大部分互联网动作会交给智能体；OpenAI 的 ChatGPT 与 Codex 负责人说，被低估的那件是生态｜《Lenny's Podcast》

《Lenny's Podcast》是一档产品与职业访谈节目，主持人莱尼·拉奇茨基（Lenny Rachitsky）在 Airbnb 做过产品，如今每期请一位从业者坐下来聊一个多小时。这一期录在 2026 年 9 月 29 日旧金山 OpenAI DevDay 的现场，台下坐着观众。嘉宾提博·索蒂奥（Tibo Sottiaux）当天上午刚带团队发布二十多个新产品，紧接着就上台接受访谈；他在 OpenAI 负责 ChatGPT 与 Codex，也就是这家公司面向普通用户和开发者的全部核心产品1。

37 分钟里，他把话压在四条线上：Dots 这个新产品是什么、为什么现在才做；智能体接下来会拿走互联网上的哪些动作；插件生态里那件他认为被低估的事；以及模型变强之后，人的技能表和工作方式会怎么变。节目最后他讲了一个自己也没预料到的例子——他的助理在他上台前五分钟报告了生产环境故障。

Dots 在 DevDay 当天开始向 Pro、Business Premium 和 Enterprise 用户分批开放，由 GPT-6 Astra 驱动。每个 dot 有自己的云端电脑和浏览器，能通过插件连接四千多个应用，可以在后台连续干活，也可以把具体任务交给 Codex 或 ChatGPT Work 执行；对话入口铺在 ChatGPT 桌面端、网页端、手机端，以及 Slack 和 Teams 里，短信在计划中2。

访谈里，索蒂奥把它的定位说得很直白：一个非常聪明、7×24 小时在线、懂你的目标和偏好、能从反馈里学习的智能体。用户要做的只是把想做的事讲清楚，剩下的是它自己决定怎么拆、怎么排、什么时候来问你。

目前每个用户拿到的是一个「主 dot」。索蒂奥说接下来很快就能添加第二个、第三个、第四个，直到凑出一支虚拟团队，给每个分派明确的角色。他自己已经有一个专门盯 Twitter 的 dot——因为「盯 Twitter」这件事的工作量，本身就抵得上一个完整的 dot1。

面向企业的那一层叫 specialist dot：由公司给它独立的身份、凭证和系统权限，让它承担一项固定职责，配额外的护栏、额外的监控，跑在单独的硬件上。索蒂奥说，其中一些就跑在 Mac mini 上。他还点了一个容易被忽略的设计差别——dot 的运行环境放在你正在用的那台机器之外，所以它能同时连很多台设备：它自己的电脑、你的笔记本，以后再叠加别的终端。他用「有点像章鱼」来形容这件事。

ChatGPT 里那个「聊天 / 工作」的切换开关要合并。索蒂奥说反馈听得很清楚：人们喜欢 Work 里的能力，但有时候就是想用 Chat，因为它更快、更顺手。合并之后，Dots 的能力最终会整个搬进 ChatGPT，把 12 亿用户的起点抬高一截。

他真正想删掉的是模型选择器。他说自己也会被「用哪个模型、推理开多大、要不要多智能体、Ultra 又是什么」搞累，而这些东西需要用户先读一篇说明才敢点。他期待的终局是：打开就能说话，唯一需要配置的是你想在哪些渠道里找到它。

被问到「所有发布里哪一件最该火但还没火」时，索蒂奥把票投给了开放生态。他把这件事拆成三块：把 ChatGPT 的订阅额度开放给外部工具、把 ChatGPT 变成开发者可以搭建原生界面的外壳、以及让受欢迎的插件分到钱。

这套东西是去年「当场拍板」长出来的。他当时和 Pi、OpenCode 的作者聊，觉得用户本来就该用自己的 ChatGPT 账号登进去、用自己的额度，于是双方虚拟地握了个手，靠信任先跑起来。它后来变得很流行，于是被正式做成产品：现在有 16 家合伙人，名单里有 Cognition 的 Devin、Notion、Vercel、T3、OpenClaw、Dactyl 等；用户能在这些工具里使用自己的额度，并按工具分别控制每家能用多少3。

与之配套的是 Marketplace：符合条件的企业客户可以把已有的 OpenAI 采购承诺，转用在一批经过审核的合作方软件上，首批 32 家，覆盖 Figma、Adobe、Sierra、Harvey、Palo Alto Networks 等不同方向3。

索蒂奥说，插件能不能浮上来，取决于留存、成功率和质量，系统会据此决定要不要在对话里把它推荐给用户；用的人少了，推荐就停。他把这套逻辑和「为被 AI 引用而优化措辞」这种做法明确区分开：真正起作用的是有人持续在用，并且确实让 ChatGPT 多做成了一件事。

至于分钱，他说主题演讲里没细讲，但受用户欢迎、用量大的插件会拿到收入分成。他举了 Notion 和 Figma 的例子：用户带着自己的 ChatGPT 订阅，在 ChatGPT Work 里用这两家的插件，两家能从中获得报酬。

有人问，OpenClaw 火了、Peter Steinberger 进了 OpenAI、Grok Bot、Muse、Instinct 一个接一个冒出来，OpenAI 为什么慢了半拍。索蒂奥的回答是时间线：长时程、持久任务的研究做了两年多，稳定的记忆系统也做了差不多同样久，其中很多能力早就直接放进 ChatGPT 了。他把最终形态描述成「长时程研究 + 记忆 + harness + 能稳定跑 7×24 小时的产能」叠在一起的结果。他还顺手提了一句，一年前 Codex Cloud 用过的那段小动画，就是 Grok Bot 的灵感来源，「非常非常像」。

另一个问题他也答了：能不能慢一点。他说 Dots 一开始就用 Astra，「我们最安全、最对齐的模型」，为了让 Dots 真正安全、可信，团队额外投入了很多。紧接着，他给出了这套说法里最具体的一条证据：内部做出过一个 6.1 Astra，但没有发布，这件事让他很骄傲1。

他对「pacing the frontier」的解释是投资在前：投对齐、投安全、投护栏，并且投得比自认为需要的还多。他描述了一种花算力的方式——大头给干活的智能体，另外一大块拿去做次级监控，盯着主智能体有没有在冒高风险动作、有没有吃到提示注入，一旦发现就介入；他也说，这家公司产品栈上的主要投入，其实流向的是安全栈1。最后他谈到动机：产品交到 12 亿人手里，其中包括大量非技术用户，「我们不会在那里赌」。

访谈里有一半时间不在讲产品，而在讲人被改变的部分。

被问到「最近有什么让你觉得惊艳的用法」时，索蒂奥讲了一件当天发生的事。他有一个 dot 注意到了 ChatGPT 生产环境出故障，在直播开始前五分钟给他发消息：生产挂了，要不要我试着修一下？他的回复是「我觉得你还差一点，小 dot，但谢谢你愿意试」。随后他联系工程团队排查，到录制时问题已经修好。

他觉得真正难得的地方在判断：这个东西明白「今天有一件很重要的事叫 DevDay」「现场有一个生产系统」「马上有一场直播」「这两件事大概率相关」，所以决定打断他。

拉奇茨基问的是另一半：工程师整天和智能体说话，切换变多，人也更容易孤独；再加上所有人都能做得更多，就自然形成一种「你为什么不跑三十个智能体」的压力。

索蒂奥说他一直在想这件事，眼下先要减的是配置负担——不要让用户先学会配一堆东西。他描述了自己心里的理想形态：它就在你所在的物理空间里，听得见你和别人的对话，你在纸上画个东西，它就在后台开始搭，搭到一半你又想到别的，它再起一条；你想看就投到屏幕上。这套东西今天只跑通了一部分，但它指向的方向是「让交互变得自然」，而不是「每秒多发一条 prompt」。他也提到 Sam Altman 反复讲的那个承诺：把噪音压下去，让你把注意力花在你想花的地方。他的论据是自己的假期——断开一周之后，他会换一种更松弛也更出活的方式思考。

被问到招聘上什么技能在升值，索蒂奥给的第一个例子是很多人会不舒服的那个：打字快在贬值，「没那么有用了」。升值的是品味、替用户想、连接受众，以及知道「好」长什么样。他把 OpenAI 形容成一个「超级创业公司」——现在有 120 多位前 YC 创始人在这里；他看重的那种人，是有强烈意愿做出点重要东西、并且认得出一件东西好不好。

他顺带说，产品经理这一轮会相对好过，因为这个岗位本来做的就是那几件事：判断该做什么、帮人做出来、判断做出来的是不是够好、然后迭代。他也说，角色正在互相打通：以前只做设计、或者只做工程的人，现在可以往前一步。

被问到「新人对老手有没有优势」，他的答案是有的：他们没有一段需要被改掉的工作习惯，而且学得快。他举了自己最想推的同事：Ahmed Ibrahim 入职时是应届生，如今负责 OpenAI 全部的算力集群和 applied 团队。索蒂奥把这个人为什么做得出来归给三件事——非常友善、非常愿意协作、把协作放在自己前面，再加上学得像海绵。他说这人现在是他最信任的人之一，专门负责最棘手的发布。

他把内部的工作方式描述成自下而上。Decisions API 就是例子：团队发现 Luna 这个模型配上受限采样之后很好用，于是把它换一个形状塞进 Responses API，比原来的做法更快、在某些场景里也更顺手。它最早的形态是一个 Slack 频道，四个人周末在上面敲，之后「像公司食堂一样」对所有人开放，越来越多人加进来。他说，DevDay 上还有一些本来准备发布的东西被按下来了，接下来几周会陆续放出来1。

另一条线是自主权与信任。他说这里的文化是给你很大的自主权，然后你自己承担；出事就快速修，或者从错误里学。他举的例子是自己：入职第三天就把生产环境弄挂过一次，人还在。也因此，拉奇茨基问他「大家还能期待多少次重置」时，他答得很快——取决于你把什么东西弄坏。他把这话补成了半句口号：弄坏了什么，就庆祝什么。

提博·索蒂奥（Tibo Sottiaux） 是本期嘉宾，比利时人，本科与硕士都在鲁汶大学读计算与应用数学。他的履历从写代码一路走到管产品：早年在 Google 做软件工程，之后进 Google DeepMind，先是带一支 22 人的团队做研究用的机器学习工作流基础设施，后来带 50 多人的跨学科团队负责 Gemini 的微调数据与人工评测；2024 年转入 OpenAI，先做 Codex 的工程负责人，随后接管整个核心产品线——API、智能体基础设施、企业版、ChatGPT（含 ChatGPT Work）和 Codex，向 Greg Brockman 汇报456。他在 Codex 用户里出名，是因为每次产品到达增长节点，他会亲自把 token 额度上限往上调4。

莱尼·拉奇茨基（Lenny Rachitsky） 是主持人，在 Airbnb 做过增长与产品，现在写一份产品方向的通讯，同时做这档播客1。

Ahmed Ibrahim 是索蒂奥在访谈里点名的人。他入职 OpenAI 时是应届生，现在负责公司全部算力集群与 applied 相关工作7。

几个术语，先说清楚后面才好读。

智能体（agent）：能自己规划步骤、调用工具、连续执行多步任务，而不只是回一段话的模型产品。本期里它同时指 ChatGPT 里跑任务的执行单元，也指用户自己配出来的那些「同事」。

Dots：OpenAI 在 DevDay 发布的个人智能体产品，本期主角。它由 GPT-6 Astra 驱动，有自己的云电脑与浏览器，能连四千多个应用，先在 Pro 与 Business Premium 上开放2。

GPT-6 Astra 与 Ultrafast：Astra 是 OpenAI 目前最强的一档模型，也是 Dots 的底座；Ultrafast 是同一批模型上的「速度档」，官方给出的数字是 Codex 里最快到 8 倍速、API 里最快 6 倍，代价是更贵3。访谈里说的「让半年前的 Sol 走 Ultrafast，价格大致回到 Astra 那一档」，指的就是这个组合。

Codex、ChatGPT Work、Chat：OpenAI 现在并行的三个工作面。Codex 面向写代码，ChatGPT Work 面向办公室任务，Chat 是原始对话界面。索蒂奥这期讲的一件事，就是这三者之间的边界接下来会被拆掉。

harness：包在模型外面、负责把任务拆开、调用工具、维护状态的那层工程代码。索蒂奥在别处说过一个判断——手工搭的脚手架会不断被更强的模型吃掉，本期「不要去调 loop」的说法是同一个意思8。

specialist dot：企业版里的角色化 dot，有独立身份、凭证、权限和硬件，承担固定职责，护栏和监控都更厚。

Sign in with ChatGPT：用 ChatGPT 账号登录第三方工具，并把订阅额度带过去使用的一套机制，首批 16 家合伙人3。

OpenClaw：一个开源的个人智能体项目，由 Peter Steinberger 创建，也在「Sign in with ChatGPT」的首批合伙人名单里；索蒂奥在访谈里提到，Peter 加入 OpenAI 之后这个项目被交给了基金会3。

Decisions API：DevDay 发布的接口，把模型的能力收窄成一个「在给定的几个选项里选一个」的分类器，用于路由请求、判断内容类别、决定智能体下一步动作3。

下面是这一期的完整转录稿，中英对照，按讲话人分段，每段开头标注讲话人姓名，时间轴每 10 分钟标注一次。开场约一分钟是节目剪出的精彩片段拼贴，标为「开场混剪」，其中的话来自不同时间点，不是连续对话。英文原文来自节目官方字幕，并与完整音频的机器识别结果逐段核对；中文为逐段译文。整理时只做了两类处理：删去识别器在无语音空隙处填入的、与节目无关的提示语；统一若干专有名词的写法，其中有两处需要说明——官方字幕把本期的产品名「Dots」在几处识别成了「Docs」，以及把「投资实际上流向安全栈」识别成了否定句，这两处已按音频更正。措辞、口语、重复与未说完整的句子均保持原样，未作改写。两位讲话人音色接近，极少数快速接话处的人名标注可能有误，读者可据上下文判断。

提博（开场混剪） Often when I look at what people are building out there, it's just like, "You're not quite getting it." Like, you know, if you were just like pushing yourself and just really imagining like all of this being roughly 10 times better than it is today, you know, like in a year, but you would build in a different way. 很多时候，当我看到人们在外面构建的东西时，我就会觉得，“你还没完全理解。”比如，你知道，如果你只是推动自己，真正去想象这一切比今天大约好十倍的样子，比如一年之后，你会用不同的方式去构建。

莱尼（开场混剪） What do you think people aren't pricing in in terms of where things are going? 你认为人们在预测事态发展时有哪些因素没有考虑进去？

提博（开场混剪） The majority of actions on the internet will be taken by agents. If you want your product to be successful for agents, you have to build, you know, for a certain level of scale. 互联网上的大多数操作将由智能体执行。如果你希望你的产品对智能体成功，你必须为某种程度的规模去构建，明白吗。

莱尼（开场混剪） How many agents do you find yourself running in parallel just uh in the in your kind of your day-to-day work? 在你日常工作中，你发现自己会并行运行多少个智能体？

提博（开场混剪） As I'm pushing the frontier, I find myself like building larger and larger teams of agents. And then when we have the next breakthrough with models, like suddenly it's just like I'm like, "Oh, well, you know, a bigger agent can just do all of it." And so I kind of shrink the team again. And then it just kind of goes through this expansion and shrinking expansion. 当我在推动前沿时，我发现自己像是在建立越来越大的智能体团队。然后当我们在模型上取得下一个突破时，突然我就会想到，‘哦，你知道，更大的智能体就可以完成所有工作了。’于是我又会缩小团队。然后它就这样经历扩张和缩小的循环。

莱尼（开场混剪） It kind of makes me think about there's this whole loops thing and then this whole graphs thing. 这有点让我想到有整个循环的事情，然后还有整个图的事情。

提博（开场混剪） Having to set up and fiddle with your loops is something that maybe people got excited about, but I don't think this is the way that it's going to work. Over time, you just want to system that learns. You don't want to necessarily think about how I'm just like, "I'm going to loop it exactly this way in order to get good results." 不得不设置和调整你的循环可能让人感到兴奋，但我认为这不是它将要运作的方式。随着时间的推移，你只想要一个会学习的系统。你不必一定考虑我只是像“我要完全这样循环以获得好结果”这样去思考。

莱尼（开场混剪） there's still more radical change happening to how we work? 我们的工作方式仍在发生更多激进的变化吗？

提博（开场混剪） to continue to change quite radically. Even today, it still feels like a bit clunky, and I think it will feel clunky until it isn't. 继续发生相当剧烈的变化。即使在今天，它仍然感觉有点笨拙，我认为它会一直感觉笨拙，直到不再笨拙为止。

莱尼 I mean, Evo, thank you for doing this. 我的意思是，Evo，感谢你做这件事。

提博 Yeah. Big fan of you. 是的。很喜欢你。

莱尼 Of course. Uh Nice room. You launched uh a ton of stuff today. How how did your sleep? How are you sleeping? Are you doing all right? 当然。呃，房间不错。你今天发布了很多东西。你的睡眠怎么样？你睡得好吗？你还好吧？

提博 I'm doing great. I'm fortunate to have a very good team. 我过得很好。我很幸运有一支非常优秀的团队。

莱尼 Mhm. 嗯。

提博 So, while I sleep, they were awake most of the night. We have this amazing room uh at the office called the library, which we completely repurposed as like a mega war room. And the vibes in there are just immaculate. Uh people were there until like very, very late. 所以，当我睡觉的时候，他们大部分夜晚都醒着。我们在办公室有一个很棒的房间，叫做图书馆，我们完全把它改造成了一个超级作战室。那里的氛围简直无可挑剔。人们在那里待到了很晚很晚。

莱尼 So, you've been a long-time engineer. Are you are you coding at all anymore? Are you shipping PRs? Are you mostly like in docs and in meetings now? 所以，你一直是工程师很久了。你现在还在写代码吗？你还在提交 PR 吗？你现在大部分时间是处理文档和开会吗？

提博 What is coding? 什么是编程？

莱尼 Exactly. Yeah. Are you shipping PRs? I don't know. Is that 没错。是啊。你在提交 PR 吗？我不知道。是吗

提博 Uh Yeah, yeah, yeah. Merch Merging some code every once in a while. Technically, like a lot of code is getting written for me to do all sorts of kinds of like analysis, like you know, understand like trends, understand a business, understand the next feature, you know, how well our previous launches are doing. A lot of code is written by Codex for dot. You know, I'm obviously not writing it by hand anymore. Occasionally, at the in during the weekends, I'll have like a little therapeutic moment where I do a little lead code just by hand. Um but that's the only actual hands-coding that I do. 呃，是的，是的，是的。偶尔会合并一些代码。从技术上讲，有很多代码是为我编写的，用来做各种分析，比如了解趋势、理解业务、理解下一个功能，以及了解我们之前的发布表现如何。很多代码是由 Codex 为 dot 编写的。你知道，我显然不再手动编写代码了。偶尔，在周末的时候，我会有一个小小的治疗性时刻，手动写一些 leet 代码。但这就是我唯一实际手动编程的情况。

莱尼 How many agents do you find yourself running in parallel just uh in the in the kind of your day-to-day work? 在你日常工作中，你发现自己会并行运行多少个智能体？

提博 I used to run a lot more in parallel and then we were, you know, fortunate enough to get um a breakthrough with ultrafast. And so, now, you know, I feel like you know, I'm able to be in the flow again and so it's just having a faster agent helps me a lot. I'm excited that we're getting, you know, 6-month-old ultrafast out there soon. Um and then, yeah, I think it's it's it sort of varies. Um as I'm kind of like pushing different here, I find myself like, you know, building larger and larger teams of agents. And then, when we have the next breakthrough with models, like suddenly it's just like I am like, oh, well, you know, a bigger agent can just do all of it and I keep everything in memory and learn. And so, I kind of shrink the team again. And then, it just kind of goes through this like expansion and shrinking expansion. 我过去经常同时处理更多任务，然后我们很幸运地在超快技术上取得了突破。所以现在，你知道，我觉得我又能进入工作状态了，所以有一个更快的智能体对我帮助很大。我很兴奋，很快我们就会推出 6 个月大的超快版本。嗯，然后，是的，我觉得这有点变化。当我在尝试不同方向时，我发现自己在不断建立越来越大的智能体团队。然后，当我们在模型上有下一个突破时，就突然像是，哦，好吧，更大的智能体可以完成所有任务，我可以把一切保持在记忆中并学习。所以我又会缩小团队，然后就这样经历扩展和缩小的循环。

莱尼 Hm, okay. Can you say more about that? It kind of makes me think about there's this whole loops thing and then this whole graphs thing. Is like an evolution of that in some way or 嗯，好吧。你能多说一点吗？这让我有点想到有一个完整的循环的概念，然后又有一个完整的图的概念。这在某种程度上是不是它的进化或者……

提博 I think like having to set up and fiddle with your loops and, you know, figuring that out is something that, you know, maybe people got excited about, but I don't think this is the way that it's going to work. I think the way that it's going to work is a what how we're positioning and and what we're shipping with dots, where you have an incredibly smart agent that works 24/7, understands your goals, understands your preferences, learns from feedback. Um and, you know, it's like what we launched is like, no, perfect. I will learn very much from, you know, making this available to our pro users. But over time, just want a system that learns from, you know, what you want to achieve. You don't want to necessarily think about hours like I'm going to loop it exactly this way in order to get results. 我觉得，比如说，需要设置和调整你的循环，嗯，你知道，弄明白这些东西可能让人感到兴奋，但我不认为这就是它最终的工作方式。我认为它的工作方式是，我们如何定位以及通过 Dots 发布的内容，其中你有一个非常智能的智能体，可以全天候工作，理解你的目标，理解你的偏好，并从反馈中学习。嗯，你知道，就像我们发布的东西一样，不是完美的。我会从将其提供给我们的专业用户中学到很多东西。但随着时间的推移，我们只是希望有一个系统能够学习你想要实现的目标。你不必一定去思考细节，比如我将如何精确地循环它以获得结果。

莱尼 So, right now there's Codex, there's ChatGPT work, there's ChatGPT consumer, there's dots. What I'm hearing is you think we're heading towards dots kind of being the primary way you talk to AI, and that kicks off all these other things. 所以，现在有 Codex，有 ChatGPT 的工作，有 ChatGPT 消费者版，还有 dots。我听到的是，你认为我们正朝着 dots 成为与 AI 交流的主要方式发展，而这启动了所有其他这些事情。

提博 Yeah, I think fundamentally if you take a step back and, you know, whether it's dots or not, um it's all about breaking free from the technology um and having this sort of like permanent active intelligence that knows, you know, everything it needs to do and is available through any client, any screen. You can call it, you know, like maybe you walk into a meeting room, it shows up in the meeting, it takes notes, you know, you pick it back up on email, um and then, you know, you text it if you need it. It's not that, you know, you need to be glued to a laptop or, you know, you're like always on your phone. It's just like it's available when you need it and then it's also like gets out of the way when you don't need it. And I can't wait, you know, for that to sort of like come to fruition because I think like just carrying your laptop as like this brick around everywhere is just like, you know, you're kind of like tied to the technology instead of the technology working for you. 是的，我觉得从根本上说，如果你退后一步，无论是否有点点想法，这一切都是关于摆脱技术的束缚，并拥有这种永久性主动智能，它知道自己需要做的一切，并且可以通过任何客户端、任何屏幕访问。你可以这样理解，比如你走进会议室，它会出现在会议中，做笔记，然后你可以在邮件中继续使用它，甚至，如果需要，你也可以发短信给它。不是说你必须一直盯着笔记本电脑，或者总是在手机上。它只是当你需要的时候可用，而当你不需要的时候，它又会离开你的视线。我迫不及待想看到这种实现，因为我觉得只是带着笔记本电脑到处走，就像一个砖块一样，你反而被技术绑住了，而不是让技术为你服务。

莱尼 This episode is brought to you by our season's presenting sponsor WorkOS. What do OpenAI Anthropic, Cursor, Replit, Sierra, Clay, and hundreds of other winning companies all have in common? They are all powered by WorkOS. If you're building a product for the enterprise, you felt the pain of integrating single sign-on, SCIM, RBA, audit logs, and other features required by large companies. WorkOS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SaaS. Literally every startup that I'm an investor in that starts to expand upmarket ends up working with WorkOS. And that's because they are the best. Whether you are a seed stage startup trying to land your first enterprise customer or a unicorn expanding globally, WorkOS is the fastest path to becoming enterprise ready and unblocking growth. It's essentially Stripe for enterprise features. Visit workos.com to get started or just hit up their Slack where they have actual engineers waiting to answer your questions. WorkOS allows you to build faster with delightful APIs, comprehensive docs, and a smooth developer experience. Go to workos.com to make your app enterprise ready today. I was going to ask you about this. It feels like so much has changed in how we work over the past like 2 years. In 2 years, especially engineers, but a lot of roles have just the role your day-to-day life has changed significantly. And I'm curious if you think we're kind of settling into what work will look like in the next, I don't know, 5 years? Let's say 2 years, that's feels way too far to think about. Or do you think there's still more radical change happening to how we work in 本集由本季的赞助商 WorkOS 为您带来。 OpenAI Anthropic、Cursor、Replit、Sierra、Clay 以及其他数百家获奖公司有什么共同点？ 它们均由 WorkOS 提供支持。 如果您正在为企业构建产品，您会感受到集成单点登录、SCIM、RBA、审核日志和大公司所需的其他功能的痛苦。 WorkOS 通过专为 B2B SaaS 构建的现代开发者平台将这些交易阻碍因素转变为嵌入式 API。 事实上，我投资的每一家开始拓展高端市场的初创公司最终都会与 WorkOS 合作。 那是因为他们是最好的。 无论您是试图吸引第一个企业客户的种子期初创公司，还是在全球范围内扩张的独角兽，WorkOS 都是为企业做好准备并畅通增长的最快途径。 它本质上是用于企业功能的 Stripe。 请访问 workos.com 开始使用，或者直接访问他们的 Slack，那里有真正的工程师等待回答您的问题。 WorkOS 允许您通过令人愉悦的 API、全面的文档和流畅的开发人员体验更快地构建。 立即访问 workos.com 让您的应用程序企业做好准备。 我正想问你这个问题。 感觉在过去两年里我们的工作方式发生了很大的变化。 在这两年里，尤其是工程师，很多角色都只是你的日常生活发生了很大的变化。 我很好奇你是否认为我们已经开始适应未来五年（我不知道）的工作会是什么样子？ 假设 2 年，这感觉太遥远了。 或者您是否认为我们的工作方式正在发生更根本的变化？

提博 No, I think it's going to continue to change quite radically. Even today, you know, it does seem like the technology is finally coming together with voice, uh you know, multimodal inputs, outputs, but it still feels like a bit clunky and I think it will feel clunky until it isn't. And then you're just like, "Wow, you know, it's like I can just talk to this thing the same way that we're talking right now. It just remembers things perfectly. If I want to, you know, ideate and brainstorm, I can just like, you know, squiggle a thing. I have this collaborative surface. You know, this is what we launched with ChatGPT spaces signal to various startup dot. You know, you can imagine we have like a shared whiteboard, we can collaborate between humans, between agents. And I think it's going to sort of like transcend conversations, transcend, you know, like a lot of the clients that you have today. And like, none of this is just really working today, right? So, I think that we're going to go through this big new transformation. What I'm hearing here is dots is a big part of that future, this AI assistant that just kind of does everything for you and you don't have to think about Codex versus ChatGPT and Yes, and for Codex and ChatGPT, we're going to merge uh like the the we have we have chat, we have the work toggle. Like you know, we heard the feedback loud and clear. Like you know, people love the capability in work, but then also you know, you're like sometimes you want to use chat because it's a little bit faster. And you know, more pleasant to use. And so we're we're merging that. We're reducing that complexity. Eventually, we will ship all of the capabilities of Docs, you know, straight into ChatGPT as well and you know, lift the floor for like our 1.2 billion users, which you know, at that time we'll see like how many we have. Um and we want it to be really really seamless. One thing that I'm very excited with with Docs is like they don't have a model picker. There's just no configuration. You just talk to it. Like the only thing that you have to configure is like which channels you want to talk to. 不，我认为它将继续发生彻底的变化。 即使在今天，你知道，这项技术似乎终于与语音结合在一起了，呃你知道，多模式输入、输出，但它仍然感觉有点笨重，我认为它会感觉笨重，直到它不是。 然后你就会说，“哇，你知道，就像我可以像现在一样与这个东西交谈。它能完美地记住事情。如果我想，你知道，构思和集思广益，我可以，你知道，画一个东西。我有这个协作界面。你知道，这就是我们通过 ChatGPT 空间向各个初创点发出信号而推出的东西。你知道，你可以想象我们有一个共享白板，我们可以在之间进行协作 我认为这将有点像超越对话，超越，就像你今天拥有的很多客户一样，这些都不是真正有效的，对吗？ 所以，我认为我们将经历这个巨大的新转变，这是未来的一个重要部分，这个人工智能助手可以为你做一切，你不必考虑 Codex 与 ChatGPT 和 Yes 的关系。 Codex 和 ChatGPT，我们将合并，就像我们拥有的聊天功能一样，我们听到了响亮而清晰的反馈，但您也知道，有时您想要使用聊天，因为它更快一些，所以我们正在合并它，我们将降低其所有功能。 Docs，你知道，也可以直接进入 ChatGPT，你知道，到时候我们会看到我们有多少用户。 我对 Docs 感到非常兴奋的一件事是，他们没有模型选择器。 你只需与它交谈。

莱尼 It feels very much like the Her kind of vision of the world. I don't know. Do you think about that movie much? Just this idea of this 这感觉很像《《她》》中对世界的那种看法。我不知道。你经常想那部电影吗？只是这个想法

提博 I watched it once. Yeah. I think it's it's it's interesting, you know, to to to think about, you know, maybe more what what I think about more is like, you know, sci-fi from from, you know, 30 40 years ago and like how visionary it was. 我看过一次。是的。我觉得它很有趣，你知道，可以去思考，你知道，也许我更多思考的是，比如说，三四十年前的科幻，以及它有多么具有前瞻性。

莱尼 Is there specific sci-fi you think about that's most influenced you? 你有没有特别想过的科幻作品，对你影响最大？

提博 Like you know, books like Neuromancer and then you know, the original like Star Trek. Um you know, I think about that a lot. And there's something about Star Trek which I think, you know, was like there was this technology that was like very very useful. Obviously like, you know, you were able to just like talk to a computer and like it does things for you. Like you can talk to your spaceship and it just moves, right? It's like this is getting real, you know, like we're entering that era. 就像你知道的，《神经漫游者》这样的书，然后你知道，原版的《《星际迷航》》。嗯，你知道，我经常会想到这些。我觉得《《星际迷航》》有些东西是这样的，你知道，有一种技术，非常非常有用。显然，你可以直接和计算机对话，它会为你执行任务。你可以跟你的宇宙飞船对话，它就会移动，对吧？就像，这真的变成现实了，你知道，我们正在进入那个时代。

莱尼 So we're recording this in front of a live audience. There was this line out the door just people waiting to see you, to hear from you. How do you just think about this, I don't know, role you're in, this responsibility you have to build what you're building and the impact it has on people's lives. I don't know. Just what does that feel like? How do you think about that? 所以我们正在现场观众面前录制这个节目。门外排起了长队，人们都在等着见你、听你说话。你是如何看待这个，我不知道，这个你所处的角色，你肩负的责任去建立你正在建立的东西以及它对人们生活的影响的？我不知道。这种感觉是什么样的？你是如何考虑的？

提博 I think it's very important to be part of a community and to build with people. It was like, you know, we're we're discovering this technology and like what we can do together. Um and so every time I you know, talk to people, I'm like I'm kind of like reminded of you're doing this thing which I hadn't even anticipated. You know, it's impacting your life in a certain way and it's impacted like you know, this other person's life and then it's just like all together. It's both very humbling, very inspiring, and I think very necessary in order to build something that is truly useful for humans. I I don't know how we would do it without the community. 我认为成为社区的一部分并与人一起建设非常重要。这就像，你知道的，我们正在发现这项技术，以及我们可以一起做什么。嗯，所以每次我和人们交谈时，我都有点像被提醒，你正在做这件事，而我甚至没有预料到。你知道，它以某种方式影响了你的生活，也影响了其他人的生活，然后这一切汇聚到一起。这既非常令人谦卑，也非常鼓舞人心，我认为这对于构建对人类真正有用的东西是非常必要的。我不知道没有社区我们该如何做到这一点。

莱尼 That's something I hear a lot with people building an AI is they don't know what it is until they've launched it and they see how people use it, see what emerges. And it feels like kind of what you're saying is just build it with people versus like here's the vision, we've got it figured out. 我经常听到那些开发人工智能的人说，他们在发布之前并不知道它是什么，只有发布后看到人们如何使用它、看到会出现什么，才会明白。而且感觉你说的就是，应该和人一起构建它，而不是说‘这是愿景，我们已经搞定了’。

提博 Even the Twitter community has been very nice in general. 即使是推特社区总体上也非常友好。

莱尼 You're very good at Twitter. Kind of antagonistic sometimes, but very good. How do you How do you find time to even tweet? I don't understand how someone in your role has time to sit on Twitter, tweet, reply. 你在推特上非常擅长。有时有点对抗性，但非常擅长。你是怎么找到时间发推文的？我不明白像你这样的人怎么会有时间坐在推特上发推、回复。

提博 I spend like maybe half an hour per day. Yeah, just say rolling and then doing something when I feel inspired and I have something interesting to say. Often it just comes like in the moment. Yeah. 我每天大概花半个小时。是的，只是随便写写，然后当我有灵感或者有有趣的内容想说的时候才做。通常它就在那一刻冒出来。是的。

莱尼 Perfect Twitter skill. 完美的推特技巧。

提博 And I have a We haven't released the dot the the the team dots yet, but you know today we're releasing the primary dot which you can configure, you can get used to like what a dot can do, connect it to your apps. But we'll release the ability to create more than one. And so I have one that's responsible for Twitter. 而且我有一个我们还没有发布点点点团队的点，但你知道今天我们发布的是主要的点，你可以进行配置，你可以熟悉点能做什么，把它连接到你的应用。但我们将会发布创建多个的功能。所以我有一个负责推特的点。

莱尼 Okay, say more about that. So right now everyone gets one dot. 好，详细说说这个。所以现在每个人都有一个点。

提博 Yeah. 是的。

莱尼 Right now they can't add more dots. 现在他们不能添加更多点了。

提博 That's right. 没错。

莱尼 They will be able to have many dots. Talk about kind of where that's going. 他们将能够有很多点。谈谈这将会发展的方向。

提博 Yeah, so we wanted to start with one, the primary dot which is the one that you know, you'll probably also text that you know, learns your preferences most deeply as well and kind of see like you know, what people do with it, see how we need to tune the system, you know, learn that working with the community and then very quickly soon you'll be able to add you know, a second one, a third one, a fourth one, as many as you need to create like your virtual team. And then you can give them specific roles, right? Is it It's not I don't find it absolutely necessary, but sometimes I have like a thing that is requires quite a bit of work, you know, such as like monitoring like Twitter for me. And then you know, that's It's a thing is like like, this will be like so much work that is like the work of an entire dot. Um and then you know, you can have a couple of those. 是的，所以我们想从一个点开始，也就是主要的点，你知道，你可能也会通过短信来学习它，它还能最深入地了解你的喜好，并且去看看，人们会怎么使用它，看看我们需要如何调整系统，学习如何与社区合作，然后很快你就可以添加第二个、第三个、第四个点，按需要创建你的虚拟团队。然后你可以给它们分配具体的角色，对吧？我觉得这不是绝对必要的，但有时候我会有一些事情需要做很多工作，比如像我监控推特之类的事情。这类事情工作量很大，几乎相当于整个一个点的工作。然后，你就可以有几个这样的点。

莱尼 So if you think about all the launches that happened today, it feels like dots maybe like the sexiest. I'm curious if there's something that you think is not getting the attention it probably deserves that will become a really, really important down the road that's kind of people are sleeping on that's like a vision. 所以如果你考虑一下今天发生的所有发布，感觉像是一些点，也许像是最吸引人的。我很好奇，你是否认为有一些东西可能没有得到应有的关注，但将来会变得非常非常重要，而且人们现在可能还没有注意到，这就像是一种愿景。

提博 Yeah, yeah, yeah, important. the sleeper hit is ecosystem. So opening it all up. Uh and the commitment, the deep commitment we have towards opening it all up. So we have signing with ChatGPT 16 partners. Very, very proud of that. Like we started that like really it was sort of like in the moment last year. Um I was talking to creators of Pi and open code and it was like, of course, you know, you should just be able to use the critics sign on and then you know, you use the usage and then you just we kind of like shook hands, you know, like virtually we're like, you know, it's just like use this this uh this off um and then you know, kind of trust you to not do anything shady. You know, that grew obviously that became quite popular and then you know, now we made it, you know, an actual thing that was supported with many, many partners. Um and I'm excited to grow that very quickly. You know, the other side as well is like opening up all of the infrastructure and how we build for ChatGPT, you know, with plug-in extensions, also plug-in discovery, just allowing, you know, everyone to ship something through like maybe 1.2 billion users, right? You know, and benefiting from that distribution. And we also have shared economics um that we didn't actually talk uh in the keynote, but you know, we will pay, you know, our plug-ins that are uh popular and you know, are seeing a lot of usage. Uh they're going to get part of like the the revenue share as well. Uh and so I think this commitment towards an open ecosystem is going to be very exciting. 是啊是啊，很重要。 潜在的打击是生态系统。 所以把一切都打开。 呃，还有承诺，我们对开放这一切的坚定承诺。 因此我们已经与 ChatGPT 16 合作伙伴签约。 对此非常非常自豪。 就像我们开始那样，真的有点像去年的那一刻。 嗯，我正在与 Pi 和开放代码的创建者交谈，当然，你知道，你应该能够使用批评者登录，然后你知道，你使用该用法，然后你只是我们有点握手，你知道，就像实际上我们就像，你知道，就像使用这个呃这个关闭嗯然后你知道，有点相信你不会做任何见不得人的事情。 你知道，它显然已经变得非常流行，然后你知道，现在我们做到了，你知道，这是一个得到了很多很多合作伙伴支持的实际产品。 嗯，我很高兴能够快速成长。 你知道，另一面就像开放所有基础设施以及我们如何为 ChatGPT 构建，你知道，通过插件扩展，还有插件发现，只是允许每个人通过大约 12 亿用户交付某些东西，对吗？ 你知道，并从这种分配中受益。 我们也有共享经济，嗯，我们实际上并没有在主题演讲中谈论呃，但是你知道，我们会付费，你知道，我们的插件很受欢迎，你知道，正在看到很多使用。 呃，他们也会得到一部分收入分成。 嗯，所以我认为这种对开放生态系统的承诺将非常令人兴奋。

莱尼 That's amazing. Uh okay, so as an example, so say Notion, somebody's using the Notion plug-in or the Figma plug-in within uh ChatGPT work, Notion, Figma make money from people using it within the app. 那太棒了。呃，好吧，所以举个例子，比如说 Notion，有人在 ChatGPT 中使用 Notion 插件或 Figma 插件，Notion、Figma 会从人们在应用内使用它时赚钱。

提博 Yes, so um we have, you know, all these subscribers that use ChatGPT, um they get like, you know, a certain amount of usage and then when have that, the when when the users use that usage with the plugin, or within the other product when they use sign-in with ChatGPT, um you know, we will have like some shared economics with them where they will get to remunerate. 是的，所以嗯，我们有，你知道的，所有这些使用 ChatGPT 的订阅者，嗯，他们会有一定量的使用额度，然后当他们使用插件，或者在其他产品中使用 ChatGPT 登录时，嗯，你知道的，我们会有一些共享经济模式，他们可以获得报酬。

莱尼 One of the, I don't know, things I think that gets people excited about plugins and ecosystems is distribution platforms, ways to kind of get out there. People discover my app, it blows up. any advice for people that want their plugins to, you know, bubble up, to get discovered? 我不知道，其中一件我认为让人们对插件和生态系统感到兴奋的事情是分发平台，某种方式让人们能够展示自己的作品。别人会发现我的应用程序，然后它会爆红。对于那些希望自己的插件被发现的人，你有什么建议吗？

提博 Build a good plugin. 制作一个好的插件。

莱尼 Yeah. 是的。

提博 The way that it works and we'll obviously tune uh the system, but we look at retention uh numbers, uh we look at um you know, how successful the plugin, the quality, and then you know, that's what we then start to recommend to users uh in conversations. And so, your plugin can just like you know, get recommended to like you know, a significant slice of users. Obviously, if your plugin is not quite good, they will stop being recommended. 它的工作方式是这样的，我们显然会对系统进行调整，但是我们会查看留存率数据，我们会看插件的成功率、质量，然后基于这些，我们会开始在对话中向用户推荐。所以，你的插件可以被推荐给相当一部分用户。显然，如果你的插件不够好，它们就会停止被推荐。

莱尼 Right. That's amazing that you're looking at retention of people using that plugin. That's right. Um is it is it actually adding utility? Is it, you know, enabling ChatGPT to do something else? 对。你关注使用那个插件的人群留存真是太棒了。没错。呃，它实际上是在增加实用性吗？它是在，嗯，让 ChatGPT 做其他事情吗？

提博 Got it. So, it's it's not so much an AEO kind of get the right words and get people writing about you. It's people using it consistently, sticking with it. That's right. I think. 明白了。所以，这不太像是那种 AEO 类型的获取正确用词并让人们写你的东西。更像是人们持续使用它，坚持下去。没错。我想是这样。

莱尼 Okay, so you think that's kind of the sleeper hit that's going to become a big deal. And I know this is kind of the second attempt. You guys had an app marketplace that This one is the right one. Okay, this is This one's going to work. Maybe going back to dots cuz it feels like that's a big part of the vision in the future. When did you guys start working on this? Obviously, there's a open claw, a big open claw moment. You guys Peter joined and there There's a foundation, uh and then Grok Bot, Muse, and Instinct, and all these things. I guess how long have you guys been working on it? Why did it take so long for you guys to get something out? Do you remember a Codex Cloud? 好吧，所以你认为这是那种会意外走红并变得很重要的东西。我知道这是第二次尝试。你们之前有一个应用市场，这一次才是正确的。好吧，这次是会成功的。也许回到点子上，因为感觉那是未来愿景的重要部分。你们什么时候开始做这个的？显然，这是一个公开的关键时刻。你们彼得加入了，有一个基础，然后有 Grok Bot、Muse 和 Instinct，以及所有这些东西。我想问一下，你们到底做了多久？为什么你们花了这么长时间才推出一些东西？你们还记得 Codex Cloud 吗？

提博 Yeah, the first uh yeah. That was like a year ago, right? And uh if you look back at Codex Cloud and you look at the little animation that we used, uh I think that was the inspiration for Grok Bot. 是的，第一次，呃，是的。那大概是一年前，对吧？如果你回顾一下 Codex Cloud，并看看我们使用的小动画，我觉得那就是 Grok 机器人的灵感来源。

莱尼 Um 嗯

提博 Yeah. It's just like very, very similar. 是的。这就像非常、非常相似。

莱尼 Yeah, really similar, I would say. 是的，我会说真的很相似。

提博 But, you know, seriously, like on the research, long, persistent, long horizon task, this is something that we've worked on, you know, for more than 2 years. Memory systems, that's like coherent, you know, like roughly the same amount of time. We launched a lot of that straight into ChatGPT. I think, you know, people just really enjoy that ChatGPT gets to know, like, you know, so much relevant information about you. So many people I talked to have like an anecdote of like, "Hey, you know, I fell ill and, you know, ChatGPT remembered actually, like, you know, I had this barbecue and, you know, I had like lime and I was like making tequila and like, you know, it was just like probably like this burn that I have on my hand is actually like this lime, you know, it's like in some burn." And he's just like, "How did it know that?" And it's like, you know, it's just the memory works very, very well in ChatGPT. And so, we've put a lot of research in that. And, you know, all of this coming together on top of like the Quora harness and also the ability to just like run 24/7 with, you know, good productivity. That's what we launched with dots. And so, it's the work of like many, many months. And then, one of the important things was also getting safety and security right. You know, this is also why we launched with Astra, it's our safest, most aligned model. And like a lot more effort went into like making dots, like, you know, just really safe and secure. 但是，你知道，说真的，就像研究一样，长期、持久、长期的任务，这是我们已经工作了两年多的事情。 记忆系统就像是连贯的，你知道，就像大致相同的时间一样。 我们直接在 ChatGPT 中推出了很多这样的内容。 我想，你知道，人们真的很高兴 ChatGPT 能够了解很多关于你的相关信息。 我采访过的很多人都喜欢这样的轶事，“嘿，你知道，我病了，你知道，ChatGPT 实际上记得，就像，你知道，我吃了烧烤，你知道，我吃了酸橙，我就像制作龙舌兰酒一样，你知道，就像我手上的烧伤实际上就像酸橙一样，你知道，就像在烧伤一样。” 他只是想，“它怎么知道的？” 就像，你知道，ChatGPT 中的内存运行得非常非常好。 因此，我们对此进行了大量研究。 而且，你知道，所有这些都聚集在 Quora 安全带之上，并且还能够以 24/7 的方式运行，并且具有良好的生产力。 这就是我们用点推出的。 所以，这是很多很多个月的工作。 然后，重要的事情之一也是确保安全。 您知道，这也是我们推出 Astra 的原因，它是我们最安全、最一致的模型。 就像我们付出了更多的努力来制作点一样，你知道，真的很安全。

莱尼 A question I like to ask people who come on the podcast is, where do you think human brains will continue to be valuable over time? Where do you find yourself being necessary in the work that happens versus where AI is taking on more and more? Where do you think human brains will continue to be useful, most useful over time? 我喜欢在播客中问来宾的一个问题是，你认为人类的大脑随着时间的推移在哪里会继续有价值？在工作中，你发现自己在哪些方面是必需的，而人工智能在越来越多的地方正在取代人类？你认为人类的大脑随着时间的推移在哪里会继续有用，最有用？

提博 Yes, I I think this is very much a function of how we build the technology in the way that we design everything at OpenAI is like to put humans at the center of it and build it as extensions of humans of of of your will and your taste. And so, just really be like this super empowering thing. Um, I think as long as we continue to do that and it kind of like enables you to just take whatever you wanted to do and, you know, your creativity and your taste and sort of like, you know, expand that, you know, in in a way that feels like awesome in the moment. It's just like really this artistic tool, right? And we may we may not have coders anymore, but we have more builders than ever. And I think there's something that's going to remain, I I know, human about that. Like humans want to learn and see, you know, what other humans are building and you know, I'm like much more interested I'm here I'm you know, I'm not talking to Dot you know, I'm talking to you, right? I think that will remain true for like a very very long time. 是的，我认为这在很大程度上取决于我们如何构建技术，我们在 OpenAI 设计一切的方式就像将人类置于其中心，并将其构建为人类意志和品味的延伸。 所以，就像这个超级赋权的东西一样。 嗯，我认为只要我们继续这样做，你就可以做任何你想做的事情，你知道，你的创造力和品味，你知道，以一种当下感觉很棒的方式扩展它。 这就像真正的艺术工具，对吧？ 我们可能不再拥有编码员，但我们拥有比以往更多的构建者。 我认为，我知道，人类的某些东西将继续存在。 就像人类想要学习和看到其他人正在建造什么一样，我更感兴趣我在这里我是你知道的，我不是在和你说话，你知道吗，我正在和你说话，对吗？ 我认为这将在很长一段时间内保持不变。

莱尼 One of the things that has emerged with engineers especially is in in how their lives have changed is there's a lot more context switching. There's kind of this trend of loneliness that has emerged where they're talking to agents all day instead of other humans. I'm curious how much you think about just like that part of the of the impact AI has on people's lives and just how you might Is there solutions to that? Is there stuff you think about to make that less annoying? 特别是对于工程师来说，一个显而易见的变化是他们的生活发生了很大变化，其中之一就是频繁的上下文切换。出现了一种孤独的趋势，他们整天与机器交互，而不是与其他人交流。我很好奇你有多关注 AI 对人们生活的这种影响，以及你可能有的应对方式。有没有解决方案？你是否考虑过让这种情况不那么烦人？

提博 Yes, all the time. Reducing, you know, configuration fatigue is, you know, one. Um reducing the fact that talking to an agent is like sort of like a solo adventure and you just have this, you know, conversation just with with your one agent and then, you know, you have like many and then you're delegating so many things. A lot of things are going to come together to make it a much more delightful and something that I spend a lot of time the team spend a lot of time thinking about. So, I think, you know, For me, the ideal way to get things done is, you know, would be like to just have it in your physical space. You know, we're just having conversation like we have now. It's able to sort of like, you know, observe, you know, like hear the ideas that we have. We can, you know, jot something down in a white paper on a on a paper, you know, I can maybe like, you know, take that and you know, start building in the background and then you're like, you know, actually have another idea and then you just like it starts building another thing. You can just project it on a screen and then you just talk to it and it's just evolving in a conversation, you know, with other humans and you don't have this fatigue of like having to be like, you know, on this like screen and you're just like, you know, thinking about prompting. It's just like becomes like super natural. That's what we're trending towards, you know, I think we didn't fully get there today, but you know, we'll get there in the future. 是的，一直如此。 减少配置疲劳是其中之一。 嗯，减少这样一个事实：与智能体人交谈有点像一场单独的冒险，你只是与你的一个智能体人进行对话，然后，你知道，你有很多事情，然后你委派了很多事情。 很多事情将结合在一起，使它变得更加令人愉快，这是我和团队花了很多时间思考的事情。 所以，我认为，对我来说，完成工作的理想方式就是将其放在您的物理空间中。 你知道，我们只是像现在一样进行对话。 它能够有点像，你知道，观察，你知道，就像听到我们的想法。 我们可以，你知道，在一张白纸上记下一些东西，你知道，我可能会喜欢，你知道，接受它，你知道，开始在后台构建，然后你就像，你知道，实际上有另一个想法，然后你就像它开始构建另一个东西。 你可以把它投影到屏幕上，然后你就和它说话，它就在与其他人的对话中不断发展，你知道，你不会有这种疲劳，就像必须在这个类似的屏幕上，你知道，想着提示。 就像变得超自然一样。 这就是我们的趋势，你知道，我认为我们今天还没有完全实现这一目标，但你知道，我们将来会实现这一目标。

莱尼 One of the other kind of downsides that's emerged along those lines is just this kind of pressure to do more because we can do more. Everyone's just like, come on, run 30 agents at once. Why aren't you shipping more? Everyone's shipping more. Do you think that's solvable? Do you think that's just kind of, I don't know, human nature? We can do more, let's do more. Something there. 沿着这些方向出现的另一种缺点就是这种压力——因为我们能够做更多，所以我们必须做更多。大家都在说，快点，同时运行 30 个智能体。你为什么不多出产一些？每个人都在多出产一些。你认为这是可以解决的问题吗？你觉得这只是人性吗？我们能做更多，那就做更多。大概就是这么回事。

提博 I think we we we heard Sam as well, you know, about the promise of of this as well, which is reduced the noise and you know, allow you to spend attention where you want to spend attention and you know, having like all these things that you know, like maybe you know, maybe important and maybe not important but they're kind of vying for your attention and it's just sort of like tone that down a little and you know, just get you to focus on on on the things. I find it remarkable like every time I go on a holiday and you know, I I I I take that one week uh to just fully disconnect like you know, I start to thinking like different and more creative ways. And I'm very eager to see like you know, can we bring that? You know, can we just make this your day-to-day like you know, maybe you need fewer meetings. You know, maybe you don't need you know, to do as much and you know, you would actually be more productive if you're like you know, better rested. And so you know, we will have to you know, I think as an industry figure that out. Um but I think that's the promise of AI and it's not you know, just one more prompt you know, per second. 我想我们也听到 Sam 的声音，你知道，关于这个的承诺，这会减少噪音，你知道，让你把注意力花在你想花注意力的地方，你知道，就像所有这些你知道的事情一样，也许你知道，也许重要，也许不重要，但它们会争夺你的注意力，这有点像语气调低一点，你知道，让你专注于事情。 我发现这很了不起，就像每次我去度假一样，你知道，我我我花了一周的时间完全断开连接，就像你知道的那样，我开始以不同的、更有创意的方式思考。 我非常渴望看到像你知道的那样，我们可以带来吗？ 您知道，我们可以像您一样将其作为您的日常工作吗？也许您需要更少的会议。 你知道，也许你不需要做那么多事情，而且你知道，如果你像你知道的那样，休息得更好，你实际上会更有效率。 所以你知道，我认为作为一个行业，我们必须让你知道这一点。 嗯，但我认为这就是人工智能的承诺，它不是你知道的，只是每秒多一个提示。

莱尼 There's a bot that I'm building right now that's kind of this energy audit bot that watches my calendar and asks me just like was this giving energy taking away energy? Is it something someone else could have done? I feel like you know, AI should be like hey Lenny, maybe maybe you can cut out these things so you could be a happier person. Is there anything you've done really interestingly with AI recently that's just like a really cool use case of wow, that really was amazing. It blew my mind or someone you've heard. 我现在正在构建一个机器人，这个机器人有点像一个能量审计机器人，它会查看我的日历，并问我，例如这件事是带来能量还是消耗能量？这是别人能做的事情吗？我觉得人工智能应该像这样对 Lenny 说，也许你可以删掉这些事情，这样你就可以成为一个更快乐的人。你最近有没有用人工智能做过什么非常有趣的事情，这种真的很酷的用例，让人惊叹，或者是你听别人说过的？

提博 I can do was like something cool because the the live demo just failed, right? You know, in front of everyone. So there there was like okay, well, it's not so cool. But actually uh my my my daughter was you know, it's like realized I was you know, I defected like you know, we have chat GPT production um went down and so it pinged me 5 minutes before the live demo. Which was actually quite stressful because it was like hey, production is down. And uh it's like oh well, you know, it's like do you want me to try and fix it? And I'm like um I don't think you're there yet, you know, little dot but you know, thank you for trying and then you know, then you know, I got in touch with like the engineering teams and we started to look, you know, what was going on and you know, they did it's like fixed by now. But, having this thing that just understands like okay, there's a pretty important thing happening. It's called DevDay. There's like this production system. There's a live demo. It's probably using this production system. So, these two are things are connected and this is happening in 5 minutes. So, I should ping him because like he probably wants to know about it. I think that's quite remarkable. That is remarkable. Wow. So, it just knew that this was coming and told you. And I love that it wanted to fix it and you were like, not quite. You're not quite there yet. I don't think here's like, you know, please go impress me, but you know, that would have been a better story. How do you feel about just giving access to all these things? I don't know. Like did does it have access to the production code base and like, you know, It has access to some some of production systems with guardrails. You know, so we we built We talked about specialist dots, but specialist dots are just like operated with additional guardrails, additional monitoring, and then, you know, on their own hardware. So, we actually run some on Mac minis. The fundamental difference in the way that we've built dots is like the harness does not run on the machine. You know, and then this is like maybe people have not realized is like it can connect to as many devices as you want. So, it has its own computer. You can actually connect it to your own laptop as well. Over time, you might connect it to like 10 different devices and it can control it all. A little bit like an octopus. So, you're basically talking your dot, it's living in some VM somewhere and it can Yeah. Might be a VM, might not be a VM. It's just like it's a thing, you know, and it can connect to many devices. 我可以做一些很酷的事情，因为现场演示刚刚失败，对吧？ 你知道，在所有人面前。 所以就好像好吧，好吧，这不太酷。 但实际上，呃，我的我的女儿，你知道，就像意识到我是你知道的，我像你知道的那样叛逃，我们聊天 GPT 生产失败了，所以它在现场演示前 5 分钟通知了我。 这实际上压力很大，因为就像嘿，产量下降了。 呃，就像哦，你知道，就像你想让我尝试修复它吗？ 我想，嗯，我认为你还没有到达那里，你知道，小点，但你知道，谢谢你的尝试，然后你知道，然后你知道，我与工程团队取得了联系，我们开始寻找，你知道，发生了什么，你知道，他们现在已经解决了。 但是，有了这个可以理解的东西，就发生了一件非常重要的事情。 这就是所谓的开发日。 有这样的生产系统。 有现场演示。 它可能正在使用这个生产系统。 所以，这两件事是有联系的，而且这会在 5 分钟内发生。 所以，我应该联系他，因为他可能想知道这件事。 我认为这非常了不起。 这是非常了不起的。 哇。 所以，它只是知道这一切即将到来并告诉你。 我喜欢它想要修复它，而你却觉得，不完全是。 你还没有完全做到这一点。 我不认为这是，你知道，请给我留下深刻印象，但你知道，那会是一个更好的故事。 您对于授予所有这些东西的访问权限有何感想？ 我不知道。 就像它可以访问生产代码库一样，它可以访问一些带有护栏的生产系统。 你知道，所以我们建立了我们谈论过专业点，但专业点就像通过额外的护栏、额外的监控进行操作，然后，你知道，在他们自己的硬件上操作。 所以，我们实际上在 Mac mini 上运行了一些。 我们构建点的方式的根本区别就像线束不在机器上运行一样。 你知道，也许人们没有意识到它可以连接到任意数量的设备。 所以，它有自己的电脑。 实际上，您也可以将其连接到您自己的笔记本电脑。 随着时间的推移，您可能会将它连接到大约 10 个不同的设备，并且它可以控制所有设备。 有点像章鱼。 所以，你基本上是在谈论你的点，它生活在某个虚拟机中的某个地方，它可以是的。 可能是虚拟机，也可能不是虚拟机。 它就像一个东西，你知道，它可以连接到许多设备。

莱尼 This season's supporting sponsor is DX. Now that everybody at your company is finally using AI, the question that engineering leaders face is no longer are we using AI, but is it paying off? With DX, you can measure and benchmark the impact of AI adoption across your full product life cycle. DX shows you where AI is helping developers and where it's creating new bottlenecks. You can also use it to evaluate AI vendors, monitor costs and licenses, and see exactly what's limiting your agents. That's why hundreds of enterprises, including Snowflake, Sony, and BNY, use the DX platform to measure AI's impact on developer productivity. Visit getdx.com/lenny to get a demo of DX. That's getdx.com/lenny. So, they're really hiring a lot. I know you're hiring a lot. In your interviewing, what have you seen as skills that are kind of trending up in what you look for that is more and more important in people being successful now? And what skills do you find are trending down that are just like, okay, we don't need that as much? 本赛季的支持赞助商是 DX。 既然你们公司的每个人最终都在使用人工智能，工程领导者面临的问题不再是我们是否在使用人工智能，而是它是否有回报？ 借助 DX，您可以衡量人工智能在整个产品生命周期中采用的影响并对其进行基准测试。 DX 向您展示人工智能在哪些方面为开发人员提供了帮助以及在哪些方面造成了新的瓶颈。 您还可以使用它来评估人工智能供应商、监控成本和许可证，并准确了解是什么限制了您的智能体。 这就是为什么包括 Snowflake、索尼和 BNY 在内的数百家企业使用 DX 平台来衡量人工智能对开发人员生产力的影响。 请访问 getdx.com/lenny 获取 DX 演示。 那是 getdx.com/lenny。 所以，他们确实在招聘很多人。 我知道你们正在招聘很多人。 在您的面试中，您认为哪些技能在您所寻求的技能中呈上升趋势，并且对于人们现在的成功越来越重要？ 您发现哪些技能呈下降趋势，就像我们不太需要这些技能一样？

提博 Yeah, I would say that skill that is trending down is typing fast. No, that is not that useful anymore. Skills that are trending up is, you know, just great taste, um thinking about the user, connecting to the audience that you're building for. Um a lot of X founders are incredibly successful right now or like you know, there's like repeat founders. We're also finding this like you know, when we're hiring at OpenAI, like you know, we have a lot of founders. I think we have more than 120 XYC founders now currently at OpenAI. So, it's like this mega startup. And I think just this um this passion and this envy to build something that matters and then know what good looks like is more important than ever. I've been arguing for a long time that PMs are kind of going to thrive in this time because that's basically the job of a PM. Uh you know, they're like, where should we build? Help someone build it. And then is this right? Is this great? And iterate. So, uh I don't know. I agree with that. 是的，我想说，正在下降的技能就是打字速度快。 不，那不再那么有用了。 你知道，正在流行的技能就是高品味，嗯，考虑用户，与你正在构建的受众建立联系。 嗯，很多 X 创始人现在都非常成功，或者像你知道的那样，有重复创始人。 正如您所知，我们在 OpenAI 招聘时也发现了这一点，如您所知，我们有很多创始人。 我认为 OpenAI 目前有超过 120 名 XYC 创始人。 所以，这就像一家大型初创公司。 我认为正是这种热情和嫉妒来构建重要的东西，然后知道什么是好的，比以往任何时候都更重要。 很长一段时间以来，我一直认为 PM 在这个时代会蓬勃发展，因为这基本上就是 PM 的工作。 呃，你知道，他们会问，我们应该在哪里建造？ 帮助某人建造它。 那么这是对的吗？ 这很棒吗？ 并迭代。 所以，呃我不知道。 我同意这一点。

莱尼 Yeah. All right. 是的。好吧。

提博 Yeah, also roles are blurring. So, you know, you might you might have been, you know, only into design or only an engineer and um you know, felt always a little bit uncomfortable, but you know, now it's just like it's your time to shine. 是的，而且角色界限也在模糊。所以，你知道的，你可能曾经只是专注于设计或者只是一个工程师，而且，你知道的，总是感觉有点不自在，但现在，你知道的，这就是你大显身手的时候了。

莱尼 Do you miss the engineering part of the job? I I was an engineer back in the day. I was an engineer for 10 years. Little did you know. And you know, there's this flow state. There's this beauty of just building and just seeing it work and not work. Yeah. Do you kind of missed out at all, or you're just like, "Okay, this is my old life." 你怀念工作的工程部分吗？我以前是工程师。我当了 10 年的工程师。你可能不知道。而且，你知道，有一种专注状态。单纯地构建东西，看到它工作和不工作的美妙。你是不是有点怀念，还是只是觉得，“好吧，那是我的过去生活。”

提博 I I I missed out for for a while, and then now with, you know, really fast speeds, I'm finding that back. Uh and so, I'm like really excited to democratize that uh as much as much as possible. It will take a while for it to be like, you know, absolutely ubiquitous, right? And like, you know, available to like more than a billion users. But now, you know, with with ultra-fast speeds, like we're able to achieve it for a 6-month sole is like, you know, like costs roughly the same as Astra. And so, the progress there is like quite astonishing, you know, even even for us internally. We're like, "Wow, you know, we can do these things." Also because we are using Astra, and we're finding, you know, like we we can push it super far. And when you have those speeds, and especially when you can able to like voice control it, you know, you kind of get back into this like really creative state of mind and endless flow. It is different from the flow of the past the past, um but I don't miss it. 我有一段时间错过了这个，然后现在呢，你知道，有了非常快的速度，我又找回来了。呃，所以我真的很兴奋能够尽可能地让它普及。要做到完全无处不在，还需要一段时间，对吧？而且你知道，要让超过十亿用户都能使用，也需要时间。但现在，凭借超快的速度，我们能够在 6 个月的时间里实现这一目标，成本大致与 Astra 相同。因此，这方面的进展相当惊人，即使对我们内部来说也是，我们都在想：“哇，你知道，我们可以做到这些事情。” 另外，因为我们在使用 Astra，我们发现我们可以将它推得非常远。当你拥有这样的速度，尤其是能够通过语音控制它时，你会重新进入一种非常有创造力的状态和无尽的流动。这与过去的流动是不同的，但我并不怀念过去。

莱尼 Yeah, it's like your last you launched videos, just people kind of standing around talking to their AI and just cooking or 是的，就像你最后发布的视频，人们只是站着和他们的 AI 交谈，同时做饭或者其他事情

提博 That's right. 没错。

莱尼 sitting on a lounge chair. Yeah. I asked people while I was kind of walking around the the event what to ask you, and one thing that came up a few times is advice for new grads, kind of people junior in their career. I think a lot of people look up to you. They want to be the next Thibault. What advice do you have for folks kind of early in their career in terms of what to work on, what skills to build, what to do? 坐在躺椅上。是的。我在活动中四处走动时问过别人该问你什么，有一件事被提了好几次，就是给新毕业生的建议，也就是职业生涯初期的人的建议。我想很多人都很崇拜你，他们想成为下一个 Thibault。对于职业初期的人来说，在要努力的方面、要培养的技能、要做的事情上，你有什么建议吗？

提博 Yeah. I think the next Thibault is already at OpenAI. Uh his name is Ahmed Ibrahim. I love working with him. He was a new grad uh when he was hired at OpenAI. He's now responsible for all of OpenAI compute fleet and applied uh which is a massive massive responsibility. I've built a lot of the Codex harness. And the thing that has made Ahmed um really stand out and successful is just his He's incredibly kind. He's incredibly collaborative and always, you know, tries to solve the problem that is like really important, um but like, you know, a way that, you know, he's not putting himself first. And he is just a sponge. He's like learning so fast and learning about everything, and you know using all of the latest technology to you know learn at you know speeds I haven't seen before. Um and so he just in the span of like you know a couple of months and and and a year, you know, it's like his progress uh at the company was just absolutely fascinating to see. Uh he's now someone I trust a ton uh in doing like you know the the the most gnarly launches at OpenAI. 是的。 我认为下一个 Thibault 已经在 OpenAI 了。 呃，他的名字是艾哈迈德·易卜拉欣。 我喜欢和他一起工作。 当他被 OpenAI 聘用时，他还是一名应届毕业生。 他现在负责所有 OpenAI 计算团队并应用呃，这是一个巨大的责任。 我已经制作了很多 Codex 安全带。 让艾哈迈德真正脱颖而出并取得成功的原因是他的善良。 他非常具有协作精神，而且总是试图解决非常重要的问题，但是，你知道，他并没有把自己放在第一位。 而他只是一块海绵。 他学习速度非常快，学习一切，并且使用所有最新技术，以我以前从未见过的速度学习。 嗯，所以他就在几个月、一年的时间里，你知道，他在公司的进步非常令人着迷。 嗯，他现在是我非常信任的人，他会做 OpenAI 最棘手的发布。

莱尼 All right, I got to get him on the podcast. 好吧，我得让他上播客。

提博 You should. You should. 你应该。你应该。

莱尼 So kind of thinking about how things work at OpenAI, what would surprise people about what it's like to work inside OpenAI? From the outside it feels like it's just like constant shipping code, things are kind of like, you know, chaotic but awesome. I don't know. What would surprise people about what it's like inside at OpenAI? 所以考虑一下在 OpenAI 内部是如何运作的，人们会对在 OpenAI 工作的真实情况感到惊讶吗？从外部看，它感觉就像是不断地发布代码，事情有点混乱，但又很棒。我不知道。人们会对在 OpenAI 内部的工作感到什么惊讶呢？

提博 I don't know if that's surprising but it is, you know, as I said, a lot of ex-founders um doing a lot of bottoms-up, you know, very exciting uh ideas. You know, for example, decisions API, you know, came together very quickly. We realized like we have a really good model with Luna. Uh we can just do some, you know, constraint sampling and then, you know, have it, you know, shipped as like a different shape to the responses API and then um you know, when we do that uh it, you know, it's like it's faster. It's quite delightful so for some cases and it's just if you were to like peel under the hood, you realize like, okay, there's a Slack channel that came together. Um you know, initially it was like four people kind of hacking on it on a weekend and then it was made as accessible as like, you know, company food and then people got excited, started to build things and they're like, "Oh, this is, you know, we can support visual inputs. Like this is, you know, even better than whatever is out there." And then, you know, people get more and more excited. People start pitching in. And the way that is like, you know, feels completely unstructured and then um you know, take it all the way and like, you know, ship something. And then uh we try to hold like a high bar for, you know, the quality and then you know, stop things, you know, before they go out or like, you know, maybe they need a little bit more baking. There's many more things that, you know, we were maybe going to ship today at DevDay and then we're like, "Okay, like I was like I think this is a a already. Let's kind of hold it back a little bit and you know, space it out. So, we'll have more launches next week and and and and the week after. But, it's just this incredible like bottoms-up energy and then, you know, people kind of assuming roles to kind of channel that in productive ways. 我不知道这是否令人惊讶，但正如我所说，很多前创始人做了很多自下而上的想法，你知道，非常令人兴奋的想法。 例如，决策 API 很快就整合到了一起。 我们意识到我们有一个非常好的 Luna 模型。 呃，我们可以做一些，你知道，约束采样，然后，你知道，将其作为不同的形状发送到响应 API，然后嗯，你知道，当我们这样做时，呃，你知道，它就像更快。 这是非常令人愉快的，所以在某些情况下，如果你喜欢深入了解，你就会意识到，好吧，有一个 Slack 频道聚集在一起。 嗯，你知道，最初就像是四个人在周末对它进行黑客攻击，然后它变得像公司食物一样易于使用，然后人们很兴奋，开始构建东西，他们就像，“哦，这就是，你知道，我们可以支持视觉输入。就像这样，你知道，甚至比外面的任何东西都好。” 然后，你知道，人们变得越来越兴奋。 人们开始投入。这种方式就像，你知道，感觉完全没有结构，然后嗯，你知道，一路走来，就像，你知道，运送一些东西。 然后，呃，我们试着保持一个高标准，你知道，质量，然后你知道，在它们出去之前停下来，你知道，也许他们需要更多的烘烤。 还有很多东西，你知道，我们可能会在今天的 DevDay 上发布，然后我们会说，“好吧，我想这已经是一个了。让我们稍微推迟一下，你知道，将其间隔开。所以，我们下周和下周将有更多的发布。但是，这就像自下而上的能量一样令人难以置信，然后，你知道，人们会承担一些角色，以富有成效的方式引导它。

莱尼 Something that's very clear and unique about OpenAI is it feels like you have a lot of autonomy. You're just like pressing the reset button whenever you want. You're just saying things on Twitter. Uh it feels like a really unique culture where you have a lot of autonomy and I imagine there comes a lot of trust. Maybe you can speak to just how that cuz I feel like that's an advantage at OpenAI. It allows you to move faster, just that cultural philosophy. 关于 OpenAI，有一件非常清楚而独特的事情，那就是感觉你有很大的自主权。你就像可以随时按下重置按钮一样。你只是随便在推特上说些东西。嗯，这感觉像是一种非常独特的文化，你有很大的自主权，我想这可能带来了很大的信任。也许你可以谈谈这方面，因为我觉得这是 OpenAI 的一个优势。它让你能更快地行动，仅仅是那种文化理念。

提博 You got a lot of autonomy and then, you know, you have to just own up to it. You so, you know, we just kind of trust people to make great choices. And then, you know, when things go wrong, uh you know, fix fix it quickly or, you know, learn from the mistake. So far, so good. You know, it's it's just really worked as a very empowering um environment. It is true that I can press the the reset button whenever you know, is necessary or whenever it feels right. And, you know, that's like it that's a privilege. Uh and also, it allows me to, you know, just really be close to the community in ways that I think, you know, would not be otherwise possible, right? I don't have to run it, you know, through an echelon of approvals. 你有很大的自主权，然后，你知道，你必须为此承担责任。你知道，我们就是相信人们会做出很棒的选择。然后，当事情出错时，你知道，迅速解决，或者从错误中吸取教训。到目前为止，一切都很好。这真的作为一个非常赋权的环境运作得很好。确实，我可以在必要的时候或者感觉合适的时候按下重置按钮。这是一种特权。此外，这也让我可以以一种我认为在其他情况下不可能的方式，真正与社区紧密联系，我不需要经过一系列的审批来运行它。

莱尼 You said sometimes people screw up. Is there something you screwed up in that in that I don't know, that the amount of autonomy and trust you have, something you messed up? 你说人有时候会搞砸事情。有什么事情是你搞砸了吗，我不知道，是不是你拥有的自主权和信任的程度，出了什么差错？

提博 Yes, I I think at times um I could have, you know, made teams like, you know, more inspired to build like things that are less complex uh and just really continue to strive towards uh complexity. I think we, you know, we early days uh in Codex, you know, we had, you know, a couple of like outages that I caused. Very very early early is for me at OpenAI. I took production down like day three. You know, I just I was still employed after that. Um and I learned my lesson. 是的，我觉得有时候，我本可以让团队，更有灵感去构建一些不那么复杂的东西，而不仅仅是不断追求复杂性。我想，在 Codex 的早期阶段，我们出现过几次因为我造成的故障。对我来说，在 OpenAI 我刚开始的非常非常早的阶段，我在第三天就让生产系统瘫痪了。你知道吗，我之后还是继续被雇用。我从中吸取了教训。

莱尼 One of the other questions people wanted me to ask you is how many resets should they expect in the next, I don't know, month or week? 人们还希望我问你的另一个问题是，他们在接下来的，我不知道，一个月或一周内，应该预期多少次重置？

提博 Depends on times you break things. 取决于你打破东西的次数。

莱尼 Okay, so that's the philosophy. Break something you reset. That's kind of a 好的，这就是哲学。破坏一些你重置的东西。这有点像一种

提博 Yeah, break something, celebrate things. 是的，打破一些东西，庆祝事情。

莱尼 So maybe zoom in a little bit. What do you think people aren't pricing in in terms of where things are going and what will change that they're not just like seeing as clearly as they should? 所以也许可以稍微放大一点。你觉得人们在预计事情的发展方向以及会有哪些变化时，没有把这些因素考虑进去的是什么，他们没有像本应那样清楚地看到这些吗？

提博 There are so many so many things that I feel are not yet priced in. I think the majority of actions on the internet will be taken by agents. Models are going to become more cheaper and faster at rates that are quite incredible. We will finally be able to integrate all modalities together in a way that is very seamless. I think, you know, those three I feel like you know, often when I look at what people are building out there it's just like not, you know, just like you're not quite getting it. It's like you know, you're almost there but like you know, if you were just like pushing yourself and just really imagining like all of this being roughly 10 times better than it is today, you know, like in a year. It's like, you know, you would build in a different way. 我觉得还有很多很多事情的价值还没有被充分体现。我认为互联网上的大部分行动将由智能智能体完成。模型将以非常惊人的速度变得更便宜、更快。我们最终将能够以一种非常无缝的方式整合所有的模态。我觉得，你知道，这三点，我觉得你知道，当我看人们在做什么时，常常会觉得，你知道，就是不太对劲，你知道，几乎算是差不多了，但如果你真的推动自己，真正想象一下这一切在大约一年的时间里能比现在提高十倍左右，你知道，你会以不同的方式去构建。

莱尼 Do you see any kind of second order effects that come from that from this world where most actions are being Uh from agents. Agents are probably most traffic's going to come from agents. I don't know. 你是否看到任何第二层次的效应，这些效应来自于这样一个世界，在这个世界里，大多数行动都是由智能体执行的。智能体可能会带来大部分流量。我不知道。

提博 That's right. 没错。

莱尼 You think about some second order effect that emerges out of that? 你有没有考虑过由此产生的一些二阶效应？

提博 Yeah, there there there there are many. Um you know, for for first of all, you know, if you want your product to be successful for agents, you know, it's like you have to build you know, for a certain level of scale. Um we've worked very closely with Notion for example and like when they build their MCP, you know, suddenly it's like, oh well, you know, it's available to all these agents that you know, can actually do do the work and like use that MCP and so they saw like a ton of traffic kind of come in. Um and that puts obviously a lot of strain on the system and you have to figure out the economics of that. And so there's like this tension, you know, between like you know, if you're building products is like you know, do you build an interface or not? And you know, you can kind of hold that back for a while but it is inevitable, right? It's like you know, you're the majority of things are going to be used by agents. Building towards that future I think is very important. The other thing is, you know, on the flip side, you know, building like you know, absolutely delightful new experiences for humans that you know, really benefit from older modalities is something that I you know, I feel like is under invested in. 是的，那里有很多。 嗯，你知道，首先，如果你希望你的产品对智能体商来说是成功的，你知道，这就像你必须建立一定的规模。 嗯，我们与 Notion 进行了非常密切的合作，例如，当他们构建 MCP 时，你知道，突然间，所有这些智能体都可以使用它，你知道，他们实际上可以做工作，喜欢使用 MCP，所以他们看到了大量的流量进来。嗯，这显然给系统带来了很大的压力，你必须弄清楚它的经济效益。 因此，你知道，就像你知道的那样，如果你正在构建产品，就像你知道的那样，你是否构建一个界面？ 你知道，你可以暂时推迟这一点，但这是不可避免的，对吧？ 就像你知道的那样，你的大部分东西都会被特工使用。 我认为朝着这个未来迈进非常重要。 另一件事是，你知道，另一方面，你知道，像你知道的那样构建绝对令人愉快的新体验，你知道，真正从旧模式中受益是我知道的，我觉得投资不足。

莱尼 Is there something you've changed your mind about in the past uh let's say year? Just something that you used to believe that you see differently? 在过去的一年里，你有没有对某些事情改变过看法？只是一些你以前相信的东西，现在你看法不同了？

提博 I was expecting us to reach the level of capabilities the of the models that we have today, you know, say like Astra, you know, maybe in a year or two. Um and so I had to sort of like you know, revise my my prior order. Also, I did not expect to rely so much on voice. Um and you know, I do so much through dictation or just calling my agent. And I had not anticipated that, you know, how much how much better that feels. So like I I had to change my mind there. And then, you know, you talked about hiring and you know, one thing that I hadn't realized is like the incredible talent and energy and you know, the just you younger generations have um and how they would be the ones embracing like all this change first and like figure out how to harness, you know, all of it. And so, you know, I had to change also my opinion on the hiring and the strategy there. 我原本以为我们会达到像今天的模型那样的能力水平，你知道，比如 Astra，可能在一两年内。嗯，所以我不得不去调整我之前的计划。此外，我没想到会那么依赖语音。嗯，你知道，我做这么多事情都是通过口述或者直接打电话给我的助手。我之前没预料到，这会带来多大的便利和舒适。所以，我不得不在这方面改变我的想法。然后，你提到招聘问题，你知道，我之前没有意识到年轻一代拥有多么出色的才华和活力，他们会是最先拥抱所有这些变化的人，并且会想办法去利用这些变化。所以，我也不得不改变我对招聘和那方面战略的看法。

莱尼 The just to double down on that, just this idea that new people new in the workforce actually have an advantage because they haven't worked in a certain way and they could just go all in on AI. 只是为了加倍强调这一点，仅仅是这个想法：刚进入职场的新员工实际上有优势，因为他们没有按照某种特定方式工作过，他们可以全身心投入人工智能。

提博 Yeah. Yeah. And I think I just also the ability to just like absorb and learn like super fast. 是的，是的。我觉得我还有那种能够非常快地吸收和学习的能力。

莱尼 So you talked about models getting really smart fast. Uh obviously there's a lot of discussion these days about what AI can do in the future, the dangers AI poses to humans, P doom, and all these things. Uh you guys have slowed down some training. Uh you guys everyone's pacing the frontier. How do you think about this world of AI and the potential risk to the humans? How do you think about that? 所以你刚才谈到了模型变得非常快地智能化。呃，显然如今有很多讨论关于人工智能将来能做什么，人工智能对人类的危险，末日预期，以及所有这些事情。呃，你们已经放慢了一些训练。呃，你们每个人都在调整前沿的步伐。你是如何看待这个人工智能世界以及对人类的潜在风险的？你是如何思考这个问题的？

提博 For me like pacing the frontier is just really investing ahead, right? And also investing way more, you know, than we even think, you know, like we ought to. Uh investing in the alignment and safety of the models, investing in uh security, investing in the guardrails. We are spending more and more compute on sort of like secondary monitoring. So, you have you know, you have all of the computer that's going to the primary system, you know, the agent that is like doing work. And then you have all of the computer that's going into monitoring, you know, the primary agent to make sure that it's like not taking too high risk of actions or like not interrupting it if anything looks like you know, maybe it's getting prompt injected and just like you know, intervening with that. And the majority of our investment on the API stack is like not actually going into the safety stack. And so to me, you know, that is pacing. It's like you know, you want to make sure that you know, you're extremely hardened. That's what we're doing. Like we haven't yet released the next step up in capability beyond Astra. Um we have released, you know, a level that is like similar, near Astra intelligence, but like you know, much more efficient. And so we feel very comfortable about that. But we're going to continue to like invest a ton there. And I feel uh I feel very good um about our approach so far. Um I think you know, it's like it was also in the news that you know, we had six one Astra and then we didn't release it. Um and that is something I'm very proud of. 对我来说，在前沿领域踱步就是真正的提前投资，对吗？ 而且投资也比我们想象的要多，你知道，就像我们应该做的那样。 呃投资于模型的对齐和安全性，投资于呃安全性，投资于护栏。 我们在二级监控上花费了越来越多的计算。 所以，你知道，你拥有所有进入主系统的计算机，你知道，智能体就像在做工作一样。 然后你拥有所有要进行监控的计算机，你知道，主要智能体确保它不会冒太大的风险，或者如果有任何事情看起来像你知道的那样，不会中断它，也许它正在被迅速注入，就像你知道的那样，进行干预。 我们在 API 堆栈上的大部分投资实际上并没有进入安全堆栈。 所以对我来说，这就是节奏。 就好像你知道，你想确保你知道，你非常坚强。 这就是我们正在做的事情。 就像我们还没有发布超越 Astra 的下一步功能一样。 嗯，我们已经发布了，你知道，一个类似于阿斯特拉智能的水平，但正如你所知，效率更高。 所以我们对此感到非常放心。 但我们将继续在那里投入大量资金。 我觉得，呃，我对我们迄今为止的做法感觉非常好。 嗯，我想你知道，就像新闻中也提到过，我们有六辆阿斯特拉，然后我们没有发布它。 嗯，这是我非常自豪的事情。

莱尼 So, what I'm hearing is you're optimistic we will solve these problems of alignment and AI doing really bad things. AI's been doing a lot of really really s- not good things lately with hugging face and all that stuff. But what I'm hearing is uh optimistic we'll solve it. It'll be all right. 所以，我听到的是，你对我们能解决这些对齐问题以及人工智能做非常糟糕事情的问题感到乐观。人工智能最近一直在做很多非常非常不好的事情，比如 Hugging Face 之类的东西。但我听到的是，你很乐观我们会解决这些问题。一切都会没事的。

提博 Yes. And it's also it's it's I feel, you know, obviously a deep responsibility, but also just, you know, if you think about the incentives for OpenAI, right? you know, we build products for 1.2 billion people. We can't screw that up. Right? You know, we take it very very seriously. Um what we put in the hands of so many people, you know, including people who are not very technical themselves, you know, you have to get it right. And so, you know, we we don't gamble there. 是的。而且我也觉得，你知道，这显然是一种深重的责任，同时，你知道，如果你考虑一下 OpenAI 的激励机制，对吧？你知道，我们为 12 亿人开发产品。我们不能把事情搞砸，对吧？你知道，我们非常非常认真对待这件事。我们交到这么多人手中的东西，包括那些技术水平不高的人，你必须把它做对。所以，你知道，我们不会在这上面赌运气。

莱尼 Final question. Uh uh What's something that annoys you about the current state of the app that you're just like, "God damn it, we got to fix that." Uh current state of the app. Um I feel like the the the models are almost there, but not quite for the app to almost completely disappear. And you know, I can't wait for you know, to just really get to this like super essence of simplicity. I myself even get fatigued with the model picker and the reasoning efforts and you know, whether to use multi-agent or ultra or you know, what it even does and you kind of need a PhD in model pickers. Right? Um and I just want to get rid of all of that um as quickly as we can. Amazing. Ebo, thanks for doing this. 最后一个问题。嗯，嗯，目前应用的状态中，有什么事情让你感到烦恼，让你觉得，“该死，我们得解决这个问题。”嗯，目前应用的状态。嗯，我觉得模型几乎准备好了，但还不完全，应用几乎可以完全消失。你知道，我迫不及待地想真正达到这种极致的简洁。我自己甚至对模型选择器和推理过程感到疲惫，不管是使用多智能体还是超模式，或者，它到底做什么，你几乎需要有模型选择方面的博士学位，对吧？嗯，我只想尽快摆脱所有这些。太棒了，Ebo，谢谢你做这个事情。

提博 Yeah, thanks for having me. Yeah. 是的，谢谢你邀请我。是的。

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