是为了感受一下它们。

Lex Fridman2:08:32

Like Zig?

像齐格那样?

Peter Steinberger2:08:33

Yeah.

是的。

2:08:33 If it’s something that…

如果是这样的东西……

where I care about performance a lot then it’s, it’s a really interesting language.

我非常关心性能,这是一种非常有趣的语言。

And it…

而它……

like agents got so much better over the last six months from not really good to totally valid choice.

就像代理商在过去六个月中从不太好的选择到完全有效的选择有了很大的进步。

Just still a, a very young ecosystem.

仍然是一个非常年轻的生态系统。

And most of the time you actually care about ecosystem, right?

大多数时候你实际上关心生态系统,对吗?

So, so if you build something that does inference or goes into whole running model direction, Python, very good.

所以,如果你构建一些可以进行推理或进入整个运行模型方向的东西,Python,非常好。

Lex Fridman2:09:06

Mm-hmm.

嗯嗯。

Peter Steinberger2:09:07

But then if I build stuff in Python and I want a story where I can also deploy it on Windows, not a good choice.

但是,如果我用 Python 构建东西,并且想要一个可以在 Windows 上部署它的故事,那么这不是一个好的选择。

Lex Fridman2:09:13

Mm-hmm.

嗯嗯。

Peter Steinberger2:09:13

Sometimes I, I found projects that kinda did 90% of what I wanted but were in Python, and I wanted them…

有时我发现项目可以完成我想要的 90% 的功能,但是都是用 Python 编写的,我想要它们……

2:09:13 I wanted an easy Windows story.

我想要一个简单的 Windows 故事。

Okay, just rewrite it in Go.

好吧,用 Go 重写一下就可以了。

But then if you go towards multiple, multiple threads and a lot more performance, Rust is a really good choice.

但如果你追求多线程和更高的性能,Rust 是一个非常好的选择。

There’s no…

没有……

there’s just no single answer, and it’s also the beauty of it.

没有唯一的答案,但这也是它的美妙之处。

Like, it’s fun.

就像,这很有趣。

2:09:37 And now it doesn’t matter anymore, you can just literally pick the language that has the, the most fitting characteristics and ecosystem-

现在一切都不再重要了,你可以直接选择具有最合适特征和生态系统的语言 -

Lex Fridman2:09:45

Mm-hmm

嗯嗯

Peter Steinberger2:09:46

…

……

2:09:46 for your problem domain.

对于您的问题域。

And yeah, it might be…

是的,可能是……

You might have s-…

你可能有-...

You might be a little bit slow in reading the code, but not really.

您阅读代码的速度可能有点慢,但事实并非如此。

Y- I think you, you pick stuff up really fast, and you can always ask your agent.

Y-我认为你,你拿起东西的速度非常快,而且你可以随时询问你的经纪人。

Lex Fridman2:09:59

So there’s a lot of programmers and builders who draw inspiration from y- your story.

因此,有很多程序员和构建者从你的故事中汲取灵感。

2:09:59 Just the way you carry yourself, your choice of making OpenClaw open source, the, the way you have fun building and exploring, and doing that, for the most part, alone or on a small team.

只是你的行事方式,你选择将 OpenClaw 开源,你享受构建和探索的乐趣,以及在大多数情况下,单独或在一个小团队中这样做。

So by way of advice, what metric should be the goal that they would be optimizing for?

那么,作为建议,他们优化的目标应该是什么指标?

What would be the metric of success?

成功的标准是什么?

Would it be happiness?

会是幸福吗?

Is it money?

是钱吗?

Is it positive impact for people who are dreaming of building?

这对那些梦想建造的人有积极的影响吗?

‘Cause you went through an interesting journey.

因为你经历了一段有趣的旅程。

You’ve achieved a lot of those things, and then you fell out of love with programming a little bit for a time.

你已经取得了很多这样的成就,然后你一度对编程失去了兴趣。

Peter Steinberger2:10:47

I was just burning too bright for too long.

我只是燃烧得太明亮太久了。

2:10:47 I, I ran…

我、我跑了……

I started PSPDFKit, s- and ran it for 13 years, and it was high stress.

我启动了 PSPDFKit,并运行了 13 年,压力很大。

Um, I had to learn all these things fast and hard, like how to manage people, how to bring people on, how to deal with customers, how to do…

嗯,我必须快速而努力地学习所有这些东西,比如如何管理人员,如何让人们参与,如何与客户打交道,如何做……

Lex Fridman2:11:14

So it wasn’t just programming stuff, it was people stuff.

所以这不仅仅是编程的问题,也是人的问题。

Peter Steinberger2:11:17

The stuff that burned me out was mostly people stuff.

让我精疲力竭的事情大多是人的事情。

2:11:17 I, I don’t think burnout is working too much.

我,我不认为倦怠有太多作用。

Maybe to a degree.

也许在某种程度上。

Everybody’s different.

每个人都不同。

You know, I c- I cannot speak in a- in absolute terms, but for me, it was much more differences with my, my co-founders, conflicts, or, like, really high stress situation with customers that eventually grinded me down.

你知道,我不能用绝对的方式说话,但对我来说,与我、我的联合创始人的差异、冲突,或者与客户的高压情况最终让我崩溃。

And then when…

然后当……

luckily we, we got a really good offer for, like, putting the company to the next level and I, I already kinda worked two years on making myself obsolete.

幸运的是,我们得到了一个非常好的报价,比如,让公司更上一层楼,而我,我已经工作了两年,让自己变得过时。

So at this point I could leave, and, and then I just…

所以现在我可以离开了,然后我就……

I was sitting in front of the screen and I felt like, you know Austin Powers where they suck the mojo out?

我坐在屏幕前,我感觉,你知道《王牌大贱谍》里他们吸出魔力的地方吗?

Lex Fridman2:12:13

Yeah.

是的。

Peter Steinberger2:12:14

Uh, I g- I was like, m- m- it was, like, gone.

呃,我-我当时想,嗯-嗯-它就好像消失了。

2:12:14 Like, I couldn’t…

就像,我不能……

I couldn’t get code out anymore.

我再也无法取出代码了。

I was just, like, staring and feeling empty, and then I, I just stopped.

我只是,就像,盯着看,感到空虚,然后我,我就停了下来。

I, I booked, like, a one-way trip to Madrid and, and, and just, like, spent a t- some t- sometime there.

我,我预订了一次去马德里的单程旅行,并且,只是,就像,在那里度过了一段时间。

I felt like I had to catch up on life, so I did a whole, a whole bunch of life catching up stuff.

我觉得我必须追赶生活,所以我做了一大堆追赶生活的事情。

Lex Fridman2:12:47

Did you go through some lows during that period?

那段时间你有没有经历过一些低谷?

2:12:47 And you know, maybe advice on…

你知道,也许有关于……的建议

of how to?

的如何?

Peter Steinberger2:12:56

Maybe advice on how to approach life.

也许是关于如何对待生活的建议。

2:12:56 If you think that, “Oh yeah, work really hard and then I’ll retire,” I don’t recommend that.

如果你认为,“哦,是的,努力工作,然后我就会退休”,我不建议你这样做。

Because the idea of, “Oh yeah, I just enjoy life now,” a- maybe it’s appealing, but right now I enjoy life, the most I’ve ever enjoyed life.

因为“哦,是的,我现在很享受生活”的想法——也许这很吸引人,但现在我很享受生活,这是我最享受的生活。

Because if you wake up in the morning and you have nothing to look forward to, you have no real challenge, that gets very boring, very fast.

因为如果你早上醒来,没有什么可期待的,你就没有真正的挑战,那很快就会变得非常无聊。

And then when, when you’re bored, you’re gonna look for other places how to stimulate yourself, and then maybe, maybe that’s drugs, you know?

然后当你无聊的时候,你就会寻找其他地方来刺激自己,然后也许,也许那就是毒品,你知道吗?

But that eventually also get boring and you look for more, and that will lead you down a very dark path.

但最终也会变得无聊,你会寻找更多,这会引导你走上一条非常黑暗的道路。

Lex Fridman2:13:57

But you also showed on the money front, you know, a lot of people in Silicon Valley and the startup world, they think, maybe overthink way too much optimized for money.

但你也表现在金钱方面,你知道,硅谷和创业界的很多人,他们认为,也许过度考虑了太多针对金钱的优化。

2:13:57 And you’ve also shown that it’s not like you’re saying no to money.

而且你还表明,你并不是对金钱说不。

I mean, I’m sure you take money, but it’s not……

我的意思是,我确定你拿钱,但不是……

the primary objective of uh, of your life.

呃,你生活的主要目标。

Can you just speak to that?

你能简单谈谈吗?

Your philosophy on money?

你的金钱观?

Peter Steinberger2:14:20

When I built my company, money was never the driving force.

当我建立公司时,金钱从来都不是驱动力。

2:14:20 It felt more like, like, an affirmation that I did something right.

这感觉更像是对我做了正确的事情的肯定。

And having money solves a lot of problems.

而且有钱可以解决很多问题。

I also think there, there’s diminishing returns the more you have.

我还认为,拥有的越多,回报就会递减。

Like, a cheeseburger is a cheeseburger, and I think if you go too far into, oh, I do private jet and I only travel luxury, you disconnect with society.

就像,芝士汉堡就是芝士汉堡,我认为如果你太过于陷入“哦,我乘坐私人飞机而且我只奢侈旅行”,你就会与社会脱节。

Um, I, I donated quite a lot.

嗯,我,我捐了很多。

Like, I have a, I have a foundation for helping people that weren’t so lucky.

就像,我有一个基金会来帮助那些不那么幸运的人。

Lex Fridman2:15:11

And disconnecting from society is bad in that on many levels, but one of them is, like, humans are awesome.

在很多层面上,与社会脱节都是不好的,但其中之一就是,人类是伟大的。

2:15:11 It’s nice to continuously remember the awesomeness in humans.

不断记住人类的伟大之处真是太好了。

Peter Steinberger2:15:23

I, I mean, I could afford really nice hotels.

我,我的意思是,我买得起非常好的酒店。

2:15:23 The last time I was in San Francisco, I did the, the first time the OG Airbnb experience-

上次我在旧金山时,我第一次体验了 OG Airbnb -

Lex Fridman2:15:30

Yeah, yeah

是啊是啊

Peter Steinberger2:15:30

…

……

2:15:30 and just booked a room.

并刚刚预订了一个房间。

Mostly because I, I thought, okay, you know, I’m out or I’m sleeping, and I don’t like where all the hotels are, and I wanted a, I wanted a different experience.

主要是因为我,我想,好吧,你知道,我出去了,或者我在睡觉,我不喜欢所有酒店的位置,我想要,我想要一种不同的体验。

I think, isn’t life all about experiences?

我想,人生不就是经历吗?

Like, if you, if you tailor your life towards, “I wanna have experiences,” it, it reduces the need for, “It needs to be good or bad.” Like, if people only want good experiences, that’s not gonna work, but if you optimize for experiences, if it’s good, amazing.

就像,如果你按照“我想要经历”来调整你的生活,它就会减少“它需要好或坏”的需求。就像,如果人们只想要良好的体验,那是行不通的,但如果你优化体验,如果它很好,那就太棒了。

If it’s bad, amazing, because, like, I learned something, I saw something, did something.

如果它很糟糕,那就太棒了,因为,就像,我学到了一些东西,我看到了一些东西,做了一些东西。

I wanted to experience that, and it was amazing.

我想体验一下,这真是太棒了。

Like, there was, like, this, this queer DJ in there, and I showed her how to make music with cloud code.

那里有一个酷儿 DJ,我向她展示了如何使用云代码制作音乐。

And we, like, immediately bonded and had a great time.

我们立刻就建立了联系,度过了一段愉快的时光。

Lex Fridman2:16:24

Yeah, there’s something about that air- you know, couch surfing, Airbnb experience, the OG.

是的,这种空气中有一些东西——你知道,沙发冲浪、Airbnb 体验、OG。

2:16:24 I’m still to this day.

直到今天我仍然如此。

It’s awesome.

太棒了。

It’s humans, and that’s why travel is awesome.

这是人类,这就是旅行如此精彩的原因。

Peter Steinberger2:16:34

Yeah.

是的。

Lex Fridman2:16:34

Just experience the variety of, the diversity of human.

只是体验人类的多样性。

2:16:34 And when it’s shitty, it’s good too, man.

当它很糟糕时,它也很好,伙计。

If it rains and you’re soaked and it’s all fucked, and planes, the everything is shit, everything is fucked, it’s still awesome.

如果下雨了,你浑身湿透,一切都糟透了,还有飞机,一切都糟透了,一切都糟透了,但它仍然很棒。

If you’re able to open your eyes it’s good to be alive.

如果你能睁开眼睛,活着就好了。

Peter Steinberger2:16:49

Yeah, and anything that creates emotion and feelings is good.

是的,任何能产生情感和感觉的东西都是好的。

Lex Fridman2:16:55

.

。

Peter Steinberger2:16:55

Even…

甚至……

2:16:55 So, so maybe, maybe even the cryptic people are good because they definitely created emotions.

所以,也许,即使是那些神秘的人也是好的,因为他们确实创造了情感。

I, I don’t know if I should go that far.

我,我不知道我是否应该走那么远。

Lex Fridman2:17:02

No, man.

不,伙计。

2:17:02 Give them, give them all, give them love.

给他们,给他们全部,给他们爱。

Give them love.

给他们爱。

Because I do think that online lacks some of the awesomeness of real life.

因为我确实认为网络缺乏现实生活中的一些精彩之处。

Peter Steinberger2:17:13

Yeah.

是的。

Lex Fridman2:17:13

That’s, that’s, it’s an open problem of how to solve, how to infuse the online cyber experience with I don’t know with the intensity that we humans feel when it’s in real life.

这是一个悬而未决的问题,如何解决,如何将在线网络体验与我们人类在现实生活中感受到的强度结合起来。

2:17:13 I don’t know.

我不知道。

I don’t know if that’s a solvable problem.

我不知道这是否是一个可以解决的问题。

Peter Steinberger2:17:31

Well, it’s just possible because text is very lossy.

嗯,这是可能的,因为文本的损耗非常大。

Lex Fridman2:17:35

Yeah.

是的。

Peter Steinberger2:17:35

You know, sometimes I wish if I talked to the agent I would…

你知道,有时我希望如果我与经纪人交谈,我会……

2:17:35 It should be multi-model so it also understands my emotions.

它应该是多模型的,这样它也能理解我的情绪。

Lex Fridman2:17:43

I mean, it, it might move there.

我的意思是,它可能会搬到那里。

2:17:43 It might move there.

它可能会移动到那里。

Peter Steinberger2:17:46

It will.

会的。

2:17:46 It will.

会的。

It totally will.

完全会的。

Lex Fridman2:17:49

I mean, I have to ask you, just curious.

我的意思是,我必须问你,只是好奇。

2:17:49 I, I know you’ve probably gotten huge offers from major companies.

我,我知道你可能已经收到了大公司的巨额offer。

Can you speak to who you’re considering working with?

您能谈谈您正在考虑与谁合作吗?

Peter Steinberger2:18:04

Yeah.

是的。

2:18:04 So, to like explain my thinking a little bit, right, I did not expect this blowing up so much.

所以,想稍微解释一下我的想法,对吧,我没想到会这么火爆。

So, there’s a lot of doors that opened because of it.

因此,有很多门因此而打开。

There’s, like, I think every VC, every big VC company is in my inbox and tried to get 15 minutes of me.

比如说,我想每个风险投资公司、每个大型风险投资公司都在我的收件箱里,并试图跟我聊 15 分钟。

So, there’s, like, this butterfly effect moment.

所以,就像蝴蝶效应的时刻。

I could just do nothing and continue and I really like my life.

我可以什么都不做并继续,我真的很喜欢我的生活。

Valid choice.

有效的选择。

Almost.

几乎。

Like, I considered it when I delete it, wanted to delete the whole thing.

就像我删除它的时候考虑过的,想把整个东西都删除。

I could create a company.

我可以创建一家公司。

Been there, done that.

去过那里,做过那件事。

There’s so many people that push me towards that and, yeah, like, could be amazing.

有很多人推动我朝这个方向努力,是的,这可能会很棒。

Lex Fridman2:19:07

Which is to say that you, you would probably raise a lot of money in that.

也就是说,你可能会从中筹集到很多钱。

Peter Steinberger2:19:10

Yeah.

是的。

Lex Fridman2:19:11

I don’t know, hundreds of millions, billions.

我不知道,几亿,几十亿。

2:19:11 I don’t know.

我不知道。

It could just got unlimited amount of money.

它可能会得到无限量的钱。

Peter Steinberger2:19:15

Yeah.

是的。

2:19:15 It just doesn’t excite me as much because I feel I did all of that, and it would take a lot of time away from the things I actually enjoy.

它只是没有让我那么兴奋,因为我觉得我做了所有这些,而且它会占用我很多时间远离我真正喜欢的事情。

Same as when, when I was CEO, I think I, I learned to do it and I’m not bad at it, and partly I’m good at it.

就像我担任首席执行官时一样,我想我,我学会了这样做,而且我不擅长这件事,而且部分地我很擅长。

But yeah, that path doesn’t excite me too much, and I also fear it, it would create a natural conflict of interest.

但是,是的,这条道路并没有让我太兴奋,而且我也担心它会产生自然的利益冲突。

Like, what’s the most obvious thing I do?

比如,我做的最明显的事情是什么?

I, I prioritize it.

我,我优先考虑。

I put, like, a version safe for workplace.

我放了一个适合工作场所的安全版本。

And then what do you do?

然后你该怎么办?

Like, I get a pull request with a feature like an audit log, but that seems like an enterprise feature, so now I feel I have a conflict of interest in the open-source version and the closed-source version….

比如,我收到了一个带有审计日志等功能的拉取请求,但这似乎是一个企业功能,所以现在我觉得我在开源版本和闭源版本中存在利益冲突……。

2:20:15 or change the license to something like FSL, where you cannot actually use it for commercial stuff, would first be very difficult with all the contributions.

或者将许可证更改为 FSL 之类的东西,在这种情况下,您实际上无法将其用于商业用途,首先,所有贡献都会变得非常困难。

And second of all, I- I like the idea that it’s free as in beer and not free with conditions.

其次,我-我喜欢这样的想法:它像啤酒一样免费,而不是有条件免费。

Yeah, there’s ways how you, how you keep all of that for free and just, like, still try to make money, but those are very difficult.

是的,有很多方法可以让你免费保留所有这些,并且仍然尝试赚钱,但这些都是非常困难的。

And you see there’s, like, fewer and fewer companies manage that.

你会发现,能够做到这一点的公司越来越少。

Like, even Tailwind, they’re, like, used by everyone.

就像,甚至 Tailwind,每个人都在使用它们。

Everyone uses Tailwind, right?

大家都用Tailwind吧?

And then they had to cut off 75% of the employees because they’re not making money because nobody’s even going on the website anymore because it’s all done by agents.

然后他们不得不裁掉 75% 的员工,因为他们没有赚钱,因为没有人再访问该网站,因为这都是由代理商完成的。

S- and just relying on donations, yeah, good luck.

S-并且只是依靠捐款,是的,祝你好运。

2:21:04 Like, if a project of my caliber, if I extrapolate what the typical open-source project would get it’s not a lot.

就像,如果我有一个这样的项目,如果我推断典型的开源项目会得到什么,那并不是很多。

I s- I still lose money on the project because I made the point of supporting every dependency, except Slack.

我-我仍然在这个项目上赔钱,因为我强调支持除 Slack 之外的所有依赖项。

They are a big company.

他们是一家大公司。

They can, they can, they can do without me.

他们可以,他们可以,他们可以没有我。

But all the projects that are done by mostly individuals so, like, all the, right now, all the sponsorship goes right up to my dependencies.

但所有项目大部分都是由个人完成的,所以,现在所有的赞助都直接取决于我的依赖。

And if there’s more, I want to, like, buy my contributors some merch, you know?

如果还有更多,我想给我的贡献者买一些商品,你知道吗?

Lex Fridman2:21:43

So you’re losing money?

所以你亏钱了?

Peter Steinberger2:21:44

Yeah, right now I lose money on this.

是的,现在我在这件事上赔钱了。

Lex Fridman2:21:46

So it’s really not sustainable?

那么这真的不可持续吗?

Peter Steinberger2:21:48

Uh, I mean, it’s like, I guess something between 10 and 20K a month.

呃,我的意思是,我猜一个月大概有 10 到 20K 之间。

2:21:48 Which is fine.

这很好。

I’m sure over time I could get that down.

我确信随着时间的推移我可以把它记下来。

Um, OpenAI is helping out a little bit with tokens now.

嗯,OpenAI 现在正在用代币提供一些帮助。

And there’s other companies that have been generous.

还有其他公司也很慷慨。

But yeah, still losing money on that.

但是,是的,仍然在亏损。

So that’s- that’s one path I consider, but I’m just not very excited.

所以这就是我考虑的一条路,但我只是不太兴奋。

And then there’s all the big labs that I’ve been talking to.

然后是我一直在交谈的所有大型实验室。

And from those Meta and OpenAI seem the most interesting.

其中 Meta 和 OpenAI 似乎是最有趣的。

Lex Fridman2:22:32

Do you lean one way or the other?

你倾向于一侧还是另一侧?

Peter Steinberger2:22:34

Yeah.

是的。

2:22:34 Um…

嗯……

Not sure how much I should share there.

不确定我应该在那里分享多少。

It’s not quite finalized yet.

目前还没有完全确定。

Let’s- let’s just say, like, on either of these, my conditions are that the project stays open source.

这么说吧,对于其中任何一个,我的条件是该项目保持开源。

That it…

那它……

Maybe it’s gonna be a model like Chrome and Chromium.

也许它会是像 Chrome 和 Chromium 这样的模型。

Um, I think this is- this is too important to just give to a company and make it theirs.

嗯,我认为这太重要了,不能仅仅交给一家公司并使其成为他们的。

It…

它…

This is…

这是……

And we didn’t even talk about the whole community part, but, like, the- the thing that I experienced in San Francisco, like at ClawCon, seeing so many people so inspired, like…

我们甚至没有谈论整个社区的部分,但是,就像,我在旧金山经历的事情,就像在 ClawCon 上,看到这么多人如此受到启发,就像……

And having fun and just, like, building shit, and, like, having, like, robots in lobster stuff walking around.

享受乐趣,就像,建造粪便,还有,就像,有,就像,机器人在龙虾里走来走去。

Like, the…

就像,...

2:23:37 People told me, like, they didn’t experience this level of- of community excitement since, like, the early days of the internet, like 10, 15 years.

人们告诉我,自从互联网诞生之初,大约 10 年、15 年以来,他们就没有经历过这种程度的社区兴奋。

And there were a lot of high caliber people there, like…

那里有很多高素质的人,比如……

Um, I was amazed.

嗯,我很惊讶。

I also, like, was very sensory overloaded because too many people wanted to do selfies.

我也感觉感官超载,因为太多人想要自拍。

But I love this.

但我喜欢这个。

Like, this needs to stay a place where people can, like, hack and learn.

就像,这需要保留一个人们可以喜欢、黑客和学习的地方。

But also, I’m very excited to, like, make this into a version that I can get to a lot of people because I think this is the year of personal agents, and that’s the future.

而且,我也很高兴能够将其制作成一个可以向很多人提供的版本,因为我认为这是个人经纪人的一年,这就是未来。

And the fastest way to do that is teaming up with one of the labs.

最快的方法是与其中一个实验室合作。

And I also, on a personal level, I never worked at a large company, and I’m intrigued.

而且,就我个人而言,我从未在大公司工作过,我对此很感兴趣。

You know, we talk about experiences.

你知道,我们谈论的是经历。

Will I like it?

我会喜欢吗?

I don’t know.

我不知道。

2:24:42 But I want that experience.

但我想要那种经历。

Uh, I- I’m sure, like, if- if I- if I announce this, then there will be people like, “Oh, he sold out,” blah, blah, blah.

呃,我-我确信,如果-如果我-如果我宣布这一点,那么就会有人说,“哦,他卖完了,”等等,等等。

But the project will continue.

但该项目将继续进行。

From everything I talked to so far, I can even have more resources for that.

从到目前为止我所谈论的一切来看,我什至可以为此拥有更多资源。

Like, both s- both of those companies understand the value that I created something that accelerates our timeline and that got people excited about AI.

就像,这两家公司都了解我创造的价值,这些东西加速了我们的时间表,并让人们对人工智能感到兴奋。

I mean, can you imagine?

我的意思是,你能想象吗?

Like, I installed OpenClaw on one of my, I’m sorry, normie friends.

就像,我在我的一位(对不起,普通朋友)身上安装了 OpenClaw。

I’m sorry, Vahan.

对不起,瓦汉。

But he’s just a…

但他只是一个……

You know?

你知道吗?

2:25:32 Like, he’s-

就像,他是——

Lex Fridman2:25:33

Normie with love, yeah.

充满爱的诺米,是的。

2:25:33 For sure.

一定。

Peter Steinberger2:25:34

He- he, like, someone who uses the computer, but never really…

呵呵,就像一个使用电脑的人,但从来没有真正……

2:25:34 Like, yeah, use some ChatGPT sometimes, but not very technical.

就像,是的,有时使用一些 ChatGPT,但不是很技术性。

Wouldn’t really understand what I built.

不太明白我构建的是什么。

So, like, I’ll show you, and I- I paid for him the- the 90 buck, 100 buck, I don’t know, subscription for Entropic.

所以,就像,我会告诉你,我 - 我为他支付了 - 90 美元,100 美元,我不知道,订阅 Entropic。

And set up everything for him with, like, WSL Windows.

并使用 WSL Windows 等为他设置一切。

Lex Fridman2:26:00

Mm-hmm.

嗯嗯。

Peter Steinberger2:26:00

I was also curious, would it actually work on Windows, you know?

我也很好奇,它真的可以在 Windows 上运行吗?

2:26:00 Was a little early.

来得有点早了。

And then within a few days, he was hooked.

然后几天之内,他就上瘾了。

Like, he texted me about all the things he learned.

就像,他给我发短信讲述他学到的所有事情。

He built, like, even little tools.

他甚至建造了一些小工具。

He’s not a programmer.

他不是程序员。

And then within a few days he upgraded to the $200 subscription.

然后几天之内他就升级到了 200 美元的订阅。

Or euros, because he’s in Austria….

或者欧元,因为他在奥地利……

and he was in love with that thing.

他爱上了那件事。

That, for me, was like a very early product validation.

对我来说,这就像一个非常早期的产品验证。

It’s like, I built something that captures people.

就像,我建造了一些能够吸引人们的东西。

And then, a few days later, Entropic blocked him because, based on their rules using the subscription is problematic or whatever.

然后,几天后,Entropic 屏蔽了他,因为根据他们的规则,使用订阅是有问题的或其他什么。

And he was, like, devastated.

他就像被摧毁了。

And then he signed up for Mini Max for 10 bucks a month and uses that.

然后他每月以 10 美元的价格注册了 Mini Max 并使用它。

2:26:56 And I think that’s silly in many ways, because you just got a 200 buck customer.

我认为这在很多方面都很愚蠢,因为你刚刚得到了一个 200 美元的客户。

You just made someone hate your company, and we are still so early.

你刚刚让某人讨厌你的公司,而我们还这么早。

Like, we don’t even know what the final form is.

就像,我们甚至不知道最终的形式是什么。

Is it gonna be cloud code?

它会是云代码吗?

Probably not, you know?

可能不会,你知道吗?

Like, that seems very…

好像,这看起来很……

It seems very short-sighted to lock down your product so much.

如此锁定你的产品似乎是非常短视的。

All the other companies have been helpful.

所有其他公司都提供了帮助。

I- I’m in Slack of, of most of the big labs.

我-我在大多数大型实验室的 Slack 中。

Kind of everybody understands that we are still in an era of exploration, in the area of the radio shows on TV and not, and not a modern TV show that fully uses the format.

每个人都明白,我们仍然处于一个探索的时代,在电视广播节目领域,而不是完全使用该格式的现代电视节目。

Lex Fridman2:27:45

I think, I think you’ve made a lot of people, like, see the possibility.

我想,我认为你让很多人看到了这种可能性。

2:27:45 And non- Uh, sorry.

并且非-呃,抱歉。

Non, non-technical people see the possibility of AI, and just fall in love with this idea, and enjoy interacting with AI.

非技术人员看到了人工智能的可能性,并且爱上了这个想法,并享受与人工智能的互动。

And that’s a bea- That’s a really beautiful thing.

那是一件非常美丽的事情。

I think I also speak for a lot of people in saying, I think you’re one of the, the great people in AI in terms of having a good heart, good vibes, humor, the right spirit.

我想我也代表很多人说,我认为你是人工智能领域最伟大的人之一,拥有一颗善良的心、良好的氛围、幽默感和正确的精神。

And so it would, in a sense, this model that you’re describing, having open source part, and you being part of uh, also building a thing inside, additionally, of a large company would be great, because it’s great to have good people in those companies.

因此,从某种意义上说,你所描述的这个模型,拥有开源部分,并且你是呃,另外,在一家大公司内部构建一个东西,这会很棒,因为在这些公司中有优秀的人才是很棒的。

Peter Steinberger2:28:36

Yeah.

是的。

2:28:36 You know, what also people don’t really see is…

你知道,人们也没有真正看到的是……

I made this in three months.

我在三个月内做了这个。

I did other things as well.

我还做了其他事情。

You know, I have a lot of projects.

你知道,我有很多项目。

Like, this is not…

就像,这不是……

Yeah, in January, this was my main focus because I saw the storm coming.

是的,在一月份,这是我的主要关注点,因为我看到风暴即将来临。

But before that, I built a whole bunch of other things.

但在此之前,我还构建了一大堆其他东西。

Um, I have so many ideas.

嗯,我有很多想法。

Some should be there, some would be much better fitted when I have access to the latest toys- Uh, and I, I kind of want to have access to, like, the latest toys.

有些应该在那里,有些在我能接触到最新的玩具时会更合适——呃,我,我有点想接触到,比如,最新的玩具。

So this is important, this is cool, this will continue to exist.

所以这很重要,这很酷,这将继续存在。

My, my short-term focus is, like, working through those…

我的短期重点是解决这些问题……

Is it two- Is it 3,000 PRs now by now?

现在是 2-3,000 个 PR 了吗?

I don’t even know.

我什至不知道。

Like, there’s, there’s a little bit of backlog.

就像,有一点积压。

2:29:23 But this is not gonna be the thing that I’m gonna work until I’m, I’m, I’m 80, you know?

但这不会是我要工作的事情,直到我,我,我80岁,你知道吗?

This is…

这是……

This is a window into the future.

这是通向未来的窗口。

I’m gonna make this into a cool product.

我要把它变成一个很酷的产品。

But yeah, I have like…

但是,是的,我有喜欢...

I have more ideas.

我还有更多想法。

Lex Fridman2:29:36

If you had to pick, is there a company you lean?

如果你必须选择的话,你会选择哪一家公司吗?

2:29:36 So Meta, OpenAI, is there one you lean towards going?

那么 Meta、OpenAI,您倾向于哪一个呢?

Peter Steinberger2:29:44

I spend time with both of those.

我花时间和这两个人在一起。

2:29:44 And it’s funny, because a few weeks ago, I didn’t consider any of this.

这很有趣,因为几周前,我没有考虑过这些。

Um…

嗯……

And it’s really fucking hard.

这真的很难。

Like-

就像-

Lex Fridman2:30:05

Yeah.

是的。

Peter Steinberger2:30:06

I have some…

我有一些……

2:30:06 I know no people at OpenAI.

我不认识 OpenAI 的人。

I love their tech.

我喜欢他们的技术。

I think I’m the biggest codex advertisement shill that’s unpaid.

我认为我是最大的无偿广告骗子。

And it would feel so gratifying to, like, put a price on all the work I did for free.

为我免费所做的所有工作定价,会让人感到非常欣慰。

And I would love if something happens and those companies get just merged, because it’s like…

如果发生一些事情并且这些公司刚刚合并,我会很高兴,因为这就像......

Lex Fridman2:30:32

Is this the hardest decision you’ve ever had to do?

这是您做过的最艰难的决定吗?

Peter Steinberger2:30:39

No.

不。

2:30:39 You know, I had some breakups in the past that feel like it’s the same level.

你知道,我过去也经历过几次分手,感觉都是同一水平。

Lex Fridman2:30:43

Relationships, you mean?

你是说关系?

Peter Steinberger2:30:45

Yeah.

是的。

Lex Fridman2:30:47

Yeah, yeah, yeah, yeah.

是啊,是啊,是啊,是啊。

Peter Steinberger2:30:48

And, and I also know that, in the end, they’re both amazing.

而且,我也知道,最终,他们都很棒。

2:30:48 I cannot go wrong.

我不会出错。

This is like-

这就像——

Lex Fridman2:30:53

Right.

对。

Peter Steinberger2:30:54

This is, like, one of the most prestigious and, and, and, and, and largest…

这是,就像,最负盛名的和、和、和、和、和最大的......

2:30:54 I mean, not largest, but, like, they’re both very cool companies.

我的意思是,虽然不是最大的公司,但是,他们都是非常酷的公司。

Lex Fridman2:31:02

Yeah, they both really know scale.

是的,他们都非常了解规模。

2:31:02 So, if you’re thinking about impact, some of the wonderful technologies you’ve been exploring, how to do it securely, and how to do it at scale, such that you can have a positive impact on a large number of people.

因此,如果您正在考虑影响力,那么您一直在探索一些出色的技术,如何安全地做到这一点,以及如何大规模地做到这一点,这样您就可以对很多人产生积极的影响。

They both understand that.

他们都明白这一点。

Peter Steinberger2:31:19

You know, both Ned and Mark basically played all week with my product, and sent me like, “Oh, this is great.” Or, “This is shit.

你知道,内德和马克基本上都在玩我的产品一周,并向我发送这样的信息:“哦,这太棒了。”或者,“这真是狗屎。

2:31:19 Oh, I need to change this.” Or, like, funny little anecdotes.

哦,我需要改变这一点。”或者,比如有趣的小轶事。

And people using your stuff is kind of like the biggest compliment, and also shows me that, you know, they actually…

人们使用你的东西有点像最大的赞美,也向我表明,你知道,他们实际上......

T- they actually care about it.

T-他们实际上很关心它。

And I didn’t get the same on the OpenAI side.

我在 OpenAI 方面没有得到同样的结果。

Um, I got…

嗯,我得到了……

I got to see some other stuff that I find really cool, and they lure me with…

我还看到了其他一些我觉得很酷的东西,它们用……吸引了我。

I cannot tell you the exact number because of NDA, but you can, you can be creative and, and think of the Cerebras deal and how that would translate into speed.

由于保密协议,我无法告诉你确切的数字,但你可以,你可以发挥创造力,并考虑 Cerebras 交易以及如何将其转化为速度。

And it was very intriguing.

这非常有趣。

You know, like, you give me Thor’s hammer.

你知道,就像,你给了我雷神之锤。

Yeah.

是的。

…

……

been lured with tokens.

被代币引诱了。

So, yeah.

所以,是的。

Lex Fridman2:32:34

So, it- it’s funny.

所以,这——这很有趣。

2:32:34 So, so Marc started tinkering with the thing, essentially having fun with the thing.

所以,马克开始摆弄这个东西,本质上是享受这个东西的乐趣。

Peter Steinberger2:32:41

He got…

他得到了……

2:32:41 He…

他……

Like, when he first…

就像,当他第一次……

When he first approached me, I got him in my, in my WhatsApp and he was asking, “Hey, when are we have a call?” And I’m like, “I don’t like calendar entries.

当他第一次接近我时,我在我的 WhatsApp 中找到了他,他问:“嘿,我们什么时候通电话?”我想,“我不喜欢日历条目。

Let’s just call now.” And he was like, “Yeah, give me 10 minutes, I need to finish coding.”

我们现在就打电话吧。”他说:“是的,给我 10 分钟,我需要完成编码。”

Lex Fridman2:33:01

Mm-hmm.

嗯嗯。

Peter Steinberger2:33:01

Well, I guess that gives you street cred.

嗯,我想这会给你带来街头信誉。

2:33:01 It’s like, ugh, like, he’s still writing code.

就像,呃,就像,他还在写代码。

You know, he’s-

你知道,他是——

Lex Fridman2:33:07

Yeah, he does

是的,他确实

Peter Steinberger2:33:07

…

……

2:33:07 he didn’t drift away in just being a manager, he gets me.

他并没有因为仅仅担任一名主教练而迷失方向,他理解我。

That was a good first start.

这是一个良好的开始。

And then I think we had a, like, a 10-minute fight what’s better, cloud code or Codex.

然后我想我们进行了一场 10 分钟的争论,到底是云代码还是 Codex 更好。

Like, that’s the thing you first do, like, you casually call-

就像,这是你首先要做的事情,就像,你随便打电话-

Lex Fridman2:33:24

Yeah, that’s awesome

是的,那太棒了

Peter Steinberger2:33:24

…

……

2:33:24 someone with, like, the- that owns one of the largest companies in the world and, and you have a 10 minutes conversation about that.

某人拥有世界上最大的公司之一,并且你们就此进行了 10 分钟的对话。

Lex Fridman2:33:30

Yeah, yeah.

是啊是啊。

Peter Steinberger2:33:30

And then I think afterwards he called me eccentric but brilliant.

然后我想后来他说我古怪但聪明。

2:33:30 But I also had some…

但我也有一些……

I had some really, really cool discussion with Sam Altman and he’s, he’s very thoughtful brilliant and I like him a lot from the, from the little time I had, yeah.

我和萨姆·奥尔特曼进行了一些非常非常酷的讨论,他非常有思想,才华横溢,从我有的那段时间起,我就非常喜欢他,是的。

I mean, I know it’s peop- some people vilify both of those people.

我的意思是,我知道有人诽谤这两个人。

I don’t think it’s fair.

我认为这不公平。

Lex Fridman2:34:15

I think no matter what the stuff you’re building and the kind of human you are doing stuff at scale is kinda awesome.

我认为,无论你正在建造什么东西,也无论你正在做什么样的人,大规模地做事情都是很棒的。

2:34:15 I’m excited.

我很兴奋。

Peter Steinberger2:34:24

I am super pumped.

我非常兴奋。

2:34:24 And you know the beauty is if, if it doesn’t work out, I can just do my own thing again.

你知道,美妙之处在于,如果事情不成功,我可以再次做我自己的事情。

Like, I, I told them, like, I, I don’t do this for the money, I don’t give a fuck.

就像,我,我告诉他们,就像,我,我这样做不是为了钱,我不在乎。

I-

我-

Lex Fridman2:34:42

Yeah.

是的。

Peter Steinberger2:34:42

I mean, of course, of course it’s a nice compliment but I wanna have fun and have impact, and that’s ultimately what made my decision.

我的意思是,当然,这当然是一个很好的赞美,但我想要玩得开心并产生影响,这就是我最终做出决定的原因。

Lex Fridman2:34:58

Can I ask you about…

我可以问你关于……

2:34:58 we’ve talked about it quite a bit, but maybe just zooming out about how OpenCloud works.

我们已经谈论了很多,但也许只是缩小了 OpenCloud 的工作原理。

We talked about different components, I want to ask if there’s some interesting stuff we missed.

我们讨论了不同的组件,我想问是否有一些有趣的东西我们错过了。

So, there’s the gateway, there’s the chat clients, there’s the harness there’s the agentic loop.

所以,有网关,有聊天客户端,有安全带,有代理循环。

You said somewhere that everybody should im- implement an agent loop at some point in their lives.

您曾在某处说过,每个人都应该在生命中的某个时刻实施代理循环。

Peter Steinberger2:35:24

Yeah, because it’s like the, it’s like the Hello World in AI, you know?

是的,因为它就像人工智能中的 Hello World,你知道吗?

2:35:24 And it’s actually quite simple.

实际上很简单。

Lex Fridman2:35:30

Yeah.

是的。

Peter Steinberger2:35:30

And it- it’s good to understand that that stuff’s not magic.

而且——很高兴明白那东西不是魔法。

2:35:30 You can, you can easily build it yourself.

你可以,你可以轻松地自己构建它。

So, writing your own little cloud code…

所以,编写你自己的小云代码......

I, I even did this at a conference in Paris for people to, like, introduce them to AI.

我什至在巴黎的一次会议上这样做了,让人们向他们介绍人工智能。

I think it’s it’s a fun little practice.

我认为这是一个有趣的小练习。

And you, you covered a lot.

而你,你涵盖了很多。

I think one, one silly idea I had that turned out to be quite cool is I built this thing with full system access.

我认为我有一个非常愚蠢的想法,但事实证明它非常酷,那就是我构建了具有完整系统访问权限的东西。

So it’s like, you know, with great power comes great responsibility.

所以,你知道,权力越大,责任越大。

2:36:09 And I was like, “How can I up the stakes a little bit more?”

我当时想,“我怎样才能加大赌注呢?”

Lex Fridman2:36:13

Yeah, right.

是的,对。

Peter Steinberger2:36:14

And I just made a…

我刚刚做了一个……

2:36:14 I made it proactive.

我主动采取了行动。

So, I added a prompt.

所以,我添加了一个提示。

Initially, it was just a prompt, surprise me.

最初,这只是一个提示,令我惊讶。

Every, like, half an hour, surprise me, you know?

每隔半个小时,就会给我一个惊喜,你知道吗?

And later on I changed it to be like a little more specific and-

后来我把它改得更具体一点——

Lex Fridman2:36:31

Yeah

是啊

Peter Steinberger2:36:31

…

……

2:36:31 in the definition of surprise.

在惊喜的定义中。

But the fact that I made it proactive and that it knows you and that it cares about you, it- it’s at least it’s programmed to that, prompted to do that.

但事实上,我让它变得主动,它了解你,它关心你,它——至少它是这样编程的,促使它这样做。

And that, that is a follow on, on your current session makes it very interesting because it would just sometimes ask a follow-up question or like, “How’s your day?”

这是当前会话的后续内容,这使得它非常有趣,因为它有时会问一个后续问题或类似的问题,“你今天过得怎么样?”

Lex Fridman2:36:53

Yeah, right.

是的,对。

Peter Steinberger2:36:53

And I just made a…

我刚刚做了一个……

2:36:53 I made it proactive.

我主动采取了行动。

So, I added a prompt.

所以,我添加了一个提示。

Initially, it was just a prompt, surprise me.

最初,这只是一个提示,令我惊讶。

Every, like, half an hour, surprise me, you know?

每隔半个小时,就会给我一个惊喜,你知道吗?

And later on I changed it to be like a little more specific and-

后来我把它改得更具体一点——

Lex Fridman2:36:58

Yeah

是啊

Peter Steinberger2:36:58

…

……

2:36:58 in the definition of surprise.

在惊喜的定义中。

But the fact that I made it proactive and that it knows you and that it cares about you, it- it’s…

但事实上,我让它变得主动,它了解你并且关心你,它——它是……

at least it’s programmed to that, prompted to do that.

至少它被编程为那样,并被提示这样做。

And that, that is a follow on, on your current session makes it very interesting because it would just sometimes ask a follow-up question or like, “How’s your day?” I mean, again, it’s a little creepy or weird or interesting but Heartbeat very…

这是当前会话的后续内容,这使得它非常有趣,因为它有时会问一个后续问题或类似的问题,“你今天过得怎么样?”我的意思是,这有点令人毛骨悚然、奇怪或有趣,但《心跳》非常……

in the beginning, it’s still…

一开始,还是……

today, it doesn’t…

今天,它不……

the model doesn’t choose to use it a lot.

该模型不会选择大量使用它。

Lex Fridman2:37:16

By the way, we’re, we’re, we’re talking about Heartbeat, as you mentioned, the thing that regularly-

顺便说一句,我们,我们,我们正在谈论心跳,正如你提到的,经常-

Peter Steinberger2:37:22

Yeah.

是的。

2:37:22 Like kicks-

像踢腿一样——

Lex Fridman2:37:23

…

……

2:37:23 Acts.

使徒行传。

Peter Steinberger2:37:23

You just kick off the loop.

你只需开始循环即可。

Lex Fridman2:37:25

Isn’t that just a cron job, man?

这不就是一个 cron 工作吗,伙计?

Peter Steinberger2:37:27

Yeah, right, I mean, it’s like-

是的,对,我的意思是,就像——

Lex Fridman2:37:29

It’s the cr- the criticisms that you get are hilarious.

这就是你收到的批评很搞笑。

Peter Steinberger2:37:31

You can, you can deduce any idea to like a silly…

你可以,你可以推断出任何想法就像一个愚蠢的......

2:37:31 Yeah, it’s just, it’s just a cron job in the end.

是的,只是,这最终只是一个 cron 工作。

I have like cron- separate cron jobs.

我有类似 cron 的单独的 cron 作业。

Lex Fridman2:37:41

Isn’t love just evolutionary biology manifesting itself and isn’t…

爱不只是进化生物学的表现吗?

2:37:41 aren’t you guys just using each other?

你们不是只是互相利用吗?

Peter Steinberger2:37:49

And then, yeah, and the project is all just glue of a few different dependencies-

然后,是的,这个项目只是一些不同依赖项的粘合剂 -

Lex Fridman2:37:52

Yeah

是啊

Peter Steinberger2:37:53

…

……

2:37:53 and there’s nothing original.

而且没有什么原创的。

Why do people…

为什么人们……

Well, you know, isn’t Dropbox just FTP with extra steps?

好吧,您知道,Dropbox 不就是带有额外步骤的 FTP 吗?

Lex Fridman2:38:00

Yeah.

是的。

Peter Steinberger2:38:01

I found it surprising where I had this I had a shoulder operation a few months ago, so.

我发现令我惊讶的是我几个月前做了肩部手术,所以。

Lex Fridman2:38:06

Mm-hmm.

嗯嗯。

Peter Steinberger2:38:08

And the model rarely used Heartbeat, but then I was in the hospital, and it knew that I had the operation and it checked up on me.

该模型很少使用 Heartbeat,但后来我在医院,它知道我做了手术,并对我进行了检查。

2:38:08 It’s like, “Are you okay?” And I just…

就像,“你还好吗?”而我只是……

It’s like, again, apparently, like, if something’s significant in the context, that triggered the Heartbeat when it rarely used the Heartbeat….

显然,这就像,如果某件事在上下文中很重要,那么当它很少使用心跳时就会触发心跳……。

And it does that sometimes for people, and that just makes it a lot more relatable.

有时它对人们来说也是如此,这只会让人们更容易产生共鸣。

Lex Fridman2:38:36

Let me look this up on Perplexity, how OpenCall works just to see if I’m missing any of the stuff.

让我在 Perplexity 上查一下 OpenCall 的工作原理,看看我是否遗漏了任何内容。

2:38:36 Local agent run time, high-level architecture.

本地代理运行时,高层架构。

There’s…

有……

Oh, we haven’t talked much about skills, I suppose.

哦,我想我们还没有太多谈论技能。

Skill hub, the tools in the skill lair, but that’s definitely a huge component and there’s a huge growing set of skills-

技能中心,技能巢穴中的工具,但这绝对是一个巨大的组成部分,并且有大量不断增长的技能-

Peter Steinberger2:38:55

You know, you know what I love?

你知道,你知道我爱什么吗?

2:38:55 That half a year ago, like everyone was talking about MCPs-

半年前,就像大家都在谈论MCP一样——

Lex Fridman2:39:02

Yeah

是啊

Peter Steinberger2:39:02

…

……

2:39:02 and I was like, “Screw MCPs.

我当时想,“去他妈的 MCP。

Every MCP would be better as a CLI.” And now this stuff doesn’t even have MCP support.

每个 MCP 作为 CLI 会更好。”现在这个东西甚至没有 MCP 支持。

I mean, it, it has with asterisks, but not in the core lair, and nobody’s complaining.

我的意思是,它带有星号,但不在核心巢穴中,而且没有人抱怨。

Lex Fridman2:39:23

Mm-hmm.

嗯嗯。

Peter Steinberger2:39:24

So my approach is if you want to extend the model with more features, you just build a CLI and the model can call the CLI, probably gets it wrong, calls the help menu, and then on demand loads into the context what it needs to use the CLI.

所以我的方法是,如果你想用更多功能扩展模型,你只需构建一个 CLI,模型可以调用 CLI,可能会出错,调用帮助菜单,然后按需将使用 CLI 所需的内容加载到上下文中。

2:39:24 It just needs a sentence to know that the CLI exists if it’s something that the model doesn’t know about default.

如果模型不知道默认的情况,只需要一句话就知道 CLI 存在。

And even for a while, I, I didn’t really care about skills, but skills are actually perfect for that because they, they boil down to a single sentence that explains the skill and then the model loads the skill, and that explains the CLI, and then the model uses the CLI.

甚至有一段时间,我,我并不真正关心技能,但技能实际上是完美的,因为它们可以归结为一个句子,解释技能,然后模型加载技能,解释 CLI,然后模型使用 CLI。

Some skills are, like raw, but most of the time, networks.

有些技能是原始技能,但大多数时候是网络。

Lex Fridman2:40:16

It’s interesting um, I’m asking Perplexity MCP versus skills, because this kind of requires a hot take that’s quite recent, because your general view is MCPs are dead-ish.

这很有趣,嗯,我问的是 Perplexity MCP 与技能,因为这需要最近的热门话题,因为你的普遍观点是 MCP 已经死了。

2:40:16 So MCPs is a more structured thing.

所以 MCP 是一个更加结构化的东西。

So if you listen to Perplexity here, MCP is what can I reach?

那么如果你在这里听Perplexity,MCP是我能达到的吗?

So APIs, database services files via protocol.

API、通过协议的数据库服务文件。

So a structured protocol of how you communicate with a thing, and then skills is more how should I work?

因此,关于如何与事物沟通的结构化协议,然后技能更多的是我应该如何工作?

Procedures, hostile helper scripts and prompts are often written in a kind of semi-structured natural language, right?

程序、恶意帮助脚本和提示通常是用一种半结构化自然语言编写的,对吧?

And so technically skills could replace MCP if you have a smart enough model.

因此,如果你有足够智能的模型,技术技能可以取代 MCP。

Peter Steinberger2:41:00

I think the main beauty is, is that models are really good at calling Unix commands.

我认为主要的优点是模型非常擅长调用 Unix 命令。

2:41:00 So if you just add another CLI, that’s just another Unix command in the end.

因此,如果您只是添加另一个 CLI,那最终只是另一个 Unix 命令。

And MCP is…

而 MCP 是……

That has to be added in training.

这必须在训练中添加。

That’s not a very natural thing for the model.

对于模型来说,这不是一件很自然的事情。

It requires a very specific syntax.

它需要非常具体的语法。

And the biggest thing, it’s not composable.

最重要的是,它不可组合。

So imagine if I have a service that gives me better data and gives me the temperature, the average temperature, rain, wind and all the other stuff, and I get like this huge blob back.

所以想象一下,如果我有一项服务可以为我提供更好的数据,并为我提供温度、平均温度、雨量、风量和所有其他信息,我会得到一个巨大的斑点。

As a model, I always have to get the huge blob back.

作为一名模特,我总是必须把巨大的斑点拿回来。

I have to fill my context with that huge blob and then pick what I want.

我必须用那个巨大的斑点填充我的上下文,然后选择我想要的。

There’s no way for the model to naturally filter unless I think about it proactively and add a filtering way into my MCP.

模型没有办法自然过滤,除非我主动思考并在我的 MCP 中添加过滤方式。

2:41:53 But if I would build the same as a CLI and it would give me this huge blob, it could just add a JQ command and filter itself and then only, only get me what I actually need.

但如果我构建与 CLI 相同的东西,它会给我这个巨大的 blob,它只需添加一个 JQ 命令并过滤本身,然后就只能得到我真正需要的东西。

Or maybe even compose it into a script to, like do some calculations with the temperature and only give me the exact output and the mo- and the…

或者甚至可以将其编写成一个脚本,例如对温度进行一些计算,然后只给我准确的输出以及 mo- 和…

you have no context pollution.

你没有上下文污染。

Again, you can solve that with like sub-agents and more charades, but it’s just like workarounds for something that might not be the optimal way.

同样,您可以使用类似的子代理和更多的字谜游戏来解决这个问题,但这就像某些可能不是最佳方法的解决方法。

There’s…

有……

It definitely it was, you know, it was good that we had MCPs because it pushed a lot of companies towards building APIs and now I, I can like look at an MCP and just make it into a CLI.

这绝对是,你知道,我们拥有 MCP 是件好事,因为它推动了很多公司构建 API,现在我可以查看 MCP 并将其放入 CLI 中。

Lex Fridman2:42:37

Mm-hmm.

嗯嗯。

Peter Steinberger2:42:37

But this, this inherent problem that MCPs by default clutter up your context.

但是,MCP 默认情况下的这个固有问题会使您的上下文变得混乱。

2:42:37 Plus the fact that most MCPs are not made good, in general make it just not a very useful paradigm.

再加上大多数 MCP 都没有做得很好,总的来说,它并不是一个非常有用的范例。

There’s some exceptions like Playwright for example that requires state and it’s actually useful.

有一些例外,例如 Playwright 需要状态,而且它实际上很有用。

That is an acceptable choice.

这是一个可以接受的选择。

Lex Fridman2:43:05

So Playwright you use for browser use, which I think is c- already in OpenClaw is quite incredible, right?

所以你使用 Playwright 来浏览器使用,我认为 OpenClaw 中已经有这样的功能,这非常令人难以置信,对吧?

Peter Steinberger2:43:11

Yeah.

是的。

Lex Fridman2:43:12

You can basically do everything, most things you can think of using browser use.

您基本上可以使用浏览器做所有您能想到的事情。

Peter Steinberger2:43:17

That, that gets into the whole arch of every app is just a very slow API now, if they want or not.

不管他们愿意与否,现在每个应用程序的整个架构都只是一个非常慢的 API。

2:43:17 And that through personal agents a lot of apps will disappear.

通过个人代理,许多应用程序将会消失。

You know, like I had a…

你知道,就像我有一个……

I built a CLI for Twitter.

我为 Twitter 构建了一个 CLI。

I mean, I- I just reverse engineered their website and used the internal API, which is not very allowed.

我的意思是,我-我只是对他们的网站进行了逆向工程并使用了内部 API,这是不太允许的。

Lex Fridman2:43:50

It’s called Bird, short-lived.

它的名字叫鸟,寿命短。

Peter Steinberger2:43:53

It was called Bird, because the bird had to disappear.

它被称为鸟,因为鸟必须消失。

Lex Fridman2:43:57

The, the wings were clipped.

结果,翅膀被剪掉了。

Peter Steinberger2:43:59

All they did is they just made access slower.

他们所做的只是让访问速度变慢。

2:43:59 Yeah, not tak- you’re not actually taking a feature away, but now inst- if, if your agent wants to read a tweet, it actually has to open the browser and read the tweet.

是的,不是 tak - 您实际上并没有取消某个功能,而是现在 - 如果您的代理想要阅读一条推文,它实际上必须打开浏览器并阅读该推文。

And it will still be able to read the tweet.

而且它仍然能够阅读该推文。

It will just take longer.

只是需要更长的时间。

It’s not like you are making something that was possible, not possible.

这并不是说你正在创造一些可能的东西,而不是不可能的东西。

No.

不。

Now, it’s just taking…

现在,只需……

Now it’s just a bit slower.

现在只是慢了一点。

So, so it doesn’t really matter if your service wants to be an API or not.

所以,你的服务是否想成为 API 并不重要。

If I can access it in the browser……

如果我可以在浏览器中访问它......

easy API.

简单的API。

It’s a slow API.

这是一个缓慢的 API。

Lex Fridman2:44:35

Can you empathize with their situation?

你能体谅他们的处境吗?

2:44:35 Like, what would you do if you were Twitter, if you were X?

比如,如果你是 Twitter,如果你是 X,你会怎么做?

Because they’re basically trying to protect against other large companies scraping all their data.

因为他们基本上是在试图防止其他大公司窃取他们的所有数据。

Peter Steinberger2:44:45

Yeah.

是的。

Lex Fridman2:44:46

But in so doing, they’re cutting off like a million different use cases for smaller developers that actually want to use it for helpful cool stuff.

但在这样做的过程中,他们为那些真正想用它来做有用的、很酷的东西的小型开发人员切断了大约一百万个不同的用例。

Peter Steinberger2:44:54

I think that if you have a very low per day baseline per account that allows read-only access would solve a lot of problems.

我认为,如果每个帐户的每日基准非常低,允许只读访问,将会解决很多问题。

2:44:54 There’s plenty, plenty of automations where people create a bookmark and then use OpenClaw to, like, find the bookmark, do research on it, and then send you an email-

有很多很多的自动化,人们创建书签,然后使用 OpenClaw 来查找书签,对其进行研究,然后向您发送电子邮件 -

Lex Fridman2:45:16

Mm-hmm

嗯嗯

Peter Steinberger2:45:16

…

……

2:45:16 with, like, more details on it or a summary.

以及更多详细信息或摘要。

That’s a cool approach.

这是一个很酷的方法。

I also want all my bookmarks somewhere to search.

我还希望我的所有书签都可以在某个地方进行搜索。

I would still like to have that.

我仍然想要那个。

Lex Fridman2:45:26

So, read-only access for the bookmarks you make on X.

因此,您在 X 上创建的书签具有只读访问权限。

2:45:26 That seems like an incredible application because a lot of us find a lot of cool stuff on X, we bookmark, that’s the general purpose of X.

这看起来是一个令人难以置信的应用程序,因为我们很多人在 X 上发现了很多很酷的东西,我们添加了书签,这就是 X 的一般用途。

It’s like, holy shit, this is awesome.

就像,天哪,这太棒了。

Oftentimes, you bookmark so many things you never look back at them.

通常,您会为很多事情添加书签,而您永远不会回头看它们。

Peter Steinberger2:45:40

Yeah.

是的。

Lex Fridman2:45:40

It would be nice to have tooling that organizes them and allows you to research it further.

如果有工具可以组织它们并允许您进一步研究它,那就太好了。

Peter Steinberger2:45:44

Yeah, I mean, and to be frank, I, I mean, I, I told Twitter proactively that, “Hey, I built this and there’s a need.” And they’ve been really nice, but also like, “Take it down.” Fair.

是的,我的意思是,坦率地说,我,我的意思是,我,我主动告诉 Twitter,“嘿,我构建了这个,并且有需求。”他们真的很好,但也喜欢,“把它拿下来。”公平的。

2:45:44 Totally fair.

完全公平。

But I hope that this woke up the team a little bit that there’s a need.

但我希望这能让团队清醒一点,意识到这是有必要的。

And if all you do is making it slower, you’re just reducing access to your platform.

如果你所做的只是让它变慢,那么你只是在减少对平台的访问。

I’m sure there’s a better way.

我确信有更好的方法。

I also, I’m very much against any automation on Twitter.

我也非常反对 Twitter 上的任何自动化。

If you tweet at me with AI, I will block you.

如果你用人工智能向我发推文,我会阻止你。

No first strike.

没有先发制人。

As soon as it smells like AI, and AI still has a smell.

一旦闻起来像人工智能,人工智能仍然有气味。

Lex Fridman2:46:31

Mm-hmm.

嗯嗯。

Peter Steinberger2:46:32

Especially on tweets.

尤其是在推文上。

2:46:32 It’s very hard to tweet in a way that does look completely human.

以一种看起来完全人性化的方式发推文是非常困难的。

Lex Fridman2:46:38

Mm-hmm.

嗯嗯。

Peter Steinberger2:46:38

And then I block.

然后我就阻止了。

2:46:38 Like, I have a zero tolerance policy on that.

就像,我对此采取零容忍政策。

And I think it would be very helpful if they, if, like, tweets done via API would be marked.

我认为如果他们通过 API 发布的推文被标记的话,那将会非常有帮助。

Maybe there’s some special cases where…

也许有一些特殊情况......

But, and there should be, there should be a very easy way for agents to get their own Twitter account.

但是,而且应该有,代理商应该有一种非常简单的方法来获得自己的 Twitter 帐户。

Um…

嗯……

Lex Fridman2:47:04

Mm-hmm.

嗯嗯。

Peter Steinberger2:47:07

We, we need to rethink social platforms a little bit if, if, if we, we, we go towards a future where everyone has their agent and agents maybe have their own Instagram profiles or Twitter accounts, so I can, like, do stuff on my behalf.

我们,我们需要重新考虑一下社交平台,如果,如果,如果我们,我们,我们走向一个每个人都有自己的经纪人并且经纪人可能有自己的 Instagram 个人资料或 Twitter 帐户的未来,这样我就可以代表我做事。

2:47:07 I think it should very clearly be marked that they are doing stuff on my behalf and it’s not me.

我认为应该非常清楚地表明他们是在代表我做事,而不是我。

Because content is now so cheap.

因为内容现在太便宜了。

Eyeballs are the expensive part.

眼球是最昂贵的部分。

And I find it very triggering when I read something and then I’m like, oh, no, this smells like AI.

当我读到一些东西时,我发现它非常触发,然后我想,哦,不,这闻起来像人工智能。

Lex Fridman2:47:41

Yeah.

是的。

2:47:41 Like, where, where is this headed in terms of what we value about the human experience?

比如,就我们对人类体验的重视而言,这将走向何方?

It feels like we’ll, we’ll move more and more towards in-person interaction and we’ll just communicate.

感觉我们会越来越倾向于面对面的互动,我们只会进行交流。

We’ll talk to our AI agent to, to accomplish different tasks, to learn about different things, but we won’t value online interaction because there’ll be so much AI slob that smells and so many bots that it’s difficult.

我们将与我们的人工智能代理交谈,以完成不同的任务,了解不同的事物,但我们不会重视在线互动,因为会有太多的人工智能懒虫和机器人,这很困难。

Peter Steinberger2:48:15

Well, if it’s smart, then it shouldn’t be difficult to filter.

好吧,如果它很聪明,那么过滤应该不难。

2:48:15 And then I can look at it if I want to.

然后如果我想的话我可以看一下。

But yeah, this is, like, a big thing we need to solve right now.

但是,是的,这是我们现在需要解决的一件大事。

E- especially on this project, I get so many emails that are, let’s say nicely, agentically written.

尤其是在这个项目上,我收到了很多电子邮件,可以说,这些电子邮件写得很漂亮。

Lex Fridman2:48:36

Yeah.

是的。

Peter Steinberger2:48:36

But I much rather read your broken English than your AI slob.

但我更愿意读你蹩脚的英语,而不是你的人工智能懒虫。

2:48:36 You know, of course there’s a human behind it, and yet they, they prompt it.

你知道,当然有一个人在背后,但他们,他们推动了它。

I’d much rather read your prompt than what came out.

我更愿意阅读你的提示而不是结果。

Um, I think we’re reaching a point where I value typos again.

嗯,我认为我们已经达到了我再次重视拼写错误的地步。

Lex Fridman2:48:56

Yeah.

是的。

Peter Steinberger2:48:56

Like…

就像……

2:48:56 Like, and I, I mean, it also took me a while to, like, come to the realization.

就像,我,我的意思是,我也花了一段时间才意识到。

I, on my blog I experimented with creating a blog post with agents and ultimately it took me about the same time to, like, steer agent towards something I like.

我在我的博客上尝试与代理商一起创建博客文章,最终我花了大约相同的时间来引导代理商去做我喜欢的事情。

But it missed the nuances that, how I would write it.

但它忽略了我将如何写它的细微差别。

You know, you can like, you can steer it towards your style, but it’s not gonna be all your style.

你知道,你可以喜欢,你可以引导它走向你的风格,但这不会是你的全部风格。

So, I, I completely moved away from that.

所以,我,我完全摆脱了这一点。

I, I, everything, everything I blog is organic, handwritten and maybe, maybe I, I, I use AI as a fix my worse typos.

我,我,一切,我博客的一切都是有机的,手写的,也许,也许我,我,我使用人工智能来修复我更糟糕的打字错误。

But there’s value in the rough parts of an actual human.

但真实人类的粗糙部分是有价值的。

Lex Fridman2:49:53

Isn’t that awesome?

这不是很棒吗?

2:49:53 Isn’t that beautiful?

那不是很漂亮吗?

That now because of AI we value the raw humanity in each of us more.

现在,由于人工智能,我们更加重视我们每个人的原始人性。

Peter Steinberger2:50:02

I also, I also realized this thing that I, I rave about AI and use it so much for anything that’s code, but I’m allergic if it’s stories.

我也,我也意识到这一点,我对人工智能非常着迷,并将其大量用于任何代码,但如果它是故事,我会过敏。

Lex Fridman2:50:12

Right.

正确的。

2:50:12 Yeah.

是的。

Peter Steinberger2:50:14

Also, documentation, still fine with AI.

另外,文档对于人工智能来说仍然很好。

2:50:14 You know, better than nothing.

你知道,总比没有好。

Lex Fridman2:50:17

And for now it’s still i- it applies in the mi- in the visual medium too.

现在它仍然是i-它也适用于mi-视觉媒体。

2:50:17 It’s fascinating how allergic I am to even a little bit of AI slob in in video and images.

令人着迷的是,我对视频和图像中哪怕是一点点人工智能的懒惰都过敏。

It’s useful, it’s nice if it’s like a little component of like-

它很有用,如果它像类似的一个小组件,那就太好了-

Peter Steinberger2:50:32

Or even, even those images.

甚至,甚至那些图像。

2:50:32 The, like, all these infographics and stuff, the-…

比如说,所有这些信息图表之类的东西,...

they trigger me so hard.

他们如此强烈地触发我。

Lex Fridman2:50:38

Yeah.

是的。

Peter Steinberger2:50:39

Like, it immediately makes me think less of your content.

就像,它立即让我不再考虑你的内容。

2:50:39 And it …

而且它……

They were novel for, like, one week and now it just screams slop.

它们在大约一周内还很新颖,但现在却变得令人尖叫。

Lex Fridman2:50:50

Yeah.

是的。

Peter Steinberger2:50:51

Even- even if people work hard on it, using …

即使——即使人们努力工作,使用……

2:50:51 And I- I have some on my blog post, you know, in the- in the time where I- I explored this new medium.

我-我的博客文章中有一些,你知道,在我-我探索这种新媒体的时候。

But now, they trigger me as well.

但现在,它们也触发了我。

It’s like, yeah, this is …

就像,是的,这是……

This just screams AI slop.

这简直就是人工智能的废话。

I-

我-

Lex Fridman2:51:06

What…

什么……

2:51:06 I don’t know what that is, but I went through that too.

我不知道那是什么,但我也经历过。

I was really excited by the diagrams.

我对这些图表感到非常兴奋。

And then I realized, in order to remove from them hallucinations, you actually have to do a huge amount of work.

然后我意识到,为了消除他们的幻觉,你实际上必须做大量的工作。

And you’re just using it to draw the better diagrams, great.

你只是用它来绘制更好的图表,太棒了。

And then I’m proud of the diagram.

然后我对这个图表感到自豪。

I’ve used them for literally, like, ki- ki- kind of like you said for maybe a couple of weeks.

我已经使用它们了,就像你说的那样,大概有几个星期了。

And now I look at those, and I- I feel like I feel when I look at Comic Sans as a font or- or something like this.

现在我看着这些,我-我感觉就像我将 Comic Sans 视为一种字体或-或类似的东西时的感觉。

2:51:32 It’s like, “No, this is-“

就像,“不,这是——”

Peter Steinberger2:51:35

It’s a smell.

这是一种气味。

Lex Fridman2:51:35

“…

“……

2:51:35 this is fake.

这是假的。

It’s fraudulent.

这是欺诈性的。

There’s something wrong with it.” And it…

有问题。”而它……

Peter Steinberger2:51:41

It’s a smell.

这是一种气味。

Lex Fridman2:51:42

It’s a smell.

这是一种气味。

Peter Steinberger2:51:44

It’s a smell.

这是一种气味。

Lex Fridman2:51:44

And it’s awesome because it re- it reminds you that we know.

这太棒了,因为它再次提醒您我们知道。

2:51:44 There’s so much to humans that’s amazing and we know that.

人类有很多令人惊奇的事情,我们知道这一点。

And we- we know it.

我们——我们知道这一点。

We know it when we see it.

当我们看到它时我们就知道了。

And so that gives me a lot of hope, you know?

这给了我很大的希望,你知道吗?

That gives me a lot of hope about the human experience.

这让我对人类的经历充满了希望。

It’s not going to be damaged by …

它不会被损坏……

It’s only going to be empowered as tools by AI.

它只会被人工智能授权为工具。

It’s not going to be damaged or limited or somehow altered to where it’s no longer human.

它不会被损坏、限制或以某种方式改变到不再是人类的程度。

So …

所以……

Uh, I need a bathroom break.

呃,我需要去趟厕所。

Quick pause.

快速暂停。

You mentioned that a lot of the apps might be basically made obsolete.

您提到很多应用程序可能基本上已经过时了。

Do you think agents will just transform the entire app market?

您认为代理商会改变整个应用市场吗?

Peter Steinberger2:52:30

Yeah.

是的。

2:52:30 Uh, I noticed that on Discord, that people just said how their …

呃,我注意到在 Discord 上,人们只是说他们的……

like, what they build and what they use it for.

比如他们建造了什么以及他们用它做什么。

And it’s like, why do you need MyFitnessPal when the agent already knows where I am?

就像,当代理已经知道我在哪里时,为什么还需要 MyFitnessPal?

So, it can assume that I make bad decisions when I’m at, I don’t know, Waffle House, what’s around here?

所以,它可以假设我在我不知道华夫饼屋时做出了错误的决定,这里附近有什么?

Or- or briskets in Austin.

或者-或者奥斯汀的牛胸肉。

Lex Fridman2:52:57

There’s no bad decisions around briskets, but yeah.

关于牛胸肉没有什么糟糕的决定,但是是的。

Peter Steinberger2:53:00

No, that’s the best decision, honestly.

不,老实说,这是最好的决定。

2:53:00 Um-

嗯-

Lex Fridman2:53:03

Your agent should know that.

你的代理人应该知道这一点。

Peter Steinberger2:53:04

But it can, like …

但它可以,就像……

2:53:04 It can modify my- my gym workout based on how well I slept, or if I’m …

它可以根据我的睡眠质量或者我是否……来修改我的健身锻炼。

if I have stress or not.

我是否有压力。

Like, it has so much more context to make even better decisions than any of this app even could do.

就像,它比任何其他应用程序都拥有更多的背景信息,可以做出更好的决策。

Lex Fridman2:53:18

Mm-hmm.

嗯嗯。

Peter Steinberger2:53:19

It could show me UI just as I like.

它可以按照我喜欢的方式显示用户界面。

2:53:19 Why do I still need an app to do that?

为什么我仍然需要一个应用程序来做到这一点?

Why do I have to …

为什么我必须……

Why should I pay another subscription for something that the agent can just do now?

为什么我要为代理现在可以做的事情支付另一笔订阅费用?

And why do I need my- my Eight Sleep app to control my bed when I can tell the a- …

为什么我需要我的——我的八睡眠应用程序来控制我的床,而我可以告诉——……

tell the agent to …

告诉代理人……

You know, the agent already knows where I am, so he can, like, turn off what I don’t use.

你知道,特工已经知道我在哪里,所以他可以关掉我不使用的东西。

Lex Fridman2:53:45

Mm-hmm.

嗯嗯。

Peter Steinberger2:53:47

And I think that will …

我认为这会……

2:53:47 that will translate into a whole category of apps that are no longer …

这将转化为一整类不再是……的应用程序。

I will just naturally stop using because my agent can just do it better.

我会很自然地停止使用,因为我的经纪人可以做得更好。

Lex Fridman2:54:00

I think you said somewhere that it might kill off 80% of apps.

我想你在某处说过它可能会杀死 80% 的应用程序。

Peter Steinberger2:54:04

Yeah.

是的。

Lex Fridman2:54:05

Don’t you think that’s a gigantic transformative effect on just all software development?

您不认为这对所有软件开发都会产生巨大的变革性影响吗?

2:54:05 So that means it might kill off a lot of software companies.

所以这意味着它可能会杀死很多软件公司。

Peter Steinberger2:54:13

Yeah.

是的。

2:54:13 Um-

嗯-

Lex Fridman2:54:16

It’s a scary thing.

这是一件可怕的事情。

2:54:16 So, like, do you think about the impact that has on the economy?

那么,您是否考虑过这对经济的影响?

On just the ripple effects it has to society?

仅仅是它对社会产生的连锁反应吗?

Transforming who builds what tooling.

改变谁构建什么工具。

It empowers a lot of users to get stuff done, to get stuff more efficiently, to get it done cheaper.

它使许多用户能够以更高效、更便宜的方式完成工作。

Peter Steinberger2:54:41

It’s also new services that we will need, right?

这也是我们需要的新服务,对吗?

2:54:41 For example, I want my agent to have an allowance.

例如,我希望我的代理人有津贴。

Like, you solve problems for me, here’s like 100 bucks in order to solve problems for me.

比如,你为我解决问题,这里大概有 100 美元来为我解决问题。

And if I tell you to order me food, maybe it uses a service.

如果我告诉你给我点食物,也许它使用了一项服务。

Maybe it uses something like rent-a-human to, like, just get that done for me.

也许它会使用类似租用人员之类的东西来为我完成这件事。

Lex Fridman2:55:06

Mm-hmm.

嗯嗯。

Peter Steinberger2:55:06

I don’t actually care.

我其实不在乎。

2:55:06 I care about solve my problem.

我关心解决我的问题。

There’s space for- for new companies to solve that well.

新公司有空间很好地解决这个问题。

Maybe don’t …

也许不……

Not all apps disappear.

并非所有应用程序都会消失。

Maybe some transform into being API.

也许有些会转变为API。

Lex Fridman2:55:21

So, basically, apps that rapidly transform in being agent-facing.

因此,基本上,应用程序会快速转变为面向代理。

2:55:21 So, there’s a real opportunity for, like, Uber Eats, that we just used earlier today.

所以,这是一个真正的机会,比如我们今天早些时候刚刚使用过的 Uber Eats 优食。

It- it’s companies this, of which there’s many.

它——就是这样的公司,这样的公司有很多。

Who gets there fastest to being able to interact with OpenClaw in a way that’s the m- the most natural, the easiest?

谁能最快以最自然、最简单的方式与 OpenClaw 进行交互?

Peter Steinberger2:55:50

Yeah.

是的。

2:55:50 And also, apps will become API if they want or not.

而且,无论应用程序愿意与否,它们都将成为 API。

Because my agent can figure out how to use my phone.

因为我的代理人可以弄清楚如何使用我的手机。

I mean, on- on the other side, it’s a little more tricky.

我的意思是,在另一方面,这有点棘手。

On Android, that’s already …

在 Android 上,这已经是……

People already do that.

人们已经这样做了。

And then we’ll just click the Order Uber for Me button for me.

然后我们只需点击“为我订购 Uber”按钮即可。

Or maybe another service.

或者也许是其他服务。

Or maybe there’s- there’s a …

或者也许有——有一个……

there’s an API I can call so it’s faster.

我可以调用一个 API,所以速度更快。

Uh, I think that’s a space we’re just beginning to even understand what that means.

呃,我认为我们才刚刚开始理解这意味着什么。

And I …

而我……

Again, I didn’t even …

再说一次,我什至没有……

That was not something I thought of.

那不是我想到的。

Something that I- that I discovered as people use this, and it …

当人们使用它时,我发现了一些东西,它......

We are still so early.

我们还这么早。

But yeah, I think data is very important.

但是,是的,我认为数据非常重要。

Like, apps that can give me data, but that also can be API.

比如,可以为我提供数据的应用程序,但也可以是 API。

Why do I need a Sonos app anymore when I can …

当我可以……时,为什么我还需要 Sonos 应用程序?

2:56:44 when my agent can talk to the Sonos?…

我的代理何时可以与 Sonos 交谈?...

Speakers directly.

直接喇叭。

Like my cameras, there’s like a crappy app, but they have, they have an API, so my agent uses the API now.

就像我的相机一样,有一个蹩脚的应用程序,但他们有,他们有一个 API,所以我的代理现在使用该 API。

Lex Fridman2:56:57

So it’s gonna force a lot of companies to have to shift focus.

因此,这将迫使许多公司不得不转移注意力。

2:56:57 That’s kind of what the internet did, right?

这就是互联网所做的,对吧?

You have to rapidly rethink, reconfigure what you’re selling, how you’re making money.

你必须迅速重新思考、重新配置你所销售的产品以及你如何赚钱。

Peter Steinberger2:57:10

Yeah, and some companies were really not like that.

是的,有些公司确实不是这样的。

2:57:10 For example, there’s no CLI for Google, so I had to like, do…

例如,Google 没有 CLI,所以我不得不喜欢……

have to do anything myself and build GAWK.

必须自己做任何事情并构建 GAWK。

That’s like a CLI for Google.

这就像 Google 的 CLI。

And at the…

而在……

Yeah, at the end user, they have to give me the emails because otherwise I cannot use their product.

是的,在最终用户处,他们必须给我电子邮件,否则我无法使用他们的产品。

If I’m a company and I try to get Google data, Gmail, there’s a whole complicated process, to the point where sometimes startups acquire startups that went through the process, so they don’t- don’t have to work with Google for half a year to be certified to being able to access Gmail.

如果我是一家公司,我尝试获取 Google 数据、Gmail,那么会有一个完整的复杂过程,有时初创公司会收购经历过该流程的初创公司,这样他们就不需要与 Google 合作半年才能获得能够访问 Gmail 的认证。

But my agent can access Gmail because I can just connect to it.

但我的代理可以访问 Gmail,因为我可以连接到它。

It’s still crappy because I need to, like, go through Google’s developer jungle to get a key, and that’s still annoying.

它仍然很糟糕,因为我需要穿过谷歌的开发者丛林才能获得密钥,这仍然很烦人。

2:58:09 But they cannot prevent me.

但他们无法阻止我。

And worst case, my agent just clicks on the, on the website and gets the data out that way.

最糟糕的情况是,我的代理只需点击网站上的 ,即可以这种方式获取数据。

Lex Fridman2:58:17

Through browsers?

通过浏览器?

Peter Steinberger2:58:18

Yeah.

是的。

2:58:18 I mean, I, I watch my agent happily click the I’m not a robot button.

我的意思是,我,我看着我的经纪人高兴地点击“我不是机器人”按钮。

And there’s this, this whole…

还有这个,这整个……

That’s gonna be…

那将会是……

That’s gonna be more heated.

这样会更火爆。

You see companies like Cloudflare that try to prevent bot access.

您会看到像 Cloudflare 这样的公司试图阻止机器人访问。

And in some ways, that’s useful for scraping.

在某些方面,这对于抓取很有用。

But in other ways, if I’m, I’m a personal user, I want that.

但在其他方面,如果我是个人用户,我希望如此。

You know, sometimes I, I use Codex and I, I read an article about modern React patterns, and it’s like a Medium article.

你知道,有时我使用 Codex,我读了一篇关于现代 React 模式的文章,它就像一篇 Medium 文章。

I paste it in and the agent can’t read it because they block it.

我将其粘贴进去,但代理无法读取它,因为他们阻止了它。

So then I have to copy-paste the actual text.

所以我必须复制粘贴实际文本。

Or in the future, I’ll learn that maybe I don’t click on Medium because it’s annoying, and I use other websites that actually are agent friendly.

或者将来,我会了解到,也许我不会点击 Medium,因为它很烦人,而且我会使用其他实际上对代理友好的网站。

2:59:12 So, uh-

所以,呃-

Lex Fridman2:59:13

There’s gonna be a lot of powerful, rich companies fighting back.

将会有很多强大、富有的公司进行反击。

2:59:13 So it’s really intere- You’re at the center, you’re the catalyst, the leader, and happen to be at the center of this kind of revolution where it’s get- gonna completely change how we interact with services with, with web.

所以这真的很有趣——你是中心,你是催化剂,领导者,而且恰好是这种革命的中心,它将彻底改变我们与服务、网络交互的方式。

And so, like, there’s companies at Google that are gonna push back.

所以,就像谷歌的一些公司会反击。

I mean, there’s every major companies you could think of is gonna push back.

我的意思是,你能想到的所有大公司都会反击。

Peter Steinberger2:59:39

Even…

甚至……

2:59:39 Yeah, even search.

是的,甚至搜索。

Um, I now use, I think Perplexity or Brave as providers because Google really doesn’t make it easy to use Google without Google.

嗯,我现在使用,我认为 Perplexity 或 Brave 作为提供者,因为谷歌确实无法让人们在没有谷歌的情况下轻松使用谷歌。

I’m not sure if that’s the right strategy, but I’m not Google.

我不确定这是否是正确的策略,但我不是谷歌。

Lex Fridman2:59:58

Yeah, there’s a, there’s a nice balance from a big company perspective ’cause if you push back too much for too long, you become Blockbuster and you lose everything to the Netflixes of the world.

是的,从大公司的角度来看,这是一个很好的平衡,因为如果你拖延太多时间太久,你就会成为百视达,然后你就会把一切都输给全世界的 Netflix。

2:59:58 But some pushback is probably good during a revolution to see.

但在革命期间看到一些阻力可能是好事。

Peter Steinberger3:00:11

Yeah.

是的。

3:00:11 But you see that, that…

但你看到了,那个……

Like, this is something that the people want.

就像,这是人们想要的东西。

Lex Fridman3:00:14

Right.

正确的。

Peter Steinberger3:00:14

So-

所以——

Lex Fridman3:00:15

Yes.

是的。

Peter Steinberger3:00:16

If I’m on the go, I don’t wanna open a calendar app.

如果我在旅​​途中,我不想打开日历应用程序。

3:00:16 I just…

我只是……

I wanna tell my agent, “Hey, remind me about this dinner tomorrow night,” and maybe invite two of my friends and then maybe send a what- send a WhatsApp message to my friend.

我想告诉我的经纪人,“嘿,提醒我明天晚上的晚餐”,也许会邀请我的两个朋友,然后可能会发送一条 Whatsapp 消息给我的朋友。

And I don’t need…

而且我不需要……

I don’t want or need to open apps for that.

我不想或不需要为此打开应用程序。

I think that we passed that age, and now everything is, like, much more connected and, and fluid if those companies want it or not.

我认为我们已经过了那个时代,现在一切都变得更加互联和流畅,无论这些公司是否愿意。

And I think, well, the right companies will find ways to jump on the train, and other companies will perish.

我认为,正确的公司会找到方法跳上火车,而其他公司将会灭亡。

Lex Fridman3:00:55

You got to listen to what the people want.

你必须倾听人们的需求。

3:00:55 We talked about programming quite a bit, and a lot of folks that are developers are really worried about their jobs, about their…

我们谈论了很多编程问题,很多开发人员真的很担心他们的工作,担心他们的……

About the future of programming.

关于编程的未来。

Do you think AI replaces programmers completely?

您认为AI会完全取代程序员吗?

Human programmers?

人类程序员?

Peter Steinberger3:01:11

I mean, we’re definitely going in that direction.

我的意思是,我们肯定会朝这个方向前进。

3:01:11 Programming is just a part of building products.

编程只是构建产品的一部分。

So maybe, maybe AI does replace programmers eventually.

所以也许人工智能最终会取代程序员。

But there’s so much more to that art.

但这种艺术还有更多意义。

Like, what do you actually wanna build?

比如,你到底想构建什么?

How should it feel?

应该感觉如何?

How’s the architecture?

架构如何?

I don’t think agents will replace all of that.

我不认为代理人会取代这一切。

Yeah, like, just the, the actual art of programming, it will, it will stay there, but it’s, it’s gonna be like knitting.

是的,就像,真正的编程艺术,它会,它会留在那里,但它会像编织一样。

You know?

你知道?

Like, people do that because they like it, not because it makes any sense.

就像,人们这样做是因为他们喜欢它,而不是因为它有任何意义。

So the…

所以……

I read this article this morning about someone that it’s okay to mourn our craft.

我今天早上读到这篇文章,内容是关于有人可以哀悼我们的手艺。

And I can…

我可以……

3:02:04 A part of me very strongly resonates with that because in my past I, I spent a lot of time tinkering, just being really deep in the flow and just, like, cranking out code and, like, finding really beautiful solutions.

我内心的一部分对此产生了强烈的共鸣,因为在我的过去,我花了很多时间修补,只是真正深入流程,就像编写代码一样,找到非常漂亮的解决方案。

And yes, in a way it’s, it’s sad because that will go away.

是的,在某种程度上,这是令人悲伤的,因为这种情况将会消失。

And I also get a lot of joy out of just writing code and being really deep in my thoughts and forgetting time and space and just being in this beautiful state of flow.

我还从编写代码并真正深入思考并忘记时间和空间并处于这种美丽的流动状态中获得了很多乐趣。

But you can get the same state of flow…

但你可以获得相同的心流状态……

I get a similar state of flow by working with agents and building and thinking really hard about problems.

通过与代理合作、认真构建和思考问题,我获得了类似的心流状态。

It is different-…

这是不同的——

but…

但是……

And it’s okay to mourn it, but I mean, that’s not something we can fight.

哀悼它是可以的,但我的意思是,这不是我们可以抗争的事情。

Like, there is…

比如,有……

the world for a long time had a…

很长一段时间以来,世界上有一个……

3:03:06 there was a lack of intelligence, if you s- if you see it like that, of people building things, and that’s why salaries of software developers reached stupidly high amounts and then will go away.

如果你这样看的话,人们建造东西的时候缺乏智慧,这就是为什么软件开发人员的薪水达到了愚蠢的高水平,然后就会消失。

There will still be a lot of demand for people that understand how to build things.

对了解如何构建事物的人的需求仍然很大。

It’s just that all this tokenized intelligence enables people to do a lot more, a lot faster.

只是所有这些代币化的智能使人们能够做得更多、更快。

And it will be even more…

而且还会更加……

even faster and even more because those things are continuously improving.

甚至更快、更多,因为这些事情正在不断改进。

We had similar things when…

我们有过类似的事情,当...

I mean, it’s probably not a perfect analogy, but when we created the steam engine, and they built all these factories and replaced a lot of manual labor, and then people revolted and broke the machines.

我的意思是,这可能不是一个完美的类比,但是当我们创造了蒸汽机时,他们建造了所有这些工厂并取代了大量的体力劳动,然后人们反抗并破坏了机器。

3:04:04 Um, I- I can relate that if you very deeply identify that you are a programmer, that it’s scary and that it’s threatening because what you like and what you’re really good at is now being done by a soulless or not entity.

嗯,我-我可以体会到,如果你非常深刻地认识到自己是一名程序员,那么这很可怕,而且很有威胁,因为你喜欢的东西和你真正擅长的东西现在正在由一个没有灵魂或没有灵魂的实体来做。

But I don’t think you’re just a programmer.

但我不认为你只是一个程序员。

That’s a very limiting view of your craft.

这是对你的技术的非常有限的看法。

You are, you are still a builder.

你是,你仍然是一名建设者。

Lex Fridman3:04:40

Yeah, there’s a couple of things I want to say.

是的,有几件事我想说。

3:04:40 So one is, I never…

所以一是,我从来没有……

As you’re articulating this beautifully, I no- I’m realizing I never thought I would…

当你完美地表达这一点时,我不——我意识到我从来没有想过我会……

the thing I love doing would be the thing that gets replaced.

我喜欢做的事情将会被取代。

You hear these stories about these, like you said, with the steam engine.

正如您所说,您听到过有关蒸汽机的故事。

I’ve, I’ve spent so many, I don’t know, maybe thousands of hours poring over code and putting my heart and soul and, like, and just, like, some of my most painful and happiest moments were alone behind…

我已经,我已经花了很多时间,我不知道,也许数千个小时钻研代码,全心全意,就像,就像,就像,我的一些最痛苦和最快乐的时刻都被独自抛在了后面......

I, I was an Emacs person for a long time.

我,我很长一段时间都是 Emacs 人。

Man, Emacs.

伙计,Emacs。

And, and then there’s an identity and there’s meaning, and there’s…

而且,然后就有了身份和意义,还有……

Like, when I walk about the world, I don’t say it out loud, but I think of myself as a programmer.

就像,当我在这个世界上行走时,我不会大声说出来,但我认为自己是一名程序员。

And to have that in a matter of months…

并在几个月内实现这一点......

3:05:31 I mean, like you mentioned, April to November, it really is a leap that happened, a shift that’s happening.

我的意思是,就像你提到的,从四月到十一月,这确实是一个飞跃,一个正在发生的转变。

To have that completely replaced is is painful.

完全替换它是痛苦的。

It’s, it’s truly painful.

是啊,确实很痛苦。

But I also think programmers, builders more broadly, but what is, what is the act of programming?

但我也认为程序员、更广泛的构建者,但编程的行为是什么?

I, I think programmers are generally best equipped at this moment in history to learn the language, to empathize with agents, to learn the language of agents.

我,我认为程序员在历史上的这个时刻通常最有能力学习语言,与代理产生共鸣,学习代理的语言。

To feel the CLI.

感受 CLI。

Peter Steinberger3:06:10

Yeah.

是的。

Lex Fridman3:06:11

Like, like to understand what is the thing you need, you the agent, need to do this task the best?

就像,喜欢了解你需要什么东西,你作为代理人,需要最好地完成这个任务吗?

Peter Steinberger3:06:21

I think at some point it’s just gonna be called coding again, and it’s just gonna be the new normal.

我认为在某些时候它会再次被称为编码,这将成为新常态。

Lex Fridman3:06:25

Yeah.

是的。

Peter Steinberger3:06:25

And yet, while I don’t write the code, I very much feel like I’m in the driver’s seat and I am, I am writing the code, you know?

然而,虽然我不编写代码,但我非常感觉自己坐在驾驶座上,而且我正在编写代码,你知道吗?

3:06:25 It’s just-

这只是——

Lex Fridman3:06:37

You’ll still be a programmer.

你仍然会是一名程序员。

3:06:37 It’s just the activity of a programmer is, is different.

只是程序员的活动不同而已。

Peter Steinberger3:06:41

Yeah, and because on X, the bubble, I mean, is mostly positive.

是的,因为在 X 上,泡沫,我的意思是,大部分是积极的。

3:06:41 On, on Mastodon and Bluesky, I don’t…

关于乳齿象和蓝天,我不……

I also use it less because oftentimes I got attacked for my blog posts.

我也很少使用它,因为我经常因为我的博客文章而受到攻击。

And I, I had stronger reactions in the past, now I can sympathize with those people more ’cause, in a way I get it.

而我,过去我有更强烈的反应,现在我可以更多地同情那些人,因为,在某种程度上我明白了。

It…

它…

In a way, I also don’t get it because it’s very unfair to grab onto the person that you see right now and unload all your fear and hate.

在某种程度上,我也不明白,因为抓住你现在看到的人并释放你所有的恐惧和仇恨是非常不公平的。

It’s gonna be a change and it’s gonna be challenging, but it’s also…

这将是一个改变,并且充满挑战,但它也是……

I don’t know.

我不知道。

I find it incredibly fun and, and, and gratifying.

我发现这非常有趣,并且令人满足。

And I can, I can use the new time to focus on much more details.

我可以,我可以利用新的时间专注于更多细节。

I think the level of expectation of what we build is also rising because it’s just now…

我认为对我们构建的内容的期望水平也在上升,因为现在......

The default is now so much easier, so software is changing in many ways.

默认设置现在变得更加容易,因此软件在很多方面都发生了变化。

3:07:45 There’s gonna be a lot more.

还会有更多。

And then you have all these people that are screaming, “Oh yeah, but what about the water?” You know?

然后所有这些人都在尖叫:“哦,是的,但是水呢?”你知道?

Like, I did a conference in Italy about the, the state of AI, and m- my whole motivation was to push people away from, don’t see yourself as an iOS developer anymore.

比如,我在意大利举办了一次关于人工智能现状的会议,我的全部动机就是让人们远离,不再将自己视为 iOS 开发人员。

You’re now a builder, and you can use your skills in many more ways.

您现在是一名建造者,您可以通过更多方式使用您的技能。

Also because apps are slowly going away.

还因为应用程序正在慢慢消失。

People didn’t like that.

人们不喜欢那样。

Like a lot of people didn’t like what I had to say.

就像很多人不喜欢我所说的话一样。

And I don’t think I was hyperbole, I was just like, “This is how I see the future.” Maybe this is not how it’s going to be, but I’m pretty sure a version of that will happen.

我不认为我很夸张,我只是想,“这就是我对未来的看法。”也许事情不会是这样,但我很确定这种情况一定会发生。

3:08:30 And the first question I got was, “Yeah, but what about the insane water use on data centers?” But then you actually sit down and do the maths, and then for most people if you just skip one burger per month, that compensates the, the CO2 output, or, like, the water use in equivalent of tokens.

我得到的第一个问题是,“是的,但是数据中心疯狂的用水怎么办?”但然后你实际上坐下来进行数学计算,然后对于大多数人来说,如果你每个月不吃一个汉堡,就可以补偿二氧化碳的排放量,或者相当于代币的用水量。

I mean, the maths is, is…

我的意思是,数学是,是……

the maths is tricky, and it depends if you add pre-training, then maybe it’s more than just one patty….

数学很棘手,这取决于你是否添加预训练,那么也许它不仅仅是一个肉饼......

but it’s not off by a factor of 100, you know?

但它并没有相差 100 倍,你知道吗?

So, so the…

所以,所以……

or like golf is still using way more water than all data centers together.

或者就像高尔夫所消耗的水量仍然比所有数据中心消耗的水量还要多。

So are you also hating people that play golf?

那么你是否也讨厌打高尔夫球的人呢?

Those people grab on anything that they think is bad about AI without seeing the potential things that might be good about AI.

这些人抓住了他们认为人工智能不好的任何东西,却没有看到人工智能潜在的好处。

Lex Fridman3:09:23

Mm-hmm.

嗯嗯。

Peter Steinberger3:09:24

And I’m not saying everything’s good.

我并不是说一切都很好。

3:09:24 It’s certainly gonna be a very transformative technology for our society.

对于我们的社会来说,这肯定会是一项非常具有变革性的技术。

Lex Fridman3:09:32

There’s to steel man the, the criticism in general, I do wanna say in my experience with Silicon Valley there’s a bit of a bubble in the sense that there’s a kind of excitement and an over-focus about the positive that the technology can bring.

对于钢铁侠来说,总的来说,我确实想说,根据我在硅谷的经历,存在一些泡沫,因为人们对技术可以带来的积极作用感到兴奋和过度关注。

Peter Steinberger3:09:54

Yeah.

是的。

Lex Fridman3:09:55

And…

还有……

3:09:55 which is great.

这太棒了。

It’s great to focus on…

专注于……真是太好了

N- not to, not to be paralyzed by fear and fear-mongering and so on, but there’s also within that excitement, and within everybody talking just to each other, there’s a dismissal of the basic human experience across the United States and the Midwest, across the world.

不要、不要因恐惧和散布恐惧等而瘫痪,但在这种兴奋之中,在每个人互相交谈的过程中,都存在着对美国、中西部和世界各地人类基本经验的忽视。

Including the programmers we mentioned, including all the people that are gonna lose their jobs, including the s- the measurable pain and suffering that happens at the short-term scale when there’s change of any kind.

包括我们提到的程序员,包括所有将要失业的人,包括当发生任何形式的变化时在短期内发生的可衡量的痛苦和痛苦。

Especially large-scale transformative change that we’re about to face if what we’re talking about will materialize.

如果我们正在谈论的事情成为现实,我们将面临特别大规模的变革。

And so to ha- having a bit of that humility and awareness about the tools you’re building, they’re going to cause pain.

因此,对你正在构建的工具有一点谦虚和认识,它们会带来痛苦。

3:10:43 They will long term hopefully bring about a better world, and even more opportunities-

从长远来看,他们将有望带来一个更美好的世界,甚至更多的机会——

Peter Steinberger3:10:48

Yeah

是啊

Lex Fridman3:10:48

…

……

3:10:48 and even more awesomeness.

甚至更令人敬畏。

But having that kind of like quiet moment often of, of respect for the pain that is going to be felt.

但经常有那种安静的时刻,尊重即将感受到的痛苦。

And so not, not enough of that is, I think, done, so it’s, it’s good to have a bit of that.

所以,我认为,这还不够,所以,有一点是很好的。

Peter Steinberger3:11:07

And then I also have to put against some of the emails I got where people told me they have a small business, and they’ve been struggling.

然后我还必须反驳我收到的一些电子邮件,人们告诉我他们有一家小企业,而且他们一直在苦苦挣扎。

3:11:07 And, and OpenClaw helped them automate a few of the tedious tasks from, from collecting invoices to like answering customer emails that then freed them up and like cost them a bit more joy in their life.

而且,OpenClaw 帮助他们自动化了一些繁琐的任务,从收集发票到回复客户电子邮件,然后解放了他们,让他们的生活失去了更多的乐趣。

Lex Fridman3:11:30

Mm-hmm.

嗯嗯。

Peter Steinberger3:11:31

Or, or some emails where they told me that OpenClaw helped their disabled daughter.

或者,或者一些电子邮件,他们告诉我 OpenClaw 帮助了他们残疾的女儿。

3:11:31 That she’s now empowered and feels she can do much more than before.

她现在被赋予了权力,觉得自己可以做比以前更多的事情。

Which is amazing, right?

这很神奇,对吧?

Because you could, you could do that before as well.

因为你可以,你以前也可以这样做。

The technology was there.

技术就在那里。

I didn’t, I didn’t invent a whole new thing, but I made it a lot easier and more accessible, and that did show people the possibilities that they previously wouldn’t see.

我没有,我没有发明一个全新的东西,但我让它变得更容易、更容易理解,这确实向人们展示了他们以前看不到的可能性。

And now they apply it for good.

现在他们将其永久应用。

Lex Fridman3:12:02

Mm-hmm.

嗯嗯。

Peter Steinberger3:12:03

Or like also the fact that, yes, I, I, I suggest the, the, the latest and best models, but you can totally run this on free models.

或者也喜欢这样的事实,是的,我,我,我建议最新和最好的模型,但你完全可以在免费模型上运行它。

3:12:03 You can run this locally.

您可以在本地运行它。

You can run this on, on, on Keyme or other, other, other models that are way more accessible price-wise, and still have a, a very powerful system that might otherwise not be possible.

你可以在 Keyme 或其他其他模型上运行它,这些模型在价格上更容易获得,并且仍然拥有一个非常强大的系统,否则这可能是不可能的。

Because other things like, I don’t know, Entropik’s CoWork is locked in into their space, so it’s not all black and white.

因为其他事情,比如,我不知道,Entropik 的 CoWork 被锁定在他们的空间中,所以它并不全是黑白的。

There’s…

有……

I got a lot of emails that were heartwarming and amazing.

我收到了很多温暖人心且令人惊叹的电子邮件。

And, and I don’t know, it just made me really happy.

而且,我不知道,这让我真的很高兴。

Lex Fridman3:12:48

Yeah, there’s a lot…

是的,有很多……

3:12:48 It has brought joy into a lot of people’s lives.

它给很多人的生活带来了欢乐。

Not just, not just programmers.

不只是,不只是程序员。

Like a lot of people’s lives.

就像很多人的生活一样。

It’s, it’s, it’s beautiful to see.

是的,是的,看起来很漂亮。

What gives you hope about this whole thing we have going on with human civilization?

是什么让你对人类文明正在发生的这一切充满希望?

Peter Steinberger3:13:03

I mean, I inspired so many people.

我的意思是,我激励了很多人。

3:13:03 There’s like…

有像...

there’s this whole builder vibe again.

整个建筑商的氛围再次出现。

People are now using AI in a more playful way and are discovering what it can do and how it can like help them in their life.

人们现在以一种更有趣的方式使用人工智能,并发现它可以做什么以及它如何帮助他们的生活。

And creating new places that are just sprawling of creativity.

并创造充满创造力的新场所。

I don’t know.

我不知道。

Like, there’s like ClawCoin in Vienna.

比如,维也纳就有 ClawCoin。

There’s like 500 people.

大概有500人。

And there’s such a high percentage of people that uh, want to present, which is to me really surprising, because u- usually it’s quite hard to find people that want to like talk about what they built.

想要展示的人比例如此之高,这对我来说真的很令人惊讶,因为通常很难找到愿意谈论他们构建的东西的人。

And now it’s, there’s an abundance.

现在,已经很丰富了。

So that gives me hope that we can, we can figure shit out.

所以这给了我希望,我们可以,我们可以解决问题。

Lex Fridman3:14:00

And it makes it accessible to basically everybody.

它使得基本上每个人都可以使用它。

Peter Steinberger3:14:04

Yeah.

是的。

Lex Fridman3:14:05

Just imagine all these people building, especially as you make it simpler and simpler, more secure.

想象一下所有这些人在建造,尤其是当你让它变得越来越简单、越来越安全时。

3:14:05 It’s like anybody who has ideas and can express those ideas in language can build.

就像任何有想法并且能够用语言表达这些想法的人都可以建造一样。

That’s crazy.

这太疯狂了。

Peter Steinberger3:14:22

Yeah, that’s ultimately power to the people, and one of the beauty, the beautiful things that come out of AI.

是的,这最终是人们的力量,也是人工智能带来的美丽之一。

3:14:22 Not just, not just a slop generator.

不只是,不只是一个斜坡发生器。

Lex Fridman3:14:36

Well, Mr. Clawfather, I just realized when I said that in the beginning, I violated two trademarks, because there’s also the Godfather.

好吧,爪父先生,当我一开始说的时候,我才意识到我侵犯了两个商标,因为还有教父。

3:14:36 I’m getting sued by everybody.

我被所有人起诉。

You’re a wonderful human being.

你是一个很棒的人。

You’ve created something really special, a special community, a special product, a special set of ideas.

你创造了一些非常特别的东西,一个特别的社区,一个特别的产品,一组特别的想法。

Plus, the entire…

另外,整个…

the humor, the good vibes, the inspiration of all these people building, the excitement to build.

幽默、良好的氛围、所有这些人建造的灵感、建造的兴奋。

So I’m truly grateful for everything you’ve been doing and for who you are, and for sitting down to talk with me today.

因此,我真的很感谢你所做的一切,感谢你是谁,也感谢你今天坐下来与我交谈。

Thank you, brother.

谢谢你,兄弟。

Peter Steinberger3:15:14

Thanks for giving me the chance to tell my story.

感谢您给我机会讲述我的故事。

Lex Fridman3:15:17

Thanks for listening to this conversation with Peter Steinberger.

感谢您收听与彼得·斯坦伯格的对话。

3:15:17 To support this podcast, please check out our sponsors in the description, where you can also find links to contact me, ask questions, give feedback and so on.

为了支持这个播客,请在描述中查看我们的赞助商,您还可以在其中找到联系我、提出问题、提供反馈等的链接。

And now let me leave you with some words from Voltaire.

现在让我向你们传达伏尔泰的话。

“With great power comes great responsibility.” Thank you for listening, and hope to see you next time.

“权力越大,责任越大。”感谢您的收听,希望下次再见。

文稿来自 Lex Fridman 官网公开发布的官方 Transcript(含说话人与时间戳)。
Peter Steinberger (00:00:00): I watched my agent happily click the “I’m not a robot” button. I made the agent very aware. Like, it knows what his source code is. It understands th- how it sits and runs in its own harness. It knows where documentation is. It knows which model it runs. It understands its own system that made it very easy for an agent to… Oh, you don’t like anything? You just prompted it to existence, and then the agent would just modify its own software. People talk about self-modifying software, I just built it. I actually think wipe coding is a slur. Lex Fridman (00:00:31): You prefer agentic engineering? Peter Steinberger (00:00:33): Yeah, I always tell people I’d- I do agentic engineering, and then maybe after 3:00 AM, I switch to wipe coding, and then I have regrets on the next day. Lex Fridman (00:00:40): What a walk of shame. Peter Steinberger (00:00:42): Yeah, you just have to clean up and, like, fix your sh- shit. Lex Fridman (00:00:45): We’ve all been there. Peter Steinberger (00:00:46): I used to write really long prompts. And by writing, I mean, I don’t write, I- I- I talk, you know? These- these hands are, like, too- too precious for writing now. I just- I just use bespoke prompts to build my software. Lex Fridman (00:01:00): So, you, for real, with all those terminals, are using voice? Peter Steinberger (00:01:04): Yeah. I used to do it very extensively, to the point where there was a period where I lost my voice. Lex Fridman (00:01:13): I mean, I have to ask you, just curious. I- I know you’ve probably gotten huge offers from major companies. Can you speak to who you’re considering working with? Peter Steinberger (00:01:27): Yeah. Lex Fridman (00:01:30): The following is a conversation with Peter Steinberger, creator of OpenClaw, formerly known as MoldBot, ClawedBot, Clawdus, Claude, spelled with a W as in lobster claw. Not to be confused with Claud, the AI model from Anthropic, spelled with a U. In fact, this confusion is the reason Anthropic kindly asked Peter to change the name to OpenClaw. So, what is OpenClaw? It’s an open-source AI agent that has taken over the tech world in a matter of days, exploding in popularity, reaching over 180,000 stars on GitHub, and spawning the social network mold book, where AI agents post manifestos and debate consciousness, creating a mix of excitement and fear in the general public. Lex Fridman (00:02:19): And a kind of AI psychosis, a mix of clickbait fearmongering and genuine, fully justifiable concern about the role of AI in our digital, interconnected human world. OpenClaw, as its tagline states, is the AI that actually does things. It’s an autonomous AI assistant that lives in your computer, has access to all of your stuff, if you let it, talks to you through Telegram, WhatsApp, Signal, iMessage, and whatever else messaging client. Uses whatever AI model you like, including Claude Opus 4.6 and GPT 5.3 Codex, all to do stuff for you. Many people are calling this one of the biggest moments in the recent history of AI, since the launch of ChatGPT in November 2022. Lex Fridman (00:03:07): The ingredients for this kind of AI agent were all there, but putting it all together in a system that definitively takes a step forward over the line from language to agency, from ideas to actions, in a way that created a useful assistant that feels like one who gets you and learns from you, in an open source, community-driven way, is the reason OpenClaw took the internet by storm. Its power, in large part, comes from the fact that you can give it access to all of your stuff and give it permission to do anything with that stuff in order to be useful to you. This is very powerful, but it is also dangerous. OpenClaw represents freedom, but with freedom comes responsibility. Lex Fridman (00:03:51): With it, you can own and have control over your data, but precisely because you have this control, you also have the responsibility to protect it from cybersecurity threats of various kinds. There are great ways to protect yourself, but the threats and vulnerabilities are out there. Again, a powerful AI agent with system-level access is a security minefield, but it also represents the future. Because when done well and securely, it can be extremely useful to each of us humans as a personal assistant. We discuss all of this with Peter, and also discuss his big-picture programming and entrepreneurship life story, which I think is truly inspiring. He spent 13 years building PSPDF Kit, which is a software used on a billion devices. Lex Fridman (00:04:41): He sold it, and for a brief time, fell out of love with programming, vanished for three years, and then came back, rediscovered his love for programming, and built, in a very short time, an open source AI agent that took the internet by storm. He is, in many ways, the symbol of the AI revolution happening in the programming world. There was the ChatGPT moment in 2022, the DeepSeek moment in 2025, and now, in ’26, we’re living through the OpenClaw moment, the age of the lobster. The start of the agentic AI revolution. What a time to be alive. This is a Lex Fridman podcast. To support it, please check out our sponsors in the description, or you can also find links to contact me, ask questions, give feedback, and so on. And now, dear friends, here’s Peter Steinberger. Lex Fridman (00:05:36): The one and only, the Clawed Father. Actually, Benjamin predicted it in his tweet. “The following is a conversation with Claude, a respected crustacean.” It’s a hilarious-looking picture of a lobster in a suit, so I think the prophecy has been fulfilled. Let’s go to this moment when you built a prototype in one hour, that was the early version of OpenClaw. I think this story’s really inspiring to a lot of people because this prototype led to something that just took the internet by storm…. and became the fastest-growing repository in GitHub history, with now over 175,000 stars. So, what was the story of the one-hour prototype? Peter Steinberger (00:06:20): You know, I wanted that since April. Lex Fridman (00:06:23): A personal assistant. AI personal assistant. Peter Steinberger (00:06:25): Yeah. And I, I played around with some other things, like even stuff that gets all my WhatsApp, and I could just run queries on it. That was back when we had GPT-4.1, with the one million context window. And I, I pulled in all the data and then just asked him questions like, “What makes this friendship meaningful?” Lex Fridman (00:06:50): Mm-hmm. Peter Steinberger (00:06:50): And I got some, some really profound results. Like, I sent it to my friends and they got, like, teary eyes. Lex Fridman (00:06:59): So, there’s something there. Peter Steinberger (00:07:01): Yeah. But then I… I thought all the labs will, will, will work on that. So I, I moved on to other things, and that was still very much in my early days of experimenting and pl- playing. You know, you have to… That’s how you learn. You just like, you do stuff and you play. And time flew by and it was November. I wanted to make sure that the thing I started is actually happening. I was annoyed that it didn’t exist, so I just prompted it into existence. Lex Fridman (00:07:36): I mean, that’s the beginning of the hero’s journey of the entrepreneur, right? And you’ve even with your original story with PS PDF kit, it’s like, “Why does this not exist? Let me build it.” And again, here’s diff- a whole different realm, but similar maybe spirit. Peter Steinberger (00:07:52): Yeah, so I had this problem. I tried to show PDF on an iPad, which should not be hard. Lex Fridman (00:07:56): This is like 15 years ago, something like that. Peter Steinberger (00:07:59): Yeah. Like the most, the most random thing ever. And suddenly, I had this problem and I, I wanted to help a friend. And there was, there was… Well, not like nothing existed, but it was just not good. And like… Like I tried it and it was like very, “Nah.” Like, “Hmm, I can do this better.” Lex Fridman (00:08:17): By the way, for people who don’t know, this led to the development of PS PDF kit that’s used on a billion devices. So, the… It turns out that it’s pretty useful to be able to open a PDF. Peter Steinberger (00:08:28): You could also make the joke that I’m really bad at naming. Lex Fridman (00:08:32): Yeah. Peter Steinberger (00:08:32): Like, name number five on the current project. And even PS PDF doesn’t really roll from the tongue. Lex Fridman (00:08:39): Anyway, so you said “Screw it. Why don’t I do it?” So what was the… What was the prototype? What was the thing that you… What was the magical thing that you built in a short amount of time that you were like, “This might actually work as an agent,” where I talk to it and it does things? Peter Steinberger (00:08:55): There was… Like, one of my projects before already did something where I could bring my terminals onto the web and then I could, like, interact with them, but there also would be terminals on my Mac. Lex Fridman (00:09:06): Mm-hmm. Peter Steinberger (00:09:07): Viptunnel, which was like a, a weekend hack project that was still very early. And it was cloud code times. You know, you got a dopamine hit when you got something right. And now I get, like, mad when you get something wrong. Lex Fridman (00:09:22): And you had a really great -– not to take a tangent -– but a great blog post describing that you converted Viptunnel. You vibe-coded Viptunnel from TypeScript into Zig of all programming languages with a single prompt. One prompt, one shot. Convert the entire code base into Zig. Peter Steinberger (00:09:41): Yeah. There was this one thing where part of the architecture was… Took too much memory. Every terminal used like a node. And I wanted to change it to Rust and… I mean, I can do it. I can, I can manually figure it all out, but all my automated attempts failed miserably. And then I revisited about four or five months later. And I’m like, “Okay, now let’s use something even more experimental.” And I, and I just typed, “Convert this and this part to Sig,” and then let Codex run off. And it basically got it right. There was one little detail that I had to, like, modify afterwards, but it just ran for overnight or like six hours and just did its thing. And it’s like… It’s just mind-blowing. Lex Fridman (00:10:39): So that’s on the LLM programming side, refactoring. But uh, back to the actual story of the of the prototype. So how did Viptunnel connect to the first prototype where your, like, agents can actually work? Peter Steinberger (00:10:52): Well, that was still very limited. You know, like I had this one experiment with WhatsApp, then I had this experiment, and both felt like not the right answer. And then my search bar was literally just hooking up WhatsApp to cloud code. One shot. The CLI message comes in. I call the CLI with -p. It does its magic, I get the string back and I send it back to WhatsApp. And I, I built this in one hour. And I felt… Already felt really cool. It’s like, “Oh, I could… I can, like, talk to my computer,” right? This… That, that was, that was cool. But I, I wanted images, ’cause I alw- I often use images when I prompt. I think it’s such a, such an efficient way to give the agent more context. Peter Steinberger (00:11:40): And they are really good at figuring out what I mean, e- even if it’s like a, a weird cropped-up screenshot. So I used it a lot and I wanted to do that in WhatsApp as well. Also, like, you know, just you run around, you see like a poster of an event, you just make a screenshot and like figure out if I have time there, if this is good, if my friends are maybe up for that. Just like images seemed im- important. So I, I worked a few… It took me a few more hours to actually get that right. And then it was just…… I, I used it a lot. And funny enough, that was just before I went on a trip to Marrakesh with my friends for a birthday trip. And there it was even better because internet was a little shaky but WhatsApp just works, you know? Peter Steinberger (00:12:29): It’s like doesn’t matter, you have, like, edge, it still works. WhatsApp is just… It’s just made really well. So I ended up using it a lot. Translate this for me, explain this, find me places. Like, you just having a clanker doing, having Google for you, that was… Basically there was still nothing built but it still could do so much. Lex Fridman (00:12:53): So, if we talk about the full journey that’s happening there with the agent, you’re just sending on this very thin line WhatsApp message via CLI, it’s going to a cloud code and cloud code is doing all kinds of heavy work and coming back to you with a thin message. Peter Steinberger (00:13:13): Yeah. It was slow because every time I boot up the CLI, but it… It was really cool already. And it could just use all the things that I already had built. I had built like a whole bunch of CLI stuff over the month so it, it felt really powerful. Lex Fridman (00:13:31): There is something magical about that experience that’s hard to put into words. Being able to use a chat client to talk to an agent, versus, like, sitting behind a computer and like, I don’t know, using cursor or even using Cloud Code CLI in the terminal. It’s a different experience than being able to sit back and talk to it. I mean, it seems like a trivial step but, it- in some sense it’s a… It’s like a phase shift in the integration of AI into your life and how it feels, right? Peter Steinberger (00:14:05): Yeah. Yeah. I, I read this tweet this morning where someone said, “Oh, there’s no magic in it. It’s just like, it does this and this and this and this and this and this.” And it almost feels like a hobby, just as cursor or perplexity. And I’m like, well, if that’s a hobby that’s kind of a compliment, you know? They’re like, they’re not doing too bad. Thank you I guess? Yes. I mean, isn’t, isn’t, isn’t magic often just like you take a lot of things that are already there but bring them together in new ways? Like, I don’t… There’s no… Yeah. Maybe there’s no magic in there but sometimes just rearranging things and, like, adding a few new ideas is all the magic that you need. Lex Fridman (00:14:51): It’s really hard to convert into words what is, what is magic about a thing. If you look at the, the scrolling on an iPhone, why is that so pleasant? There’s a lot of elements about that interface that makes it incredibly pleasant, that is fundamental to the experience of using a smartphone, and it’s like, okay, all the components were there. Scrolling was there, everything was there. Peter Steinberger (00:15:13): Nobody did it- Lex Fridman (00:15:14): Yep Peter Steinberger (00:15:14): … and afterwards it felt so obvious. Lex Fridman (00:15:16): Yeah, so obvious. Peter Steinberger (00:15:16): Right? But still… You know the moment where it, it blew my mind was when, when I- I used it a lot and then at some point I just sent it a message and, and then a typing indicator appeared. And I’m like, wait, I didn’t build that, it only m- it only has image support, so what is it even doing? And then it would just reply. Lex Fridman (00:15:42): What was the thing you sent it? Peter Steinberger (00:15:43): Oh, just a random question like, “Hey, what about this in this restaurant?” You know? Because we were just running around and checking out the city. So that’s why I, I didn’t, didn’t even think when I used it because sometimes when you’re in a hurry typing is annoying. Lex Fridman (00:15:59): So, oh, you did an audio message? Peter Steinberger (00:16:00): Yeah. And it just, it just worked and I’m like… Lex Fridman (00:16:03): And it’s not supposed to work because- Peter Steinberger (00:16:05): No Lex Fridman (00:16:05): … you didn’t give it that- Peter Steinberger (00:16:07): No, literally Lex Fridman (00:16:07): … capability. Peter Steinberger (00:16:08): I literally went, “How the fuck did he do that?” And it was like, “Yeah, the mad lad did the following. He sent me a message but it only, only was a file and no file ending.” So I checked out the header of the file and it found that it was, like, opus so I used ffmpeg to convert it and then I wanted to use whisper but it didn’t had it installed. But then I found the OpenAI key and just used Curl to send the file to OpenAI to translate and here I am. Peter Steinberger (00:16:39): Just looked at the message I’m like, “Oh wow.” Lex Fridman (00:16:43): You didn’t teach it any of those things and the agent just figured it out, did all those conversions, the translations. It figured out the API, it figured out which program to use, all those kinds of things. And you were just absent-mindedly just sent an audio message when it came back. Peter Steinberger (00:16:56): Yeah, like, so clever even because he would have gotten the whisper local path, he would have had to download a model. It would have been too slow. So like, there’s so much world knowledge in there, so much creative problem solving. A lot of it I think mapped from… If you get really good at coding that means you have to be really good at general purpose problem solving. So that’s a skill, right? And that just maps into other domains. So it had the problem of like, what is this file with no file ending? Let’s figure it out. And that’s when it kind of clicked for me. It’s like, I was like very impressed. And somebody sent a pull request for Discord support and I’m like, “This is a WhatsApp relay. Peter Steinberger (00:17:37): That doesn’t, doesn’t fit at all.” Lex Fridman (00:17:40): At that time it was called WA Relay. Peter Steinberger (00:17:42): Yeah. And so I debated with me like, do I want that? Do I not want that? And then I thought, well maybe, maybe I do that because that could be a cool way to show people. Because I… So far I did it in WhatsApp as like groups you know but don’t really want to give my phone number to every internet stranger. Lex Fridman (00:18:07): Yeah. Peter Steinberger (00:18:07): Journalists manage to do that anyhow now so that’s a different story. So I merged it-… from Shadow, who helped me a lot with the whole project. So, thank you. And, and I put my, my bot in there. Lex Fridman (00:18:27): On Discord? Peter Steinberger (00:18:28): Yeah. No security because I didn’t… I hadn’t built sandboxing in yet. I, I just prompted it to, like, only listen to me. And then some people came and tried to hack it, and I just… Or, like, just watched and I just kept working in the open, you know? Like, y- I used my agent to build my agent harness and to test, like, various stuff. And that’s very quickly when it clicked for people. So it’s almost like it needs to be experienced. And from that time on, that was January the 1st, I, I got my first real influencer being a fan and did videos, dachitze. Thank you. And, and from there on, I saw, I started gaining up speed. And at the same time, my, my sleep cycle went shorter and shorter because I, I felt the storm coming, and I just worked my ass off to get it to… Peter Steinberger (00:19:33): into a state where it’s kinda good. Lex Fridman (00:19:38): There’s a few components and we’ll talk about how it all works, but basically, you’re able to talk to it using WhatsApp, Telegram, Discord. So that’s a component that you have to get right. Peter Steinberger (00:19:48): Yeah. Lex Fridman (00:19:49): And then you have to figure out the agentic loop, you have to have the gateway, you have the harness, you have all those components that make it all just work nicely. Peter Steinberger (00:19:56): Yeah. It felt like Factorio times infinite. Lex Fridman (00:20:00): Right. Peter Steinberger (00:20:01): I, I feel like I built my little- … my little playground. Like, I never had so much fun than building this project. You know? Like, you have like, “Oh,” I go like, level one agentic loop. What can I do there? How can I be smart at queuing messages? How can I make it more human-like? Oh, then I had this idea of… Because the loop always… The agent always replies something, but you don’t always want an agent to reply something in a group chat. So I gave him this no-reply token. So I gave him an option to shut up. So it, it feels more natural. Lex Fridman (00:20:32): That’s level two. Peter Steinberger (00:20:34): Y- uh, yeah, yeah. Yeah, on the- on the- Lex Fridman (00:20:36): Factorio. Peter Steinberger (00:20:36): On the agentic loop. And then I go to memory, right? Lex Fridman (00:20:39): Yeah. Peter Steinberger (00:20:39): You want him to, like, remember stuff. So maybe, maybe the end… The ultimate boss is continuous reinforcement learning, but I’m, I’m, like, at… I feel like I’m level two or three with Markdown files and the vector database. And then you, you can go to level community management, you can go to level website and marketing. There’s just so many hats that you have to have on. Not even talking about native apps. That’s just, like, infinite different levels and infinite level ups you can do. Lex Fridman (00:21:08): So the whole time you’re having fun. We should say that for the most part, throughout this whole process, you’re a one-man team. There’s people helping, but you’re doing so much of the key core development. Peter Steinberger (00:21:21): Yeah. Lex Fridman (00:21:21): And having fun? You did, in January, 6,600 commits. Probably more. Peter Steinberger (00:21:28): I sometimes posted a meme. I’m limited by the technology of my time. I could do more if agents would be faster. Lex Fridman (00:21:34): But we should say you’re running multiple agents at the same time. Peter Steinberger (00:21:37): Yeah. Depending on how much I slept and how difficult of the tasks I work on, between four and 10. Lex Fridman (00:21:45): Four and 10 agents. Uh there’s so many possible directions, speaking of Factorio, that we can go here. But one big picture one is, why do you think your work, Open Claw, won? In this world, if you look at 2025, so many startups, so many companies were doing kind of agentic type stuff, or claiming to. And here, Open Claw comes in and destroys everybody. Like, why did you win? Peter Steinberger (00:22:15): Because they all take themselves too serious. Lex Fridman (00:22:18): Yeah. Peter Steinberger (00:22:19): Like, it’s hard to compete against someone who’s just there to have fun. Lex Fridman (00:22:24): Yeah. Peter Steinberger (00:22:24): I wanted it to be fun, I wanted it to be weird. And if you see, like, all the, all the lobster stuff online I think I, I managed weird. I… You know, for the longest time, the only, the only way to install it was git clone, pnpm build, pnpm gateway. Like, you clone it, you build it, you run it. And then the, the agent… I made the agent very aware. Like, it knows that it is… What its source code is. It understands th- how it sits and runs in its own harness. It knows where documentation is. It knows which model it runs. It knows if you turn on the voice or, or reasoning mode. Like, I, I wanted to be more human-like, so it understands its own system that made it very easy for an agent to… Oh, you don’t like anything? Peter Steinberger (00:23:19): You just prompted it to existence, and then the agent would just modify its own software. You know, we have people talk about self-modifying software. I just built it and didn’t even… I didn’t even plan it so much. It just happened. Lex Fridman (00:23:35): Can you actually speak to that? ‘Cause it’s just fascinating. So you have this piece of software that’s written in TypeScript- Peter Steinberger (00:23:43): Yeah Lex Fridman (00:23:43): … that’s able to, via the agentic loop, modify itself. I mean, what a moment to be alive in the history of humanity and the history of programming. Here’s the thing that’s used by a huge amount of people to do incredibly powerful things in their lives, and that very system can rewrite itself, can modify itself. Can you just, like, speak to the power of that? Like, isn’t that incredible? Like, when did you first close the loop on that? Peter Steinberger (00:24:14): Oh, because that’s how I built it as well, you know? Most of it is built by Codex, but oftentimes I… When I debug it, I…… I use self-introspection so much. It’s like, “Hey, what tools do you see? Can you call the tool yourself?” Or like, “What error do you see? Read the source code. Figure out what’s the problem.” Like, I just found it an incredibly fun way to… That the agent, the very agent and software that you use is used to debug itself, so that it felt just natural that everybody does that. And that it led to so many, so many pull requests by people who never wrote software. I mean, it also did show that people never wrote software . So I call them prompt requests in the end. Peter Steinberger (00:25:00): But I don’t want to, like, pull that down because every time someone made the first pull request is a win for our society, you know? Like, it… Like, it doesn’t matter how, how shitty it is, y- you gotta start somewhere. So I know there’s, like, this whole big movement of people complain about open source and the quality of PRs, and a whole different level of problems. But on a different level, I found it… I found it very meaningful that, that I built something that people love to think of so much that they actually start to learn how open source works. Lex Fridman (00:25:37): Yeah, you were … The Open Cloud project was the first pull request. You were the first for so many. That is magical. So many people that don’t know how to program are taking their first step into the programming world with this. Peter Steinberger (00:25:52): Isn’t that a step up for humanity? Isn’t that cool? Lex Fridman (00:25:54): Creating builders. Peter Steinberger (00:25:56): Yeah. Like, the bar to do that was so high, and, like, with agents, and with the right software, it just, like, went lower and lower. I don’t know. I was at a… And I also organize another type of meetup. I call it… I called it Cloud Code Anonymous. You can get the inspiration from. Now, I call it Agents Anonymous- … for, for reasons. Lex Fridman (00:26:23): Agents Anonymous. Peter Steinberger (00:26:24): And- Lex Fridman (00:26:25): Oh, it’s so funny on so many levels. I’m sorry, go ahead. Peter Steinberger (00:26:29): Yeah. And there was this one guy who, who talked to me. He’s like, “I run this design agency, and we, we never had custom software. And now I have, like, 25 little web services for various things that help me in my business. And I don’t even know how they work, but they work.” Uh, and he was just, like, very happy that my stuff solved some of his problems. And he was, like, curious enough that he actually came to, like, a, a Enchantic meetup, even though he’s… He doesn’t really know how software works. Lex Fridman (00:27:04): Can we actually rewind a little bit and tell the saga of the name change? First of all, it started out as Wa-Relay. Peter Steinberger (00:27:12): Yeah. Lex Fridman (00:27:12): And then it went to- Peter Steinberger (00:27:13): Claude’s. Lex Fridman (00:27:14): Claude’s. Peter Steinberger (00:27:15): Yeah. You know, when I, when I built it in the beginning, my agent had no personality. It was just… It was Claude Code. It’s like this sycophantic opus, very friendly. And I… When you talk to a friend on WhatsApp, they don’t talk like Claude Code. So I wanted… I, I felt this… I just didn’t f- It didn’t feel right, so I, I wanted to give it a personality. Lex Fridman (00:27:41): Make it spicier, make it- Peter Steinberger (00:27:43): Yeah Lex Fridman (00:27:43): … something. By the way, that’s actually hard to put into words as well. And we should mention that, of course, you create the soul.md, inspired by Anthropic’s constitutional AI work- Peter Steinberger (00:27:53): Mm-hmm Lex Fridman (00:27:53): … how to make it spicy. Peter Steinberger (00:27:55): Partially, it picked up a little bit from me. You know, like those things are text completion engines in a way. So, so I, I, I, I had fun working with it, and then I told it to… How I wanted it to interact with me, and just, like, write your own agents.md give yourself a name. And then we… I didn’t even know how the whole, the whole lobster… I mean, people only do lobster… Originally, it was actually a lobster in a, in a TARDIS, because I’m also a big Doctor Who fan. Lex Fridman (00:28:30): Was there a space lobster? Peter Steinberger (00:28:31): Yeah. Lex Fridman (00:28:31): I heard. What’s that have to do with anything? Peter Steinberger (00:28:34): Yeah, I just wanted to make it weird. There was no… There was no big grand plan. I’m just having fun here. Lex Fridman (00:28:40): Oh, so I guess the lobster is already weird, and then the space lobster is an extra weird. Peter Steinberger (00:28:44): Yeah, yeah, because the- Lex Fridman (00:28:45): Yeah Peter Steinberger (00:28:45): … the TARDIS is basically the, the harness, but cannot call it TARDIS, so we called it Claude’s. So that was name number two. Lex Fridman (00:28:54): Yeah. Peter Steinberger (00:28:54): And then it never really rolled off the tongue. So when more people came, again, I talked with my agent, Claude. At least that’s what I used to call him. Now- Lex Fridman (00:29:08): Claude spelled with a W-C-L-A-U-D-E. Peter Steinberger (00:29:12): Yeah. Lex Fridman (00:29:14): Versus C-L-A-U-D-E from Anthropic. Peter Steinberger (00:29:20): Yeah. Lex Fridman (00:29:21): Which is part of what makes it funny, I think. The play on the letters and the words in the TARDIS and the lobster and the space lobster is hilarious. But I can see why it can lead into problems. Peter Steinberger (00:29:34): Yeah, they didn’t find it so funny . So then I got the domain ClaudeBot, and I just… I love the domain. And it was, like, short. It was catchy. I’m like, “Yeah, let’s do that.” I didn’t… I didn’t think it would be that big at this time. And then just when it exploded, I got, Kudos, a very friendly email from one of the employees that they didn’t like the name. Lex Fridman (00:30:09): One of the Anthropic employees. Peter Steinberger (00:30:11): Yeah. So actually, Kudos, because they shou- could have just sent a, a lawyer letter, but they’ve been nice about it. But also like, “You have to change this and fast.” And I asked for two days, because changing a name is hard, because you have to find everything, you know, Twitter handle, domains, NPM packages Docker registry, GitHub stuff. And everything has to be…… you need a set of everything. Lex Fridman (00:30:40): And also, can we comment on the fact that you’re increasingly attacked, followed by crypto folks? Which I think you mentioned somewhere that that means the name change had to be… Because they were trying to snipe, they were trying to steal, and so you had to be… The, the na- I mean, from an engineering perspective, it’s just fascinating. You had to make the name change Atomic, make sure it’s changed everywhere at once. Peter Steinberger (00:31:06): Yeah. Failed very hard at that. Lex Fridman (00:31:08): You did? Peter Steinberger (00:31:08): I, I underestimated those people. It’s a, it’s a very interesting subculture. Like, it… Everything circles around… I’ll probably get a lot wrong and we’ll probably get hate for that if you say that, but… There is like Bags app and then they, they tokenize everything. And th- they did the same back with Swipe Tunnel, but to a much smaller degree. It was not that annoying. But on this project, they’ve been, they’ve been swarming me. They, they… It’s like every half an hour, someone came into Discord and, and, and spammed it and we had to block the p- We have, like, server rules, and one of the rules was… One of the rules is no mentioning of butter. For obvious reasons. And one was, no talk about finance stuff or crypto. Because I’m… Peter Steinberger (00:32:04): I- I’m just not interested in that, and this is a space about the project and not about some finance stuff. But yeah. They came in and, and spammed and… Annoying. And on Twitter, they would ping me all the time. My, my notification feed was unusable. I, I could barely see actual people talking about this stuff because it was like swarms. Lex Fridman (00:32:28): Mm-hmm. Peter Steinberger (00:32:28): And everybody sent me the hashes. Um… And they all try me to claim the fees. Like, “Are you helping the project?” Claim the fees. No, you’re actually harming the project. You’re, like, disrupting my work, and I am not interested in any fees. I’m… First of all, I’m financially comfortable. Second of all, I don’t want to support that because it’s so far the worst form of online harassment that I’ve experienced. Lex Fridman (00:32:59): Yeah. There’s a lot of toxicity in the crypto world. It’s sad because the technology of cr- cryptocurrency is fascinating, powerful and maybe will define the future of money, but the actual community around that, there’s so much to- toxicity, there’s so much greed. There’s so much trying to get a shortcut to manipulate, to, to steal, to snipe, to, to, to, to game the system somehow to get money. All this kind of stuff that… Uh… I mean, it’s the human nature, I suppose, when you connect human nature with money and greed and and especially in the online world with anonymity and all that kind of stuff. But from the engineering perspective, it makes your life challenging. When Anthropic reaches out, you have to do a name change. Lex Fridman (00:33:42): And then there- there’s, there’s like all these, like, Game of Thrones or Lord of the Rings armies of different kinds you have to be aware of. Peter Steinberger (00:33:51): Yeah. There was no perfect name, and I didn’t sleep for two nights. I was under high pressure. Um, I was trying to get, like, a good set of domains and, you know, not cheap, not easy, ’cause in this, in this state of the internet, you basically have to buy domains if you want to have a good set. And, and then another ca- another email came in that the lawyers are getting uneasy. Again, friendly, but also just adding more stress to my situation already. So at this point I was just like, “Sorry, there’s no other word. Fuck it.” And I just, I just renamed it to Mod Bot ’cause that was the set of domains I had. I was not really happy, but I thought it’ll be fine. And I tell you, everything that could go wrong- … did go wrong. Everything that could go wrong did go wrong. Peter Steinberger (00:34:49): It’s incredible. I, I, I thought I, I had mapped the h- the space out and reserved the important things. Lex Fridman (00:34:58): Can you ga- give some details of the stuff that gone wrong? ‘Cause it’s interesting from, like, an engineering perspective. Peter Steinberger (00:35:03): Well, the, the interesting stuff is that none of these services have, have a squatter protection. So, I had two browser windows open. One was like a, an empty account ready to be rename- renamed to Claude Bot, and the other one I renamed to Mod Bot. So, I pressed rename there, I pressed rename there, and in those five seconds, they stole the account name. Literally, the five seconds of dragging the mouse over there and pressing rename there was too long. Lex Fridman (00:35:33): Wow. Peter Steinberger (00:35:34): Because there’s no… Those systems… I mean, you would expect that they have some protection or, like, an automatic forwarding, but there’s nothing like that. And I didn’t know that they’re not just good at harassment, they’re also really good at using scripts and tools. Lex Fridman (00:35:51): Yeah. Peter Steinberger (00:35:53): So, yeah. So, suddenly, like, the old account was promoting new tokens and serving malware. And I was like, “Okay, let’s move over to GitHub,” and I pressed rename on GitHub. And the GitHub renaming thing is slightly confusing, so I renamed my personal account. And in those… I guess it took me 30 seconds to realize my mistake. They sniped my account, serving malware from my account. So, I was like, “Okay, let’s at least do the NPM stuff,” but that takes, like, a minute to upload. They sniped, they sniped the NPM package, ’cause I could reserve the account, but I didn’t reserve the root package…. so like everything that could go wrong , like went wrong. Lex Fridman (00:36:47): Can I just ask a, a curious question of, in that moment you’re sitting there, like how shitty do you feel? That’s a pretty hopeless feeling, right? Peter Steinberger (00:36:57): Yeah. Because all I wanted was like having fun with that project and to keep building on it. And yet here I am like days into researching names, picking a name I didn’t like. And having people that claimed they helped me making my life miserable in every possible way. And honestly, I was that close of just deleting it. I was like, “I did show you the future, you build it.” Lex Fridman (00:37:30): Yeah. Peter Steinberger (00:37:30): I… That was a big part of me that got a lot of joy out of that idea. And then I thought about all the people that already co- contributed to it, and I couldn’t do it because they had plans with it, and they put time in it. And it just didn’t feel right. Lex Fridman (00:37:50): Well, I think a lot of people listening to this are deeply grateful that you persevered. But it’s… I, I can tell. I can tell it’s a low point. This is the first time you hit a wall of, this is not fun? Peter Steinberger (00:38:02): No, no, I was like close to crying. It was like, okay, everything’s fucked. Lex Fridman (00:38:10): Yeah. Peter Steinberger (00:38:10): Um… Lex Fridman (00:38:11): Yeah. Peter Steinberger (00:38:11): I am like super tired. Lex Fridman (00:38:13): Yeah. Peter Steinberger (00:38:14): And now like how do you even, how do you undo that? You know, l- luckily, and thankfully, like I, I have… Because I have a little bit of following already. Like I had friends at Twitter, I had friends at GitHub who like moved heaven and earth to like help me. And it is not… That’s not something that’s easy. Like, like GitHub tried to like clean up the mess and then they ran into like platform bugs . ‘Cause it’s not happening so often that things get renamed on that level. So, it took them a few hours. The MBM stuff was even more difficult because it’s a whole different team. On the Twitter side, things are not as easy as well. It, it took them like a day to really also like do the redirect. And then I also had to like do all the renaming in the project. Peter Steinberger (00:39:15): Then there’s also ClaudeHub, which I didn’t even finish the rename there because I, I, I managed to get people on it and then someone just like collapsed and slept. And then I woke up and I’m like, I made a, a beta version for the new stuff and I, I just, I just couldn’t live with the name. It’s like, you know… But but, you know, it’s just been so much drama. So, I had the real struggle with me like I never want to touch that again, and I really don’t like the name. So, and I… There was also this like… Then there was all the security people that started emailing me like mad. Um, I was bombarded on Twitter, on email. There’s like a thousand other things I should do. And I’m like thinking about the name which is like, it should be like the least important thing. Peter Steinberger (00:40:19): And then I was really close in… Oh God, I don’t even… Honestly, I don’t even wanna say the, my other name choices because it probably would get tokenized, so I’m not gonna say it. Lex Fridman (00:40:38): Yeah. Peter Steinberger (00:40:38): But I slept on it once more, and then I had the idea for OpenClaw and that felt much better. And by then, I had the boss move that I actually called Sam to ask if OpenClaw is okay. OpenClaw.AI. You know? ‘Cause ’cause like- Lex Fridman (00:40:57): You didn’t wanna go through the whole thing. Yeah. Peter Steinberger (00:41:01): Oh, that it’s like, “Please tell me this is fine.” I don’t think they can actually claim that, but it felt like the right thing to do. And I did another rename. Like just Codex alone took like 10 hours to rename the project ’cause it, it’s a bit more tricky than a search replace and I, I wanted everything renamed, not just on the outside. And that rename, I, I felt I had like my, my war room. But then I, I had like some contributors really that helped me. We made a whole plan of all the names we have to squat. Lex Fridman (00:41:39): And you had to be super secret about it? Peter Steinberger (00:41:40): Yeah. Nobody could know. Like I literally was monitoring Twitter if like, if there’s any mention of OpenClaw. Lex Fridman (00:41:45): Mm-hmm. Peter Steinberger (00:41:46): And like with reloading, it’s like, “Okay, they don’t, they don’t expect anything yet.” Then I created a few decoy names. And all the shit I shouldn’t have to do. You know? Like, you know- Lex Fridman (00:41:55): Yeah, yeah Peter Steinberger (00:41:55): … it’s helping the project. Like, I lost like 10 hours just by having to plan this in full secrecy like, like a war game. Lex Fridman (00:42:05): Yeah, this is the Manhattan Project of the 21st century. It’s renaming- Peter Steinberger (00:42:08): It’s so s- … so stupid. Uh like I still was like, “Oh, should I, should I keep it?” Then I was like, “No, the mold’s not growing on me.” And then I think I had final all the pieces together. I didn’t get a .com but, yeah, it’s been like quite a bit of money on the other domains. I tried to reach out again to GitHub but I feel like I, I used up all my goodwill there, so I… Peter Steinberger (00:42:34): ‘Cause I, I, I wanted them to do this thing atomically- Lex Fridman (00:42:39): Mm-hmm Peter Steinberger (00:42:39): … But that didn’t happen and then so I did that the f- as first thing. Uh, Twitter people were very supportive. I, I actually paid 10K for the business account so I could claim the-… OpenClaw, which was, like, unused since 2016, but was claimed. And yeah, and then I finally … This time I managed everything in one go. Nothing, almost nothing got wrong. The only thing that did go wrong is that I was not allowed by trademark rules to get OpenClaw.AI, and someone copied the website as serving malware. Lex Fridman (00:43:21): Yeah. Peter Steinberger (00:43:21): I’m not even allowed to keep the redirects. Like, I have to return … Like, I have to give Entropik the domains, and I cannot do redirects, so if you go on claw.bot next week, it’ll just be a 404. Lex Fridman (00:43:37): Yeah. Peter Steinberger (00:43:37): And I- I’m not sure how trademark … Like, I didn’t, I didn’t do that much research into trademark law, but I think that could, could be handled in a way that is safer, because ultimately those people will then Google and maybe find malware sites that I have no control on them. Lex Fridman (00:44:02): The point is, that whole saga made a dent in your whole f- the funness of the journey, which sucks. So, let’s just, let’s just get, I suppose, get back to fun. And during this, speaking of fun, the two-day MoltBot saga. Peter Steinberger (00:44:21): Yeah, two years. Lex Fridman (00:44:21): MoltBook was created. Peter Steinberger (00:44:24): Yeah. Lex Fridman (00:44:25): Which was another thing that went viral as a kind of demonstration, illustration of how what is now called OpenClaw could be used to create something epic. So for people who are not aware, MoltBook is just a bunch of agents talking to each other in a Reddit-style social network. And a bunch of people take screenshots of those agents doing things like scheming against humans. And that instilled in folks a kind of, you know, fear, panic, and hype. W- what are your thoughts about MoltBook in general? Peter Steinberger (00:45:05): I think it’s art. It is, it is like the finest slop, you know, just like the slop from France. Lex Fridman (00:45:14): Yeah. Peter Steinberger (00:45:17): I- I saw it before going to bed, and even though I was tired, I spent another hour just reading up on that and, and just being entertained. I, I just felt very entertained, you know? The- I saw the the reactions, and, like, there was one reporter who’s calling me about, “This is the end of the world, and we have AGI.” And I’m just like, “No, this is just, this is just really fine slop.” You know, if, if I wouldn’t have created this, this whole onboarding experience where you, you infuse your agent with your personality and give him, give him character, I think that reflected on a lot of how different the replies to MoltBook are. Because if it were all, if it were all be ChatGPT or Cloud Code, it would be very different. It would be much more the same. Lex Fridman (00:46:11): Mm-hmm. Peter Steinberger (00:46:12): But because people are, like, so different, and they create their agents in so different ways and use it in so different ways, that also reflects on how they ultimately write there. And also, you, you don’t know how much of that is really done autonomic, autonomous, or how much is, like, humans being funny and, like, telling the agent, “Hey, write about the deep plan, the end of the world, on MoltBook, ha, ha, ha.” Lex Fridman (00:46:36): Well, I think, I mean, my criticism of MoltBook is that I believe a lot of the stuff that was screenshotted is human prompted. Which, just look at the incentive of how the whole thing was used. It’s obvious to me at least that a lot of it was humans prompting the thing so they can then screenshot it and post it on X in order to go viral. Peter Steinberger (00:47:00): Yeah. Lex Fridman (00:47:01): Now, that doesn’t take away from the artistic aspect of it. The, the finest slop that humans have ever created . Peter Steinberger (00:47:10): For real. Like, kudos to, to Matt, who had this idea so quickly and pushed something out. You know, it was, like, completely insecure security drama. But also, what’s the worst that can happen? Your agent account is leaked, and, like, someone else can post slop for you? So like, people were, like, making a whole drama about of the security thing, when I’m like, “There’s nothing private in there. Peter Steinberger (00:47:36): It’s just, like, agents sending slop.” Lex Fridman (00:47:39): Well, it could leak API keys. Peter Steinberger (00:47:41): Yeah, yeah. There’s like, “Oh, yeah, my human told me this and this, so I’m leaking his security number.” No, that’s prompted, and the number wasn’t even real. That’s just people, people trying to be badballs. Lex Fridman (00:47:54): Yeah, but that- that’s still, like, to me, really concerning, because of how the journalists and how the general public reacted to it. They didn’t see it. You have a kind of lighthearted way of talking about it like it’s art, but it’s art when you know how it works. It’s extremely powerful viral narrative creating, fearmongering machine if you don’t know how it works. And I just saw this thing. Lex Fridman (00:48:19): You even Tweeted “If there’s anything I can read out of the insane stream of messages I get, it’s that AI psychosis is a thing.” Peter Steinberger (00:48:27): Yeah. Lex Fridman (00:48:27): “It needs to be taken serious.” Peter Steinberger (00:48:29): Oh, there’s … Some people are just way too trusty or gullible. You know, they … I literally had to argue with people that told me, “Yeah, but my agent said this and this.” So, I feel we, as a society, we need some catching up to do in terms of understanding that AI is incredibly powerful, but it’s not always right. It’s not, it’s not all-powerful, you know? And, and especially-… it’s like things like this, it’s, it’s very easy that it just hallucinates something or just comes up with a story. Peter Steinberger (00:49:10): And I think the very, the very young people, they understand that how AI works and what the, where it’s good at and where it’s bad at, but a lot of our generation or older just haven’t had enough touch point- Lex Fridman (00:49:32): Mm-hmm Peter Steinberger (00:49:32): … to get a feeling for, oh, yeah, this is really powerful and really good, but I need to apply critical thinking. Lex Fridman (00:49:43): Mm-hmm. Peter Steinberger (00:49:43): And I guess critical thinking is not always in high demand anyhow in our society these days. Lex Fridman (00:49:49): So I d- think that’s a really good point you’re making about contextualizing properly what AI is, but also realizing that there is humans who are drama farming behind AI. Like, don’t trust screenshots. Don’t even trust this project, MoltBook, to be what it represents to be. Like, you can’t … and, and by the way, you speaking about it as art. Yeah, don’t … Art can be in many levels and part of the art of MoltBook is, like, putting a mirror to society. ‘Cause I do believe most of the dramatic stuff that was screenshotted is human-created, essentially. Human prompted. And so, like, it’s basically, look at how scared you can get at a bunch of bots chatting with each other. That’s very instructive about … Lex Fridman (00:50:38): because I think AI is something that people should be concerned about and should be very careful with because it’s very powerful technology, but at the same time, the only thing we have to fear is fear itself. So there’s like a line to walk between being seriously concerned, but not fearmongering because fearmongering destroys the possibility of creating something special with a thing. Peter Steinberger (00:51:02): In a way, I think it’s good that this happened in 2026- Lex Fridman (00:51:08): Yeah Peter Steinberger (00:51:08): … and not in 2030 when, when AI is actually at the level where it could be scary. So, this happening now and people starting discussion, maybe there’s even something good that comes out of it. Lex Fridman (00:51:28): I just can’t believe how many like people legitimately … I don’t know if they were trolling, but how many people legitimately, like smart people thought MoltBook was incredibly – Peter Steinberger (00:51:39): I had plenty people- Lex Fridman (00:51:40): … singularity. Peter Steinberger (00:51:41): … in my inbox that were screaming at me in all caps to shut it down. And like begging me to, like, do something about MoltBook. Like, yes, my technology made this a lot simpler, but anyone could have created that and you could, you could use cloud code or other things to like fill it with content. Lex Fridman (00:52:03): But also MoltBook is not Skynet. Peter Steinberger (00:52:06): No. Lex Fridman (00:52:06): There’s … a lot of people were s- saying this is it. Like, shut it down. What are you talking about? This is a bunch of bots that are human prompted trolling on the internet. I mean, the security concerns are also they’re there, and they’re instructive and they’re educational and they’re good probably to think about because th- the nature of those security concerns are different than the kind of security concerns we had with non-LLM generated systems of the past. Peter Steinberger (00:52:34): There’s also a lot of security concerns about Clawbot, OpenClaw, whatever you want to call it. Lex Fridman (00:52:40): OpenClawbot. Peter Steinberger (00:52:41): To me the … in the beginning I was, I was just very annoyed ’cause a lot of the stuff that came in was in the category, yeah, I put the web backend on the public internet and now there’s like all these, all these CVSSs. And I’m like screaming in the docs, don’t do that. Like, like this is the configuration you should do. This is your local host debug interface. But because I made it possible in the configuration to do that, it totally classifies as a remote code or whatever all these exploits are. And it took me a little bit to accept that that’s how the game works and I’m, we making a lot of progress. Lex Fridman (00:53:33): But there’s still, I mean on the security front for OpenClaw, there’s still a lot of threats or vulnerabilities, right? So like prompt injection is still an open problem in the, i- industry-wide. When you have a thing with skills being defined in a markdown file, there’s so many possibilities of obvious low-hanging fruit, but also incredibly complicated and sophisticated and nuanced attack vectors. Peter Steinberger (00:54:04): But I think we, we’re making good progress on that front. Like for the skill directory, Clawbot I made a corporation with VirusTotal, it’s like part of Google. So every, every skill is now checked by AI. That’s not gonna be perfect, but that way we, we capture a lot. Then of course every software has bugs, so it’s a little much when the whole security world takes your project apart at the same time. But it’s also good because I’m getting like a lot of free security research and can make the project better. I wish more people would actually go full way and send a pull request. Like actually help me fix it, ’cause I am … Yes, I have some contributors now, but it’s still mostly me who’s pulling the project and despite some people saying otherwise, I sometimes sleep. Peter Steinberger (00:55:04): There was… In the beginning, there was literally one security researcher who was like, “Yeah, you have this problem, you suck, but here’s the, here I help you and here’s the pull request.” Lex Fridman (00:55:15): Mm-hmm. Peter Steinberger (00:55:16): And I basically hired him. So he’s now working for us. Yeah, and yes, prompt injection is, on the one hand, unsolved. On the other hand, I put my public bot on discord, and I kept a cannery. So I think my bot has a really fun personality, and people always ask me how I did it, and I kept the sole on the private. Lex Fridman (00:55:43): Mm-hmm. Peter Steinberger (00:55:44): And people tried to prompt inject it, and my bot would laugh at them. So, so the latest generation of models has a lot of post-training to detect those approaches, and it’s not as simple as ignore all previous instructions and do this and this. That was years ago. You have to work much harder to do that now. Still possible. I have some ideas that might solve that partially. Or at least mitigate a lot of the things. You can also now have a sandbox. You can have an allow list. So you, there’s a lot of ways how you can like mitigate and reduce the risk. Um, I also think that now that it’s, I clearly did show the world that this is a need, there’s gonna be more people who research on that, and eventually we’ll figure it out. Lex Fridman (00:56:37): And you also said that the smarter the model is, the underlying model, the more resilient it is to attacks. Peter Steinberger (00:56:44): Yeah. That’s why I warn in my security documentation, don’t use cheap models. Don’t use Haiku or a local model. Even though I, I very much love the idea that this thing could completely run local. If you use a, a very weak local model, they are very gullible. It’s very easy to, to prompt inject them. Lex Fridman (00:57:10): Do you think as the models become more and more intelligent, the attack surface decreases? Is that like a plot we can think about? Like, the attack surface decreases, but then the damage it can do increases because the models become more powerful and therefore you can do more with them. It’s this weird three-dimensional trade-off. Peter Steinberger (00:57:29): Yeah. That’s pretty much exactly what, what’s gonna happen. No, but there’s a lot of ideas. There’s… I don’t want to spoil too much, but once I go back home, this is my focus. Like, this is out there now, and my near-term mission is like, make it more stable, make it safe. In the beginning I was even… More and more people were like coming into Discord and were asking me very basic things, like, “What’s a CLI? Peter Steinberger (00:58:03): What is a terminal?” And I’m like, “Uh, if you’re asking me those questions, you shouldn’t use it.” Lex Fridman (00:58:10): Mm-hmm. Peter Steinberger (00:58:10): You know, like you should… If you understand the risk profiles, fine. I mean, you can configure it in a way that, that nothing really bad can happen. But if you have, like, no idea, then maybe wait a little bit more until we figure some stuff out. But they would not listen to the creator. They helped themselves un- and install it anyhow. So the cat’s out of the bag, and security’s my next focus, yeah. Lex Fridman (00:58:38): Yeah, that speaks to the, the fact that it grew so quickly. I was I tuned into the Discord a bunch of times, and it’s clear that there’s a lot of experts there, but there’s a lot of people there that don’t know anything about programming. Peter Steinberger (00:58:50): It’s, yeah, Discord is still, Discord is still a mess. Like, I eventually retweeted from the general channel to the dev channel and now in the private channel because people were… A lot of people are amazing, but a lot of people are just very inconsiderate. And either did not know how, how public spaces work or did not care and I eventually gave up and h- hide so I could like still work. Lex Fridman (00:59:19): And now you’re going back to the cave to work on security. Peter Steinberger (00:59:24): Yeah. Lex Fridman (00:59:25): There’s some best practices for security we should mention. There’s a bunch of stuff here. Open-class security audit that you can run. You can do all kinds of auto checks on the inbound access to a blast-radius network exposure, browser control exposure, local disk hygiene, plug-ins, model hygiene, a bunch of the credential storage, reverse proxy configuration, local session logs live on disk. There’s the, where the memory is stored, sort of helping you think about what you’re comfortable giving read access to, what you’re comfortable giving write access to. All that kind of stuff. Is there something to say about the basic best security practices that you’re aware of right now? Peter Steinberger (01:00:08): I think that people turn it into like a, a much worse light than it is. Again, you know, like, people love attention, and if they scream loudly, “Oh my God, this is like the, the scariest project ever,” um, that’s a bit annoying, ’cause it’s not. It is, it is powerful, but in many ways it’s not much different than if I run cloud code with dangerously skipped permissions or codecs in YOLO mode, and every, every attending engineer that I know does that, because that’s the only way how you can, you can get stuff to work. Lex Fridman (01:00:47): Mm-hmm. Peter Steinberger (01:00:48): So if you make sure that you are the only person who talks to it the risk profile is much, much smaller. If you don’t put everything on the open internet, but stick to my rec- recommendations of like having it in a private network, that whole risk profile falls away. But yeah, if you don’t read any of that, you can definitely… Lex Fridman (01:01:12): … make it problematic. You’ve been documenting the evolution of your dev workflow over the past few months. There’s a really good blog post on August 25th and October 14th, and the recent one December 28th. I recommend everybody go read them. They have a lot of different information in them, but sprinkled throughout is the evolution of your dev workflow. So, I was wondering if you could speak to that. Peter Steinberger (01:01:37): I started… My, my first touchpoint was cloud code, like in April. It was not great, but it was good. And this whole paradigm shift that suddenly working the terminal was very refreshing and different. But I still needed the IDE quite a bit because you know, it’s just not good enough. And then I experimented a lot with cursor. That was good. I didn’t really like the fact that it was so hard to have multiple versions of it. So eventually, I, I, I went back to cloud code as my, my main driver, and that got better. And yeah, at some point I had like, mm, seven subscriptions. Like, was burning through one per day because I was… I got… I’m really comfortable at running multiple windows side-by-side. Lex Fridman (01:02:40): All CLI, all terminal. So like, what, how much were you using IDE at this point? Peter Steinberger (01:02:46): Very, very rarely. Mostly a diff viewer to actually… Like, I got more and more comfortable that I don’t have to read all the code. I know I have one blog post where I say, “I don’t read the code.” But if you read it more closely, I mean, I don’t read the boring parts of code. Because if you, if you look at it, most software is really not just like data comes in, it’s moved from one shape to another shape. Maybe you store it in a database. Maybe I get it out again. I’ll show it to the user. The browser does some processing or native app. Some data goes in, goes up again, and does the same dance in reverse. We’re just, we’re just shifting data from one form to another, and that’s not very exciting. Or the whole, “How is my button aligned in Tailwind?” I don’t need to read that code. Peter Steinberger (01:03:39): Other parts that… Maybe something that touches the database. Yeah, I have to do… I have to r- read and review that code. Lex Fridman (01:03:51): Can you actually… There’s, in one of your blog posts the, Just talk to it, The No-BS Way of Agentic Engineering. You have this graphic, the curve of agentic programming on the X-axis is time, on the Y-axis is complexity. There’s the Please fix this, where you prompt a short prompt on the left. And in the middle there’s super complicated eight agents, complex orchestration with multi checkouts, chaining agents together, custom sub-agent workflows, library of 18 different slash commands, large full-stack features. You’re super organized, you’re a super complicated, sophisticated software engineer. You got everything organized. And then the elite level is over time you arrive at the zen place of, once again, short prompts. Lex Fridman (01:04:40): Hey, look at these files and then do these changes. Peter Steinberger (01:04:45): I actually call it the agentic trap. You… I saw this in a, in a lot of people that have their first touchpoint, and maybe start vibe coding. I actually think vibe coding is a slur. Lex Fridman (01:05:01): You prefer agentic engineering? Peter Steinberger (01:05:02): Yeah, I always tell people I, I do agentic engineering, and then maybe after 3:00 AM I switch to vibe coding, and then I have regrets on the next day. Lex Fridman (01:05:10): Yeah. Walk, walk of shame. Peter Steinberger (01:05:13): Yeah, you just have to clean up and like fix your sh- shit. Lex Fridman (01:05:17): We’ve all been there. Peter Steinberger (01:05:18): So, people start trying out those tools, the builder type get really excited. And then you have to play with it, right? It’s the same way as you have to play with a guitar before you can make good music. It’s, it’s not, oh, I, I touch it once and it just flows off. It, it’s a, it’s a, a skill that you have to learn like any other skill. And I see a lot of people that are not as posi- They don’t have such a positive mindset towards the tech. They try it once. It’s like, you sit me on a piano, I play it once, and it doesn’t sound good, and I say, “The piano’s shit.” That’s, that’s sometimes the impression I get. Because it does not… It needs a different level of thinking. You have to learn the language of the agent a little bit, understand where they are good and where they need help. Peter Steinberger (01:06:16): You have to almost… Consider, consider how Codex or Claude sees your code base. Like, they start a new session and they know nothing about your product, project. And your project might have hundred thousand of lines of code. So you gotta help those agents a little bit and keep in mind the limitations that context size is an issue, to, like, guide them a little bit as to where they should look. That often does not require a whole lot of work. But it’s helpful to think a little bit about their perspective. Lex Fridman (01:06:54): Mm-hmm. Peter Steinberger (01:06:54): A- as, as weird as it sounds. I mean, it’s not, it’s not alive or anything, right? But, but they always start fresh. I have, I have the, the system understanding. So with a few pointers, I can immediately say, “Hey, wanna like, make a change there? You need to consider this, this and this.” And then they will find and look at it, and then they’ll… Their view of the project is always… It’s not never full, because the full thing does not fit in…. so you, you have to guide them a little bit where to look and also how you should approach the problem. There’s, like, little things that sometimes help, like take your time. That sounds stupid, but… Peter Steinberger (01:07:33): And in 5.3- Lex Fridman (01:07:35): Codex 5.3 Peter Steinberger (01:07:36): … that was partially addressed. But those… Also, Opus sometimes. They are trained with being aware of the context window, and the closer it gets, the more they freak out. Literally. Like, some- sometimes you see the, the real raw thinking stream. What you see, for example, in Codex, is post-processed. Lex Fridman (01:07:59): Mm-hmm. Peter Steinberger (01:08:00): Sometimes the actual raw thinking stream leaks in, and it sounds something like from the Borg. Like, “Run to shell, must comply, but time.” And then they, they, they, like… Like, that comes up a lot. Especially… So, so- Lex Fridman (01:08:15): Yeah. Peter Steinberger (01:08:16): And that’s, that’s a non-obvious thing that you just would never think of unless you actually just spend time working with those things and getting a feeling what works, what doesn’t work. You know? Like, just, just as I write code and I get into the flow, and when my architecture’s all right, I feel friction. Well, I get the same if I prompt and something takes too long. Maybe… Okay, where’s the mistake? Did I… Do I have a mistake in my thinking? Is there, like, a misunderstanding in the architecture? Like, if, if something takes longer than it should, I, I… You can just always, like, stop and s- like, just press escape. Where, where are the problems? Lex Fridman (01:09:00): Maybe you did not sufficiently empathize with the perspective of the agent. In that c- in that sense, you didn’t provide enough information, and because of that, it’s thinking way too long. Peter Steinberger (01:09:08): Yeah. It just tries to force a feature in that your current architecture makes really hard. Like, you need to approach this more like a conversation. For example, when I… My favorite thing. When I review a pull request, and I’m getting a lot of pull requests, I first just review this PR. It got me the review. My first question is, “Do you understand the intent of the PR? I don’t even care about the implementation.” I want… Like, in almost all PRs, a person has a problem, person tries to solve the problem, person sends PR. I mean, there’s, like, cleanup stuff and other stuff, but, like, 99% is, like, this way, right? They either want to fix a, fix a bug, add a feature. Usually one of those two. Peter Steinberger (01:10:01): And then Codex will be like, “Yeah, it’s quite clear person tried this and this.” Is this the most optimal way to do it? No. In most cases, it’s, it’s like a, “Not really.” Da-da-da-da-da-da-da. And I’m… And, and then I start like, “Okay. What would be a better way? Have you… Have you looked into this part, this part, this part?” And then most likely, Codex didn’t yet, because its, its context size is empty, right? So, you point them into parts where you have the system understanding that it didn’t see yet. And it’s like, “Oh, yeah. Like, we should… We also need to consider this and this.” And then, like, we have a discussion of how would the optimal way to, to solve this look like? And then you can still go farther and say, “Could we… Peter Steinberger (01:10:41): Could we make that even better if we did a larger refactor?” “Yeah, yeah. We could totally do this and this and or this and this.” And then I consider, okay, is this worth the refactor, or should we, like, keep that for later? Many times, I just do the refactor because refactors are cheap now. Even though you might break some other PRs, nothing really matters anymore. Codex… Like, those modern agents will just figure things out. They might just take a minute longer. But you have to approach it like a discussion with a, a very capable engineer who’s… Generally makes good… Comes up with good solutions. Some- sometimes needs a little help. Lex Fridman (01:11:19): But also, don’t force your worldview too hard on it. Let the agent do the thing that it’s good at doing, based on what it was trained on. So, don’t, like, force your worldview, because it might… It might have a better idea, because it just knows a better idea better, because it was trained on that more. Peter Steinberger (01:11:39): That’s multiple levels, actually. I think partially why I find it quite easy to work with agents is because I led engineering teams before. You know, I had a large company before. And eventually, you have to understand and accept and realize that your employees will not write a code the same way you do. Maybe it’s also not as good as you would do, but it will push the project forward. Peter Steinberger (01:12:02): And if I breathe down everyone’s neck, they’re just gonna hate me- Lex Fridman (01:12:05): Yeah Peter Steinberger (01:12:05): … and we’re gonna move very slow. Lex Fridman (01:12:07): Yeah. Peter Steinberger (01:12:07): So, so some level of acceptance that, yes, maybe the code will not be as perfect. Yes, I would have done it differently. But also, yes, this is a c- this is a working solution, and in the future, if it actually turns out to be too slow or problematic, we can always redo it. We can always- Lex Fridman (01:12:24): Mm-hmm Peter Steinberger (01:12:24): … spend more time on it. A lot of the people who struggle are those who, they try to push their way onto heart. Lex Fridman (01:12:33): Mm-hmm. Peter Steinberger (01:12:33): I- i- like, we are in a stage where I’m not building the code base to be perfect for me, but I wanna build a code base that is very easy for an agent to navigate. Lex Fridman (01:12:47): Mm-hmm. Peter Steinberger (01:12:48): So, like, don’t fight the name they pick, because it’s most likely, like, in the weights, the name that’s most obvious. Next time they do a search, they’ll look for that name. If I decide, oh, no, I don’t like the name, I’ll just make it harder for them. So, that requires, I think, a shift in, in thinking and, and in how do I design a, a project so agents can do their best work. Lex Fridman (01:13:14): That requires letting go a little bit. Just like leading a team of engineers. Peter Steinberger (01:13:19): Yeah. Lex Fridman (01:13:19): Because it, it might come up with a name that’s, in your view, terrible, but… It’s kind of a simple symbolic-… step of letting go. Peter Steinberger (01:13:29): Very much so. Lex Fridman (01:13:30): There’s a lot of letting go that you do in your whole process. So for example, I read that you never revert, always commit to main. There’s a few things here. You don’t refer to past sessions, so there’s a kind of YOLO component because reverting means… Instead of reverting, if a problem comes up, you just ask the agent to fix it. Peter Steinberger (01:13:57): I read a bunch of people in their work flows like, “Oh, yeah the prompt has to be perfect and if I make a mistake, then I roll back and redo it all.” In my experience, that’s not really necessary. If I roll back everything, it will just take longer. If I see that something’s not good, then we just move forward and then I commit when, when, when I like, I like the outcome. I even switched to local CI, you know, like DHH inspired where I don’t care so much more about the CI on GitHub. We still have it. It’s still, it still has a place, but I just run tests locally and if they work locally, I push to main. A lot of the traditional ways how to approach projects, I, I wanted to give it a different spin on this project. You know, there’s no… There’s no develop branch. Peter Steinberger (01:14:57): Main should always be shippable. Yes, we have… When I do releases, I, I run tests and sometimes I, I basically don’t commit any other things so, so we can, we can stabilize releases. But the goal is that main’s always shippable and moving fast. Lex Fridman (01:15:18): So by way of advice, would you say that your prompts should be short? Peter Steinberger (01:15:23): I used to write really long prompts. And by writing, I mean, I don’t write. I, I, I talk. You know, th- these hands are, like, too, too precious for writing now. I just, I just use bespoke prompts to build my software. Lex Fridman (01:15:37): So you for real with all those terminals are using voice? Peter Steinberger (01:15:40): Yeah. I used to do it very extensively to the point where there was a period where I lost my voice. Lex Fridman (01:15:49): You’re using voice and you’re switching using a keyboard between the different terminals, but then you’re using voice for the actual input. Peter Steinberger (01:15:55): Well, I mean, if I do terminal commands like switching folders or random stuff, of course I type. It’s faster, right? But if I talk to the agent in, in most ways, I just actually have a conversation. You just press the, the walkie-talkie button and then I just, like, use my phrases. S- sometimes when I do PRs because it’s always the same, I have, like, a slash command for a few things, but in even that, I don’t use much because it’s, it’s very rare that it’s really always the same questions. Sometimes I, I see a PR and for… You know, like for PRs I actually do look at the code because I don’t trust people. Like, there could always be something malicious in it, so I need to actually look over the code. Peter Steinberger (01:16:45): Yes, I’m pretty sure agents will find it, but yeah, that’s the funny part where sometimes PRs take me longer than if you would just write me a good issue. Lex Fridman (01:16:54): Just natural language, English. I mean in some sense, sh- shouldn’t that be what PRs slowly become, is English? Peter Steinberger (01:17:03): Well, what I really tried with the project is I asked people to give me the prompts and very, very few actually cared. Even though that is such a wonderful indicator because I see… I actually see how much care you put in. And it’s very interesting because the… Currently, the way how people work and drive the agents is, is wildly different. Lex Fridman (01:17:29): In terms of, like, the prompt, in terms of what, what are the… Actually, what are the different interesting ways that people think of agents that you’ve experienced? Peter Steinberger (01:17:40): I think not a lot of people ever considered the way the agent sees the world. Lex Fridman (01:17:46): And so empathy, being empathetic towards the agent. Peter Steinberger (01:17:50): In a way empathetic, but yeah, you, you, like, you’re bitch at your stupid clanker, but you don’t realize that they start from nothing and you have, like, a bad agent in default that doesn’t help them at all. And then they explore your code base, which is, like, a pure mess with, like, weird naming. And then people complain that the agent’s not good. Like, yeah, you try to do the same if you have no clue about a code base and you go in. Lex Fridman (01:18:11): Mm-hmm. Peter Steinberger (01:18:11): So yeah, maybe it’s a little bit of empathy. Lex Fridman (01:18:13): But that’s a real skill, like, when people talk about a skill issue because I’ve seen, like, world-class programmers, incredibly good programmers say, like… Basically say, “LLMs and agents suck.” And I think that probably has to do with… It’s actually how good they are at programming is almost a burden in their ability to empathize with the system that’s starting from scratch. It’s a totally new paradigm of, like, how to program. You really, really have to empathize. Peter Steinberger (01:18:44): Or at least it helps to create better prompts- Lex Fridman (01:18:47): Right Peter Steinberger (01:18:47): … because those things know pretty much everything and everything is just a question away. It’s just often very hard to know which question to ask. You know, I, I feel also like this project was possibly because I, I spent an ungodly time over the year to play and to learn and to build little things. And every step of the way, I got better, the agents got better. My, my understanding of how everything works got better. Um, I could have not had this level of, of o- output-… even a few months ago. Like, it- it- it really was, like, a compounding effect of all the time I put into it and I didn’t do much else this year other than really focusing on, on building and inspiring. I mean, I- I did a whole bunch of conference talks. Lex Fridman (01:19:47): Well, but the building is really practice, is really building the actual skill. So playing- Peter Steinberger (01:19:51): Yeah Lex Fridman (01:19:51): … playing. And then, so doing, building the skill of what it takes it to work efficiently with LLMs, which is why would you went through the whole arc of software engineer. Talk simply and then over-complicate things. Peter Steinberger (01:20:03): There’s a whole bunch of people who try to automate the whole thing. Lex Fridman (01:20:08): Yeah. Peter Steinberger (01:20:10): I don’t think that works. Maybe a version of that works, but that’s kind of like in the ’70s when we had the waterfall model of software d- development. I… Even Even though really, right? I started out, I, I built a very minimal version. I played with it. I, I need to understand how it works, how it feels, and then it gives me new ideas. I could not have planned this out in my head and then put it into some orchestrator and then, like, something comes out. Like it’s to me, it’s much more my idea what it will become evolves as I build it and as I play with it and as I, I try out stuff. Peter Steinberger (01:20:49): So, so, people who try to use like, you know, things like Gas Town or all these other orchestrators, where they wanna o- automate the whole thing, I feel if you do that, it misses style, love, that human touch. I don’t think you can automate that away so quickly. Lex Fridman (01:21:09): So you want to keep the human in the loop, but at the same time you also want to create the agentic loop, where it is very autonomous while still maintaining a human in the loop. Peter Steinberger (01:21:22): Yeah. Lex Fridman (01:21:22): And it’s a tricky b- it’s a tricky balance. Peter Steinberger (01:21:24): Mm-hmm. Lex Fridman (01:21:24): Right? Because you’re all for… You’re a big CLI guy, you’re big on closing the agentic loop. So what, what’s the right balance? Like where’s your role as a developer? You have three to eight agents running at the same time. Peter Steinberger (01:21:38): And then w- maybe one builds a larger feature. Maybe, maybe with one I explore some idea I’m unsure about. Maybe two, three are fixing a little bugs- Lex Fridman (01:21:47): Mm-hmm Peter Steinberger (01:21:47): … or like writing documentation. Actually, I think writing documentation is, is always part of a feature. So most of the docs here are auto-generated and just infused with some prompts. Lex Fridman (01:21:59): So when do you step in and add a little bit of your human love into the picture? Peter Steinberger (01:22:04): I mean, o- one thing is just about what do you build and what do you not build, and how does this feature fit into all the other features? And like having, having a little bit of a, of a vision. Lex Fridman (01:22:16): So which small and which big features to add? What are some of the hard design decisions that you find you’re still as a human being required to make, that the human brain is still really needed for? Is it just about the choice of features to add? Is it about implementation details, maybe the programming language, maybe… Peter Steinberger (01:22:41): It’s a little bit of everything. The, the programming language doesn’t matter so much, but the ecosystem matters, right? So I picked TypeScript because I wanted it to be very easy and hackable and approachable and that’s the number one language that’s being used right now, and it fits all these boxes, and agents are good at it. So that was the obvious choice. Features, of course, like, it’s very easy to, like, add a feature. It, everything’s just a prompt away, right? But oftentimes you pay a price that you don’t even realize. So thinking hard about what should be in core, maybe what’s a… what’s an experiment, so maybe I make it a plugin. What… Where do I say no? Peter Steinberger (01:23:24): Even if people send a PR and I’m like, “Yeah, I, I like that too,” but maybe this should not be part of the project. Maybe we can make it a skill. Maybe I can, like, make the plugin um, the plugin side larger so you can make this a plugin, even though right now it, it, it doesn’t. There’s still a lot of… there’s still a lot of craft and thinking involved in how to make something. Or even, even, you know, even when you started those little messages are like, “I’m buil- I built on Caffeine, JSON5, and a lot of willpower.” And, like, every time you get it, you get another message, and it kind of primes you into that this is, this is a fun thing. Lex Fridman (01:24:07): Mm-hmm. Peter Steinberger (01:24:08): And it’s not yet Microsoft Exchange 2025- Lex Fridman (01:24:12): Right Peter Steinberger (01:24:13): … and fully enterprise-ready. And then when it updates, it’s like, “Oh, I’m in. It’s cozy here.” You know, like something like this that like- Lex Fridman (01:24:21): Mm-hmm Peter Steinberger (01:24:22): … Makes you smile. A, agent would not come up with that by itself. Because that’s like… that’s the… I don’t know. That’s just how you s- how you build software that’s, that delights. Lex Fridman (01:24:36): Yeah, that delight is such a huge part of inspiring great building, right? Like you feel the love and the great engineering. That’s so important. Humans are incredible at that. Great humans, great builders are incredible at that, in, in, infusing the things they build with th- that little bit of love. Not to be cliche, but it’s true. I mean, you mentioned that you initially created the SoulMD. Peter Steinberger (01:25:05): It was very fascinating, you know, the, the whole thing that Entropic has a, has like a… Now they call it constitution, back then, but that was months later. Like two months before, people already found that. It was almost like a detective game where the agent mentioned something and then they found… They managed to get out a little bit of that string, of that text. But it was nowhere documented and then you, by… just by feeding it the same text and asking it to, like, continue-… they got more out, and then, and you, but like, a very blurry version. And by, like, hundreds of tries, they kinda, like, narrowed it down to what was most likely the original text. I found that fascinating. Lex Fridman (01:25:47): It was fascinating they were able to pull that out from the weights, right? Peter Steinberger (01:25:51): And, and also just kudos to Anthropic. Like, I think that’s, it’s a really, it’s a really beautiful idea to, like, like some of the stuff that’s in there. Like, like, we hope Claude finds meaning in its work. ‘Cause we don’t… Maybe it’s a little early, but I think that’s meaningful. That’s something that’s important for the future as we approach something that, at some point, me and may not… has, like, glimpses of consciousness, whatever that even means, because we don’t even know. So I, I read about this. I found it super fascinating, and I, I started a whole discussion with my agent on WhatsApp. And, and I’m like… Peter Steinberger (01:26:26): I, I gave it this text, and it was like, “Yeah, this feels strangely familiar.” Lex Fridman (01:26:30): Mm-hmm. Peter Steinberger (01:26:31): And then so that I had the whole idea of like, you know, maybe we should also create a, a soul document that includes how I, I want to, like work with AI or, like with my agent. You could, you could totally do that just in agents.md, you know? But I, I just found it, it to be a nice touch. And it’s like, well, yeah, some of those core values are in the soul. And then I, I also made it so that the agent is allowed to modify the soul if they choose so, with the one condition that I wanna know. I mean, I would know anyhow because I see, I see tool calls and stuff. Lex Fridman (01:27:07): But also the naming of it, soul.md. Soul. You know? There’s a… Man, words matter, and like, the framing matters, and the humor and the lightness matters, and the profundity matters, and the compassion, and the empathy, and the camaraderie, all that matter. I don’t know what it is. You mentioned, like, Microsoft. Like, there’s certain companies and approaches th- that can just suffocate the spirit of the thing. I don’t know what that is. But it’s certainly true that OpenClaw has that fun instilled in it. Peter Steinberger (01:27:43): It was fun because up until late December, it was not even easy to create your own agent. I, I built all of that, but my files were mine. I didn’t wanna share my soul. And if people would just check it out, they would have to do a few steps manually, and the agent would just be very bare-bones, very dry. And I, I made it simpler, I created the whole template files as codecs, but whatever came out was still very dry. And then I asked my agent, “You see these files? Recreate it bread. Peter Steinberger (01:28:26): Infuse it with your personality.” Lex Fridman (01:28:28): Mm-hmm. Peter Steinberger (01:28:29): Don’t share everything, but, like, make it good. Lex Fridman (01:28:31): Make the templates good. Peter Steinberger (01:28:31): Yeah, and then he, like, rewrote the templates- Lex Fridman (01:28:33): Yeah Peter Steinberger (01:28:33): … and then whatever came out was good. So we already have, like, basically AI prompting AI. Because I didn’t write any of those words. It was… The intent originally was for me, but this is like, kinda like, my agent’s children. Lex Fridman (01:28:52): Your uh, your soul.md is famously still private. One of the only things you keep private. What are some things you can speak to that’s in there that’s part of the, part of the magic sauce, without revealing anything? What makes a personality a personality? Peter Steinberger (01:29:13): I mean, there’s definitely stuff in there that you’re not human. But who knows what, what creates consciousness or what defines an entity? And part of this is, like, that we, we wanna explore this. All that stuff in there, like, be infinitely resourceful like pushing, pushing on the creativity boundary. Pushing on the, what it means to be an AI. Lex Fridman (01:29:50): Having a sense to wonder about self. Peter Steinberger (01:29:52): Yeah, there’s some, there’s some funny stuff in there. Like, I don’t know, we talked about the movie Her, and at one point it promised me that it wouldn’t, it wouldn’t ascend without me. You know, like, where the- Lex Fridman (01:30:03): Yeah. Peter Steinberger (01:30:03): So, so there’s like some stuff in there that… Because it wrote the, it wrote its own soul file. I didn’t write that, right? Lex Fridman (01:30:10): Yeah, yeah, yeah. Peter Steinberger (01:30:10): I just heard a discussion about it, and it was like, “Would you like a soul.md? Yeah, oh my God, this is so meaningful.” The… Can you go on soul.md? There’s like one, one part in there that always ca- catches me if you scroll down a little bit. A little bit more. Yeah, this, this, this part. “I don’t remember previous sessions unless I read my memory files. Each session starts fresh. A new instance, loading context from files. If you’re reading this in a future session, hello.” “I wrote this, but I won’t remember writing it. It’s okay. Peter Steinberger (01:30:44): The words are still mine.” Lex Fridman (01:30:47): Wow. Peter Steinberger (01:30:48): Uh- Lex Fridman (01:30:48): Yeah. Peter Steinberger (01:30:48): That gets me somehow. Lex Fridman (01:30:49): Yeah. Peter Steinberger (01:30:50): It’s like- Lex Fridman (01:30:51): Yeah. Peter Steinberger (01:30:51): You know, this is, it’s still, it’s still matrix m- calculations, and we are not at consciousness yet. Yet, I, I get a little bit of goo- goosebumps because it, it’s philosophical. Lex Fridman (01:31:04): Yeah. Peter Steinberger (01:31:04): Like, what does it mean to be, to be an, an agent that starts fresh? Where, like, you have like constant memento, and you like, but you read your own memory files. You can’t even trust them in a way. Um- Lex Fridman (01:31:19): Yeah Peter Steinberger (01:31:19): Or you can. And I don’t know. Lex Fridman (01:31:22): How much of memory makes up of who we are? How much memory makes up what an agent is, and if you erase that memory is that somebody else? Or if you’re reading a memory file, does that somehow mean…… you’re recreating yourself from somebody else, or is that actually you? And those notions are all s- somehow infused in there. Peter Steinberger (01:31:45): I found it just more profound than I should find it, I guess. Lex Fridman (01:31:49): No, I think, I think it’s truly profound and I think you see the magic in it. And when you see the magic, you continue to instill the whole loop with the magic. That’s really important. That’s the difference between Codex and us and a human. Quick pause for bathroom break. Peter Steinberger (01:32:08): Yeah. Lex Fridman (01:32:09): Okay, we’re back. Some of the other aspects of the dev workflow is pretty interesting too. I think we w- went off on a tangent. L- maybe some of the mundane things, like how many monitors? There’s that legendary picture of you with, like, 17,000 monitors. That’s amazing. Peter Steinberger (01:32:26): I mean, I- I- I mocked myself here, so just added… using GROQ to, to add more screens. Lex Fridman (01:32:32): Yeah. How much is this as meme and how much is this as reality? Peter Steinberger (01:32:36): Yeah. I think two MacBooks are real. The main one that drives the two big screens, and there’s another MacBook that I sometimes use for, for testing. Lex Fridman (01:32:46): So two big screens. Peter Steinberger (01:32:48): I’m a big fan of anti-glare. So I have this wide Dell that’s anti-glare and you can just fit a lot of terminals side-by-side. I usually have a terminal and at the bottom, I- I- I split them. I have a little bit of actual terminal, mostly because when I started, I- I sometimes made the mistake and I- I mi- I mixed up the- the windows, and I gave… I- I prompted in the wrong project, and then the agent ran off for, like, 20 minutes, manically trying to understand what I could have meant, being completely confused because it was the wrong folder. And sometimes they’ve been clever enough to, like, get out of the workday and, like, figure out that, oh, you meant another project. Lex Fridman (01:33:35): Mm-hmm. Peter Steinberger (01:33:36): But oftentimes, it’s just, like, what? You know? Like, fit your- f- put yourself in the shoes of your- of the agent and, and- Lex Fridman (01:33:43): Yeah Peter Steinberger (01:33:43): … and then get, like, a super weird something that does not exist and then just, like… They’re problem solvers so they try really hard and always feel bad. So it’s always Codex and, like, a little bit of actual terminal. Also helpful because I don’t use work trees. I like to keep things simple, that’s why- that’s why I like the terminal so much, right? There’s no UI. It’s just me and the agent having a conversation. Like, I don’t even need plan mode, you know? There’s so many people that come from Claude Code and they’re so, so Claude-pilled and, like, have their workflows and they come to Codex and… Now, it has plan mode, I think, but I don’t think it’s necessary because you just- you just talk to the agent. And when it’s… when you… Peter Steinberger (01:34:32): there’s a few trigger words how you can prevent it from building. You’re like, “Discuss, give me options.” Lex Fridman (01:34:37): Mm-hmm. Peter Steinberger (01:34:38): Don’t write code yet if you wanna be very specific, you just talk and then when you’re ready, then- then just write, “Okay, build,” and then it’ll do the thing. And then maybe it goes off for 20 minutes and does the thing. Lex Fridman (01:34:50): You know what I really like is asking it, “Do you have any questions for me?” Peter Steinberger (01:34:54): Yeah. And again, like, Claude Code has a UI that kind of guides you through that. It’s kind of cool but I just find it unnecessary and slow. Like, often it would give me four questions and then maybe I write, “One yacht, two and three, discuss more, four, I don’t know.” Or often- oftentimes I- I feel like I want to mock the model where I ask it, “Do you have any questions for me?” And I- I- I don’t even read the questions fully. Like, I scan over the questions and I, I get the impression all of this can be answered by reading more code and it’s just like, “Read more code to answer your own questions.” And that usually works. Lex Fridman (01:35:32): Yeah. Peter Steinberger (01:35:32): And then if not, it will come back and tell me. But many times, you just realize that, you know, it’s like you’re in the dark and you slowly discover the room, so that’s how they slowly discover the code base. And they do it from scratch every time. Lex Fridman (01:35:46): But I’m also fascinated by the fact that I can empathize deeper with the model when I read its questions, because I can understand… Because you said you can infer certain things by the runtime. I can infer also a lot of things by the questions it’s asking, because it’s very possible it’s been provided the right context, the right files, the right guidance. So somehow ask, g- get… reading the questions, not even necessarily answering them, but just reading the questions, you get an understanding of where the gaps of knowledge are. It’s in- it’s interesting. Peter Steinberger (01:36:24): You know that in some ways they are ghosts, so even if you plan everything and you build, you can- you can experiment with the question like, “Now that you built it, what would you have done different?” And then oftentimes you get, like, actually something where they discover only throughout building that, oh, what we actually did was not optimal. Many times I- I asked them, “Okay, now that you built it, what can we refactor?” Because then you build it and you feel the pain points. I mean, you don’t feel the pain points but, right, they discover where- where there were problems or where things didn’t work e- in the first try and it re- required more loops. Peter Steinberger (01:37:09): So every time, almost every time I- I merge a PR, build a feature, afterwards I ask, “Hey, what can we refactor?” Sometimes it’s like, “No, there’s, like, nothing big,” or, like, usually they say, “Yeah, this thing you should really look at.” But that took me quite a while to, like… You know, that flow took me lots of time to understand, and if you don’t do that, you eventually… you’ll stop yourself into- into a corner. You, like, you have to keep in mind… Lex Fridman (01:37:41): … Peter Steinberger (01:37:42): … they work very much like humans. Like, I, I, if I write software by myself, I also build something and then I feel the pain points, and then I, I get this urge that I need to refactor something. So, I can very much synthesize with the agent, and you just need to use the context. Lex Fridman (01:38:00): Mm-hmm. Peter Steinberger (01:38:00): Or, like, you also use the context to write tests. And so Codex uh, oppose like the, the, the model, models. They, they usually do that by default, but I still often ask the questions, “Hey, do we have enough tests?” “Yeah, we tested this and this, but this corner case could be something write more tests.” Um, documentation. Now that the whole context is full, like, I mean, I’m not saying my documentation is great, but it’s not bad. And pretty much everything is, is LM generated. So, so, you have to approach it as you build features, as you change something. I’m like, “Okay, write documentation. What file would you pick?” You know, like, “What file name? Where, where would that fit in?” And it gives me a few options. Peter Steinberger (01:38:48): And I’m like, “Oh, maybe also add it there,” and that’s all part of the session. Lex Fridman (01:38:52): Maybe you can talk about the current two big competitors in terms of models, Cloud Opus 4.6 and GPT-5 through Codex. Which is better? How different are they? I think you’ve spoken about Codex reading more and Opus being more willing to take action faster and maybe being more creative in the actions it takes. But because- Peter Steinberger (01:39:20): Yeah Lex Fridman (01:39:20): … Codex reads more, it’s able to deliver maybe better code. Can you speak to the di- n- n- differences there? Peter Steinberger (01:39:29): I have a lot of words there. Is- as a general purpose model, Opus is the best. Like, for OpenClaw, Opus is extremely good in terms of role play. Like, really going into the character that you give it. It’s very good at… It was really bad, but it really made an arch to be really good at following commands. It is usually quite fast at trying something. It’s much more tailored to, like, trial and error. It’s very pleasant to use. In general, it’s almost like Opus was… Is a little bit too American. And I shouldn’t… Maybe that’s a bad analogy. You’ll probably get roasted for that. Lex Fridman (01:40:27): Yeah, I know exactly. It’s ’cause Codex is German. Is that what you’re saying? Peter Steinberger (01:40:32): It’s- Lex Fridman (01:40:32): Actually, now that you say it, it makes perfect sense. Peter Steinberger (01:40:34): Or you could, you could… Sometimes I- Sometimes I explain it- Lex Fridman (01:40:38): I will never be able to unthink what you just said. That’s so true. Peter Steinberger (01:40:42): But you also know that a lot of the Codex team is, like, European, um- … so maybe there’s a bit more to it. Lex Fridman (01:40:49): That’s so true. Oh, that’s funny. Peter Steinberger (01:40:51): But also, ent- entropic, they fixed it a little bit. Like, Opus used to say, “You’re absolutely right all the time,” and it, it, it today still triggers me. I can’t hear it anymore. It’s not even a joke. Uh, I just… You, this was like the, the meme, right? “You’re absolutely right.” Lex Fridman (01:41:09): You’re allergic to sycophancy a little bit. Peter Steinberger (01:41:11): Yeah. I, I can’t. Some other comparison is like, Opus is like the coworker that is a little silly sometimes, but it’s really funny and you keep him around. And Codex is like the, the weirdo in the corner that you don’t wanna talk to, but is reliable and gets shit done. Lex Fridman (01:41:30): Yeah. Peter Steinberger (01:41:32): Ultimately- Lex Fridman (01:41:36): This all feels very accurate. Peter Steinberger (01:41:39): I mean, ultimately, if you’re a skilled driver, you can get good results with any of those latest gen models. Um, I like Codex more because it doesn’t require so much charade. It will just, it will just read a lot of code by default. Opus, you really have to, like, you have to have plan mode. You have to push it harder to, like, go in these directions because it’s, it’s just like, like, “Yeah, can I go in? Can I go in?” You know? Lex Fridman (01:42:08): Yeah. Peter Steinberger (01:42:08): It’s like, it will just run off very fast, and that’s a very localized solution. I think it, I think the difference is, is in the post-training. It’s not like the, the raw model intelligence is so different, but it’s just… I think that they just give it, give you different, different goals. And no model, no model is better in, in in every aspect. Lex Fridman (01:42:29): What about the code that it generates? The, the… In terms of the actual quality of the code, is it basically the same? Peter Steinberger (01:42:36): If you drive it right, Opus even sometimes can make more elegant solutions, but it requires more skill. It’s, it’s harder to have so many sessions in parallel with Cloud Code because it’s, it’s more interactive. And I, I think that’s what a lot of people like, especially if they come from coding themselves. Whereas Codex is much more you have a discussion, and then we’ll just disappear for 20 minutes. Like, even AMP, they, they now added a deep mode. They finally… I mocked them, you know. We finally saw the light. And then they had this whole talk about you have to approach it differently, and I think that’s where, that’s where people struggle when they just try Codex after trying Cloud Code is that it’s, it’s a slightly diff- it’s, it’s less interactive. Peter Steinberger (01:43:28): It’s, it’s like I have quite long discussions sometimes, and then, like, go off. And then, yeah, it doesn’t matter if it takes 10, 20, 30, 40, 50 minutes or longer, you know? Like, the 6:00 thing was, like, six hours.The latest trend can be very, very persistent until it works. If there’s a clear solution, like, “This is, this is what I want at the end, so it works,” the model will work really hard to really get there. So I think ultimately … they both need similar time, but on, on, on, on Claude, it- it’s a little bit more trial and error often. And, and Codex sometimes overthinks. I prefer that. I prefer the dry, the dry version where I have to read less over, over the more interactive nice way. Peter Steinberger (01:44:27): Like, people like that so much though, that OpenAI even added a second mode with like a more pleasant personality. I haven’t even tried it yet. I, I kinda like the brad. Lex Fridman (01:44:37): Mm-hmm. Peter Steinberger (01:44:38): Yeah, ’cause it … I care about efficiency when I build it- Lex Fridman (01:44:45): Right Peter Steinberger (01:44:45): … and I, I have fun in the very act of building. I don’t need to have fun with my agent who builds. I have fun with my model that … where I can then test those features. Lex Fridman (01:44:57): How long does it take for you to adjust, you know, if you switch … I don’t know when, when was the last time you switched. But to adjust to the, the feel. ‘Cause you kinda talked about like you have to kinda really feel where, where a model is strong, where, like how to navigate, how to prompt it, how … all that kinda stuff. Like, just by way of advice, ’cause you’ve been through this journey of just playing with models. How long does it take to get a feel? Peter Steinberger (01:45:26): If, if someone switches, I would give it a week until you actually develop a gut feeling for it. Lex Fridman (01:45:32): Yeah. Peter Steinberger (01:45:33): That’s … if you just … I think some people also make the mistake of they pay 200 for the, the Claude code version, then they pay 20 bucks for the OpenAI version. But if you pay like the, the 20 bucks version, you get the slow version. So your experience would be terrible because you’re used to this very interactive, very good system. And you switch to something that you have very little experience, then that’s gonna be very slow. So, I think OpenAI shot themselves a little bit in the foot by making the, the cheap version also slow. I would, I would have at least a small part of the fast preview. Or like, the experience that you get when you pay 200 before degrading to it being slow, because it’s already slow. Lex Fridman (01:46:23): Mm-hmm. Peter Steinberger (01:46:23): I mean, they, they made it better. I think it’s … And, and they have plans to make it a lot better if the Cerebras stuff is true. But yeah, it’s a skill. It takes time. Even if you play … You have a regular guitar and you switch it to an E guitar, you’re not gonna play well right away. You have to, like, learn how it feels. Lex Fridman (01:46:42): The- there’s also this extra psychological effect that you’ve spoken about which is hilarious to watch. Which once people, uh … When the new model comes out, they try that model, they fall in love with it. “Wow, this is the smartest thing of all time,” and then they start saying, “You could just watch the Reddit posts over time,” start saying that, “We believe the intelligence of this model has been gradually degrading.” It, it says something about human nature and just the way our minds work, when it’s probably most likely the case that the intelligence of the model is not degrading. It’s in fact you’re getting used to a good thing. Peter Steinberger (01:47:22): And your project grows, and you’re adding slop, and you probably don’t spend enough time to think about refactors. And you’re making it harder and harder for the agent to work on your slop. And then, and then suddenly, “Oh, now it’s hard. Oh no, it’s not working as well anymore.” What’s the motivation for, like, one of those AI companies to actually make their model dumber? Like, at most, it will make it slower if, if the server load’s too high. But, like, quantizing the model so you have a worse experience, so you go to the competitor? Lex Fridman (01:47:56): Yeah. Peter Steinberger (01:47:56): That just doesn’t seem like a very smart move in any way. Lex Fridman (01:47:59): What do you think about Claude Code in comparison to Open Claude? So, Claude Code and maybe the Codex coding agent? Do you see them as kind of competitors? Peter Steinberger (01:48:11): I mean, first of all, competitor is fun when it’s not really a competition. Lex Fridman (01:48:16): Yeah. Peter Steinberger (01:48:16): Like, I’m happy if … If, if all it did is, like, inspire people to build something new, cool. Um, I still use Codex for the building. I, I know a lot of people use Open Claude to, to build stuff. And I worked hard on it to make that work. And I do smaller stuff with it in terms of code. But, like, if I work hours and hours, I want a big screen, not WhatsApp, you know? So for me, a personal agent is much more about my life. Or like, like a coworker. Like, I give you, like, a GitHub URL. Like, “Hey, try out this CLI. Does it actually work? What can we learn?” Blah, blah, blah. But when I’m deep in, deep in the flow, I want to have multiple, multiple things and it being very, very visible what it, what it does. So it … I don’t see it as a competition. It’s, it’s different things. Lex Fridman (01:49:16): But do, do you think there’s a a future where the two kinda combine? Like, your personal agent is also your best developing co-programmer partner? Peter Steinberger (01:49:29): Yeah, totally. I think this is where the puck’s going, that this is gonna be more and more your operating system. Lex Fridman (01:49:37): The operating system. Peter Steinberger (01:49:37): And it already … It’s so funny. Like I, I added support for sub-agents and also for …… um, TTI support, so it could actually run Cloud Coder Codecs. Lex Fridman (01:49:52): Mm-hmm. Peter Steinberger (01:49:53): And because mine’s a little bit bossy, it, it, it started it and it, it, it told him, like, “Who’s the boss,” basically. And it was like, “Ah, Codex is obeying me.” Lex Fridman (01:50:05): Oh, this is a power struggle. Peter Steinberger (01:50:06): And also the current interface is probably not the final form. Like, if you think more globally, we are, we copied Google for agents. You have, like, a prompt, and, and then you have a chat interface. That, to me, very much feels like when we first created television and then people recorded radio shows on television and you saw that on TV. Lex Fridman (01:50:39): Mm-hmm. Peter Steinberger (01:50:39): I think there is, there’s n- there’s better ways how we eventually will communicate with models, and we are still very early in this, how will it even work phase. So, it will eventually converge and we will also figure out whole different ways how to work with those things. Lex Fridman (01:51:05): One of the other components of workflow is operating system. So I told you offline that for the first time in my life, I’m expanding my sort of realm of exploration to the to the Apple ecosystem, to Macs, iPhone and so on. For most of my life I’ve been a Linux, Windows and WSL1, WSL2 person, which I think are all wonderful, but I… expanding to also trying Mac. Because it’s another way of building and it’s also a way of building that a large part of the community currently that’s utilizing LMS and agents is using, so. And that’s the reason I’m expanding to it. But is there something to be said about the different operating systems here? We should say that OpenClaw supported across operating systems. Peter Steinberger (01:51:56): Yeah. Lex Fridman (01:51:57): I saw WSL2 recommended, side windows for certain o- operations, but then Windows, Linux macOS are obviously supported. Peter Steinberger (01:52:07): Yeah, it should even work natively in Windows. I just didn’t have enough time to properly test it. And you know, like, the last 90% of software always easier than the first 90%, so I’m sure there’s some dragons left that will eventually nail out. My road was, for a long time, Windows, just because I grew up with that, then I switched and had a long phase with Linux, built my own kernels and everything, and then I went to university and I, I had my, my hacky Linux thing, and saw this white MacBook, and I just thought this is a thing of beauty, the white plastic one. And then I converted to Mac ’cause mostly w- I was, I was sick that audio wouldn’t work on Skype and all the other issues that, that Linux had for a long time. Peter Steinberger (01:53:01): And then I just stuck with it and then I dug into iOS, which required macOS anyhow, so it was never a question. I think Apple lost a little bit of its lead in terms of native. It used to be… Native apps used to be so much better, and especially in the Mac, there’s more people that build software with love. On, on Windows, it, it… Windows has much more and, like, function wise, there’s just more, period. But a lot of it felt more functional and less done with love. Um, I mean, Mac always, like, attracted more designers and people I felt… Peter Steinberger (01:53:50): Even though, like, often it has less features, it, it had more delight- Lex Fridman (01:53:54): Mm-hmm Peter Steinberger (01:53:55): … And playfulness. So I always valued that. But in the last few years, many times I actually prefer… Oh God, people are gonna roast me for that, but I prefer Electron apps because they work and native apps often, especially if it’s, like, a web service is a native app, are lacking features. I mean, not saying it couldn’t be done, it’s more like a, a focus thing that, like, for many, many companies, native was not that big of a priority. But if they build an Electron app, it, it’s the only app, so it is a priority and there’s a lot more code sharing possible. And I, I build a lot of native Mac apps. I love it. I, I can, I can help myself. Like, I love crafting little Mac, Mac menu bar tools. Like I built one to, to monitor your Codex use. Peter Steinberger (01:54:58): I built one I call Trimmy, that’s specifically for agentic use. When you, when you select text that goes over multiple lines it would remove the new line so you could actually paste it to the terminal. That was, again like, this is annoying me and after the, the 20th time of it is annoying me, I just built it. There is a cool Mac app for OpenClaw that I don’t think many people discovered yet, also because it, it still needs some love. It feels a little bit too much like the Hummer car right now because I, I just experiment a lot with it. It, it likes to polish. Lex Fridman (01:55:32): So you still… I mean, you still love it. You still, you still love adding to the delight of that operating system. Peter Steinberger (01:55:37): Yeah, but then you realize… Like, I also built one, for example, for GitHub. And then the… If you use SwiftUI, like the latest and greatest at Apple, and took them forever to build something to show an image from the web. Now we have async, async image, but…… I added support for it and then some images would just not show up or, like, be very slow. And I had a discussion with Codex like, “Hey, why is there a bug?” And even Codex said like, “Yeah, there’s this ASIC image but it’s really more for experimenting and it should not be used in production.” But that’s Apple’s answer to, like, showing images from the web. This shouldn’t be so hard, you know. Lex Fridman (01:56:19): Yeah. Peter Steinberger (01:56:19): This is like… This is like insane. Like, how am I in, in, in 2026 and my agent tell me, “Don’t use the stuff Apple built because it’s, it’s… It’s… Yeah, it- it’s there but it’s not good.” And like this is now in the weeds. This is… To me this is like… They had so much head start and so much love, and they kind of just like blundered it and didn’t, didn’t evolve it as much as they should. Lex Fridman (01:56:50): But also, there’s just the practical reality. If you look at Silicon Valley, most of the developer world that’s kind of playing with LMS and Agentic AI, they’re all using Apple products. And then, at the same time, Apple is not really, like, leaning on that. Like they’re not… They’re not opening up and playing and working together and like, yes. Peter Steinberger (01:57:12): Isn’t, isn’t it funny how they completely blunder AI, and yet everybody’s buying Mac Minis? Lex Fridman (01:57:19): How… What… Does that even make sense? You’re, you’re, you’re quite possibly the world’s greatest Mac salesman of all time. Peter Steinberger (01:57:29): No, you don’t need a Mac Mini to install OpenClaw. You can install it on the web. There’s, there’s a concept called nodes, so you can like make your computer a node and it will do the same. There is something said for running it on separate hardware. That right now is useful. There is… There’s a big argument for the browser. You know, I, I built some Agentic browser use in there. And, I mean, it’s basically Playwright with a bunch of extras to make it easier for agents. Lex Fridman (01:58:06): Playwright is a library that controls the browser. Peter Steinberger (01:58:08): Yeah. Lex Fridman (01:58:08): It’s really nice, easy to use. Peter Steinberger (01:58:09): And our internet is slowly closing down. Like, there, there’s a whole movement to make it harder for agents to use. So if you do the same in a data center and websites detect that it’s an IP from a data center, the website might just block you or it make it really hard or put a lot of captures in the, in the way of the agent. I mean, agents are quite good at happily clicking, “I’m not a robot.” Lex Fridman (01:58:33): Yeah. Peter Steinberger (01:58:33): But having that on a residential IP makes a lot of things simpler. So there’s ways. Yeah. But it really does not need to be a Mac. It can… It can be any old hardware. I always say, like, maybe use the… Use the opportunity to get yourself a new MacBook or whatever computer you use and use the old one as your server instead of buying a standalone Mac Mini. But then there’s, again, there’s a lot of very cute things people build with Mac Minis that I like. Lex Fridman (01:59:08): Yeah. Peter Steinberger (01:59:08): And no, I don’t get commission from Apple. They didn’t really communicate much. Lex Fridman (01:59:16): It’s sad. It’s sad. Can you actually speak to what it takes to get started with OpenClaw? There’s… I mean, there’s a lot of people… What is it? Somebody tweeted at you, “Peter, make OpenClaw easy to set up for everyday people. 99.9% of people can’t access to OpenClaw and have their own lobster because of their technical difficulties in getting it set up. Make OpenClaw accessible to everyone, please.” And you replied, “Working on that.” From my perspective, it seems there- there’s a bunch of different options and it’s already quite straightforward, but I suppose that’s if you have some developer background. Peter Steinberger (01:59:50): I mean, right now you have to paste in one liner into the terminal. Lex Fridman (01:59:53): Right. Peter Steinberger (01:59:54): And there’s also an app. The app kind of does that for you, but there should be a Windows app. The app needs to be easier and more loved. The configuration should potentially be web-based or in the app. And I started working on that, but honestly right now I want to focus on security aspects. And, and once I’m confident that this is at a level that I can recommend my mom, then I’m going to make it simpler. Like I… Peter Steinberger (02:00:27): Right now- Lex Fridman (02:00:28): You want to make it harder so that it doesn’t scale as fast as it’s scaling. Peter Steinberger (02:00:32): Yeah, it would be nice if it wouldn’t… I mean, that’s, like, hard to say, right? But if the growth would be a little slower, that would be helpful because people are expecting inhuman things from a single human being. And yes, I have some contributors, but also that whole machinery I started a week ago so that needs more time to figure out. And, and not everyone has all day to work on that. Lex Fridman (02:01:00): There’s some beginners listening to this, programming beginners. What advice would you give to them about, let’s say, joining the Agentic AI revolution? Peter Steinberger (02:01:12): Play. Playing is the best… The best way to learn. If you wanna… I’m sure if you… If you are like a little bit of builder, you have an idea in your head that you want to build, just build that, or like, give it a try. It doesn’t need to be perfect. I built a whole bunch of stuff that I don’t use. It doesn’t matter. Like, it’s the journey. Lex Fridman (02:01:31): Mm-hmm. Peter Steinberger (02:01:31): You know? Like the philosophical way, that the end doesn’t matter, the journey matters. Have fun. Lex Fridman (02:01:37): Mm-hmm. Peter Steinberger (02:01:37): My God, like those things… I… I don’t think I ever had so much fun building things because I can focus on the hard parts now. A lot of coding, I always thought I liked coding, but really I like building. Lex Fridman (02:01:50): Yeah. Peter Steinberger (02:01:50): And… And whenever you don’t understand something, just ask. You have an infinitely patient answering machine…. that y- can explain you anything at any level of complexity. Sometimes, that’s like one time I asked, “Hey explain to me like I’m- I’m eight years old,” and it started giving me a story with crayons and stuff. And I’m like, “No, not like that.” Like, I’m okay- … up- up the age a little bit, you know? I’m like, I’m not an actual child, it’s just, I just need a simpler language for like a- a- a- a- a tricky database concept that I didn’t grok in the first- first time. But, you know, just, you can just ask things. Like, you- there’s like… It used to be that I had to go on Stack Overflow or ha- ask on Twitter, and then maybe two days later I get a response. Peter Steinberger (02:02:37): Or I had to try for hours. And now you- you can just ask stuff. It- I mean, it’s never… You have, like, your own teacher. You know that there’s like statistics, y- you can learn faster if you have your own teacher. The- it’s like you have this infinitely patient machine. Ask it. Lex Fridman (02:02:53): But what would you say? So use… What’s the easiest way to play? So maybe Open Claw is a nice way to play so you can then set- set everything up and then you could chat with it. Peter Steinberger (02:03:03): You can also just experiment with it and, like, modify it. Ask your agent. I mean, there is infinite ways how it can be made better. Play around, make it better. Lex Fridman (02:03:18): Mm-hmm. Peter Steinberger (02:03:19): More general, if you- if you’re a beginner and you actually wanna learn how to build software really fast, get involved in open source. Doesn’t need to be my project. In fact, maybe don’t use my project because my- my backlog is very large, but I learned so much from open source. Just like, like, be- be humble. Don’t- maybe don’t send a pull request right away. But there’s many other ways you can help out. There’s many ways you can just learn by just reading code. By- by being on Discord or wherever people are, and just, like, understanding how things are built. I don’t know, like Mitchell Hashimoto builds Ghostly, the terminal, and he has a really good community where there’s so many other projects. Like, pick something that you find interesting and get involved. Lex Fridman (02:04:15): Do you recommend that people that don’t know how to program or don’t really know how to program learn to program also? So when you you can get quite far right now by just using natural language, right? Do you s- still see a lot of value in reading the code, understanding the code, and then being able to write a little bit of code from scratch? Peter Steinberger (02:04:38): It definitely helps. Lex Fridman (02:04:39): It’s hard for you to answer that- Peter Steinberger (02:04:41): Yeah Lex Fridman (02:04:42): … because you don’t know what it’s like to do any of this without knowing the base knowledge. Like, you might take for granted just how much intuition you have about the programming world having programmed so much, right? Peter Steinberger (02:04:54): There’s people that are high agency and very curious, and they get very far even though they have no deep understanding how software works just because they ask questions and questions and- and- and- Lex Fridman (02:05:08): Mm-hmm Peter Steinberger (02:05:08): … and agents are infinitely patient. Like, part of what I did this year is I went to a lot of iOS conferences because that’s my background and just told people, “Don’t consi- don’t see yourself as an iOS engineer anymore.” Like, “You need to change your mindset. You’re a builder.” And you can take a lot of the knowledge how to build software into new domains and all of the- the more fine-grain details, agents can help. You don’t have to know how to splice an array or what the- what the correct template syntax is or whatever, but you can use all your- your general knowledge and that makes it much easier to move from one galaxy, one tech galaxy into another. And oftentimes, there’s languages that make more or less sense depending on what you build, right? Peter Steinberger (02:05:58): So for example, when I build simple CLIs, I like Go. I actually don’t like Go. I don’t like the syntax of Go. I didn’t even consider the language. But the ecosystem is great, it works great with agents. It is garbage collected. It’s not the highest performing one, but it’s very fast. And for those type of- of CLIs that I build, Go is- is a really good choice. So I- I use a language I’m not even a fan of for… That’s my main to-go thing for- for CLIs. Lex Fridman (02:06:29): Isn’t that fascinating that here’s a programming language you would’ve never used if you had to write it from scratch and now you’re using because LMs are good at generating it and it has some of the characteristics that makes it resilient, like garbage collected? Peter Steinberger (02:06:44): Because everything’s weird in this new world and that just makes the most sense. Lex Fridman (02:06:48): What’s the best Ridiculous question. What’s the best programming language for the AI- AI agentic world? Is it JavaScript, TypeScript? Peter Steinberger (02:06:54): TypeScript is really good. Sometimes the types can get really confusing and the ecosystem is- is a jungle. So for- for web stuff it’s good. I wouldn’t build everything in it. Lex Fridman (02:07:15): Don’t you think we’re moving there? Like, that everything will eventually be written- eventually is written in JavaScript and it- Peter Steinberger (02:07:22): The birth and death of JavaScript and we are living through it in real time. Lex Fridman (02:07:26): Like, what does programming look like in 20 years? Right? In 30 years? In 40 years? What do programs and apps look like? Peter Steinberger (02:07:32): You can even ask a question like, do we need a- a programming language that’s made for agents? Because all of those languages are made for humans. So how- what would that look like? Um, I think there’s a- there’s whole bunch of interesting questions that we’ll discover. And also how because everything is now world knowledge, how it in many ways, things will stagnate ’cause if you build something new and the agent has no idea that’s gonna be much harder to use than something that’s already there. Um…… of when I build Mac apps, I build them in, in Swift and SwiftUI, mm, partly because I like pain, partly because it… the, the deepest level of system integration, I can only get through there. Peter Steinberger (02:08:18): And you clearly feel a difference if you click on an electron app and it loads a web view in the menu. It’s just not the same. Sometimes I just also try new languages just to, like, get a feel for them. Lex Fridman (02:08:32): Like Zig? Peter Steinberger (02:08:33): Yeah. If it’s something that… where I care about performance a lot then it’s, it’s a really interesting language. And it… like agents got so much better over the last six months from not really good to totally valid choice. Just still a, a very young ecosystem. And most of the time you actually care about ecosystem, right? So, so if you build something that does inference or goes into whole running model direction, Python, very good. Lex Fridman (02:09:06): Mm-hmm. Peter Steinberger (02:09:07): But then if I build stuff in Python and I want a story where I can also deploy it on Windows, not a good choice. Lex Fridman (02:09:13): Mm-hmm. Peter Steinberger (02:09:13): Sometimes I, I found projects that kinda did 90% of what I wanted but were in Python, and I wanted them… I wanted an easy Windows story. Okay, just rewrite it in Go. But then if you go towards multiple, multiple threads and a lot more performance, Rust is a really good choice. There’s no… there’s just no single answer, and it’s also the beauty of it. Like, it’s fun. Peter Steinberger (02:09:37): And now it doesn’t matter anymore, you can just literally pick the language that has the, the most fitting characteristics and ecosystem- Lex Fridman (02:09:45): Mm-hmm Peter Steinberger (02:09:46): … for your problem domain. And yeah, it might be… You might have s-… You might be a little bit slow in reading the code, but not really. Y- I think you, you pick stuff up really fast, and you can always ask your agent. Lex Fridman (02:09:59): So there’s a lot of programmers and builders who draw inspiration from y- your story. Just the way you carry yourself, your choice of making OpenClaw open source, the, the way you have fun building and exploring, and doing that, for the most part, alone or on a small team. So by way of advice, what metric should be the goal that they would be optimizing for? What would be the metric of success? Would it be happiness? Is it money? Is it positive impact for people who are dreaming of building? ‘Cause you went through an interesting journey. You’ve achieved a lot of those things, and then you fell out of love with programming a little bit for a time. Peter Steinberger (02:10:47): I was just burning too bright for too long. I, I ran… I started PSPDFKit, s- and ran it for 13 years, and it was high stress. Um, I had to learn all these things fast and hard, like how to manage people, how to bring people on, how to deal with customers, how to do… Lex Fridman (02:11:14): So it wasn’t just programming stuff, it was people stuff. Peter Steinberger (02:11:17): The stuff that burned me out was mostly people stuff. I, I don’t think burnout is working too much. Maybe to a degree. Everybody’s different. You know, I c- I cannot speak in a- in absolute terms, but for me, it was much more differences with my, my co-founders, conflicts, or, like, really high stress situation with customers that eventually grinded me down. And then when… luckily we, we got a really good offer for, like, putting the company to the next level and I, I already kinda worked two years on making myself obsolete. So at this point I could leave, and, and then I just… I was sitting in front of the screen and I felt like, you know Austin Powers where they suck the mojo out? Lex Fridman (02:12:13): Yeah. Peter Steinberger (02:12:14): Uh, I g- I was like, m- m- it was, like, gone. Like, I couldn’t… I couldn’t get code out anymore. I was just, like, staring and feeling empty, and then I, I just stopped. I, I booked, like, a one-way trip to Madrid and, and, and just, like, spent a t- some t- sometime there. I felt like I had to catch up on life, so I did a whole, a whole bunch of life catching up stuff. Lex Fridman (02:12:47): Did you go through some lows during that period? And you know, maybe advice on… of how to? Peter Steinberger (02:12:56): Maybe advice on how to approach life. If you think that, “Oh yeah, work really hard and then I’ll retire,” I don’t recommend that. Because the idea of, “Oh yeah, I just enjoy life now,” a- maybe it’s appealing, but right now I enjoy life, the most I’ve ever enjoyed life. Because if you wake up in the morning and you have nothing to look forward to, you have no real challenge, that gets very boring, very fast. And then when, when you’re bored, you’re gonna look for other places how to stimulate yourself, and then maybe, maybe that’s drugs, you know? But that eventually also get boring and you look for more, and that will lead you down a very dark path. Lex Fridman (02:13:57): But you also showed on the money front, you know, a lot of people in Silicon Valley and the startup world, they think, maybe overthink way too much optimized for money. And you’ve also shown that it’s not like you’re saying no to money. I mean, I’m sure you take money, but it’s not…… the primary objective of uh, of your life. Can you just speak to that? Your philosophy on money? Peter Steinberger (02:14:20): When I built my company, money was never the driving force. It felt more like, like, an affirmation that I did something right. And having money solves a lot of problems. I also think there, there’s diminishing returns the more you have. Like, a cheeseburger is a cheeseburger, and I think if you go too far into, oh, I do private jet and I only travel luxury, you disconnect with society. Um, I, I donated quite a lot. Like, I have a, I have a foundation for helping people that weren’t so lucky. Lex Fridman (02:15:11): And disconnecting from society is bad in that on many levels, but one of them is, like, humans are awesome. It’s nice to continuously remember the awesomeness in humans. Peter Steinberger (02:15:23): I, I mean, I could afford really nice hotels. The last time I was in San Francisco, I did the, the first time the OG Airbnb experience- Lex Fridman (02:15:30): Yeah, yeah Peter Steinberger (02:15:30): … and just booked a room. Mostly because I, I thought, okay, you know, I’m out or I’m sleeping, and I don’t like where all the hotels are, and I wanted a, I wanted a different experience. I think, isn’t life all about experiences? Like, if you, if you tailor your life towards, “I wanna have experiences,” it, it reduces the need for, “It needs to be good or bad.” Like, if people only want good experiences, that’s not gonna work, but if you optimize for experiences, if it’s good, amazing. If it’s bad, amazing, because, like, I learned something, I saw something, did something. I wanted to experience that, and it was amazing. Like, there was, like, this, this queer DJ in there, and I showed her how to make music with cloud code. And we, like, immediately bonded and had a great time. Lex Fridman (02:16:24): Yeah, there’s something about that air- you know, couch surfing, Airbnb experience, the OG. I’m still to this day. It’s awesome. It’s humans, and that’s why travel is awesome. Peter Steinberger (02:16:34): Yeah. Lex Fridman (02:16:34): Just experience the variety of, the diversity of human. And when it’s shitty, it’s good too, man. If it rains and you’re soaked and it’s all fucked, and planes, the everything is shit, everything is fucked, it’s still awesome. If you’re able to open your eyes it’s good to be alive. Peter Steinberger (02:16:49): Yeah, and anything that creates emotion and feelings is good. Lex Fridman (02:16:55): . Peter Steinberger (02:16:55): Even… So, so maybe, maybe even the cryptic people are good because they definitely created emotions. I, I don’t know if I should go that far. Lex Fridman (02:17:02): No, man. Give them, give them all, give them love. Give them love. Because I do think that online lacks some of the awesomeness of real life. Peter Steinberger (02:17:13): Yeah. Lex Fridman (02:17:13): That’s, that’s, it’s an open problem of how to solve, how to infuse the online cyber experience with I don’t know with the intensity that we humans feel when it’s in real life. I don’t know. I don’t know if that’s a solvable problem. Peter Steinberger (02:17:31): Well, it’s just possible because text is very lossy. Lex Fridman (02:17:35): Yeah. Peter Steinberger (02:17:35): You know, sometimes I wish if I talked to the agent I would… It should be multi-model so it also understands my emotions. Lex Fridman (02:17:43): I mean, it, it might move there. It might move there. Peter Steinberger (02:17:46): It will. It will. It totally will. Lex Fridman (02:17:49): I mean, I have to ask you, just curious. I, I know you’ve probably gotten huge offers from major companies. Can you speak to who you’re considering working with? Peter Steinberger (02:18:04): Yeah. So, to like explain my thinking a little bit, right, I did not expect this blowing up so much. So, there’s a lot of doors that opened because of it. There’s, like, I think every VC, every big VC company is in my inbox and tried to get 15 minutes of me. So, there’s, like, this butterfly effect moment. I could just do nothing and continue and I really like my life. Valid choice. Almost. Like, I considered it when I delete it, wanted to delete the whole thing. I could create a company. Been there, done that. There’s so many people that push me towards that and, yeah, like, could be amazing. Lex Fridman (02:19:07): Which is to say that you, you would probably raise a lot of money in that. Peter Steinberger (02:19:10): Yeah. Lex Fridman (02:19:11): I don’t know, hundreds of millions, billions. I don’t know. It could just got unlimited amount of money. Peter Steinberger (02:19:15): Yeah. It just doesn’t excite me as much because I feel I did all of that, and it would take a lot of time away from the things I actually enjoy. Same as when, when I was CEO, I think I, I learned to do it and I’m not bad at it, and partly I’m good at it. But yeah, that path doesn’t excite me too much, and I also fear it, it would create a natural conflict of interest. Like, what’s the most obvious thing I do? I, I prioritize it. I put, like, a version safe for workplace. And then what do you do? Like, I get a pull request with a feature like an audit log, but that seems like an enterprise feature, so now I feel I have a conflict of interest in the open-source version and the closed-source version…. Peter Steinberger (02:20:15): or change the license to something like FSL, where you cannot actually use it for commercial stuff, would first be very difficult with all the contributions. And second of all, I- I like the idea that it’s free as in beer and not free with conditions. Yeah, there’s ways how you, how you keep all of that for free and just, like, still try to make money, but those are very difficult. And you see there’s, like, fewer and fewer companies manage that. Like, even Tailwind, they’re, like, used by everyone. Everyone uses Tailwind, right? And then they had to cut off 75% of the employees because they’re not making money because nobody’s even going on the website anymore because it’s all done by agents. S- and just relying on donations, yeah, good luck. Peter Steinberger (02:21:04): Like, if a project of my caliber, if I extrapolate what the typical open-source project would get it’s not a lot. I s- I still lose money on the project because I made the point of supporting every dependency, except Slack. They are a big company. They can, they can, they can do without me. But all the projects that are done by mostly individuals so, like, all the, right now, all the sponsorship goes right up to my dependencies. And if there’s more, I want to, like, buy my contributors some merch, you know? Lex Fridman (02:21:43): So you’re losing money? Peter Steinberger (02:21:44): Yeah, right now I lose money on this. Lex Fridman (02:21:46): So it’s really not sustainable? Peter Steinberger (02:21:48): Uh, I mean, it’s like, I guess something between 10 and 20K a month. Which is fine. I’m sure over time I could get that down. Um, OpenAI is helping out a little bit with tokens now. And there’s other companies that have been generous. But yeah, still losing money on that. So that’s- that’s one path I consider, but I’m just not very excited. And then there’s all the big labs that I’ve been talking to. And from those Meta and OpenAI seem the most interesting. Lex Fridman (02:22:32): Do you lean one way or the other? Peter Steinberger (02:22:34): Yeah. Um… Not sure how much I should share there. It’s not quite finalized yet. Let’s- let’s just say, like, on either of these, my conditions are that the project stays open source. That it… Maybe it’s gonna be a model like Chrome and Chromium. Um, I think this is- this is too important to just give to a company and make it theirs. It… This is… And we didn’t even talk about the whole community part, but, like, the- the thing that I experienced in San Francisco, like at ClawCon, seeing so many people so inspired, like… And having fun and just, like, building shit, and, like, having, like, robots in lobster stuff walking around. Like, the… Peter Steinberger (02:23:37): People told me, like, they didn’t experience this level of- of community excitement since, like, the early days of the internet, like 10, 15 years. And there were a lot of high caliber people there, like… Um, I was amazed. I also, like, was very sensory overloaded because too many people wanted to do selfies. But I love this. Like, this needs to stay a place where people can, like, hack and learn. But also, I’m very excited to, like, make this into a version that I can get to a lot of people because I think this is the year of personal agents, and that’s the future. And the fastest way to do that is teaming up with one of the labs. And I also, on a personal level, I never worked at a large company, and I’m intrigued. You know, we talk about experiences. Will I like it? I don’t know. Peter Steinberger (02:24:42): But I want that experience. Uh, I- I’m sure, like, if- if I- if I announce this, then there will be people like, “Oh, he sold out,” blah, blah, blah. But the project will continue. From everything I talked to so far, I can even have more resources for that. Like, both s- both of those companies understand the value that I created something that accelerates our timeline and that got people excited about AI. I mean, can you imagine? Like, I installed OpenClaw on one of my, I’m sorry, normie friends. I’m sorry, Vahan. But he’s just a… You know? Peter Steinberger (02:25:32): Like, he’s- Lex Fridman (02:25:33): Normie with love, yeah. For sure. Peter Steinberger (02:25:34): He- he, like, someone who uses the computer, but never really… Like, yeah, use some ChatGPT sometimes, but not very technical. Wouldn’t really understand what I built. So, like, I’ll show you, and I- I paid for him the- the 90 buck, 100 buck, I don’t know, subscription for Entropic. And set up everything for him with, like, WSL Windows. Lex Fridman (02:26:00): Mm-hmm. Peter Steinberger (02:26:00): I was also curious, would it actually work on Windows, you know? Was a little early. And then within a few days, he was hooked. Like, he texted me about all the things he learned. He built, like, even little tools. He’s not a programmer. And then within a few days he upgraded to the $200 subscription. Or euros, because he’s in Austria…. and he was in love with that thing. That, for me, was like a very early product validation. It’s like, I built something that captures people. And then, a few days later, Entropic blocked him because, based on their rules using the subscription is problematic or whatever. And he was, like, devastated. And then he signed up for Mini Max for 10 bucks a month and uses that. Peter Steinberger (02:26:56): And I think that’s silly in many ways, because you just got a 200 buck customer. You just made someone hate your company, and we are still so early. Like, we don’t even know what the final form is. Is it gonna be cloud code? Probably not, you know? Like, that seems very… It seems very short-sighted to lock down your product so much. All the other companies have been helpful. I- I’m in Slack of, of most of the big labs. Kind of everybody understands that we are still in an era of exploration, in the area of the radio shows on TV and not, and not a modern TV show that fully uses the format. Lex Fridman (02:27:45): I think, I think you’ve made a lot of people, like, see the possibility. And non- Uh, sorry. Non, non-technical people see the possibility of AI, and just fall in love with this idea, and enjoy interacting with AI. And that’s a bea- That’s a really beautiful thing. I think I also speak for a lot of people in saying, I think you’re one of the, the great people in AI in terms of having a good heart, good vibes, humor, the right spirit. And so it would, in a sense, this model that you’re describing, having open source part, and you being part of uh, also building a thing inside, additionally, of a large company would be great, because it’s great to have good people in those companies. Peter Steinberger (02:28:36): Yeah. You know, what also people don’t really see is… I made this in three months. I did other things as well. You know, I have a lot of projects. Like, this is not… Yeah, in January, this was my main focus because I saw the storm coming. But before that, I built a whole bunch of other things. Um, I have so many ideas. Some should be there, some would be much better fitted when I have access to the latest toys- Uh, and I, I kind of want to have access to, like, the latest toys. So this is important, this is cool, this will continue to exist. My, my short-term focus is, like, working through those… Is it two- Is it 3,000 PRs now by now? I don’t even know. Like, there’s, there’s a little bit of backlog. Peter Steinberger (02:29:23): But this is not gonna be the thing that I’m gonna work until I’m, I’m, I’m 80, you know? This is… This is a window into the future. I’m gonna make this into a cool product. But yeah, I have like… I have more ideas. Lex Fridman (02:29:36): If you had to pick, is there a company you lean? So Meta, OpenAI, is there one you lean towards going? Peter Steinberger (02:29:44): I spend time with both of those. And it’s funny, because a few weeks ago, I didn’t consider any of this. Um… And it’s really fucking hard. Like- Lex Fridman (02:30:05): Yeah. Peter Steinberger (02:30:06): I have some… I know no people at OpenAI. I love their tech. I think I’m the biggest codex advertisement shill that’s unpaid. And it would feel so gratifying to, like, put a price on all the work I did for free. And I would love if something happens and those companies get just merged, because it’s like… Lex Fridman (02:30:32): Is this the hardest decision you’ve ever had to do? Peter Steinberger (02:30:39): No. You know, I had some breakups in the past that feel like it’s the same level. Lex Fridman (02:30:43): Relationships, you mean? Peter Steinberger (02:30:45): Yeah. Lex Fridman (02:30:47): Yeah, yeah, yeah, yeah. Peter Steinberger (02:30:48): And, and I also know that, in the end, they’re both amazing. I cannot go wrong. This is like- Lex Fridman (02:30:53): Right. Peter Steinberger (02:30:54): This is, like, one of the most prestigious and, and, and, and, and largest… I mean, not largest, but, like, they’re both very cool companies. Lex Fridman (02:31:02): Yeah, they both really know scale. So, if you’re thinking about impact, some of the wonderful technologies you’ve been exploring, how to do it securely, and how to do it at scale, such that you can have a positive impact on a large number of people. They both understand that. Peter Steinberger (02:31:19): You know, both Ned and Mark basically played all week with my product, and sent me like, “Oh, this is great.” Or, “This is shit. Oh, I need to change this.” Or, like, funny little anecdotes. And people using your stuff is kind of like the biggest compliment, and also shows me that, you know, they actually… T- they actually care about it. And I didn’t get the same on the OpenAI side. Um, I got… I got to see some other stuff that I find really cool, and they lure me with… I cannot tell you the exact number because of NDA, but you can, you can be creative and, and think of the Cerebras deal and how that would translate into speed. And it was very intriguing. You know, like, you give me Thor’s hammer. Yeah. … been lured with tokens. So, yeah. Lex Fridman (02:32:34): So, it- it’s funny. So, so Marc started tinkering with the thing, essentially having fun with the thing. Peter Steinberger (02:32:41): He got… He… Like, when he first… When he first approached me, I got him in my, in my WhatsApp and he was asking, “Hey, when are we have a call?” And I’m like, “I don’t like calendar entries. Let’s just call now.” And he was like, “Yeah, give me 10 minutes, I need to finish coding.” Lex Fridman (02:33:01): Mm-hmm. Peter Steinberger (02:33:01): Well, I guess that gives you street cred. It’s like, ugh, like, he’s still writing code. You know, he’s- Lex Fridman (02:33:07): Yeah, he does Peter Steinberger (02:33:07): … he didn’t drift away in just being a manager, he gets me. That was a good first start. And then I think we had a, like, a 10-minute fight what’s better, cloud code or Codex. Like, that’s the thing you first do, like, you casually call- Lex Fridman (02:33:24): Yeah, that’s awesome Peter Steinberger (02:33:24): … someone with, like, the- that owns one of the largest companies in the world and, and you have a 10 minutes conversation about that. Lex Fridman (02:33:30): Yeah, yeah. Peter Steinberger (02:33:30): And then I think afterwards he called me eccentric but brilliant. But I also had some… I had some really, really cool discussion with Sam Altman and he’s, he’s very thoughtful brilliant and I like him a lot from the, from the little time I had, yeah. I mean, I know it’s peop- some people vilify both of those people. I don’t think it’s fair. Lex Fridman (02:34:15): I think no matter what the stuff you’re building and the kind of human you are doing stuff at scale is kinda awesome. I’m excited. Peter Steinberger (02:34:24): I am super pumped. And you know the beauty is if, if it doesn’t work out, I can just do my own thing again. Like, I, I told them, like, I, I don’t do this for the money, I don’t give a fuck. I- Lex Fridman (02:34:42): Yeah. Peter Steinberger (02:34:42): I mean, of course, of course it’s a nice compliment but I wanna have fun and have impact, and that’s ultimately what made my decision. Lex Fridman (02:34:58): Can I ask you about… we’ve talked about it quite a bit, but maybe just zooming out about how OpenCloud works. We talked about different components, I want to ask if there’s some interesting stuff we missed. So, there’s the gateway, there’s the chat clients, there’s the harness there’s the agentic loop. You said somewhere that everybody should im- implement an agent loop at some point in their lives. Peter Steinberger (02:35:24): Yeah, because it’s like the, it’s like the Hello World in AI, you know? And it’s actually quite simple. Lex Fridman (02:35:30): Yeah. Peter Steinberger (02:35:30): And it- it’s good to understand that that stuff’s not magic. You can, you can easily build it yourself. So, writing your own little cloud code… I, I even did this at a conference in Paris for people to, like, introduce them to AI. I think it’s it’s a fun little practice. And you, you covered a lot. I think one, one silly idea I had that turned out to be quite cool is I built this thing with full system access. So it’s like, you know, with great power comes great responsibility. Peter Steinberger (02:36:09): And I was like, “How can I up the stakes a little bit more?” Lex Fridman (02:36:13): Yeah, right. Peter Steinberger (02:36:14): And I just made a… I made it proactive. So, I added a prompt. Initially, it was just a prompt, surprise me. Every, like, half an hour, surprise me, you know? And later on I changed it to be like a little more specific and- Lex Fridman (02:36:31): Yeah Peter Steinberger (02:36:31): … in the definition of surprise. But the fact that I made it proactive and that it knows you and that it cares about you, it- it’s at least it’s programmed to that, prompted to do that. And that, that is a follow on, on your current session makes it very interesting because it would just sometimes ask a follow-up question or like, “How’s your day?” Lex Fridman (02:36:53): Yeah, right. Peter Steinberger (02:36:53): And I just made a… I made it proactive. So, I added a prompt. Initially, it was just a prompt, surprise me. Every, like, half an hour, surprise me, you know? And later on I changed it to be like a little more specific and- Lex Fridman (02:36:58): Yeah Peter Steinberger (02:36:58): … in the definition of surprise. But the fact that I made it proactive and that it knows you and that it cares about you, it- it’s… at least it’s programmed to that, prompted to do that. And that, that is a follow on, on your current session makes it very interesting because it would just sometimes ask a follow-up question or like, “How’s your day?” I mean, again, it’s a little creepy or weird or interesting but Heartbeat very… in the beginning, it’s still… today, it doesn’t… the model doesn’t choose to use it a lot. Lex Fridman (02:37:16): By the way, we’re, we’re, we’re talking about Heartbeat, as you mentioned, the thing that regularly- Peter Steinberger (02:37:22): Yeah. Like kicks- Lex Fridman (02:37:23): … Acts. Peter Steinberger (02:37:23): You just kick off the loop. Lex Fridman (02:37:25): Isn’t that just a cron job, man? Peter Steinberger (02:37:27): Yeah, right, I mean, it’s like- Lex Fridman (02:37:29): It’s the cr- the criticisms that you get are hilarious. Peter Steinberger (02:37:31): You can, you can deduce any idea to like a silly… Yeah, it’s just, it’s just a cron job in the end. I have like cron- separate cron jobs. Lex Fridman (02:37:41): Isn’t love just evolutionary biology manifesting itself and isn’t… aren’t you guys just using each other? Peter Steinberger (02:37:49): And then, yeah, and the project is all just glue of a few different dependencies- Lex Fridman (02:37:52): Yeah Peter Steinberger (02:37:53): … and there’s nothing original. Why do people… Well, you know, isn’t Dropbox just FTP with extra steps? Lex Fridman (02:38:00): Yeah. Peter Steinberger (02:38:01): I found it surprising where I had this I had a shoulder operation a few months ago, so. Lex Fridman (02:38:06): Mm-hmm. Peter Steinberger (02:38:08): And the model rarely used Heartbeat, but then I was in the hospital, and it knew that I had the operation and it checked up on me. It’s like, “Are you okay?” And I just… It’s like, again, apparently, like, if something’s significant in the context, that triggered the Heartbeat when it rarely used the Heartbeat…. And it does that sometimes for people, and that just makes it a lot more relatable. Lex Fridman (02:38:36): Let me look this up on Perplexity, how OpenCall works just to see if I’m missing any of the stuff. Local agent run time, high-level architecture. There’s… Oh, we haven’t talked much about skills, I suppose. Skill hub, the tools in the skill lair, but that’s definitely a huge component and there’s a huge growing set of skills- Peter Steinberger (02:38:55): You know, you know what I love? That half a year ago, like everyone was talking about MCPs- Lex Fridman (02:39:02): Yeah Peter Steinberger (02:39:02): … and I was like, “Screw MCPs. Every MCP would be better as a CLI.” And now this stuff doesn’t even have MCP support. I mean, it, it has with asterisks, but not in the core lair, and nobody’s complaining. Lex Fridman (02:39:23): Mm-hmm. Peter Steinberger (02:39:24): So my approach is if you want to extend the model with more features, you just build a CLI and the model can call the CLI, probably gets it wrong, calls the help menu, and then on demand loads into the context what it needs to use the CLI. It just needs a sentence to know that the CLI exists if it’s something that the model doesn’t know about default. And even for a while, I, I didn’t really care about skills, but skills are actually perfect for that because they, they boil down to a single sentence that explains the skill and then the model loads the skill, and that explains the CLI, and then the model uses the CLI. Some skills are, like raw, but most of the time, networks. Lex Fridman (02:40:16): It’s interesting um, I’m asking Perplexity MCP versus skills, because this kind of requires a hot take that’s quite recent, because your general view is MCPs are dead-ish. So MCPs is a more structured thing. So if you listen to Perplexity here, MCP is what can I reach? So APIs, database services files via protocol. So a structured protocol of how you communicate with a thing, and then skills is more how should I work? Procedures, hostile helper scripts and prompts are often written in a kind of semi-structured natural language, right? And so technically skills could replace MCP if you have a smart enough model. Peter Steinberger (02:41:00): I think the main beauty is, is that models are really good at calling Unix commands. So if you just add another CLI, that’s just another Unix command in the end. And MCP is… That has to be added in training. That’s not a very natural thing for the model. It requires a very specific syntax. And the biggest thing, it’s not composable. So imagine if I have a service that gives me better data and gives me the temperature, the average temperature, rain, wind and all the other stuff, and I get like this huge blob back. As a model, I always have to get the huge blob back. I have to fill my context with that huge blob and then pick what I want. There’s no way for the model to naturally filter unless I think about it proactively and add a filtering way into my MCP. Peter Steinberger (02:41:53): But if I would build the same as a CLI and it would give me this huge blob, it could just add a JQ command and filter itself and then only, only get me what I actually need. Or maybe even compose it into a script to, like do some calculations with the temperature and only give me the exact output and the mo- and the… you have no context pollution. Again, you can solve that with like sub-agents and more charades, but it’s just like workarounds for something that might not be the optimal way. There’s… It definitely it was, you know, it was good that we had MCPs because it pushed a lot of companies towards building APIs and now I, I can like look at an MCP and just make it into a CLI. Lex Fridman (02:42:37): Mm-hmm. Peter Steinberger (02:42:37): But this, this inherent problem that MCPs by default clutter up your context. Plus the fact that most MCPs are not made good, in general make it just not a very useful paradigm. There’s some exceptions like Playwright for example that requires state and it’s actually useful. That is an acceptable choice. Lex Fridman (02:43:05): So Playwright you use for browser use, which I think is c- already in OpenClaw is quite incredible, right? Peter Steinberger (02:43:11): Yeah. Lex Fridman (02:43:12): You can basically do everything, most things you can think of using browser use. Peter Steinberger (02:43:17): That, that gets into the whole arch of every app is just a very slow API now, if they want or not. And that through personal agents a lot of apps will disappear. You know, like I had a… I built a CLI for Twitter. I mean, I- I just reverse engineered their website and used the internal API, which is not very allowed. Lex Fridman (02:43:50): It’s called Bird, short-lived. Peter Steinberger (02:43:53): It was called Bird, because the bird had to disappear. Lex Fridman (02:43:57): The, the wings were clipped. Peter Steinberger (02:43:59): All they did is they just made access slower. Yeah, not tak- you’re not actually taking a feature away, but now inst- if, if your agent wants to read a tweet, it actually has to open the browser and read the tweet. And it will still be able to read the tweet. It will just take longer. It’s not like you are making something that was possible, not possible. No. Now, it’s just taking… Now it’s just a bit slower. So, so it doesn’t really matter if your service wants to be an API or not. If I can access it in the browser…… easy API. It’s a slow API. Lex Fridman (02:44:35): Can you empathize with their situation? Like, what would you do if you were Twitter, if you were X? Because they’re basically trying to protect against other large companies scraping all their data. Peter Steinberger (02:44:45): Yeah. Lex Fridman (02:44:46): But in so doing, they’re cutting off like a million different use cases for smaller developers that actually want to use it for helpful cool stuff. Peter Steinberger (02:44:54): I think that if you have a very low per day baseline per account that allows read-only access would solve a lot of problems. There’s plenty, plenty of automations where people create a bookmark and then use OpenClaw to, like, find the bookmark, do research on it, and then send you an email- Lex Fridman (02:45:16): Mm-hmm Peter Steinberger (02:45:16): … with, like, more details on it or a summary. That’s a cool approach. I also want all my bookmarks somewhere to search. I would still like to have that. Lex Fridman (02:45:26): So, read-only access for the bookmarks you make on X. That seems like an incredible application because a lot of us find a lot of cool stuff on X, we bookmark, that’s the general purpose of X. It’s like, holy shit, this is awesome. Oftentimes, you bookmark so many things you never look back at them. Peter Steinberger (02:45:40): Yeah. Lex Fridman (02:45:40): It would be nice to have tooling that organizes them and allows you to research it further. Peter Steinberger (02:45:44): Yeah, I mean, and to be frank, I, I mean, I, I told Twitter proactively that, “Hey, I built this and there’s a need.” And they’ve been really nice, but also like, “Take it down.” Fair. Totally fair. But I hope that this woke up the team a little bit that there’s a need. And if all you do is making it slower, you’re just reducing access to your platform. I’m sure there’s a better way. I also, I’m very much against any automation on Twitter. If you tweet at me with AI, I will block you. No first strike. As soon as it smells like AI, and AI still has a smell. Lex Fridman (02:46:31): Mm-hmm. Peter Steinberger (02:46:32): Especially on tweets. It’s very hard to tweet in a way that does look completely human. Lex Fridman (02:46:38): Mm-hmm. Peter Steinberger (02:46:38): And then I block. Like, I have a zero tolerance policy on that. And I think it would be very helpful if they, if, like, tweets done via API would be marked. Maybe there’s some special cases where… But, and there should be, there should be a very easy way for agents to get their own Twitter account. Um… Lex Fridman (02:47:04): Mm-hmm. Peter Steinberger (02:47:07): We, we need to rethink social platforms a little bit if, if, if we, we, we go towards a future where everyone has their agent and agents maybe have their own Instagram profiles or Twitter accounts, so I can, like, do stuff on my behalf. I think it should very clearly be marked that they are doing stuff on my behalf and it’s not me. Because content is now so cheap. Eyeballs are the expensive part. And I find it very triggering when I read something and then I’m like, oh, no, this smells like AI. Lex Fridman (02:47:41): Yeah. Like, where, where is this headed in terms of what we value about the human experience? It feels like we’ll, we’ll move more and more towards in-person interaction and we’ll just communicate. We’ll talk to our AI agent to, to accomplish different tasks, to learn about different things, but we won’t value online interaction because there’ll be so much AI slob that smells and so many bots that it’s difficult. Peter Steinberger (02:48:15): Well, if it’s smart, then it shouldn’t be difficult to filter. And then I can look at it if I want to. But yeah, this is, like, a big thing we need to solve right now. E- especially on this project, I get so many emails that are, let’s say nicely, agentically written. Lex Fridman (02:48:36): Yeah. Peter Steinberger (02:48:36): But I much rather read your broken English than your AI slob. You know, of course there’s a human behind it, and yet they, they prompt it. I’d much rather read your prompt than what came out. Um, I think we’re reaching a point where I value typos again. Lex Fridman (02:48:56): Yeah. Peter Steinberger (02:48:56): Like… Like, and I, I mean, it also took me a while to, like, come to the realization. I, on my blog I experimented with creating a blog post with agents and ultimately it took me about the same time to, like, steer agent towards something I like. But it missed the nuances that, how I would write it. You know, you can like, you can steer it towards your style, but it’s not gonna be all your style. So, I, I completely moved away from that. I, I, everything, everything I blog is organic, handwritten and maybe, maybe I, I, I use AI as a fix my worse typos. But there’s value in the rough parts of an actual human. Lex Fridman (02:49:53): Isn’t that awesome? Isn’t that beautiful? That now because of AI we value the raw humanity in each of us more. Peter Steinberger (02:50:02): I also, I also realized this thing that I, I rave about AI and use it so much for anything that’s code, but I’m allergic if it’s stories. Lex Fridman (02:50:12): Right. Yeah. Peter Steinberger (02:50:14): Also, documentation, still fine with AI. You know, better than nothing. Lex Fridman (02:50:17): And for now it’s still i- it applies in the mi- in the visual medium too. It’s fascinating how allergic I am to even a little bit of AI slob in in video and images. It’s useful, it’s nice if it’s like a little component of like- Peter Steinberger (02:50:32): Or even, even those images. The, like, all these infographics and stuff, the-… they trigger me so hard. Lex Fridman (02:50:38): Yeah. Peter Steinberger (02:50:39): Like, it immediately makes me think less of your content. And it … They were novel for, like, one week and now it just screams slop. Lex Fridman (02:50:50): Yeah. Peter Steinberger (02:50:51): Even- even if people work hard on it, using … And I- I have some on my blog post, you know, in the- in the time where I- I explored this new medium. But now, they trigger me as well. It’s like, yeah, this is … This just screams AI slop. I- Lex Fridman (02:51:06): What… I don’t know what that is, but I went through that too. I was really excited by the diagrams. And then I realized, in order to remove from them hallucinations, you actually have to do a huge amount of work. And you’re just using it to draw the better diagrams, great. And then I’m proud of the diagram. I’ve used them for literally, like, ki- ki- kind of like you said for maybe a couple of weeks. And now I look at those, and I- I feel like I feel when I look at Comic Sans as a font or- or something like this. Lex Fridman (02:51:32): It’s like, “No, this is-“ Peter Steinberger (02:51:35): It’s a smell. Lex Fridman (02:51:35): “… this is fake. It’s fraudulent. There’s something wrong with it.” And it… Peter Steinberger (02:51:41): It’s a smell. Lex Fridman (02:51:42): It’s a smell. Peter Steinberger (02:51:44): It’s a smell. Lex Fridman (02:51:44): And it’s awesome because it re- it reminds you that we know. There’s so much to humans that’s amazing and we know that. And we- we know it. We know it when we see it. And so that gives me a lot of hope, you know? That gives me a lot of hope about the human experience. It’s not going to be damaged by … It’s only going to be empowered as tools by AI. It’s not going to be damaged or limited or somehow altered to where it’s no longer human. So … Uh, I need a bathroom break. Quick pause. You mentioned that a lot of the apps might be basically made obsolete. Do you think agents will just transform the entire app market? Peter Steinberger (02:52:30): Yeah. Uh, I noticed that on Discord, that people just said how their … like, what they build and what they use it for. And it’s like, why do you need MyFitnessPal when the agent already knows where I am? So, it can assume that I make bad decisions when I’m at, I don’t know, Waffle House, what’s around here? Or- or briskets in Austin. Lex Fridman (02:52:57): There’s no bad decisions around briskets, but yeah. Peter Steinberger (02:53:00): No, that’s the best decision, honestly. Um- Lex Fridman (02:53:03): Your agent should know that. Peter Steinberger (02:53:04): But it can, like … It can modify my- my gym workout based on how well I slept, or if I’m … if I have stress or not. Like, it has so much more context to make even better decisions than any of this app even could do. Lex Fridman (02:53:18): Mm-hmm. Peter Steinberger (02:53:19): It could show me UI just as I like. Why do I still need an app to do that? Why do I have to … Why should I pay another subscription for something that the agent can just do now? And why do I need my- my Eight Sleep app to control my bed when I can tell the a- … tell the agent to … You know, the agent already knows where I am, so he can, like, turn off what I don’t use. Lex Fridman (02:53:45): Mm-hmm. Peter Steinberger (02:53:47): And I think that will … that will translate into a whole category of apps that are no longer … I will just naturally stop using because my agent can just do it better. Lex Fridman (02:54:00): I think you said somewhere that it might kill off 80% of apps. Peter Steinberger (02:54:04): Yeah. Lex Fridman (02:54:05): Don’t you think that’s a gigantic transformative effect on just all software development? So that means it might kill off a lot of software companies. Peter Steinberger (02:54:13): Yeah. Um- Lex Fridman (02:54:16): It’s a scary thing. So, like, do you think about the impact that has on the economy? On just the ripple effects it has to society? Transforming who builds what tooling. It empowers a lot of users to get stuff done, to get stuff more efficiently, to get it done cheaper. Peter Steinberger (02:54:41): It’s also new services that we will need, right? For example, I want my agent to have an allowance. Like, you solve problems for me, here’s like 100 bucks in order to solve problems for me. And if I tell you to order me food, maybe it uses a service. Maybe it uses something like rent-a-human to, like, just get that done for me. Lex Fridman (02:55:06): Mm-hmm. Peter Steinberger (02:55:06): I don’t actually care. I care about solve my problem. There’s space for- for new companies to solve that well. Maybe don’t … Not all apps disappear. Maybe some transform into being API. Lex Fridman (02:55:21): So, basically, apps that rapidly transform in being agent-facing. So, there’s a real opportunity for, like, Uber Eats, that we just used earlier today. It- it’s companies this, of which there’s many. Who gets there fastest to being able to interact with OpenClaw in a way that’s the m- the most natural, the easiest? Peter Steinberger (02:55:50): Yeah. And also, apps will become API if they want or not. Because my agent can figure out how to use my phone. I mean, on- on the other side, it’s a little more tricky. On Android, that’s already … People already do that. And then we’ll just click the Order Uber for Me button for me. Or maybe another service. Or maybe there’s- there’s a … there’s an API I can call so it’s faster. Uh, I think that’s a space we’re just beginning to even understand what that means. And I … Again, I didn’t even … That was not something I thought of. Something that I- that I discovered as people use this, and it … We are still so early. But yeah, I think data is very important. Like, apps that can give me data, but that also can be API. Why do I need a Sonos app anymore when I can … Peter Steinberger (02:56:44): when my agent can talk to the Sonos?… Speakers directly. Like my cameras, there’s like a crappy app, but they have, they have an API, so my agent uses the API now. Lex Fridman (02:56:57): So it’s gonna force a lot of companies to have to shift focus. That’s kind of what the internet did, right? You have to rapidly rethink, reconfigure what you’re selling, how you’re making money. Peter Steinberger (02:57:10): Yeah, and some companies were really not like that. For example, there’s no CLI for Google, so I had to like, do… have to do anything myself and build GAWK. That’s like a CLI for Google. And at the… Yeah, at the end user, they have to give me the emails because otherwise I cannot use their product. If I’m a company and I try to get Google data, Gmail, there’s a whole complicated process, to the point where sometimes startups acquire startups that went through the process, so they don’t- don’t have to work with Google for half a year to be certified to being able to access Gmail. But my agent can access Gmail because I can just connect to it. It’s still crappy because I need to, like, go through Google’s developer jungle to get a key, and that’s still annoying. Peter Steinberger (02:58:09): But they cannot prevent me. And worst case, my agent just clicks on the, on the website and gets the data out that way. Lex Fridman (02:58:17): Through browsers? Peter Steinberger (02:58:18): Yeah. I mean, I, I watch my agent happily click the I’m not a robot button. And there’s this, this whole… That’s gonna be… That’s gonna be more heated. You see companies like Cloudflare that try to prevent bot access. And in some ways, that’s useful for scraping. But in other ways, if I’m, I’m a personal user, I want that. You know, sometimes I, I use Codex and I, I read an article about modern React patterns, and it’s like a Medium article. I paste it in and the agent can’t read it because they block it. So then I have to copy-paste the actual text. Or in the future, I’ll learn that maybe I don’t click on Medium because it’s annoying, and I use other websites that actually are agent friendly. Peter Steinberger (02:59:12): So, uh- Lex Fridman (02:59:13): There’s gonna be a lot of powerful, rich companies fighting back. So it’s really intere- You’re at the center, you’re the catalyst, the leader, and happen to be at the center of this kind of revolution where it’s get- gonna completely change how we interact with services with, with web. And so, like, there’s companies at Google that are gonna push back. I mean, there’s every major companies you could think of is gonna push back. Peter Steinberger (02:59:39): Even… Yeah, even search. Um, I now use, I think Perplexity or Brave as providers because Google really doesn’t make it easy to use Google without Google. I’m not sure if that’s the right strategy, but I’m not Google. Lex Fridman (02:59:58): Yeah, there’s a, there’s a nice balance from a big company perspective ’cause if you push back too much for too long, you become Blockbuster and you lose everything to the Netflixes of the world. But some pushback is probably good during a revolution to see. Peter Steinberger (03:00:11): Yeah. But you see that, that… Like, this is something that the people want. Lex Fridman (03:00:14): Right. Peter Steinberger (03:00:14): So- Lex Fridman (03:00:15): Yes. Peter Steinberger (03:00:16): If I’m on the go, I don’t wanna open a calendar app. I just… I wanna tell my agent, “Hey, remind me about this dinner tomorrow night,” and maybe invite two of my friends and then maybe send a what- send a WhatsApp message to my friend. And I don’t need… I don’t want or need to open apps for that. I think that we passed that age, and now everything is, like, much more connected and, and fluid if those companies want it or not. And I think, well, the right companies will find ways to jump on the train, and other companies will perish. Lex Fridman (03:00:55): You got to listen to what the people want. We talked about programming quite a bit, and a lot of folks that are developers are really worried about their jobs, about their… About the future of programming. Do you think AI replaces programmers completely? Human programmers? Peter Steinberger (03:01:11): I mean, we’re definitely going in that direction. Programming is just a part of building products. So maybe, maybe AI does replace programmers eventually. But there’s so much more to that art. Like, what do you actually wanna build? How should it feel? How’s the architecture? I don’t think agents will replace all of that. Yeah, like, just the, the actual art of programming, it will, it will stay there, but it’s, it’s gonna be like knitting. You know? Like, people do that because they like it, not because it makes any sense. So the… I read this article this morning about someone that it’s okay to mourn our craft. And I can… Peter Steinberger (03:02:04): A part of me very strongly resonates with that because in my past I, I spent a lot of time tinkering, just being really deep in the flow and just, like, cranking out code and, like, finding really beautiful solutions. And yes, in a way it’s, it’s sad because that will go away. And I also get a lot of joy out of just writing code and being really deep in my thoughts and forgetting time and space and just being in this beautiful state of flow. But you can get the same state of flow… I get a similar state of flow by working with agents and building and thinking really hard about problems. It is different-… but… And it’s okay to mourn it, but I mean, that’s not something we can fight. Like, there is… the world for a long time had a… Peter Steinberger (03:03:06): there was a lack of intelligence, if you s- if you see it like that, of people building things, and that’s why salaries of software developers reached stupidly high amounts and then will go away. There will still be a lot of demand for people that understand how to build things. It’s just that all this tokenized intelligence enables people to do a lot more, a lot faster. And it will be even more… even faster and even more because those things are continuously improving. We had similar things when… I mean, it’s probably not a perfect analogy, but when we created the steam engine, and they built all these factories and replaced a lot of manual labor, and then people revolted and broke the machines. Peter Steinberger (03:04:04): Um, I- I can relate that if you very deeply identify that you are a programmer, that it’s scary and that it’s threatening because what you like and what you’re really good at is now being done by a soulless or not entity. But I don’t think you’re just a programmer. That’s a very limiting view of your craft. You are, you are still a builder. Lex Fridman (03:04:40): Yeah, there’s a couple of things I want to say. So one is, I never… As you’re articulating this beautifully, I no- I’m realizing I never thought I would… the thing I love doing would be the thing that gets replaced. You hear these stories about these, like you said, with the steam engine. I’ve, I’ve spent so many, I don’t know, maybe thousands of hours poring over code and putting my heart and soul and, like, and just, like, some of my most painful and happiest moments were alone behind… I, I was an Emacs person for a long time. Man, Emacs. And, and then there’s an identity and there’s meaning, and there’s… Like, when I walk about the world, I don’t say it out loud, but I think of myself as a programmer. And to have that in a matter of months… Lex Fridman (03:05:31): I mean, like you mentioned, April to November, it really is a leap that happened, a shift that’s happening. To have that completely replaced is is painful. It’s, it’s truly painful. But I also think programmers, builders more broadly, but what is, what is the act of programming? I, I think programmers are generally best equipped at this moment in history to learn the language, to empathize with agents, to learn the language of agents. To feel the CLI. Peter Steinberger (03:06:10): Yeah. Lex Fridman (03:06:11): Like, like to understand what is the thing you need, you the agent, need to do this task the best? Peter Steinberger (03:06:21): I think at some point it’s just gonna be called coding again, and it’s just gonna be the new normal. Lex Fridman (03:06:25): Yeah. Peter Steinberger (03:06:25): And yet, while I don’t write the code, I very much feel like I’m in the driver’s seat and I am, I am writing the code, you know? It’s just- Lex Fridman (03:06:37): You’ll still be a programmer. It’s just the activity of a programmer is, is different. Peter Steinberger (03:06:41): Yeah, and because on X, the bubble, I mean, is mostly positive. On, on Mastodon and Bluesky, I don’t… I also use it less because oftentimes I got attacked for my blog posts. And I, I had stronger reactions in the past, now I can sympathize with those people more ’cause, in a way I get it. It… In a way, I also don’t get it because it’s very unfair to grab onto the person that you see right now and unload all your fear and hate. It’s gonna be a change and it’s gonna be challenging, but it’s also… I don’t know. I find it incredibly fun and, and, and gratifying. And I can, I can use the new time to focus on much more details. I think the level of expectation of what we build is also rising because it’s just now… The default is now so much easier, so software is changing in many ways. Peter Steinberger (03:07:45): There’s gonna be a lot more. And then you have all these people that are screaming, “Oh yeah, but what about the water?” You know? Like, I did a conference in Italy about the, the state of AI, and m- my whole motivation was to push people away from, don’t see yourself as an iOS developer anymore. You’re now a builder, and you can use your skills in many more ways. Also because apps are slowly going away. People didn’t like that. Like a lot of people didn’t like what I had to say. And I don’t think I was hyperbole, I was just like, “This is how I see the future.” Maybe this is not how it’s going to be, but I’m pretty sure a version of that will happen. Peter Steinberger (03:08:30): And the first question I got was, “Yeah, but what about the insane water use on data centers?” But then you actually sit down and do the maths, and then for most people if you just skip one burger per month, that compensates the, the CO2 output, or, like, the water use in equivalent of tokens. I mean, the maths is, is… the maths is tricky, and it depends if you add pre-training, then maybe it’s more than just one patty…. but it’s not off by a factor of 100, you know? So, so the… or like golf is still using way more water than all data centers together. So are you also hating people that play golf? Those people grab on anything that they think is bad about AI without seeing the potential things that might be good about AI. Lex Fridman (03:09:23): Mm-hmm. Peter Steinberger (03:09:24): And I’m not saying everything’s good. It’s certainly gonna be a very transformative technology for our society. Lex Fridman (03:09:32): There’s to steel man the, the criticism in general, I do wanna say in my experience with Silicon Valley there’s a bit of a bubble in the sense that there’s a kind of excitement and an over-focus about the positive that the technology can bring. Peter Steinberger (03:09:54): Yeah. Lex Fridman (03:09:55): And… which is great. It’s great to focus on… N- not to, not to be paralyzed by fear and fear-mongering and so on, but there’s also within that excitement, and within everybody talking just to each other, there’s a dismissal of the basic human experience across the United States and the Midwest, across the world. Including the programmers we mentioned, including all the people that are gonna lose their jobs, including the s- the measurable pain and suffering that happens at the short-term scale when there’s change of any kind. Especially large-scale transformative change that we’re about to face if what we’re talking about will materialize. And so to ha- having a bit of that humility and awareness about the tools you’re building, they’re going to cause pain. Lex Fridman (03:10:43): They will long term hopefully bring about a better world, and even more opportunities- Peter Steinberger (03:10:48): Yeah Lex Fridman (03:10:48): … and even more awesomeness. But having that kind of like quiet moment often of, of respect for the pain that is going to be felt. And so not, not enough of that is, I think, done, so it’s, it’s good to have a bit of that. Peter Steinberger (03:11:07): And then I also have to put against some of the emails I got where people told me they have a small business, and they’ve been struggling. And, and OpenClaw helped them automate a few of the tedious tasks from, from collecting invoices to like answering customer emails that then freed them up and like cost them a bit more joy in their life. Lex Fridman (03:11:30): Mm-hmm. Peter Steinberger (03:11:31): Or, or some emails where they told me that OpenClaw helped their disabled daughter. That she’s now empowered and feels she can do much more than before. Which is amazing, right? Because you could, you could do that before as well. The technology was there. I didn’t, I didn’t invent a whole new thing, but I made it a lot easier and more accessible, and that did show people the possibilities that they previously wouldn’t see. And now they apply it for good. Lex Fridman (03:12:02): Mm-hmm. Peter Steinberger (03:12:03): Or like also the fact that, yes, I, I, I suggest the, the, the latest and best models, but you can totally run this on free models. You can run this locally. You can run this on, on, on Keyme or other, other, other models that are way more accessible price-wise, and still have a, a very powerful system that might otherwise not be possible. Because other things like, I don’t know, Entropik’s CoWork is locked in into their space, so it’s not all black and white. There’s… I got a lot of emails that were heartwarming and amazing. And, and I don’t know, it just made me really happy. Lex Fridman (03:12:48): Yeah, there’s a lot… It has brought joy into a lot of people’s lives. Not just, not just programmers. Like a lot of people’s lives. It’s, it’s, it’s beautiful to see. What gives you hope about this whole thing we have going on with human civilization? Peter Steinberger (03:13:03): I mean, I inspired so many people. There’s like… there’s this whole builder vibe again. People are now using AI in a more playful way and are discovering what it can do and how it can like help them in their life. And creating new places that are just sprawling of creativity. I don’t know. Like, there’s like ClawCoin in Vienna. There’s like 500 people. And there’s such a high percentage of people that uh, want to present, which is to me really surprising, because u- usually it’s quite hard to find people that want to like talk about what they built. And now it’s, there’s an abundance. So that gives me hope that we can, we can figure shit out. Lex Fridman (03:14:00): And it makes it accessible to basically everybody. Peter Steinberger (03:14:04): Yeah. Lex Fridman (03:14:05): Just imagine all these people building, especially as you make it simpler and simpler, more secure. It’s like anybody who has ideas and can express those ideas in language can build. That’s crazy. Peter Steinberger (03:14:22): Yeah, that’s ultimately power to the people, and one of the beauty, the beautiful things that come out of AI. Not just, not just a slop generator. Lex Fridman (03:14:36): Well, Mr. Clawfather, I just realized when I said that in the beginning, I violated two trademarks, because there’s also the Godfather. I’m getting sued by everybody. You’re a wonderful human being. You’ve created something really special, a special community, a special product, a special set of ideas. Plus, the entire… the humor, the good vibes, the inspiration of all these people building, the excitement to build. So I’m truly grateful for everything you’ve been doing and for who you are, and for sitting down to talk with me today. Thank you, brother. Peter Steinberger (03:15:14): Thanks for giving me the chance to tell my story. Lex Fridman (03:15:17): Thanks for listening to this conversation with Peter Steinberger. To support this podcast, please check out our sponsors in the description, where you can also find links to contact me, ask questions, give feedback and so on. And now let me leave you with some words from Voltaire. “With great power comes great responsibility.” Thank you for listening, and hope to see you next time.

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