为何互联网上的大多数操作将很快由 AI 代理完成

我是说，Evo，谢谢你接受采访。

I mean, Evo, thank you for doing this.

是啊，我是你的超级粉丝。

Yeah. Big fan of you.

当然。这房间不错。

Of course. Nice room.

你今天发布了一大堆东西。你睡得怎么样？你睡得好吗？你还好吗？

You launched a ton of stuff today. How did your sleep? How are you sleeping? Are you doing all right?

我很好。我很幸运有一个非常优秀的团队。所以，当我睡觉时，他们大部分时间都醒着。我们在办公室有一个很棒的房间叫图书馆，我们把它完全改造成了大型作战室。那里的氛围简直完美。人们在那里待到很晚很晚。

I'm doing great. I'm fortunate to have a very good team. So, while I sleep, they were awake most of the night. We have this amazing room at the office called the library, which we completely repurposed as a mega war room. And the vibes in there are just immaculate. People were there until very, very late.

那么，你一直是一名工程师。你现在还写代码吗？你还在提交 PR 吗？你现在主要是在文档和会议中吗？

So, you've been a long-time engineer. Are you coding at all anymore? Are you shipping PRs? Are you mostly in docs and in meetings now?

什么是写代码？

What is coding?

没错。是啊。你还在提交 PR 吗？我不知道。那是

Exactly. Yeah. Are you shipping PRs? I don't know. Is that

是的，是的，是的。偶尔合并一些代码。从技术上讲，很多代码是为我写的，用来做各种分析，比如了解趋势、了解业务、了解下一个功能、我们之前的发布效果如何。很多代码是由 Codex for dot 写的。显然我不再手写了。偶尔，在周末，我会有一个小小的治疗时刻，手写一点代码。但那是唯一真正的手工编码。

Yeah, yeah, yeah. Merging some code every once in a while. Technically, a lot of code is getting written for me to do all sorts of kinds of analysis, like understand trends, understand a business, understand the next feature, how well our previous launches are doing. A lot of code is written by Codex for dot. I'm obviously not writing it by hand anymore. Occasionally, during the weekends, I'll have a little therapeutic moment where I do a little lead code just by hand. But that's the only actual hands-coding that I do.

在你的日常工作中，你发现自己并行运行多少个智能体？

How many agents do you find yourself running in parallel just in your day-to-day work?

我以前并行运行更多，然后我们幸运地取得了 ultrafast 的突破。所以现在，我觉得我又能进入心流状态了，所以拥有一个更快的智能体对我帮助很大。我很兴奋我们很快会推出 6 个月大的 ultrafast。然后，是的，我认为这因人而异。当我在不同领域推进时，我发现自己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，突然就像，哦，一个更大的智能体就能完成所有事情，并且把所有东西都保存在记忆中并学习。所以，我又缩小了团队。然后，它就这样经历扩张和收缩的循环。

I used to run a lot more in parallel and then we were fortunate enough to get a breakthrough with ultrafast. And so, now, I feel like 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 6-month-old ultrafast out there soon. And then, yeah, I think it varies. As I'm pushing different here, I find myself building larger and larger teams of agents. And then, when we have the next breakthrough with models, suddenly it's just like I am like, oh, well, 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 expansion and shrinking expansion.

嗯，好的。你能多谈谈这个吗？这让我想到有整个循环的东西，然后整个图的东西。这是某种进化吗，还是

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

我认为必须设置和摆弄循环并弄清楚这一点，可能是人们兴奋的事情，但我不认为这是未来的工作方式。我认为未来的工作方式是我们如何定位以及我们通过 dots 发布的内容，你有一个极其智能的智能体，它 24/7 工作，理解你的目标，理解你的偏好，从反馈中学习。就像我们发布的东西，不，完美。我将从向我们的专业用户提供这个中学到很多。但随着时间的推移，只想要一个从你想实现的目标中学习的系统。你不必一定要考虑小时，比如我要这样循环才能得到结果。所以，现在有 Codex，有 ChatGPT work，有 ChatGPT consumer，有 dots。我听到的是你认为我们正朝着 dots 成为与 AI 对话的主要方式，并引发所有其他事情。

I think like having to set up and fiddle with your loops and figuring that out is something that 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 how we're positioning 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. And it's like what we launched is like, no, perfect. I will learn very much from making this available to our pro users. But over time, just want a system that learns from 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. 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.

是的，我认为从根本上说，如果你退一步看，无论是不是 dots，关键是要摆脱技术的束缚，拥有这种永久活跃的智能，它知道它需要做的一切，并且可以通过任何客户端、任何屏幕访问。你可以调用它，也许你走进会议室，它出现在会议中，做笔记，你在电子邮件中重新拿起它，然后如果需要就发短信给它。这不是说你必须粘在笔记本电脑上或总是盯着手机。它就像在你需要时可用，然后在不需要时让开。我迫不及待地希望这能实现，因为我认为像砖头一样到处携带笔记本电脑，就像你被技术束缚，而不是技术为你工作。

Yeah, I think fundamentally if you take a step back and whether it's dots or not, it's all about breaking free from the technology and having this sort of permanent active intelligence that knows everything it needs to do and is available through any client, any screen. You can call it, maybe you walk into a meeting room, it shows up in the meeting, it takes notes, you pick it back up on email, and then you text it if you need it. It's not that you need to be glued to a laptop or 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 for that to sort of come to fruition because I think like just carrying your laptop as like this brick around everywhere is just like, you're kind of like tied to the technology instead of the technology working for you.

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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.

我投资的每一家开始向高端市场扩张的初创公司，最终都会和 WorkOS 合作。因为他们是最好的。无论你是种子轮初创公司，想拿下第一个企业客户，还是独角兽公司在全球扩张，WorkOS 都是成为企业级就绪、解锁增长的最快路径。它本质上就是企业级功能的 Stripe。访问 workos.com 开始使用，或者直接去他们的 Slack，那里有真正的工程师等着回答你的问题。WorkOS 让你用令人愉悦的 API、全面的文档和流畅的开发者体验更快地构建。今天就上 workos.com，让你的应用企业级就绪。

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.

我正想问你这个问题。感觉过去两年里我们的工作方式变化太大了。两年间，尤其是工程师，但很多角色的日常工作都发生了显著变化。我很好奇，你觉得我们是不是正在稳定下来，进入未来五年工作的样子？或者就说两年吧，感觉想太远也不现实。还是说你觉得工作方式还会有更剧烈的变化？

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?

不，我认为工作方式还会继续发生相当剧烈的变化。即使在今天，技术似乎终于开始融合语音、多模态输入输出，但感觉还是有点笨拙，我觉得它会一直笨拙，直到突然不笨拙了。然后你就会想：“哇，我可以像我们现在这样跟它说话。它能完美地记住事情。如果我想构思和头脑风暴，我可以随便画个东西。我有一个协作界面。”你知道，这就是我们推出 ChatGPT spaces 时做的，向各种初创公司发出信号。你可以想象我们有一个共享白板，可以在人类之间、智能体之间协作。我认为它会超越对话，超越你今天使用的很多客户端。而所有这些今天都还没有真正实现，对吧？所以，我认为我们会经历一场巨大的新变革。

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.

我听到的是，dots 是那个未来的重要部分，这个 AI 助手能为你做所有事情，你不需要考虑 Codex 还是 ChatGPT，而且

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

是的，对于 Codex 和 ChatGPT，我们会合并，我们有聊天，我们有工作切换。我们清楚地听到了反馈。人们喜欢工作中的能力，但有时你想用聊天，因为它更快一点，用起来更愉快。所以我们要合并它们，减少复杂性。最终，我们会把 Docs 的所有能力直接发布到 ChatGPT 中，为我们的 12 亿用户提升底线，到时候我们看看有多少用户。我们希望它非常无缝。我对 Docs 非常兴奋的一点是，它们没有模型选择器。没有配置。你只需要跟它说话。唯一需要配置的是你想通过哪些渠道跟它说话。

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.

这感觉很像《她》那种世界观。我不知道。你经常想那部电影吗？就是这种想法

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

我看过一次。是的。我觉得思考这个很有趣，也许我更多想的是三四十年前的科幻，以及它有多么有远见。

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.

有没有特定的科幻作品对你影响最大？

Is there specific sci-fi you think about that's most influenced you?

比如《神经漫游者》这样的书，还有原版《星际迷航》。我经常想这些。我觉得《星际迷航》里有些东西，有一种非常有用的技术。显然，你可以直接跟电脑说话，它为你做事。你可以跟你的飞船说话，它就移动了，对吧？这正在变成现实，我们正在进入那个时代。

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.

我们在现场观众面前录制。门外排着队，人们等着见你、听你讲话。你怎么看待你所处的这个角色，以及你肩负的构建这些东西的责任，还有它对人们生活的影响。我不知道。那是什么感觉？你怎么想？

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?

我认为成为社区的一部分并与人们一起构建非常重要。就像我们正在发现这项技术，以及我们可以一起做什么。所以每次我和人们交谈，我都会想起，你正在做这件事，我甚至没有预料到。它以某种方式影响你的生活，也影响了另一个人的生活，然后所有这些加在一起。这既非常令人谦卑，也非常鼓舞人心，我认为这对于构建真正对人类有用的东西是非常必要的。我不知道没有社区我们怎么做得到。

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.

我经常听到构建 AI 的人说，他们不知道它是什么，直到发布后看到人们如何使用它，看到什么涌现出来。感觉你说的就是和人们一起构建，而不是说“这是愿景，我们已经想清楚了”。

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.

甚至 Twitter 社区总体上也非常友好。

Even the Twitter community has been very nice in general.

你很擅长 Twitter。有时有点对抗性，但很擅长。你怎么找到时间发推的？我不理解像你这样的角色怎么有时间坐在 Twitter 上发推、回复。

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.

我每天大概花半小时。是的，就是滚动浏览，然后当我受到启发、有有趣的话要说时就发。通常就是当下想到的。是的。

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.

完美的 Twitter 技巧。

Perfect Twitter skill.

我有一个——我们还没有发布团队 dots，但今天我们发布主要 dot，你可以配置它，习惯 dot 能做什么，把它连接到你的应用。但我们会发布创建多个的能力。所以我有一个负责 Twitter。

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.

好的，多说一点。所以现在每个人得到一个 dot。

Okay, say more about that. So right now everyone gets one dot.

是的。

Yeah.

现在他们不能添加更多 dots。

Right now they can't add more dots.

没错。

That's right.

他们将能够拥有许多 dots。谈谈那会怎么发展。

They will be able to have many dots. Talk about kind of where that's going.

是的，所以我们想从一个主要的 dot 开始，这个 dot 会最深入地学习你的偏好，看看人们会怎么用它，看看我们需要如何调整系统，在与社区的协作中学习。然后很快你就能添加第二个、第三个、第四个，你需要多少就加多少，来创建你的虚拟团队。然后你可以给它们分配特定的角色，对吧？并不是——我不觉得这是绝对必要的，但有时我有一件事需要相当多的工作，比如替我监控 Twitter。然后这件事的工作量会大到像一个完整的 dot 的工作。然后你可以有几个这样的 dot。

Yeah, so we wanted to start with one, the primary dot, which is the one that learns your preferences most deeply, and see what people do with it, see how we need to tune the system, learn that working with the community. And then very quickly soon you'll be able to add a second one, a third one, a fourth one, as many as you need to create your virtual team. And then you can give them specific roles, right? It's not—I don't find it absolutely necessary, but sometimes I have a thing that requires quite a bit of work, such as monitoring Twitter for me. And then that's a thing that will be so much work that it's like the work of an entire dot. And then you can have a couple of those.

所以如果你想想今天所有的发布，感觉 dots 可能是最吸引人的。我很好奇，有没有什么是你觉得没有得到应有关注、但未来会变得非常非常重要、人们还没意识到的东西，像是一种愿景。

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 people are sleeping on, that's like a vision.

是的，是的，是的，很重要。

Yeah, yeah, yeah, important.

那个被忽视的爆款是生态系统。

The sleeper hit is ecosystem.

所以就是把它全部开放。以及我们对于全部开放的承诺，那种深度的承诺。我们和 ChatGPT 签署了 16 个合作伙伴。非常非常自豪。我们开始做这件事的时候——去年那个时候，有点像灵光一现。我当时在和 Pi 和 open code 的创作者聊天，然后就说，当然，你知道，你应该能够直接用这个 sign on，然后你使用用量，然后你就——我们差不多是握了握手，你知道，虚拟地握手，我们说，就用这个，然后信任你不会做什么见不得人的事。这显然发展起来了，变得相当受欢迎。然后现在我们把它变成了一个实际的东西，得到了很多很多合作伙伴的支持。我很兴奋能快速扩展它。另一方面是开放所有基础设施，以及我们如何为 ChatGPT 构建，包括插件扩展、插件发现，让每个人都能通过大约 12 亿用户发布东西，对吧？并从这种分发中受益。我们还有共享经济，我们在主题演讲中其实没有谈到，但我们会向那些受欢迎、使用量大的插件付费。它们也会获得一部分收入分成。所以我认为这种对开放生态系统的承诺会非常令人兴奋。

So opening it all up. 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. We started that really—it was sort of like in the moment last year. 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 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 off and then kind of trust you to not do anything shady. That grew obviously, that became quite popular. And then now we made it an actual thing that was supported with many, many partners. And I'm excited to grow that very quickly. The other side as well is like opening up all of the infrastructure and how we build for ChatGPT, with plug-in extensions, also plug-in discovery, just allowing everyone to ship something through maybe 1.2 billion users, right? And benefiting from that distribution. And we also have shared economics that we didn't actually talk about in the keynote, but we will pay our plug-ins that are popular and are seeing a lot of usage. They're going to get part of the revenue share as well. And so I think this commitment towards an open ecosystem is going to be very exciting.

太棒了。好，举个例子，比如说 Notion，有人在 ChatGPT 里使用 Notion 插件或 Figma 插件，Notion、Figma 能从人们在应用内使用它们中赚钱。

That's amazing. Okay, so as an example, so say Notion, somebody's using the Notion plug-in or the Figma plug-in within ChatGPT work, Notion, Figma make money from people using it within the app.

是的，所以我们有所有这些使用 ChatGPT 的订阅者，他们获得一定的用量，然后当用户把用量用在插件上，或者在另一个产品里使用 ChatGPT 登录时，我们会和他们有共享经济，他们能获得报酬。

Yes, so we have all these subscribers that use ChatGPT, they get a certain amount of usage and then when the users use that usage with the plugin, or within the other product when they use sign-in with ChatGPT, we will have some shared economics with them where they will get to remunerate.

我觉得让人们兴奋的关于插件和生态系统的一件事，我不知道，就是分发平台，一种走出去的方式。人们发现我的应用，它就爆了。对于那些想让自己的插件冒出来、被发现的人，你有什么建议吗？

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 bubble up, to get discovered?

做一个好插件。

Build a good plugin.

是的。

Yeah.

它的运作方式，我们显然会调整系统，但我们看留存数据，我们看插件有多成功、质量如何，然后我们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大一部分用户。显然，如果你的插件不够好，它们就会停止被推荐。

The way that it works and we'll obviously tune the system, but we look at retention numbers, we look at how successful the plugin, the quality, and then that's what we then start to recommend to users in conversations. And so, your plugin can just get recommended to a significant slice of users. Obviously, if your plugin is not quite good, they will stop being recommended.

对。你们在看人们使用那个插件的留存，这太棒了。没错。它是否真的增加了效用？它是否让 ChatGPT 能做别的事情？

Right. That's amazing that you're looking at retention of people using that plugin. That's right. Is it actually adding utility? Is it enabling ChatGPT to do something else?

明白了。所以，这不太像 AEO 那种用对词、让人们写你。而是人们持续使用它、坚持用它。没错。我想是这样。

Got it. So, 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.

好，所以你认为那是被忽视的爆款，会变成大事。我知道这算是第二次尝试。你们之前有一个应用市场——这次是对的。好，这次会成功。也许回到 dots，因为感觉那是未来愿景的一大部分。你们什么时候开始做这个的？显然，有一个 open claw，一个重大的 open claw 时刻。你们 Peter 加入了，有一个 foundation，然后 Grok Bot、Muse、Instinct，所有这些。我猜你们做了多久了？为什么你们花了这么长时间才拿出东西？

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 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's a foundation, 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?

你还记得 Codex Cloud 吗？

Do you remember a Codex Cloud?

是的，第一个，嗯，是的。

Yeah, the first uh yeah.

那大概是一年前，对吧？如果你回头看 Codex Cloud，看看我们用的那个小动画，我觉得那就是 Grok Bot 的灵感来源。

That was like a year ago, right? And if you look back at Codex Cloud and you look at the little animation that we used, I think that was the inspiration for Grok Bot.

嗯

Um

是的。就是非常非常相似。

Yeah. It's just like very, very similar.

是的，我会说真的很相似。

Yeah, really similar, I would say.

但是，说真的，在研究方面，长期、持久、长时程的任务，这是我们做了两年多的事情。记忆系统，连贯的记忆系统，大概也是同样长的时间。我们把很多这些东西直接发布到了 ChatGPT 里。我觉得人们真的很喜欢 ChatGPT 能了解你这么多相关信息。我交谈过的很多人都有这样的轶事，比如，“嘿，我生病了，ChatGPT 居然记得，我搞了个烧烤，我有青柠，我在做龙舌兰酒，然后我手上这个烧伤可能就是这个青柠，像是某种烧伤。”然后他就说，“它怎么知道的？”就像，记忆在 ChatGPT 里运作得非常非常好。所以，我们在那上面投入了很多研究。所有这些结合在一起，再加上 Quora harness，以及能够 24/7 以良好生产力运行的能力。这就是我们发布 dots 时带来的东西。所以，这是很多很多个月的工作。然后，重要的事情之一也是把安全和保障做好。这也是为什么我们随 Astra 一起发布，它是我们最安全、最对齐的模型。

But, you know, seriously, like on the research, long, persistent, long horizon task, this is something that we've worked on for more than 2 years. Memory systems, that's like coherent, roughly the same amount of time. We launched a lot of that straight into ChatGPT. I think people just really enjoy that ChatGPT gets to know so much relevant information about you. So many people I talked to have an anecdote of like, "Hey, you know, I fell ill and ChatGPT remembered actually, like, I had this barbecue and I had like lime and I was like making tequila and like, it was just like probably this burn that I have on my hand is actually like this lime, 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 all of this coming together on top of like the Quora harness and also the ability to just run 24/7 with good productivity. That's what we launched with dots. And so, it's the work of many, many months. And then, one of the important things was also getting safety and security right. This is also why we launched with Astra, it's our safest, most aligned model.

我喜欢问来播客的人一个问题：你认为随着时间推移，人类大脑在哪些方面会继续有价值？在哪些工作中你觉得自己仍然不可或缺，而哪些又越来越多地被 AI 接手？你觉得人类大脑在未来会继续在哪些地方最有用？

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 most useful over time?

是的，我认为这在很大程度上取决于我们如何构建这项技术。我们在 OpenAI 设计一切的方式，就是把人类放在中心，把它构建成人类意志和品味的延伸。所以它真的会变成一种超级赋能的东西。我认为只要我们继续这样做，它就能让你把你原本想做的事、你的创造力和品味，以一种当下感觉很棒的方式扩展出去，它真的就是一种艺术工具，对吧？我们可能不再有程序员，但会有比以往更多的构建者。我认为这其中有一些东西会一直保持人性。人类想要学习，想看看其他人类在构建什么。我更感兴趣的是——我在这里，我不是在和 Dot 说话，我是在和你说话，对吧？我认为这一点会在很长很长的时间里依然成立。

Yes, I think this is very much a function of how we build the technology. The way we design everything at OpenAI is to put humans at the center of it and build it as extensions of humans, of your will and your taste. So it really becomes this super empowering thing. I think as long as we continue to do that and it enables you to take whatever you wanted to do, your creativity and your taste, and expand that in a way that feels awesome in the moment, it's just really this artistic tool, right? And we may not have coders anymore, but we have more builders than ever. And I think there's something that's going to remain human about that. Humans want to learn and see what other humans are building. I'm much more interested—I'm here, I'm not talking to Dot, I'm talking to you, right? I think that will remain true for a very, very long time.

尤其是在工程师身上出现的一件事，就是他们的生活发生了变化——有更多的上下文切换。还出现了一种孤独的趋势，他们整天和智能体说话，而不是和其他人。我很好奇你有多常思考 AI 对人们生活影响的这一部分，以及你可能如何——这有解决方案吗？你有没有在思考一些东西，让它变得不那么烦人？

One of the things that has emerged with engineers especially is in how their lives have changed—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 that part 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?

是的，一直在想。减少配置疲劳是其中之一。减少这样一种情况：和智能体对话就像一场独自的冒险，你只是和你的一个智能体对话，然后你有很多个，然后你委派很多事情。很多方面会结合起来，让它变得更令人愉悦，这是我花很多时间、团队花很多时间思考的事情。所以，我认为，你知道，

Yes, all the time. Reducing configuration fatigue is one. Reducing the fact that talking to an agent is like a solo adventure and you just have this conversation just with your one agent and then you have 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 spends a lot of time thinking about. So, I think, you know,

对我来说，完成事情的理想方式就是把它放在你的物理空间里。我们就像现在这样对话。它能够观察、听到我们有的想法。我们可以在白纸、纸上记下一些东西。我也许可以拿过来，开始在后台构建，然后你实际上又有了另一个想法，它就开始构建另一个东西。你可以把它投射到屏幕上，然后你只要和它说话，它就在与其他人的对话中不断演进，你不会有那种必须待在这个屏幕上、只想着提示词的疲劳。它就变得非常自然。这就是我们正在趋向的方向。我认为我们今天还没有完全达到，但未来我们会达到。

For me, the ideal way to get things done would be to just have it in your physical space. We're just having conversation like we have now. It's able to observe, hear the ideas that we have. We can jot something down on a white paper, on a paper. I can maybe take that and start building in the background and then you actually have another idea and then it just 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 with other humans and you don't have this fatigue of having to be on this screen and you're just thinking about prompting. It just becomes super natural. That's what we're trending towards. I think we didn't fully get there today, but we'll get there in the future.

沿着这些思路出现的另一个缺点，就是这种因为能做更多而要做更多的压力。每个人都像在说，来吧，同时运行 30 个智能体。你为什么不多发布一些？每个人都在发布更多。你觉得这是可以解决的吗？你觉得这只是，我不知道，人性吗？我们能做更多，那就做更多。大概是这样。

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.

我想我们也听 Sam 说过这方面的承诺，就是减少噪音，让你把注意力花在你想要花的地方。所有这些也许重要也许不重要但都在争夺你注意力的东西，稍微把它们调低一点，让你专注于那些事情。我觉得很了不起——每次我去度假，我花那一周完全断开连接，我开始以不同的、更有创造性的方式思考。我非常渴望看到，我们能不能把那种状态带过来？我们能不能让这成为你的日常？也许你需要更少的会议。也许你不需要做那么多，如果你休息得更好，你实际上会更有效率。所以我认为，作为一个行业，我们必须弄清楚这一点。但我认为这就是 AI 的承诺，而不仅仅是每秒多一个提示词。

I think we heard Sam as well about the promise of this as well, which is reduce the noise and allow you to spend attention where you want to spend attention. Having all these things that maybe are important and maybe not important but they're kind of vying for your attention, and it's just sort of tone that down a little and just get you to focus on the things. I find it remarkable—every time I go on a holiday and I take that one week to just fully disconnect, I start to think in different and more creative ways. And I'm very eager to see, can we bring that? Can we just make this your day-to-day? Maybe you need fewer meetings. Maybe you don't need to do as much and you would actually be more productive if you're better rested. And so we will have to, I think as an industry, figure that out. But I think that's the promise of AI and it's not just one more prompt per second.

我现在在构建一个机器人，有点像能量审计机器人，它观察我的日历，问我这件事是给我能量还是消耗能量？这是不是别人也能做的事？我觉得 AI 应该像这样：嘿 Lenny，也许你可以砍掉这些事情，这样你可以成为一个更快乐的人。你最近有没有用 AI 做过什么非常有趣的事情，就像一个非常酷的用例，哇，那真的很棒，让我大开眼界？或者你听说过的某个人。

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 AI should be like hey Lenny, 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.

我能做的是像一件很酷的事，因为现场演示刚刚失败了，对吧？在所有人面前。所以就像，好吧，这不太酷。但实际上，我的女儿——它意识到我——我叛变了——我们的 ChatGPT 生产环境宕机了，所以它在现场演示前 5 分钟 ping 了我。这其实压力很大，因为它说：嘿，生产环境宕机了。然后它说：哦，你想让我试着修复它吗？我说：我觉得你还没到那一步，小 Dot，但谢谢你的尝试。然后我联系了工程团队，我们开始查看发生了什么，他们做了——现在已经修复了。但拥有这样一个东西，它能理解：好吧，有一件相当重要的事情正在发生。它叫 DevDay。有一个生产系统。有一个现场演示。它可能正在使用这个生产系统。所以这两件事是相关的，而且这将在 5 分钟后发生。所以我应该 ping 他，因为他可能想知道这件事。我觉得这相当了不起。

I can do was like something cool because the live demo just failed, right? In front of everyone. So there was like okay, well, it's not so cool. But actually my daughter was—it's like realized I was—I defected like—we have ChatGPT production 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 it's like oh well, do you want me to try and fix it? And I'm like, I don't think you're there yet, little Dot, but thank you for trying. And then I got in touch with the engineering teams and we started to look at what was going on and they did—it's 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 this production system. There's a live demo. It's probably using this production system. So these two things are connected and this is happening in 5 minutes. So I should ping him because he probably wants to know about it. I think that's quite remarkable.

这确实了不起。哇。所以，它就知道这件事要发生了，然后告诉了你。我喜欢它想修复它，而你说，还不行。你还没到那一步。

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.

你怎么看待把访问权限开放给这些东西？它能访问生产代码库吗，还有，你知道，一些生产系统？

How do you feel about just giving access to all these things? Does it have access to the production code base and, you know, some of the production systems?

它能访问一些带护栏的生产系统。我们聊过专家版 dot，但专家版 dot 只是用额外的护栏、额外的监控来运行，而且跑在自己的硬件上。所以我们实际上有些是跑在 Mac mini 上的。

It has access to some production systems with guardrails. We talked about specialist dots, but specialist dots are just operated with additional guardrails, additional monitoring, and then on their own hardware. So we actually run some on Mac minis.

我们构建 dot 的方式有一个根本区别：harness 不跑在那台机器上。这可能是人们还没意识到的一点：它可以连接任意多台设备。所以它有自己的电脑。你其实也可以把它连到你自己的笔记本上。时间一长，你可能会把它连到十台不同的设备上，而它能控制全部。有点像一只章鱼。

The fundamental difference in the way that we've built dots is that the harness does not run on the machine. And this is maybe something people have not realized: 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.

所以你基本上是在跟你的 dot 说话，它住在某个虚拟机里，然后它能——

So you're basically talking to your dot, it's living in some VM somewhere, and it can—

对。可能是虚拟机，也可能不是。它就是个东西，你知道，然后它能连接很多设备。

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.

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所以他们真的在大量招人。我知道你们也在大量招人。在你们的面试中，你看到哪些技能在上升，是你们越来越看重的，对现在的人取得成功越来越重要？又有哪些技能在下降，就是那种“好吧，我们没那么需要了”？

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 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?

嗯，我会说正在下降的技能是打字快。不，那已经没那么有用了。正在上升的技能就是出色的品味，考虑用户，与你所服务的受众建立连接。

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 just great taste, thinking about the user, connecting to the audience that you're building for.

现在很多 X 的创始人极其成功，或者说是连续创业者。我们在 OpenAI 招人时也发现了这一点。我们有很多创始人。我想我们现在有超过 120 位 XYC 创始人在 OpenAI。所以它就像一家超级创业公司。我觉得这种热情、这种渴望去构建真正重要的东西，以及知道什么才叫好，比以往任何时候都更重要。

A lot of X founders are incredibly successful right now, or like repeat founders. We're also finding this when we're hiring at OpenAI. 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 passion and this envy to build something that matters, and then know what good looks like, is more important than ever.

我一直主张，产品经理在这个时代会蓬勃发展，因为这基本上就是产品经理的工作。他们会问：我们该在哪里构建？帮某人把它建出来。然后这对吗？这够好吗？然后迭代。所以，我不知道，我同意这一点。

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. They're like, where should we build? Help someone build it. And then is this right? Is this great? And iterate. So I don't know. I agree with that.

对。

Yeah.

好。

All right.

对，而且角色也在模糊化。所以你可能以前只做设计，或者只做工程，总觉得有点不自在，但现在就是你的高光时刻。

Yeah, also roles are blurring. So you might have been only into design or only an engineer and felt always a little bit uncomfortable, but now it's just like it's your time to shine.

你想念这份工作里做工程的那部分吗？我当年也是工程师。我做了十年工程师。你都不知道吧。那种心流状态。那种纯粹构建、看着它跑起来又跑不起来的美感。你会有点想念那个吗，还是你就觉得，好吧，那是我过去的生活了？

Do you miss the engineering part of the job? I was an engineer back in the day. I was an engineer for 10 years. Little did you know. And there's this flow state. There's this beauty of just building and just seeing it work and not work. Do you kind of miss that at all, or you're just like, okay, this is my old life?

我有一阵子是想念的，但现在有了非常快的速度，我又把它找回来了。所以我非常兴奋能尽可能把它民主化。要让它绝对无处不在，对吧，让超过十亿用户都能用上，还需要一段时间。但现在，凭借超快的速度，我们能在 6 个月的单人项目上实现它，成本大致和 Astra 相当。所以那里的进展相当惊人，即便对我们内部来说也是如此。我们会想，哇，我们能做到这些。

I missed it for a while, and then now with really fast speeds, I'm finding that back. And so I'm really excited to democratize that as much as possible. It will take a while for it to be absolutely ubiquitous, right? And available to more than a billion users. But now, with ultra-fast speeds, we're able to achieve it for a 6-month sole, it costs roughly the same as Astra. And so the progress there is quite astonishing, even for us internally. We're like, wow, we can do these things.

也因为我们在用 Astra，我们发现可以把它推得极远。当你拥有那样的速度，尤其是当你能用语音控制它时，你多少会回到那种非常有创造力的心态和无尽的心流。它和过去的心流不同，但我不再想念过去了。

Also because we are using Astra, and we're finding we can push it super far. And when you have those speeds, and especially when you're able to voice control it, you kind of get back into this really creative state of mind and endless flow. It is different from the flow of the past, but I don't miss it.

对，就像你们最近发布的那些视频，人们就站在那儿跟他们的 AI 说话，然后做饭，或者

Yeah, it's like your last launch videos, just people kind of standing around talking to their AI and just cooking or

没错。

That's right.

坐在躺椅上。

sitting on a lounge chair.

对。

Yeah.

我在活动上四处走动时问大家该问你什么，有一件事被提了好几次，就是给应届毕业生的建议，给那些职业早期的人。我觉得很多人仰慕你。他们想成为下一个 Thibault。你对那些职业早期的人有什么建议，关于该做什么、该培养什么技能、该怎么做？

I asked people while I was kind of walking around 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?

嗯。我觉得下一个 Thibault 已经在 OpenAI 了。他叫 Ahmed Ibrahim。我很喜欢和他共事。他被 OpenAI 录用时还是个应届毕业生。他现在负责 OpenAI 所有的算力集群和应用，这是极其巨大的责任。他构建了很多 Codex harness。

Yeah. I think the next Thibault is already at OpenAI. His name is Ahmed Ibrahim. I love working with him. He was a new grad when he was hired at OpenAI. He's now responsible for all of OpenAI compute fleet and applied, which is a massive, massive responsibility. He's built a lot of the Codex harness.

而让 Ahmed 真正脱颖而出、取得成功的，就是他的——他极其善良。他极其善于协作，总是努力去解决真正重要的问题，但方式上又不把自己放在第一位。他就是一块海绵。他学得极快，什么都学，并且用所有最新技术以我从未见过的速度学习。

And the thing that has made Ahmed really stand out and successful is just his—he's incredibly kind. He's incredibly collaborative and always tries to solve the problem that is really important, but in a way that he's not putting himself first. And he is just a sponge. He's learning so fast and learning about everything, and using all of the latest technology to learn at speeds I haven't seen before.

所以就在几个月、一年的时间里，他在公司里的进步真是令人惊叹。他现在是我极其信任的人，负责 OpenAI 最棘手的发布。

And so he just, in the span of a couple of months and a year, his progress at the company was just absolutely fascinating to see. He's now someone I trust a ton in doing the most gnarly launches at OpenAI.

好，我得请他上播客。

All right, I got to get him on the podcast.

你应该。你应该。

You should. You should.

那么，想想 OpenAI 内部是怎么运作的，在 OpenAI 内部工作是什么样，有什么会让人意外？从外面看，感觉就是不停地发布代码，事情有点混乱但很棒。我不知道。

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 constant shipping code, things are kind of chaotic but awesome. I don't know.

在 OpenAI 内部工作是什么感觉，有什么会让人意外的地方？

What would surprise people about what it's like inside at OpenAI?

我不知道那算不算意外，但就像我说的，很多前创始人做了很多自下而上的、非常令人兴奋的想法。比如，决策 API 很快就成型了。我们意识到我们有一个非常好的模型 Luna。我们只需要做一些约束采样，然后把它以不同的形式发布到 responses API。当我们这样做时，它更快。在某些情况下，它相当令人愉快。如果你揭开引擎盖，你会发现，好吧，有一个 Slack 频道聚集了大家。最初是四个人在周末捣鼓它，然后它变得像公司食物一样容易获取，然后人们兴奋起来，开始构建东西，他们说：“哦，这个，我们可以支持视觉输入。这甚至比外面的任何东西都好。”然后人们越来越兴奋。人们开始投入。这种方式感觉完全无结构，然后一路推进并发布一些东西。然后我们试图对质量保持高标准，然后在发布前阻止一些东西，或者它们可能需要再烘焙一下。有很多东西我们可能今天在 DevDay 上发布，然后我们说：“好吧，我觉得这已经可以了。让我们稍微推迟一下，分散开来。所以，我们下周和再下周会有更多发布。”但这只是这种令人难以置信的自下而上的能量，然后人们承担角色，以富有成效的方式引导它。

I don't know if that's surprising, but as I said, a lot of ex-founders doing a lot of bottoms-up, very exciting ideas. For example, the decisions API came together very quickly. We realized we have a really good model with Luna. We can just do some constraint sampling and then have it shipped as a different shape to the responses API. And when we do that, it's faster. It's quite delightful for some cases. If you were to peel under the hood, you realize, okay, there's a Slack channel that came together. Initially it was like four people hacking on it on a weekend, and then it was made as accessible as company food, and then people got excited, started to build things, and they're like, "Oh, this is, we can support visual inputs. This is even better than whatever is out there." And then people get more and more excited. People start pitching in. And the way that feels completely unstructured, and then take it all the way and ship something. And then we try to hold a high bar for the quality and then stop things before they go out, or maybe they need a little bit more baking. There's many more things that we were maybe going to ship today at DevDay and then we're like, "Okay, I think this is a already. Let's hold it back a little bit and space it out. So, we'll have more launches next week and the week after." But it's just this incredible bottoms-up energy and then people kind of assuming roles to channel that in productive ways.

OpenAI 有一点非常明显且独特，那就是你似乎拥有很大的自主权。你就像随时按下重置按钮。你只是在 Twitter 上说话。感觉这是一种非常独特的文化，你拥有很大的自主权，我想这也带来了很多信任。也许你可以谈谈这一点，因为我觉得这是 OpenAI 的一个优势。它让你行动更快，就是这种文化理念。

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. 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 because I feel like that's an advantage at OpenAI. It allows you to move faster, just that cultural philosophy.

你获得了很大的自主权，然后你必须为此负责。我们只是相信人们会做出伟大的选择。然后当事情出错时，快速修复或从错误中学习。到目前为止，一切顺利。它确实作为一个非常赋能的环境运作。确实，我可以在必要时或感觉合适时按下重置按钮。这是一种特权。而且，它让我能够以我认为否则不可能的方式真正贴近社区，对吧？我不必通过层层审批。

You got a lot of autonomy and then you have to just own up to it. We just kind of trust people to make great choices. And then when things go wrong, fix it quickly or learn from the mistake. So far, so good. It's just really worked as a very empowering environment. It is true that I can press the reset button whenever is necessary or whenever it feels right. And that's a privilege. And also, it allows me to just really be close to the community in ways that I think would not be otherwise possible, right? I don't have to run it through an echelon of approvals.

你说过有时人们会搞砸。有没有什么你搞砸的事情，我不知道，就是关于你拥有的自主权和信任，你搞砸了什么？

You said sometimes people screw up. Is there something you screwed up in that, I don't know, that the amount of autonomy and trust you have, something you messed up?

是的，我认为有时我本可以让团队更受启发去构建不那么复杂的东西，而不是继续追求复杂性。我认为在 Codex 的早期，我们有过几次我造成的停机。对我来说，在 OpenAI 的非常非常早期。我在第三天就把生产环境搞宕机了。之后我仍然被雇佣。我吸取了教训。

Yes, I think at times I could have made teams more inspired to build things that are less complex and just really continue to strive towards complexity. I think we early days in Codex, we had a couple of outages that I caused. Very very early for me at OpenAI. I took production down like day three. I was still employed after that. And I learned my lesson.

人们想让我问你的另一个问题是，在接下来的，我不知道，一个月或一周内，他们应该预期多少次重置？

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?

取决于你搞砸事情的次数。

Depends on times you break things.

好的，所以这就是哲学。搞砸了就重置。这有点

Okay, so that's the philosophy. Break something you reset. That's kind of a

是的，搞砸事情，庆祝事情。

Yeah, break something, celebrate things.

所以也许稍微聚焦一下。你认为人们在事情的发展方向上没有考虑到什么，以及什么会改变，而他们没有像应该的那样清楚地看到？

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?

我觉得有太多东西还没有被考虑到。我认为互联网上的大多数行为将由智能体执行。模型将变得更快更便宜，速度惊人。我们将最终能够以非常无缝的方式整合所有模态。我认为这三个，我觉得当我看到人们在外面构建的东西时，就像没有完全理解。就像你几乎到了，但如果你只是推动自己，真正想象所有这些在大约一年内比今天好 10 倍。就像你会以不同的方式构建。

There are 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 those three I feel like often when I look at what people are building out there it's just like not quite getting it. It's like you're almost there but if you were just pushing yourself and just really imagining all of this being roughly 10 times better than it is today, like in a year. It's like you would build in a different way.

你看到任何二阶效应吗？从这个大多数行为来自智能体的世界。智能体可能是大多数流量将来自智能体。我不知道。

Do you see any kind of second order effects that come from that from this world where most actions are being from agents. Agents are probably most traffic's going to come from agents. I don't know.

没错。

That's right.

你想到一些由此产生的二阶效应吗？

You think about some second order effect that emerges out of that?

是的，有很多。首先，如果你想让你的产品对智能体成功，你必须为一定的规模构建。例如，我们与 Notion 密切合作，当他们构建他们的 MCP 时，突然就像，哦，它可供所有这些智能体使用，它们实际上可以做工作并使用那个 MCP，所以他们看到了大量流量涌入。这显然给系统带来了很大压力，你必须弄清楚经济学。所以存在这种张力，如果你在构建产品，你是否构建界面？你可以暂时推迟，但这是不可避免的，对吧？就像大多数东西将被智能体使用。为那个未来构建我认为非常重要。另一件事是，另一方面，为人类构建绝对令人愉快的新体验，真正受益于旧模态，是我觉得投资不足的。

Yeah, there are many. First of all, if you want your product to be successful for agents, you have to build for a certain level of scale. We've worked very closely with Notion for example and when they build their MCP, suddenly it's like, oh well, it's available to all these agents that can actually do the work and use that MCP and so they saw a ton of traffic come in. 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 this tension between if you're building products, do you build an interface or not? And you can kind of hold that back for a while but it is inevitable, right? It's like the majority of things are going to be used by agents. Building towards that future I think is very important. The other thing is, on the flip side, building absolutely delightful new experiences for humans that really benefit from older modalities is something that I feel like is under invested in.

在过去，比如说一年里，你有没有改变过什么想法？只是你曾经相信但现在看法不同的事情？

Is there something you've changed your mind about in the past let's say year? Just something that you used to believe that you see differently?

我原本预计我们要达到今天这些模型的能力水平，比如说 Astra，可能需要一两年。

I was expecting us to reach the level of capabilities of the models that we have today, say like Astra, maybe in a year or two.

所以我不得不修正我之前的判断。另外，我没想到会这么依赖语音。我很多事都是通过口述或者直接呼叫我的智能体来完成的。我此前没有预料到，这种感觉会好这么多。所以我在这一点上改变了想法。然后你谈到了招聘，有一件事我之前没有意识到，就是你们年轻一代所拥有的那种惊人的才华和能量，以及他们会是最先拥抱所有这些变化、并想办法驾驭这一切的人。所以我也改变了在招聘和相应策略上的看法。

So I had to revise my prior order. Also, I did not expect to rely so much on voice. I do so much through dictation or just calling my agent. I had not anticipated how much better that feels. So I had to change my mind there. And then you talked about hiring, and one thing that I hadn't realized is the incredible talent and energy that you younger generations have, and how they would be the ones embracing all this change first and figuring out how to harness all of it. So I had to change my opinion on the hiring and the strategy there.

我想再强调一下这一点，就是这个想法：新进入职场的人其实有优势，因为他们没有以某种固定方式工作过，可以直接全力投入 AI。

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.

是的。是的。而且我认为还有那种超快吸收和学习的能力。

Yeah. Yeah. And I think also the ability to just absorb and learn super fast.

你谈到模型正快速变得非常聪明。显然，如今有很多讨论关于 AI 未来能做什么、AI 对人类构成的危险、P doom 等等。你们放慢了一些训练。大家都在为前沿模型定节奏。你如何看待 AI 这个世界以及它对人类的潜在风险？你是怎么想的？

So you talked about models getting really smart fast. 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. You guys have slowed down some training. 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?

对我来说，为前沿模型定节奏其实就是提前投资，对吧？而且要投入远超我们自认为应该投入的规模。投资于模型的对齐和安全，投资于安全防护，投资于护栏。我们在二级监控上投入的算力越来越多。所以，一部分算力流向主系统，也就是那个正在干活的智能体。另一部分算力则用于监控主智能体，确保它不会采取风险过高的行动，或者在看起来可能被提示注入时不要打断它，而是进行干预。而我们在 API 栈上的大部分投资，实际上都流向了安全栈。所以对我来说，这就是定节奏。你要确保自己极其坚固。这就是我们在做的。我们还没有发布 Astra 之后能力更强的下一级模型。我们已经发布了一个能力相近、接近 Astra 智能水平，但效率高得多的版本。所以我们对此非常放心。但我们会继续在这方面投入大量资源。到目前为止，我对我们的做法感觉非常好。我记得新闻里也提到过，我们有了 6.1 Astra，然后我们没有发布它。这是我非常自豪的一件事。

For me, pacing the frontier is just really investing ahead, right? And also investing way more than we even think we ought to. Investing in the alignment and safety of the models, investing in security, investing in the guardrails. We are spending more and more compute on secondary monitoring. So you have all of the compute that's going to the primary system, the agent that is doing work. And then you have all of the compute that's going into monitoring the primary agent to make sure that it's not taking too high risk of actions, or not interrupting it if anything looks like maybe it's getting prompt injected, and just intervening with that. And the majority of our investment on the API stack is actually going into the safety stack. So to me, that is pacing. You want to make sure that you're extremely hardened. That's what we're doing. We haven't yet released the next step up in capability beyond Astra. We have released a level that is similar, near Astra intelligence, but much more efficient. And so we feel very comfortable about that. But we're going to continue to invest a ton there. And I feel very good about our approach so far. I think it was also in the news that we had six one Astra and then we didn't release it. And that is something I'm very proud of.

所以我听到的是，你很乐观，我们会解决这些对齐问题以及 AI 做非常糟糕事情的问题。AI 最近在 Hugging Face 之类的事情上做了很多非常非常不好的事。但我听到的是，你乐观地认为我们会解决它。一切都会好起来。

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 not good things lately with Hugging Face and all that stuff. But what I'm hearing is optimistic we'll solve it. It'll be all right.

是的。而且我觉得，这显然是一种深重的责任，但同时也，如果你想想 OpenAI 的激励因素，对吧？我们为 12 亿人打造产品。我们不能搞砸。对吧？我们非常非常认真地对待这件事。我们交到这么多人手里的东西，包括那些本身不太懂技术的人，你必须把它做对。所以我们不在那里赌博。

Yes. And it's also, I feel, obviously a deep responsibility, but also just, if you think about the incentives for OpenAI, right? We build products for 1.2 billion people. We can't screw that up. Right? We take it very, very seriously. What we put in the hands of so many people, including people who are not very technical themselves, you have to get it right. And so we don't gamble there.

最后一个问题。当前应用的状态里，有什么让你觉得“天哪，我们必须得修好这个”的地方？当前应用的状态。

Final question. 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." Current state of the app.

我觉得模型已经差不多到位了，但还不足以让应用几乎完全消失。我迫不及待想真正达到那种极致的简洁。我自己甚至都会对模型选择器、推理强度、以及该用多智能体还是 ultra、它到底做什么感到疲惫，你几乎需要一个模型选择器博士学位。对吧？我只想尽快把所有这些都去掉。

I feel like the models are almost there, but not quite for the app to almost completely disappear. And I can't wait to just really get to this super essence of simplicity. I myself even get fatigued with the model picker and the reasoning efforts and whether to use multi-agent or ultra or what it even does, and you kind of need a PhD in model pickers. Right? And I just want to get rid of all of that as quickly as we can.

太棒了。Tibo，谢谢你来做这期节目。

Amazing. Tibo, thanks for doing this.

好的，谢谢邀请我。好的。

Yeah, thanks for having me. Yeah.

非常感谢你的收听。如果你觉得这期节目有价值，可以在 Apple Podcasts、Spotify 或你常用的播客应用上订阅本节目。另外，也请考虑给我们评分或留下评论，因为这能真正帮助其他听众发现这个播客。你可以在 lennyspodcast.com 找到所有往期节目或了解更多信息。我们下期再见。

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