打造 Grok Bot：小团队如何创造最热 AI 产品

Grok Bot 的终极愿景非常简单。你应该拥有一支 AI 智能体团队，帮你处理工作，也帮你处理生活。

The ultimate vision of Grok Bot is incredibly simple. You should have a team of AI bots that help you with your job and help you with your life.

Grok Bot 是当下全球最火的 AI 产品。这个门槛非常高，争夺这个位置的竞争非常激烈。

Grok Bot is the hottest AI product in the world right now. That is a very high bar. There's a lot of competition for that slot.

我们想打造的不只是给开发者和工程师用的好产品。我们决定在内部组建一支很小的团队，像钻进山洞一样闭关大约一个月，唯一的目标就是做出一个出色的知识工作产品，把智能体带给公司其他所有人。

We wanted to build something that wasn't just a great product for developers and engineers. We decided to create this very small team internally to go off into a cave for about a month with the sole objective of building an amazing knowledge work product that brings agents to the rest of the company.

发布才仅仅三周。我去了一场 Grok Bot 聚会，现场有几百人，站的地方都没有。我很清楚，你们做出了非常特别的东西。

It's been only 3 weeks since launch. I went to a Grok Bot meetup. There were hundreds of people there. Standing room only. It's very clear to me that you guys have built something very special.

一旦你跳出“这是带了一堆连接的 AI 聊天”的框架，转而把它看成“这是一个有电脑的同事”，你能放心交给 AI 的事情的上限就被抬高了。

Once you start breaking out of this is AI chat with a set of connections instead to this is a colleague with a computer. It just raises the ceiling of what you would think to give to AI.

你发过一条推文：一个能完成 100% 工作的 AI，和一个只能帮你做到 90% 的 AI，感觉上是完全不同的两类东西。

You have this tweet, an AI that does 100% of the job feels categorically different from one that gets you 90% there.

让我对做 Grok Bot 如此兴奋的原因是，这是第一次在非编程任务上，我觉得自己可以真正把工作委托给 AI，不用再操心，等我回来时它已经做完了。

What made me so excited to work on Grok Bot is it was the first time for non-coding tasks that I felt like I could truly delegate work to AI, not have to think about it, and I would come back and it's done.

你觉得你们做了什么如此不同的事，让 Grok Bot 如此成功？

What is it that you think you did that is so different that made Grok Bot so successful?

是两个早期的决定，当时完全不觉得显而易见，但事后看，我认为它们是 Grok Bot 能成功的关键。

It was two early decisions that at the time definitely did not feel obvious, but in hindsight I think are critical to what makes Grok Bot work.

今天的嘉宾是 Roman Ugarte。我会把这段介绍压得很短，好让我们直接进入正题。Roman 是 Cursor 的第 15 号员工，过去两年负责增长。最近他参与孵化了 Grok Bot，一个让我着迷的产品。它改变了我的生活。我每天用它上百次，做各种各样的事。可以说，它是当下全球最火、最令人兴奋的新 AI 产品。Roman 负责 Grok Bot 的产品。从早期原型到今天，他一直是核心团队的一员。我们会聊它如何起步、将走向何方，以及自几周前发布以来他和团队学到的一切。下面，有请 Roman Ugarte。

Today my guest is Roman Ugarte. I'm going to keep this intro very short so we can get right into it. Roman was employee number 15 at Cursor. He has led growth for the last 2 years. Most recently, he helped incubate Grok Bot, a product that I am obsessed with. It has changed my life. I use it a 100 times a day for all kinds of things. And I think it's safe to say it is the hottest and most exciting new AI product in the world right now. Roman leads product for Grok Bot. He's been part of the core team from early prototype until today. And we get into how it all started, where it's all going, and all the things that he and his team have learned since it launched just a few weeks ago. With that, I bring you Roman Ugarte.

Roman，非常感谢你来，欢迎来到播客。

Roman, thank you so much for being here and welcome to the podcast.

谢谢。很高兴能来。

Thank you. It is great to be here.

我特别高兴你能来。我对 Grok Bot 太上瘾了。我把它就放在这边的窗口里。我大概有 15 个智能体，每天都在用，一直在用。前几天我去了一场聚会，一场 Grok Bot 聚会，现场有几百人，站的地方都没有。大家分享着各自使用 Grok Bot 的各种方式。我很清楚，你们做出了非常特别的东西。在 AI 世界里要突破噪音非常难。Grok Bot 是当下全球最火的 AI 产品。这个门槛非常高，争夺这个位置的竞争非常激烈。我个人注意到，我很快就把很多用例从 co-work 和 codeex 搬到了 Grok Bot，这同样感觉是件大事，一个非常特别的时刻。所以我很兴奋能聊这么多话题。我想了解你们是怎么做到的，这一切从何而来，将走向何方，以及到目前为止你们在这段旅程中学到了什么。首先，干得漂亮。做得好。你们做成的事非常难。

I am so excited to have you here. I am so hooked on Grok Bot. I have it over here in my window. I have like 15 bots that I use every day, all the time. I went to a meetup the other day, a Grok Bot meetup. There were hundreds of people there. Standing room only. People sharing all the ways they're using Grok Bot. It's very clear to me that you guys have built something very special. It's very hard to break through the noise in the AI world. Grok Bot is the hottest AI product in the world right now. That is a very high bar. There's a lot of competition for that slot. I personally noticed I've moved a lot of my use cases from co-work and codeex into Grok Bot just like very quickly which again feels like a really big deal and a very special moment. And so I'm excited to talk about so many things. I want to understand how you guys did this, where this came from. Where this is going, what you've learned about the journey so far. First, nice job. Nice work. This is very hard what you've done.

谢谢。我记得大约一个月前我亲手给你做了上手引导，我觉得你一开始是持怀疑态度的。但我们很高兴你一直在用，看到这么多人真正用上 Grok Bot，感觉非常好。

Thank you. I mean, I remember onboarding you by hand about a month ago, and I think you were skeptical at first. But we're very glad that you've been using it, and it's been great to see so many people really take advantage of Grok Bot.

我要聊聊那次上手引导。那是这套东西如何运作的一个非常有意思的环节。我记得在那次引导里，你让我试了试——你说我们来试个东西，我说好，试着写条推文来推广我最新一期播客。我就说，写条推文推广我上一期节目，就这样。结果它写得非常好。它搞清楚了上一期到底是什么，该怎么推广。所以我当时就记得自己心想，哇，这真的很棒。那我们就从起源故事开始吧。它是从哪儿开始的？最初的想法是什么，这项工作是什么时候开始的？

I'm going to talk about that onboarding. That was a very interesting element of how this worked. I actually remember in that onboarding I tried to you asked me to do like a let's try something and I was like okay try to come up with a tweet to promote my latest podcast episode. So I'm just like come up with a tweet to promote my last episode. That's it. And it was actually very good. It figured out what the hell last episode was how to promote it. So I actually remember in the moment being like wow this is really good. So let's actually start with origin story. Where did it start? What was kind of the original idea and when did the work on this begin?

是的，它真的是从一张白纸、完全从零开始做起的。我想我们很久以来就感觉到，我们想打造的不只是给开发者和工程师用的好产品，那确实是我们起步的地方。我想我们由此积累了很多关于如何打造优秀智能体和有用产品的直觉。但如果是面向知识工作的产品，会是什么样？我们决定在内部组建一支很小的团队，真的就几个人，像钻进山洞一样闭关大约一个月，唯一的目标就是做出一个出色的知识工作产品，把智能体带给公司其他所有人。我想从第一行代码到我们在内部发布这个原型，只用了大约一个月。那是一个非常快、很拼凑的原型。事后看，我觉得如果是一个大得多的团队，这根本不可能。我认为这需要一支小而专注、与公司其他部分完全隔离的团队。我是字面意义上的隔离。团队坐在办公室一个单独的区域，有私密的 Slack 频道。回头看，正是这一点让我们能推进得这么快——我们每天需要做大量微小的决定。有些事我们也许稍后会聊到，它们并不显而易见，也不是我们以前在其他产品面上做过的事。如果是一大群人，还在想着 6 到 12 个月的长期愿景，我们根本到不了最终落地的那个地方。所以从第一行代码到一个核心团队都兴奋的、可用有用的产品，大约用了一个月。然后就是把它推广到全公司、推广到所有 space act 的时刻。于是有了一次全员大会，我们分享了到目前为止的进展。这是全新的产品，希望大家用起来。我觉得最令人鼓舞的是，因为那时我们很兴奋，我们一直在用它，但用自己做的东西很容易，你多少懂它的机制、知道它擅长什么。

Yeah, it started really as a blank page completely from scratch build from zero exercise where I think we'd been feeling for a long time that we wanted to build something that wasn't just a great product for developers and engineers, which is really where we started. And I think we've gained a lot of intuition about how to build great agents and useful products that way. But what would that product look like for knowledge work? And we decided to kind of create this very small team internally. It was really just a handful of people to go off into a cave for about a month with the sole objective of building an amazing knowledge work product that brings agents to the rest of the company. And I think from the first line of code to when we released this prototype internally, it was only about a month. It was like a very quick, you know, scrappy prototype that was pulled together. And I think in hindsight this would not have been possible if it had been I think a much bigger group. I think it took a small focused group that was completely isolated from the rest of the company. And I mean that literally. It was like a separate part of the office where this team sat. Private Slack channels. And the goal, and I think in hindsight, it was a lot of what allowed us to move so quickly on this, was we needed to make a lot of micro decisions every day. Some things that maybe we'll talk about a bit later that were not obvious, were not really things that we'd done on other product surfaces before. And I think if it had been a very big group of people and we were kind of thinking about this 6 to 12 monthlong vision, we just wouldn't have really gotten to the place that we ended up landing at. And so that was about a month from first line of code to here's a functional useful product that the core team is excited about. So then there was a moment of rolling this out across the company rolling this out across all the space act. And so there was an all hands where we kind of shared the progress that had been made so far. There's this brand new product. We would love for you to use it. And I think what was most encouraging because at that point we were excited about it. I think we were using it constantly, but it's easy to use the thing that you built and you kind of understand the mechanics and what it's good for.

所以这是一次真正面对现实的压力测试：人们真的会从其他内部工具、其他外部工具切换过来，把 Grok Bot 当作他们的主要智能体界面吗？在那次全员大会之后的第一周，我简直没法形容人们对 Grok Bot 的热爱，来自你可能意想不到的人，或者公司里你可能意想不到的团队。那些每天用 ChatGPT 或某个聊天界面的人，把他们日常的智能体式任务全都切换到 Grok Bot，把它当作工作的主要界面。所以内部的接受度真的非同寻常。那一两周里我还能讲些挺好玩的故事。然后，一旦我们看到内部的接受度，我们立刻切换到：把它准备好推向全世界。要扩展到数百万用户，还有很多工作要做。然后这就引出了几周前的 GA 发布。

And so this was a real pressure test with reality: are people actually going to switch from other internal tools, other external tools, to use Grok Bot as their primary agent surface? And in that first week after that all-hands, I mean, I can't even tell you just the outpouring of love for Grok Bot from people that maybe you wouldn't expect, or from groups of the company that maybe you wouldn't expect. People who were daily driving ChatGPT or a chat interface, switching all of their day-to-day agentic tasks over to Grok Bot as their primary surface for doing work. And so the internal reception was really extraordinary. I can tell some kind of funny stories from that week or two period. And then once we saw the internal reception, we immediately switched into, let's get this ready for the world. There's a lot of work to do to scale this out to millions of users. And then that led to the GA launch that we had a few weeks ago.

本期节目由我们这一季的冠名赞助商 WorkOS 带来。OpenAI、Anthropic、Cursor、Replit、Sierra、Clay 以及数百家其他成功公司有什么共同点？它们都由 WorkOS 提供支持。如果你在为 enterprise 构建产品，你一定体会过集成单点登录、SCIM、RBAC、审计日志以及其他大公司所需功能的痛苦。WorkOS 把这些交易阻碍变成了即插即用的 API，背后是一个专为 B2B SaaS 打造的现代开发者平台。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。因为它们就是最好的。无论你是想拿下第一个 enterprise 客户的种子轮初创公司，还是正在全球扩张的独角兽，WorkOS 都是成为 enterprise ready、解除增长阻碍的最快路径。它本质上就是 enterprise 功能领域的 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。今天就访问 workos.com，让你的应用 enterprise ready。

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've felt the pain of integrating single sign-on, SCIM, RBAC, 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.

好，问题太多了。这里有一个非常有意思的。显然有 Anthropic、OpenAI。它们从一个编码智能体出发，然后想，天哪，这是个巨大的机会。接着它们想，好吧，人们把它用于知识工作。那我们就做一个知识工作的组件。所以 Co-work 就在产品内部演化出来了，然后 Codex，他们投入的是，让这个东西对各种各样的事情都有用。有意思的是，你们决定，好，Cursor，我们不会把它做进 Cursor 里。我们要从零开始做点新的。这个从一开始就很明显吗？好，这在 Cursor 这个产品里行不通，我们需要从零开始。这个决定当时有多大争议？

Okay, so many questions. One that is really interesting here. So obviously there's Anthropic, OpenAI. They went from—they had this coding agent and they're like, holy, this is a big opportunity. And then they're like, okay, people are using this for knowledge work. Let's build a knowledge work component. So there's Co-work evolved out of that within the product, and then Codex, they've invested in, let's make this useful for all kinds of things. Interestingly, you guys decided, okay, Cursor, we're not going to build this into Cursor. We're gonna start something fresh. Was that just obvious from the beginning? Okay, this is not going to work inside Cursor the product. We need to start fresh. How controversial was that decision?

这一点都不明显。我觉得你说得完全对，那是我们最初做的决定之一，当时我们讨论了很多，我很满意我们最终的选择。而且我觉得，正如你所说，它是一个全新的产品，你能控制体验的每一个像素，你对知识工作的走向有一致的愿景，而这一切都包含在这个新东西里，我认为这对成功贡献很大。但当时确实有很多讨论，比如关于 Cursor，我们的一些编码产品——人们一直用它来做非编码任务。你知道，这些编码智能体在某些事情上确实非常出色，但你会遇到一些小摩擦。有时候产品本身对非技术用户来说有点吓人。这些东西还带着品牌联想。所以我觉得我们评估了那条路，也看到了我们一些竞争对手可能在做的，就是全都放在一个界面上。每出现一种新形态就加一个新标签页，感觉有点杂乱。我觉得用户能感觉到，这不是一个关于工作应该如何运作的一致愿景，而是三种不同的愿景挤在同一个屏幕上，你可以来回切换，但这有点像把组织架构图直接发布出去，我认为用户的反应是负面的。所以我们决定，干脆完全从零开始。看看我们能走到哪里。也许会有一些非常棒的机会，把其他界面的人带进这个更以 bot 为核心的体验里，但让人们拥有一个极其简单又极其强大的体验，这一点非常重要。

It was not obvious at all. I think you're completely right that that was one of those original decisions that at the time we had a lot of discussions about, and I'm very glad with where we landed. And I think, to your point, it being a brand new product that you control every pixel of the experience and you have this consistent vision about where knowledge work is going, and it's all contained in this new thing, I think has contributed a lot to the success. But there were a lot of discussions about, you know, Cursor, for example, and some of our coding products—people use it for non-coding tasks all the time. And you know, these coding agents are really excellent at some of these things, but you run into small paper cuts. Sometimes the product itself is kind of intimidating to nontechnical users. There's a brand association with these things. And so I think we evaluated that path, and I think we saw what maybe some of our competitors have been doing, of this is all just one surface. You add new tabs for each new form factor, and it feels a little cluttered. And I think for users, they can feel that this was not a single consistent vision of the way that work should work, and instead it's three different visions that all kind of share a screen and you can hop between, but it is kind of a shipping-your-org-chart style thing that I think users are reacting negatively to. And so we decided, let's just start completely from scratch. Let's see where we can get from there. There might be some really amazing opportunities to bring people from other surfaces into this more bot-native experience, but it's really important for people to just have an amazingly simple and amazingly powerful experience.

这对大家来说是一个非常有价值的经验：这可能才是解决方案，而不是往一个复杂的现有 AI 产品里加东西。有意思的是，Codex 走了另一个方向，是一条不同的路径、不同的产品，但有意思的是，他们现在说，我们要把它做成一个东西。所以你看，有很多种做法都能行得通，而且感觉你选择的路径也会引导你，但也许回头看我们会说，那可能不是最好的主意。你提到你们做过的另一件非常独特的事，就是早期用户的 onboarding。我听说你和你的团队手动 onboarding 了两三百人，包括我。讲讲你为什么觉得这是必要的，你从这段经历中学到了什么，以及这种手动 onboarding 的阶段持续了多久。

That is a really valuable lesson for people to take away here, just that that might be the solution instead of adding into a complicated existing AI product. So interestingly, Codex went the other direction and it's like a different path and a different product, but interestingly they're like, now we're going to make it one thing. So there, you know, there's many ways to make it work, and it also feels like the path you take there will kind of lead you, but maybe we'll look back and be like, that was not maybe the best idea. Something you mentioned that you did that is also really unique is this onboarding of early users. I heard you and your team onboarded two to three hundred people manually, including me. Talk about why you thought that was necessary and what you learned from that experience, and just like how long that period was of this kind of manual onboarding.

我的意思是，你学到的东西太多了。最初几次 onboarding 相当痛苦。我很高兴你那次体验不错，Lenny。但也有一些挺糟糕的，我们学到了很多。我觉得核心团队亲自在场很重要，就坐在通话里 20 分钟，看着电脑起不来，或者看着某个人在 onboarding 时完全一头雾水。这样紧接着你就会想，这种事绝不能再发生。我们明天就得解决它，因为明天我要 onboarding 这个人，必须做得更好。所以大约有两周时间，我们处于那种模式，onboarding 了几百人。我们不仅对产品有了很多了解，我觉得我们当时其实并不清楚——有时候这类产品会有一些关于用法的群体思维。而且我觉得在内部，因为 SpaceX 内部的人一直在分享使用 Grok Bot 的技巧和窍门，一些模式开始浮现，我们认为它们对世界会有用，但我们并不确定，而且我们绝对不想给世界带来偏见。

I mean, you just learned so much. And the first few onboardings were pretty painful. I'm glad you got a good one, Lenny. But there were some that were kind of rough, and we learned a lot. And I think it was important for the core team to be in the room for those, and to just sit on a call for 20 minutes when the computer isn't spinning up, or when someone's in onboarding and they're just incredibly confused. So that immediately after, you're like, that can never happen again. We need to solve this tomorrow, because tomorrow I'm onboarding this person and it needs to go better. And so there was about a two-week period where we were in that mode and onboarded a couple hundred people. And not only did we learn a lot about the product, I think we didn't really know—I think sometimes with these products there's some groupthink of ways to use them. And I think internally, because people inside of SpaceX were just constantly sharing tips and tricks for how to use Grok Bot, some patterns were starting to emerge that we thought would be useful to the world, but we weren't really sure, and we definitely didn't want to bias the world.

有这方面的例子吗？

Is there an example of that?

我们在内部推出 Grok Bot 的时候，大概有一两周的时间里，人们使用这个产品的常见模式是你会拥有五到十个 bot，每个 bot 你给它不同的范围、不同的领域，它有点像不同工作线的简写。然后到了第二周快结束的时候，我们开始在内网 Slack 里看到这样的消息：有人提拔了他们其中一个 bot，那个 bot 表现比较突出，有点像他们的主要个人助理，把它提拔为幕僚长。然后他们实际上主要跟幕僚长对话，幕僚长会把所有这些任务分发给其他 bot，有点像管理整个团队。还有一些好玩的截图，人们真的在告诉那个被提拔的 bot 说它升职了，然后 bot 会问自己是不是加薪了、token 预算是不是更高了，诸如此类。我们注意到了这一点，我觉得公司里更多人开始稍微往那个方向转变，但并不是公司的大多数。人们使用这个产品的方式非常不同。所以在一些 onboarding 环节里，以及从早期访问计划整体来看，我们真的不想诱导用户，说“创建一个幕僚长 bot，这就是幕僚长管理其他所有 bot 的方式”，然后看看早期访问用户自己会不会走到那一步。我们确实看到很多人自己走到了那一步。于是我们在产品里有了更明确的倾向：这看起来是一个行之有效的模式，这看起来是一个我们应该稍微鼓励的模式，但它不应该是一扇单向门。还有几个内部假设的例子，我们真的很想确保它们能在实际外部使用中得到验证，而不是由我们在产品里强加。

So when we rolled out Grok Bot internally, there was about a week or two where the common pattern of the way people would interact with the product was you would have five to 10 bots and each bot you would give a different scope, different domain, and it was kind of shorthand for different lanes of work. And then around the end of week two, we started to see these messages internally in Slack of people promoting one of their bots who was a bit of a standout performer, and it was like their primary personal assistant promoting that to their chief of staff. And then they would actually mostly talk to their chief of staff. And the chief of staff would fan out all of these tasks to the other bots and would kind of manage the team. And there are some funny screenshots of people actually telling the bot they're promoting that they're promoted and the bot is asking if they get a raise and is their token budget higher, all of these things. And we kind of took note of that and I think more of the companies started to slightly shift in that direction, but it was not the majority of the company. People use this product in very different ways. And so in some of the onboarding sessions and just from the early access program in general, we really did not want to lead the witness and say, create a chief of staff bot, here's exactly the way that chief of staff should manage all of the other bots, and see if early access users would get there themselves. And we actually did see that many of them did. And so then we had a bit more of an opinionated take in the product of this feels like a pattern that's working. This feels like a pattern that we should slightly encourage, but it shouldn't be a one-way door. And there were a few other examples of internal thesis that we really wanted to make sure would bear out in actual external usage without us imposing that in the product.

还有别的吗？有什么例子浮现在脑海里吗？

Is there anything else there? Any examples come to mind?

是的，我觉得在早期 onboarding 里我们真正关注的另一件事，就是用户到底想看到多少。我觉得 Grok Bot 刚上手时和你提到的其他一些产品相比，有一点让人震惊或者说就是不一样：Grok Bot 运作的很多内部机制并不展示给用户。原因是，我们认为随着这些模型变得更聪明，就像你的队友一样，你不会要求他们逐秒汇报自己按了哪些按钮、去了哪些网站，我觉得要求你的 bot 这么做也太过分了。而且说实话，这只会让人不堪重负，弊大于利。所以我们完全朝另一个方向走：你发一条消息，告诉你的 bot 去做某件事，它就开始做。它会按自己认为合适的方式给你发进度更新。你只会看到那个小小的绿色活跃圆圈里的输入指示器，有点像 Slack 那样，表示它活跃着、正在干活、很快会回复你。但你看不到内部机制，看不到工具调用，看不到它在自己的电脑上具体点的每一个小点击。我们真的很想采取一个强硬立场：用户不需要看到所有这些机制。所以我们从那里开始。我们确实收到一些反馈，比如“我很想看到我的 bot 的待办清单”“我很想大致看到它如何排定任务优先级、在做什么”。这是很好的反馈。但听到没有人想要那种长长的纯文本流和思维链序列，也很有用。所以这也进一步确认了那个方向是对的。

Yeah, I think another thing we really tried to pay attention to in the early onboardings was just how much users wanted to see. And I think it is something a bit shocking or just different about Grok Bot when you first start using it versus some of the other products that you mentioned, where a lot of the internal mechanics of how Grok Bot works are not shown to the user. And the reason for that is we think as these models get smarter, the same way that your teammate, you wouldn't ask for second-by-second updates of exactly all the buttons they're pressing and websites they're going to, I think it's too much to ask your bots to do that, too. And I think it's honestly just overwhelming and can create more harm than good. And so we moved completely in the other direction of you send a message, you tell your bot to do something, it just starts doing it. It sends you progressive updates as it sees fit. And you just see that typing indicator in the little green active circle, kind of Slack-like, that it's active, it's doing work, it'll get back to you soon. But you don't see the internal mechanics, you don't see the tool calls, you don't see exactly every little click it's making on its own computer. And we really wanted to take a strong stance that users did not need to see all of those mechanics. And so that's where we started. And we did get some feedback that's like, I would love to see my bot's to-do list. I would love to see roughly how it's prioritizing tasks and what it's doing. And that's great feedback. But it was useful to hear that nobody wanted the long stream of just text streaming out and chain of thought sequences. So that also gave us more confirmation that that was the right direction.

你们一个小团队做了两三百场 onboarding 电话。我知道团队后来壮大了，但光是这件事就是巨大的时间投入，你甚至可以说它会分散做产品的精力。显然它不是分散精力，显然是成功的核心部分。你觉得这是人们为了搞清楚真正需要做什么而必须做的量吗？

The fact that you did two to 300 onboarding calls with a small team. I knew the team grew over time, but just that is a huge time commitment and then you could argue a distraction from the building. Clearly not a distraction, clearly a core part of the success. Do you feel like that's the volume people need to do to figure out what actually needs to happen?

有一点要强调，早期访问群体不一定只是那些非常有影响力的品味引领者。你知道，Lenny，你就属于这一类，我们当然想得到你的很多反馈，因为你非常贴近市场上许多其他产品，也是这些东西的重度用户。但我们也想让更多非传统画像的人参与早期访问，这些人是我们公司以前从未真正接触过的。举个例子，有一位咖啡店老板，是公司里某人的朋友的朋友，他听说了 Grok Bot，有一天核心团队的人给他演示了 TestFlight 版本，他非常兴奋。这位咖啡店老板最后不仅是 Grok Bot 的出色重度用户，也是我们丰富的反馈来源。我们有一个非常活跃的讨论串，里面有很多很多被发现的 bug 或功能请求，这是一个完全不同的经营小生意的用例。比如如果 Shopify 集成有点不稳定，或者它没有以某种特定方式为产品写文案，我们就会得到非常丰富的反馈，这和我们内部 dogfooding 得到的反馈类型相当不同。所以我觉得这对我们来说是一次重要的练习，去检查自己的盲区，然后说：第一，这会是一个非常通用的产品，不只是开发者用的东西。事实上，它很可能对非开发者最强大。我们需要更好地理解这个群体。第二，我们绝对生活在硅谷 AI 泡沫里，我认为这是一个有用的位置，可以推动前沿、推动这些产品演进的未来。但我们需要主动走出这个泡沫，因为我觉得这样的产品有机会真正成为主流用户和主流商业客户以有用方式与 AI 交互的途径。

Well, one thing to emphasize is the early access group is not necessarily just people that are highly influential taste makers. You know, you're in this category, Lenny, and we certainly wanted to get a lot of your feedback just from being very close to many other products on the market and just being a power user of these things, but we also wanted to get early access to more unconventional profiles that we as a company had never really interacted with. So one example is there's a coffee shop owner that was a friend of a friend through the company who had heard about Grok Bot and one day somebody on the core team had shown them a demo of the test flight and got very excited and this coffee shop owner ended up being not only an amazing power user of Grok Bot but also a rich source of feedback for us. We have a very lively thread with many, many bugs that get identified or feature requests and it's a completely different use case of running a small business. And so for example if the Shopify integration was a bit flaky or if it wasn't writing copy for products in a particular way, we would get really rich feedback on that, which is pretty different from the type of feedback we'd get from dog fooding this internally. And so I think it was an important exercise for us to check our blind spots and say, A, this is going to be a very general product that is not just a thing that developers use. In fact, it is likely that this is most powerful for non-developers. We need to understand that group much better. And then B is we absolutely live in this kind of Silicon Valley AI bubble, which I think is a useful place to be to push the frontier and push the future of how these products are evolving. But we need to actively get out of that because I think a product like this has the chance of really being the way that the mainstream user and the mainstream business customer can interact with AI in a way that's useful.

我们快速回到时间线，稍微理解一下。从第一行代码到内部 beta 是一个月，那之后发生了什么？

Let's go back to the timelines real quick just to kind of understand that. So it was a month from first line of code to internal beta and then what happened after that?

从内部 beta 到公开发布大约三周，然后截至录制时，我们距离公开发布大概三周。

It was about three weeks from internal beta to public launch and then I think we're about three weeks out from public launch as of recording this.

哇。好。所以，一个月做出第一个东西，只有三周迭代，然后发布才三周。从我的角度看，它感觉像改变了世界。所以，哇。好。在那三周内部 beta 里，变化最大的是什么？

Wow. Okay. So, month of building the first thing, three weeks only of iterating and then it's been only three weeks since launch. It feels like it changed the world from my vantage point. So, wow. Okay. What most changed in those, I don't know, in those three weeks of internal beta, let's say?

我们砍掉了很多东西。

We unshipped a lot.

我真希望我能让你看看发布前大概两周的样子，那时我们意识到核心团队有很多实验性功能，我们想获得内部反馈，这很有用。我们还在 Grok Bot 里放了类似开发者用的可见性工具，而不是单独做一个可观测性面板。比如，我们实际上有时会暴露模型大量的内部思考过程、它存储的具体记忆等等，这些对调试问题很有用。如果你在构建产品，你不想去别的地方拉取这些上下文。但我们必须非常激进地裁剪我们认为用户绝对需要看到的内容，以及他们不需要看到的。我认为那里还有更多空间可以跑，这也是团队现在专注的事情：如何无情地简化这个产品，把用户不需要主动思考的任何东西都抽象掉。所以那是一个大推进：去掉很多杂乱的东西。然后我认为那几周的第二个大推进是让它真正能用。我认为很多人想从 AI 得到的不是这个有大量下拉菜单和花哨功能的东西，而只是一个你描述任务的东西，一个对你有意义的任务，然后它去执行，带着完整的工作回来，或者带着一些东西回来让你反应，然后在下一个周期引导它。所以为了真正兑现这个承诺，其实不是很多功能产品路线图式的东西，而是在后端爬五个非常重要的问题，很多用户不会直接体验到，但当你知道你的机器人出去做某事却点不到正确的按钮，或者你的机器人出去做某事却登录不了网站，完全阻碍了你推进那个任务的能力时，你完全能感受到。所以那几周我们收集了非常丰富的集合：人们实际给机器人什么任务，我们如何量化这些东西，以及我们如何周复一周地看到，在这些任务类别中，我们在让它在幕后真正能用的非常重要维度上爬坡。

I wish I could have shown you what things looked like maybe two weeks out from launch, where we'd realized that the core team had a lot of experimental features we wanted to get internal feedback on, which was useful. We were also putting pseudo-developery visibility tools into Grok Bot instead of having a separate observability pane for those things. For example, we actually exposed a lot of the internal thinking of the models and the specific memories it would store, all of these things, which was useful to debug issues. If you're building the product, you didn't want to go somewhere else to pull that context. But we had to really aggressively trim what we think the user absolutely needs to see on the surface versus what they don't. I think there's even more room there to run, which is something the team's focused on right now: how can we just ruthlessly simplify this product and abstract away anything the user doesn't need to actively be thinking about. So that was one big push: to unhip a lot of jank. And then I think the second big push those few weeks was making it just work. I think a lot of what people want from AI is not this thing with lots of drop-down menus and bells and whistles, but just a thing where you describe a task, a task that's meaningful to you, and it goes and does it and comes back with complete work, or it comes back with something for you to react to and then steer it in its next cycle. And so in order to actually deliver on that promise, it's actually not a lot of feature product roadmap style stuff; it's like hill climbing five really important problems in the back end that many users don't directly experience, but you totally feel when your bot is going off and doing something and can't click the right button, or your bot is off and doing something and can't log into a website and it just completely stalls your ability to make progress on that task. And so those few weeks we collected a really rich set of what are tasks that people actually are giving the bot, how can we quantify these things, and how can we see week over week that across those categories of tasks we were hill climbing on very important dimensions to making that just work behind the scenes.

你爬的那些坡中，有没有一个例子是技术突破或你克服的技术挑战，真正帮助它变得能用？

Is there an example of one of those hills you were climbing that was a technical breakthrough or technical challenge you overcame that really helped it just work?

是的，一个例子来自 Grok Bot 的推出。公司内部有一个团队，可以说对机器人非常着迷，那就是我们的市场推广团队，也就是销售。销售使用的一堆工具没有良好支持的 MCP 或 API。我认为这就是为什么机器人对这个团队来说如此具有前后对比的强大力量：这些是他们无法可靠地交给其他 AI 工具的事情。我们会在流程的某个部分卡住。然后机器人感觉就像他们有了一个助手，或者感觉像他们给个人团队入职了一个人。他们给了它一台笔记本电脑，它就能跑起来。所以有一堆小事情，你知道大概有 10 到 20 个，在某些地方，出于某种原因，鼠标就是没有足够精细的控制来点击 Salesforce 仪表盘的精确部分或类似的东西，我们不得不把它带回给真正在基础设施上工作的核心团队，说这里有一个非常具体的案例，智能体没有对浏览器的这种可见性或对屏幕上像素的这种可见性，使得这个任务无法完成。这比看到仪表盘上的数字慢慢爬升要具体得多。这有点像新的工作块被解锁，你会立即感受到反馈：你发布了一个改进，它有点幕后，有点基础设施性质，然后第二天你就会收到销售团队的大量爱和感激，说这个过去七天一直失败的工作流终于能用了。这只是一个不断寻找下一个要解锁的任务然后解决它们的练习。

Yeah, one example was from rolling out Grok Bot. One group inside of the company that was actually incredibly botpilled, so to speak, was our go-to-market team, was sales. And there are a bunch of tools that sales uses that do not have well-supported MCPs or APIs. And I think that's a lot of what made the bot so before-and-after powerful for this group: these were things that they just could not give another AI tool reliably. We would get stuck at some part in the process. Then the bot kind of felt like they had an assistant or kind of felt like they onboarded someone to their personal team. They gave it a laptop and it could just run. And so there were a bunch of small things, and you know probably a list of 10 or 20 of them, of places where for whatever reason the mouse would just not have fine enough control to click on exactly that part of the Salesforce dashboard or something like that, that we would have to take back to the core team working on really the infrastructure to say here's a very concrete case of where the agent not having this visibility into the browser or this visibility into the pixels on the screen is making it impossible for this task to be done. And that was just a lot more tangible than seeing a number on a dashboard slowly creep up. It was kind of like new chunks of work getting unlocked, and you would immediately feel the feedback where you would ship an improvement that was kind of behind the scenes, kind of infrastructury, and then the next day you would just get this outpour of love and appreciation from the sales team that now this workflow that was failing the last seven days finally works. And it's just a constant exercise of finding those next tasks to unlock and then solving them.

所以，计算机使用方面的改进似乎是一个大解锁。我还听说，嗯，我请了 Adam Ward 上播客，他是招聘主管、招聘负责人，基本上是人才主管。我听说他的团队是 Grok Bot 的顶级用户之一。

So, computer use basically improvements seems like a big unlock. I heard also the um I had Adam Ward on the podcast who's head of recruiting, head of hiring, basically head of talent. I heard his team was like one of the top users of Grok Bot.

是的，招聘团队给了我们很多很好的反馈。任何时候产品，尤其是在早期，如果有小 bug，我们就会收到招聘团队一些人的消息。是的，我认为招聘的主要用例特别有趣的是，首先它作为寻源工具非常有价值。我认为 Adam 在播客中和你谈到的一件事，也是我们内部招聘理念的重要部分，就是正在找工作、在市场上并不是我们试图招聘你的前提条件。在很多方面，最好的招聘方式其实就是看看公司最大的问题，需要有人拥有它或把它提升到下一个层次。找出全世界所有人中最合适的人，然后无情地追求他们，试图说服他们加入。这是公司从一开始就有的很多理念。所以如果这是你的心态，那么真正最好的招聘工作流或要自动化的流程不是，你知道，这里有一堆简历，读一遍，帮忙分类。最有用的东西是这里有一个完整的潜在人才宇宙。帮忙把它匹配到这个非常具体的业务问题或我们正在招聘的这个非常具体的角色，并帮我联系他们。帮我约他们喝咖啡。让我们全力以赴。所以有一些案例，以真正意想不到的方式找到顶尖人才，甚至超越了只是在 LinkedIn 上寻找有趣的人。而是，这篇论文的合著者是谁，PDF 在 Google Scholar 上不存在。它只存在于这个会议网站上。我想让你每天早上都去会议网站，下载 PDF。如果有新的，你应该找到我们尚未追踪的每个新名字。你应该把那个名字加到电子表格里。你应该做研究。你应该看看 SpaceX 的每个人，看看有没有直接联系的人。如果有，你应该给他们发 Slack 消息请求介绍。就像这类始终在线的寻源用例，我认为过去非常手动，现在 AI 在这方面超级人类。我们的团队可以专注于搞定优秀候选人、与优秀候选人对话，而不是拉这些巨大的名单。

Yes, the recruiting team gave us a lot of great feedback. Anytime the product, especially in the early days, if there was a little bug, we'd get a ping from some folks on the recruiting team. Yeah, I think the main use cases for recruiting that were particularly interesting was first it was incredibly valuable as a sourcing tool. And I think one thing Adam talked about on the podcast with you, and it's a big part of our hiring philosophy internally, is be looking for a job being on the market is not a precondition for us trying to hire you. And in a lot of ways, the best way to hire is really just look at the biggest problems at the company that needs someone to own it or take it to the next level. Find out of the total universe of people in the world who would be best and then ruthlessly go after them and try to convince them to join. And this is a lot of the philosophy from the very beginning of the company. And so if that's your mindset, really the best recruiting work stream is not or workflows to automate are not, you know, here are a bunch of resumes, read through them, help sort them. The most useful thing is here's an entire universe of potential people. Help match that to this very concrete business problem or this very concrete role that we're recruiting for and help me get in touch with them. Help me get coffee with them. Let's just throw everything at it. And so there have been some cases of really kind of unexpected ways of finding top talent that is beyond even just looking on LinkedIn and trying to find interesting people. But who are the co-authors of this paper and the PDF doesn't exist on Google Scholar. It just exists on this conference website. I want you every morning to go to the conference website, download the PDFs. There are any new ones. You should find every new name that we've not yet tracked. You should add that name to a spreadsheet. You should do research. You should look at everybody at SpaceX, see if there's anyone directly connected. If so, you should send them a Slack message asking for an introduction. Like, it's those types of always-on sourcing use cases that I think in the past were incredibly manual and now it's the type of thing AI is superhuman at. And our team can focus on closing great candidates and getting conversations with great candidates and not pulling these huge lists.

哇，这真是个很酷的例子。首先，有人马上会把你刚才说的话转录下来，放进一个机器人里，做出他们自己的版本，这很棒。另一方面，我觉得你们可以把这个机器人的模板卖到十亿美元。如果我们基本上能用 Adam 团队寻找最佳人才的策略，把它变成一个机器人，天哪，招聘就民主化了。

Wow, that is such a cool example. First of all, someone's about to take the transcript of what you just said, put it into a bot, and create their version of this, which is great. On the other hand, I think you guys could sell a template of this bot for a billion dollars. If we could basically use Adam's team strategy for finding the best people and just turn it into a bot, holy moly, democratizing hiring.

我想回到几个点上。好。其中一个是你提到的“取消发布”这一点。我认为这是一个人们容易忽视的重要观点，因为 AI 不擅长告诉你该去掉什么。它很擅长说“好的，这里有更多想法，这里有更多东西”。播客上多次提到，这是一个巨大的机会。这是人类继续非常重要和有价值的一大空间，即知道不该发布什么、该砍掉什么、不该做什么。所以听到这是从原型到发布内部演进的重要部分，即决定“好，我们需要砍掉一堆东西”，这非常有趣。还有什么要补充的吗？

I want to come back to a few things. Okay. So, one is you made this point about unshipping. Such an important point I think that people can overlook because AI is not good at telling you what to take out. It's very good at okay, here's more ideas, here's more stuff. And something that's come up a number of times on the podcast is that's a big opportunity. That's a big space for humans to continue to be very important and valuable is knowing what not to ship and what to cut and what not to do. And so it's so interesting to hear that that's been a big part of the internal evolution from prototype to launch is deciding okay we need to cut a bunch of stuff. Anything more there?

是的。所以，我们内部讨论的一件事是，对于我们在 Grok Bot 上做的任何事情，发布帖是什么？比如，我们真正要告诉用户的是什么？如果不是一条推文，我想是发布推文。如果它不吸引人，也许我们就不该做它。如果它不是用户在产品中能直接感受到的东西，再进一步说，我认为有一种老派软件倾向，会说“Grok Bot 现在有了”，当你完成这个句子时，它会是“一个新按钮可以按”或“一个新的下拉菜单”或“一个新的集成，你可以按加号添加”，而应该重新表述为“Grok Bot 现在可以”，这是一种更人性化的描述这些能力的方式。我认为这迫使我们更多地从“我们能给 Grok Bot 什么工具和能力”的角度思考，而不是“我们能在产品中添加什么新东西”。给产品添加东西不是目标。那不是推动这个产品前进、让它对更多人更有用的东西。让你的机器人可靠地在幕后为你做真正有影响的工作，以一种顺畅的方式，并赋予它们这样做的能力。这才是用户真正关心的。所以，在“取消发布”的背景下，有很多“Grok Bot 现在有”的东西，我们意识到它们实际上只是不需要像素的能力。你知道，让我们尽可能多地消灭像素。那些可以只是你的机器人在幕后为你操作的东西，你不需要直接控制。我认为一个例子是，我们许多竞争对手设置自动化或例程的方式是，你进入侧边栏，按加号，选择触发事件，然后选择之后应该采取的行动。你可能会用自然语言描述，但这真的很笨拙，意味着人们不会为很多事情设置很多自动化。我们在编码领域肯定看到了这一点。所以我认为 Grok Bot 对此的回应是，实际上你应该用自然语言定义自动化。你应该告诉你的机器人：“请每天上午 8 点提醒我。”然后它就应该做到。你永远不必看到创建自动化的界面。这就是我们做出的决定。现在，平台上 99% 的自动化都是这样构建的。我认为还有很多其他地方我们可以做类似的事情。

Yeah. So, one thing we talk about internally is for anything that we're working on for Grok Bot, what is the launch post? Like, what is the thing that we would actually tell users? And if it's not a tweet, I imagine launch tweet. And if it's not compelling, maybe we shouldn't be working on it. If it's not something that users will directly feel in the product and to take that even one step further, I think there is this old school software tendency to say things like Grok Bot now has and when you think of completing that sentence it would be like a new button to press or it'd be a new drop down or it'd be a new integration that you can press plus and add and instead to reframe it as Grok Bot can now which is a much more human way of kind of describing these capabilities. And I think it's forced us to think more in the frame of what are tools and what are capabilities that we can give Grok Bot, not what are new things we can add to the product. Like adding things to the product is not the goal. That's not the thing that's going to push this product forward and make it more useful to more people. Making your bots reliably do really impactful work for you behind the scenes in a way that just works and giving them the capabilities to do that. Like that's what users actually care about. And so I think in the context of unshipping there have been a lot of Grok Bot now has things that we've realized are actually just capabilities that don't need pixels. You know, let's kill as many pixels as we can. Those can just be things that your bot manipulates behind the scenes for you and you don't need to directly control. And I think one example of this is the way that many of our competitors you set up automations or routines is you go into a sidebar, you press plus, you select, you know, what the trigger event is. You then select what action it should take after that. You might describe it in natural language and it's just really clunky and it means that people don't set up many automations for many things. We certainly have seen this in the coding realm. And so I think what Grok Bot did in response to that was actually you should just define automations in natural language. You should tell your bot, remind me that at 8 a.m. every day, please. And then it should just do it. And you should never ever have to see that interface of creating an automation. And so that's kind of the decision that we've made. And now that's how 99% of automations on the platform get built. And I think there are a bunch of other places where we can do things like that.

所以，我在 Grok Bot 发布时发推说我很喜欢它，很多人回复。他们说：“等等，你不是可以用 codecs 和 co-work 做所有这些吗？据我所知，技术上你能用 Grok Bot 做的，你也能用其他基础模型、编码助手做。所以，让我问你这个大问题。你认为你做了什么如此不同的事情，使得 Grok Bot 如此成功？”

So, I tweeted about how much I love Grok Bot when it launched and a lot of people replied. They're like, "Wait, can't you just do all this with codecs and co-work and you can technically everything as far as I know you can do with Grok Bot you can do with the other foundational models, the coding assistants. So, let me just ask you this big question. What is it that you think you did that is so different that allowed that made Grok Bot so successful?"

我认为是两个早期决定，当时肯定不明显，但事后看来，我认为对 Grok Bot 为何能为人所用至关重要。第一个是，你永远不必考虑本地和云端，以及这些工作流在哪里运行？我的电脑必须开着吗？如果我从手机启动它，它需要连接到家里的电脑吗？现在人们试图概念化这个运行时在哪里时，发生了很多混乱。我们很早就决定，这应该全部在云端。如果它在云端，并且是一个持久的同事，有自己的电脑，它就能做自己的工作。无论你在哪里与它交互，它都有相同的状态。这开启了很多非常棒的机会，可以给你的机器人发短信，从手机启动它。未来，你应该能够从任何地方呼叫你的机器人，它应该能够做真正的工作。就像这是一个独立的实体，与你的设备分开生活。我认为这是一个非常重要的决定，我认为当前的产品没有做出同样的决定，我认为因此有很多小问题，用户每天都能感受到。我认为第二个决定是更进一步，不仅这应该是一个在云端运行的智能体循环，你可以以各种方式与之交互。这些机器人拥有自己的电脑实际上非常重要，部分原因是我之前描述的，有很多任务没有良好支持的 MCP 和 API。我们人类不是通过 MCP 和 API 来做工作的。我们使用电脑，点击像素，在输入框中输入东西。你的机器人拥有这些基本能力也非常重要。但更进一步，我认为我们现在处于一个非常奇怪的时刻，我想我们会回顾并说，我很惊讶这是很多人与 AI 合作的方式，你正在入职这些超级智能的新同事，这些 AI 机器人，你要求它们和你共用同一台电脑。这太疯狂了。就像，如果你要入职一个人到你的团队，你说：“这是你的第一天。我要给你入职。你没有自己的笔记本电脑。你要坐在我旁边。我们要永远共用这台笔记本电脑，不断互相绊倒。你可以访问我的凭证。我可以访问你的凭证。”这就像，人们不这样操作是有充分理由的。我认为未来的机器人和这类 AI 同事也需要一种类似的入职方式。

I think it was two early decisions that at the time definitely did not feel obvious, but in hindsight I think are critical to what makes Grok Bot work for people. And the first is you should never have to think about local and cloud and where are these workflows running? Does my computer have to be awake? If I kick it off from my phone, does it need to be tethered to my computer back at home? Like there's so much jank happening right now when people are trying to conceptualize where this runtime lives. And we made a really early decision that this should just all be in the cloud. And if it's in the cloud and it's this persistent colleague that has its own computer, it can do its own work. It has the same state everywhere you interact with it. It opens up a lot of really amazing opportunities to text your bot, kick it off from your phone. In the future, you should be able to call your bot from anywhere and it should be able to do real work. Like this is its own entity and it lives separately from your device. And I think that was a very important decision that current products I think haven't made that same decision and I think it has a bunch of paper cuts as a result of it that users feel every day. I think the second decision was kind of to take that one step further of not only should this be an agent loop that kind of runs in the cloud and you can interact with in various ways. It's actually really important that these bots have their own computer and part of it is what I described earlier of there are a bunch of tasks that don't have well-supported MCPS and APIs. We as humans don't do our jobs via MCPS and APIs. Like we use a computer and we click on pixels and we kind of type things in input boxes. And it's very important that your bot has those baseline capabilities as well. But even to go one step further, I think we're in a really weird moment right now that I think we're going to look back on and be like, I'm surprised that this is the way that a lot of people worked with AI where you're onboarding these super intelligent new colleagues, these AI bots and you're asking them to share the same computer that you have. It's crazy. Like, if you were onboarding someone to your team and you said, "It's your first day. I'm going to onboard you. You don't have your own laptop. You're going to sit next to me. we're going to share this laptop forever and constantly trip over each other. You're going to have access to my credentials. I'm going to have access to your credentials. Like that's just there's a good reason why that's not the way people operate. And I think bots and these kind of AI colleagues of the future will also need a way to onboard them that's somewhat similar.

这太有意思了。你觉得为什么其他公司没有这么做？

That is so funny. Why do you think the other companies didn't do this?

我猜他们是在自己现有的编程助手平台和方法上做延伸，而这是一个相当大的转变。我觉得很大程度上关键在于从零开始，以及那种自由感。我们自己也有体会：Grok Bot 里的很多原语，我们之前都尝试过，或者用其他方式构建过——比如我们为编程智能体搭建的云基础设施，比如你可以给智能体命名、把它们当作独立个体来对话。这也是我们在开发者身上看到的模式，把特定的命名智能体带进 Slack。但我们没有试图把这些概念硬塞进某个新界面或现有界面里——我觉得对很多公司来说，那会是强烈的默认选择——我们决定从零开始。我们决定先把这些东西为通用知识工作真正做对，这是一个新的受众群体；其次，针对我们现在所处的这个时间点，模型已经非常强大，如果你给它们合适的工具和合适的基础设施，它们能做很多事。但这些想法并不是我们灵光一现的杰作，我觉得这也有充分的理由——这些原语早就已经受到关注，并在其他产品上获得了产品市场契合，比如 OpenClaw 这类产品。我们从中学到了很多灵感，并试着把它产品化成一个更紧凑的界面，设置更少，对更多人更易用。所以我觉得我们的竞争对手和其他试图解决这类问题的工具——我们看到的都是同一个机会。我们看到了市场上大量的反馈，但如果你被困在现有范式里，就很难付诸行动；如果你在现有范式里有大量沉没成本，从零创造新东西就非常痛苦。我认为正是这些让产品能够直接奏效，并让这么多人产生共鸣。

My guess is they were building off of their existing coding assistant platform and approach, and this was a pretty big shift. I think a lot of it comes down to starting from scratch and how freeing that is. We felt that ourselves, where a lot of the primitives in Grok Bot we had attempted or built in other ways — cloud infrastructure we built for coding agents, the way you could name agents and talk to them as discrete entities. It's a pattern we're also seeing for developers, bringing specific named agents into Slack. But instead of trying to retrofit those concepts into some new surface or an existing surface, which I think would have been the strong default for many companies, we decided to start from scratch. We decided to just try to get these things really right for general knowledge work, which is a new audience, and then second, for the point in time that we're at now, where the models are very capable and if you give them the right tools and the right infrastructure they can do a lot. But a lot of these ideas aren't strokes of genius on our part, and I think for good reason — these are primitives that had already been getting attention and product-market fit by other products, you know, the OpenClaw of the world. I think we took a lot of inspiration from that and tried to productize it into a bit of a tighter surface, something that required a little bit less setup and was more accessible to more people. So I think our competitors and other tools that have been trying to solve these types of problems — I think we're all seeing the same opportunity. We're seeing a lot of that feedback from the market, but I think it's just been hard to act on if you're stuck in the existing paradigm, and if you have a lot of sunk cost in that existing paradigm, it's very painful to create a new thing from scratch. And I think a lot of that is what allowed the product to just work and click for so many people.

所以我在这里听到的是它成功突围的关键。为每个机器人配一台云端电脑，而不是本地。一个名字，像是特定的机器人。顺便说一句，现在大家都在从智能体转向机器人了。干得漂亮。感觉是你们把它推过了临界点。好，现在我们都是机器人了。所以每个任务用例一个机器人，这和线程对话或一次性任务非常不同。然后感觉“直接就能用”是核心部分，你也谈到了花了多久才达到那个状态——好，现在它真的运行得很好。你提到了 OpenClaw——显然这是受它启发，我第一次用 OpenClaw 的时候就想，天哪，这就是未来，我们怎么能没有这个？然后 Hermes 出来了，所有人都在试图打造一个对每个人都极其易用的 OpenClaw。你能多讲讲 OpenClaw 和那段故事是如何影响你们思考这件事的吗？

So what I'm hearing here is the keys to success of what made this break out. A cloud-based computer for every bot instead of locally. A name, kind of like a specific bot. And by the way, there's this — we're all moving from agents to bots now. Nice job. Feels like you guys have pushed it over. Okay, we're all bots now. So a bot per task use case, very unique versus a thread conversation or a one-off job. And then it feels like "it just works" was a core part of this, and you talked about how long it took to get to that place of, okay, now it actually works really well. You mentioned OpenClaw — obviously this is inspired by that, which to me, when I first used OpenClaw, I'm like, holy, this is the future, how could we not have this? And then Hermes came out and everyone's been trying to build the OpenClaw that works very easily for everybody. Can you say more about how OpenClaw and that story informed the way you guys thought about it?

是的，我觉得 OpenClaw 做对了两件大事，当我们看到市场对 OpenClaw 的反应、以及我们自己使用这个产品时，都觉得非常兴奋。第一件事是：模型非常聪明，而且会继续变得更聪明，但即便在目前的能力水平上，如果你能让你的机器人访问你用来完成工作的那些工具，它就能在很多人们认为 AI 很笨、或者没有宣传中那么有影响力的地方走得很远。我认为其中很大一部分原因，只是它被以错误的方式驾驭了。所以如果你给它访问更大范围的东西，如果它能访问自己的电脑，你能走多远？我觉得 OpenClaw 真的让很多人被迫面对这个问题。然后我觉得 OpenClaw 改变 AI 心智模型的第二种方式，是真正把这些东西更多地看作同事、队友和人，更多地拟人化，把它当作一个有生命的助手实体，能访问你的生活，并进一步延伸你。所以我们吸收了很多这些，而 Grok Bot 可能延伸的是：第一，它必须非常容易设置——那种“你家里有个 VPN 和一台 Mac mini”的极客式搭建显然无法扩展到数百万用户，显然也不会是企业利用这项技术的方式。所以我们真的想带着这个意识去打造一个出色的产品。第二，我觉得有很多粗糙的边缘需要打磨，做出令人愉悦的产品体验，让这些东西直接就能用，并试着去掉一些 AI 高级用户非常熟悉的抽象概念——比如 skills。我们怎么才能让 Grok Bot 用户甚至不需要知道 skill 是什么？他们永远不该需要输入斜杠命令。这些东西应该在后台被创建为机器人可以访问的有用原语，但用户——不应该由他们来始终站在 AI 的最前沿。所以这才是我们真正尝试创新的地方。我觉得那里还有更多空间可以走。

Yeah, so I think OpenClaw got two major things right that, when we were seeing the way the market was reacting to OpenClaw and ourselves using the product, we found quite exciting. I think the first thing was: the models are really smart and they're going to continue to get smarter, but even at current capability levels, if you can just give your bot access to the tools that you use to do your job, it can get a lot of the way there in a lot of the places where people think AI is dumb or maybe not as impactful as it's been promised. A lot of that, I think, is downstream of it just being harnessed in the wrong way. So if you give access to a much larger set of things, if it has access to its own computer, how far can you go? And I think OpenClaw really forced that question for many people. And then I think the second way OpenClaw changed the mental model of AI was really viewing these things much more as colleagues and teammates and people, personifying it a bit more, and it being this helper entity that has access to your life and can extend you even further. So we took a lot of that, and I think what Grok Bot maybe extended was, first, it needs to be really easy to set up — the hacky "you have a VPN at home and a Mac mini" setup clearly was not going to scale to millions of users, clearly is not going to be the way businesses take advantage of this technology. So we really wanted to build an amazing product with that in mind. And then second, I think there are a lot of rough edges to sand down and just make a delightful product experience and make these things just work, and try to remove some of the abstractions that power users of AI are very familiar with — things like skills, for example. How can we make a Grok Bot user not even have to know what a skill is? They should never have to type a slash command. These things should be created in the background as a useful primitive that the bots have access to, but something that users — it's not incumbent on them to always be on the cutting edge of AI. And so that's really where we tried to innovate. And I think there's still more room to go there.

你说到这个，我那儿还有一台 Mac mini，上面装着我以前还活着的 OpenClaw。那是一个时代，它激发的工作太棒了。我知道它还在继续。我知道 OpenClaw 仍然有很多价值，但当我看到 Claire Vo——她一直是 OpenClaw 最大的支持者，OpenClaw 已经成为她生活、和孩子相处以及所有工作的核心部分——她刚刚把她所有的 OpenClaw 都切换了。她把它们全关了，换成了 Grok Bot。这是一个巨大的——听起来好笑，但这实际上是一个巨大的里程碑，说明事情变化有多大。Grok Bot 的愿景是什么？它会走向哪里？未来会是什么样？Grok Bot 理想的柏拉图式版本是什么？

As you say that, I have my Mac mini with my formerly alive OpenClaw on there. And that was an era, and it's so awesome the work that it has inspired. I know it continues. I know there's still a lot of value to OpenClaw, but when I saw Claire Vo, who's been like the biggest proponent of OpenClaw and has become a core part of the way she lives and works with her kids and does all her work — she just switched all of her OpenClaws. She's shut them all down and switched to Grok Bot. That's a huge — it sounds funny, but that's actually a huge milestone of just how much things have shifted. What's kind of the vision for Grok Bot? Where does this go? What does this look like in the future? What's the ideal platonic version of Grok Bot?

Grok Bot 的终极愿景非常简单，就是：你应该拥有一支 AI 机器人团队，帮你完成工作，也帮你处理生活。它应该真的感觉像一支团队。应该真的感觉像自主的队友在帮助你。你可以用各种方式引导它们。你不需要微观管理它们。它们能访问完成宏大而有野心的工作所必需的工具。

The ultimate vision of Grok Bot is incredibly simple, which is: you should have a team of AI bots that help you with your job and help you with your life. And it should really feel like a team. It should really feel like teammates that are autonomous, are helping you. You can steer them in various ways. You don't have to micromanage them. They have access to the tools necessary to do great ambitious work.

在打造这个产品时，我们在产品侧真正用作北极星的一件事是：随着我们越来越接近这个“队友”的未来，我们如何在每一个产品决策中，少从 SaaS 产品的角度思考，多从“我们要打造有用的 AI 队友”的角度思考。所以有很多例子，我们不得不推动自己更像“同事式”一点。我们有时会用这个词，当我们在争论某个产品问题时。一边有很好的论据，另一边也有很好的论据。两条路都感觉合理。在产品领域，这或许感觉没有明确的答案。然后你稍微跳出来，把自己从科技公司的氛围中抽离出来，开始想：人类会怎么做？在这种情况下，你希望你的队友怎么做？通常答案非常清晰，而且相当一致。房间里的人对于你更愿意以某种方式合作的人类队友，往往没有太多分歧。一旦答案有了，我们就只需要去构建它。这有产品层面的影响，有模型层面的影响，有很多事情需要做对才能真正交付那种体验。但某种程度上，这并非火箭科学。不需要你是天才。你只需要问：你希望人类队友怎么做？我们能否推动 AI 以类似方式行事？举个例子，我们一直在思考这些机器人应该有什么样的正确语音体验。比如在人类的语境中，我们有一个很好的类比：很多时候我在 Slack 上和队友来回沟通，分享上下文，但很多时候更简单的是直接开一个五分钟的 huddle，按下 huddle 按钮，来回交谈。我分享屏幕，展示我脑子里想的东西。他们分享屏幕。我们挂断，然后继续异步沟通。而目前还没有任何 AI 产品真正做对过这种体验。我认为这深深植根于人类协作的方式。所以我们想打造类似的东西。还有很多其他例子，这些非常清晰的模式就是有效，我认为你在与 AI 合作时也应该感受到。

And one thing we really use as a north star on the product side in building this is as we kind of get closer to this teammate future, how can we in every product decision we make think about this less from the perspective of a SAS product and more from the perspective of we're trying to build useful AI teammates. And so there have been a bunch of examples where we kind of have to push ourselves to be more like colleague pill in a way. We sometimes use that term where we're having a product debate about something. There are good arguments on one side. There are good arguments on another side. Both paths feel sensible. Like in product land, this maybe doesn't feel like there's a clear-cut answer. And then you zoom out a little bit and you remove yourself from the, you know, tech companiness of it all and you start thinking, how would a human do this? Like what would you want from your teammate in this exact situation? And oftentimes the answer is really clarifying and pretty unanimous. There's oftentimes not a lot of disagreement among the room of like how a human teammate you would prefer to work with in a certain way. And then once that answer is there, well then we just need to build it. And there are product implications, there are model implications, there's a lot of things that need to go right to actually deliver on that experience. But in some ways it's not rocket science. Doesn't require you being a genius. you just need to ask the question of what would you want from a human teammate and can we push AI to behave in a similar way and so to give some examples of that I mean we've been thinking about what the right voice experience with uh these bots should be and I think in the context of a human for example we have a really good analog of a lot of times I'm slacking back and forth with a teammate we're sharing context and a lot of times it's just much simpler to get on a fiveminute huddle with them and just press huddle talk back and forth I share my screen. I show exactly what's on my mind. They share their screen. We hop off and then we continue async from there. And that's not really an experience that any AI product has gotten right right now. And it is deeply integral to the way that I think humans collaborate. And so we want to build something like that. And there are a bunch of other examples of these like very clear patterns that just work uh that I think you should also feel when working with AI.

我喜欢“同事式”这个说法。在这次对话中已经多次提到，它如何成为做这些决策的一条主线。比如你举的电脑的例子就很好，显然人们会有自己的电脑。命名也是其中很重要的一部分。在这个领域，我脑子里有一个大问题，非常好奇你的看法：工作和个人的分离。你认为人们会有两个不同的助手，一个工作用，一个个人用，还是认为会是一个？

I love this term colleague build. such and it's come up so many times over the course of this chat already how that is kind of a throughine to making these decisions for example the computer example you gave is so good obviously people would have their own computer the naming piece is also a very important part of that a big question on my mind in the space and I'm so curious to get your take is the separation between work and personal do you think people will have two different assistants a work and a personal or do you think it'll be one

当人们想到工作产品与消费产品时，我认为过去一二十年糟糕的 B2B 软件带来了很多包袱。这导致人们看到一个在某些方面非常简单的产品，比如 ChatGPT 就是这样。我认为 Grok Bot 也有许多这样的特性，就假设它不是工作产品，或者假设它不是强力工具。当你想到上一代的强力工具时，我脑海中会浮现类似 Photoshop 的东西，有各种不同的旋钮可以非常精确地调节。工具的用户是那种终极驾驶舱飞行员，确切知道每个旋钮的作用，并能完美使用。而我认为未来的强力工具实际上会非常不同。它主要是表达意图，由人类进行良好的引导，而这些 AI 工具把所有旋钮都抽象掉了。你永远不应该看到它们，除非你需要直接操作，这可能会发生，应该有很好的可供性，但最终它真的只是与队友合作。所以界面非常对话式。很多时候，当你看到 Grok Bot，比如我走过某人的桌子，看到他们电脑上开着 Grok Bot，一瞬间我会想：哦，他们在用消息应用吗？然后发现不是，这实际上是他们用来完成大部分工作的主要工具。所以对于你个人生活和工作生活是否会有不同的机器人这个问题，我确实认为对很多人来说会有分离。他们希望个人和工作生活分开，我认为这很好，很重要，而且有很多常识性的理由说明为什么这些东西应该分开，甚至从企业的角度来看也是如此。但我认为我们的目标和努力的方向是：Grok Bot 应该成为你日常工作中大部分事情的完成方式。你应该能够把很多工作委托给 Grok Bot，专注于更高杠杆的事情。同样，它也应该成为你委托个人生活中许多低杠杆部分的方式。而这两件事实际上并不是不同的问题集。在很多方面，产品形态和解决这些问题的方式几乎相同。所以我的直觉是，一个产品将是这两者的最佳形态。而这正是我们想要打造的。

when people think about a work product versus a consumer product. I think there's just a lot of baggage that comes from the last decade or two of horrible B2B software. Um, that leads to people seeing a product that is very simple in some ways. Chat GBT was like this. I think Grok Bot has many of these properties and assuming that it's not a work product or assuming that it's not a power tool. And when you think of a power tool in this kind of last generation, I in my head picture something a bit like Photoshop for example, where there are all of these different dials to turn very precisely. You know, the user of the tool is this kind of um you know, ultimate um cockpit flyer who knows exactly what all the knobs do and can like use them perfectly. And I think power tools of the future will actually be very different from that. Uh where it is mostly just intent being expressed and good steering on the part of the human and these AI tools abstract away all of the knobs. you should never see them unless you need to directly manipulate it which might happen and there should be a great affordance for that but ultimately it really is just working with a teammate and so the interface for that is quite conversational and so in a lot of ways Grok Bot when you look at it like when I walk by someone's desk and I see Grok Bot up on their computer for me for a split second I'm like oh are they on like a messaging app and it's like no they're you know this is actually the primary tool that they're using to do much of their work and so I think to question of are you going to have a different set of bots for your personal life and a different set of bots for your work life. Um I do think there will be a separation for many people. They want a separation between personal and and work life and I think that's I think that's great. I think that's important and I think there are a lot of common sense reasons why those things should be separate even from the perspective of of an enterprise. But I think our goal and the thing we're trying to build towards is Grok Bot should be the way that a large portion of the things you do day-to-day in your work. You should be able to delegate a lot of that to Grok Bot and focus on the higher leverage things. And then it should similarly be the way that you delegate a lot of the low leverage parts of your personal life. And those two things actually are not different problem sets. In a lot of ways, the product form factor and the ways of solving those problems is pretty much the same. And so my instinct is that I think one product will be the best form factor for both of those things. And that's really what we want to build.

哇，那是一个巨大的 TAM。我喜欢听到这个。非常合理。显然问题是如何避免交叉污染，你知道，个人东西以某种方式渗透或泄露工作内容。但感觉这还好。所以我听到的是，这就是方向。问题只是如何做到这一点，让人们感到超级安全，有类似 SOC 2 之类的东西到位，同时也感觉真的很有趣。

Bam. That's a big TAM right there. Uh I love I love to hear it. Makes so much sense. Obviously the question is how do you avoid crosscontamination, you know, personal stuff somehow uh infiltrating exfiltrating stuff from work. Uh but feels like that's kind of okay. So what I'm hearing is that's the direction. The question is just how to do that and make people feel super safe. have kind of like the sock tube stuff in place and also just feel really fun.

本集由 Mercury 赞助。现在有了 spend，银行业务截然不同。我成为 Mercury 客户已经很多年了。我把所有商业银行业务都转到了 Mercury，老实说，我不能再满意了。这就是在线银行由产品人而非银行家构建时的感觉。现在有了 spend，你可以给团队个人卡，设置每人或每团队的支出限额，并自动从 Gmail 或短信中提取费用收据。你甚至可以给你的 AI 智能体自己的卡，有自己的限额和政策。大多数创始人开始时都一样，公司所有人共用一张卡。它一直有效，直到失效。有人超支，收据不见了，你花两天时间试图弄清楚谁花了什么以及为什么。

This episode is brought to you by Mercury. Radically different banking now with spend. I've been a Mercury customer for so many years now. I switched all my business banking to Mercury and honestly I could not be happier. It's what online banking feels like when it's built by product people, not by bankers. And now with spend, you can give your team individual cards, set spending limits per person or per team, and have expense receipts automatically pulled in from Gmail or over text. You can even give your AI agents their own cards with their own limits and policies. Most founders start out the same way, one card used by everybody at the company. It works until it stops working. Someone goes over, a receipt disappears, you spend two days trying to figure out who spent what and why.

Spend 是直接内置于 Mercury 的费用管理工具。你团队的所有卡片、预算和报销，都与你的业务思考放在同一个地方。无需催促，无需手动审核，无需月底手忙脚乱。结果是团队可以快速行动，创始人不再是瓶颈。了解更多并注册请访问 mercury.com。Mercury 是一家金融科技公司，不是 FDIC 保险银行。银行服务由 Choice Financial Group 和 column NA 提供，均为 FDIC 成员。IO 卡由 Patriot Bank 发行，为 FDIC 成员，依据 Mastercard International Incorporated 的许可。

Spend is expense management built directly into Mercury. All your team's cards, budgets, and reimbursements. All live in the same place as your business thinking. No chasing, no manual reviews, no end of month scramble. The result is a team that can move fast and a founder who is no longer the bottleneck. Learn more and get signed up at mercury.com. Mercury is a fintech company, not an FDIC insured bank. Banking services provided to Choice Financial Group and column NA members FDIC. The IO card is issued by Patriot Bank and a member FDIC pursuant to a license from Mastercard International Incorporated.

让我问几个技术问题。在计算机方面，作为 Grobot 账户的一部分，你得到的东西最简单的理解方式是什么？是像在云中运行、支持多登录的虚拟机吗？还是每个机器人有独立的虚拟机实例？你能分享多少就分享多少，我们该怎么理解？

Let me ask a couple technical questions. On the computer side, what's the simplest way to think about what you get as part of your Grobot account? Is it like a VM that is running in the cloud with multiple login? Is it like a separate VM instance per bot? How do we understand that as much as you could share?

是的。我想回到产品的队友框架，进一步延伸这个类比：如果我们是一个团队的，你和我，你不得不手动接管我的电脑，开始点击东西，说“你做错了，你应该去这里，手动输入”。希望这种情况几乎为零。希望这不是你真正需要和同事或队友做的事情。同样地，我认为现在我们处于计算机使用还不错的阶段，正在变得更好。很快，计算机概念将完全从用户那里抽象掉。你永远不应该点击进入远程虚拟机。你永远不应该需要接管。如果有浪费的路径，你需要引导它到正确的路径。所以中期来看，我认为计算机概念对用户来说是一个重要的概念，但实际上不会是他们与之交互的东西。所以我认为思考 Grok Bot 的正确方式是它是一个机器人团队。它是一个智能体团队，为你工作。就它们能访问什么而言，它们能访问你与它们过去交互的非常长的记忆集。所以我认为当前的范式是你为每个离散的工作单元创建一个新聊天。我认为这有很多问题。我发现自己总是在聊天之间复制粘贴。我认为这不是分组工作类别的好方法。相反，就像在团队中一样，你有好的方式来分组工作类别，比如角色。你应该有不同工作泳道的角色，它应该向你学习，并随着时间的推移变得更聪明。所以我认为一个非常关键的事情是这些是长期存在的智能体。这些不是一次性的单独会话，这些智能体随着时间的推移变得更聪明。然后第二件事是这些智能体可以访问你期望人类同事拥有的所有工具，即 API、MCP。这很好，但然后还可以访问自己的计算机，它可以像你一样自由操作。

Yeah. I think to go back to the teammate frame of the product, to extend the analogy even further, if we were on a team together, you and me, I think the number of times that you would have to manually take over my computer and start clicking on things and like, you're doing this wrong, you should go here instead and type in manually. Hopefully is pretty close to zero. Hopefully that is not something you have to really do with a colleague or a teammate. And so similarly, I think right now we're in a place where computer use is good. It's getting much better. And in very short order, I think the computer concept will be completely abstracted away from the user. You should never be clicking into a remote virtual machine. You should never have to take control. If there's like a wasteful path and you have to kind of steer it into the correct path. So in the medium term, I think the computer concept will be an important concept for users to have, but will not actually be something that they're interacting with. So I think the right way of thinking about Grok Bot is it's a team of bots. It's a team of agents that do work for you. And in terms of what they have access to, they have access to a very long memory set of your past interactions with them. And so I think there's a current paradigm of you create a new chat for each discrete unit of work. I think there are a lot of problems with that. I find myself copying and pasting between chats all the time. I think it's just not a great way of grouping categories of work. Instead, the same way on a team, you have a good way of grouping categories of work of kind of roles. You should have roles of kind of different swim lanes of work that you do and it should learn from you and it should get smarter over time. So I think that's one very critical thing is these are long-lived agents. These are not individual one-off sessions and these agents get smarter over time. And then the second thing is those agents have access to all of the tools that you would expect a human colleague to have which is the APIs, the MCPs. That's great, but then access to its own computer which it can freely manipulate the way that you would.

在我参加的这个聚会上，Shub，我想是 go-to-market 团队的，演示了一些让大家惊叹的东西，因为每个智能体里都有一个计算机，你可以在计算机上运行很多不同的东西。他在 Grok Bot 里运行 Grok Bot，就像机器人可以运行自己的 Grok Bot。我知道他用它来测试和观察回归等，但这只是一个扩展思维的想法。我很好奇你能走多少层，直到宇宙自我崩溃。

At this meetup that I went to, Shub, who's on the I think go-to-market team, demoed something that blew everyone's mind because you have a computer within each agent you can run a lot of different things on the computer. He was running Grok Bot within Grok Bot, like the bot can run its own Grockbots. And I know he was using it for testing and watching regressions and things like that, but that's just like a mind-expanding idea. And I'm curious how many levels you can go before the universe collapses on itself.

我也这样做。这实际上是非常有用的事情，就是为你的一个机器人下载 Grok Bot。我的就像一个 QA 测试机器人。这样，如果有 bug 报告，或者我们正在测试新构建，例如桌面应用的新版本，我可以直接说：“嘿，这里有 10 个工作流，我们需要确保每个版本都变得更好。我要你测试它。我要你把它写到这个 Notion 文档中，那里有我们过去对所有客户端版本所做测试的详尽列表，并进行比较。”所以我认为一旦你开始突破“这是带有一组连接的 AI 聊天”，我认为这是大多数人现在的概念，而是“这是一个有计算机的同事，任何我会让同事在计算机上做的事情，我都可以让 Arpot 做”。我认为这只是提高了你考虑给 AI 做的事情的上限。

I do that one too. That one's actually a very useful thing to do is you download Grok Bot for one of your bots. Mine is like a QA tester bot. And that way if there's ever bug report or if we're kind of testing out a new a new build, for example, of the desktop app, I can just say, "Hey, here are 10 workflows that we need to make sure are getting better release after release. I want you to test it. I want you to write it to this notion document that has like an extensive list of all of the past tests that we've done of past client versions and compare them." And so I think once you start breaking out of this is AI chat with a set of connections which is I think where most people are conceptually now instead to this is a colleague with a computer and anything I would ask a colleague to do on a computer I can ask Arpot to do. It just raises the ceiling I think of what you would think to give to AI.

你有没有见过或使用过其他扩展思维的 Grok Bot 用例或方式？

Are there any other mind-expanding use cases or ways to use Grok Bot that you've seen that or you use?

我从许多用户那里看到的一个模式很简单，但我认为如果你持续投资让它变得更好，会有很多深度。这就是我可以对优化我的设置变得有点书呆子气的地方。就是 Grok Bot 作为信息狂，在某种程度上只是消耗大量信息，从你的认知负荷中移除，给你平静，然后带着重要的东西来找你。我认为 V1 实现，很多人做的，是 Grok Bot 坐在 Slack 和电子邮件之上，我告诉它高层次：这是我在[公司]的角色，这是我关心的。我希望你在这些情况下通知我。在这些情况下，你不需要直接 ping 我，但你应该把它包含在我每天阅读的每日汇总中。这就像 V1 实现。我不确定 V10 实现是什么，但也许我在 V3 或 4，就是你可以给这些机器人一个完整的信息消防水管。所以我把我的连接到 X 上所有提到 Grok Bot 的地方，它与我们的内部上下文交互。它与 QA 测试器交互，看看它是否能重现我们收到的任何 bug 或反馈。我连接到我自己的消息服务，以便快速对反馈采取行动并联系人们。我认为有这种始终在线的幕僚长实体，可以保持你对真正重要事情的专注，但总是像在监视，看看是否有任何应该引起你注意的事情。我们已经看到一些有趣的案例，人们实际上给他们的 Grock 机器人——我还没有这样做，但也许很快——给他们的 Grock 机器人访问权限，能够呼叫他们。所以如果发生超级紧急的事情，他们在喝咖啡或其他什么，他们会被 Grok Bot 呼叫，这是你只想在紧急情况下做的事情，你真的想信任那个 Grok Bot，你知道，没有误报。到目前为止，那些人报告说这非常有用和成功。

One pattern that I've seen from many users that is simple but I think there's a lot of depth if you keep investing in making it better. And this is kind of where I can get kind of nerdy about optimizing my setup. It's Grok Bot as an infovore in some ways of just consuming huge quantities of information removing that from your own cognitive load giving you peace and then coming to you with the stuff that's important and I think the V1 implementation of that which many people do is Grok Bot sits on top of Slack and it sits on top of email and I tell it high level here's my role at the here's kind of what I care about. I want you to notify me in these cases. In these cases, you don't need to ping me directly, but you should include this in your daily roundup that I read every day. That's like the V1 implementation. I'm not sure what the V10 implementation is, but like maybe I'm at V3 or four, which is you can give these bots a complete fire hose of information. So I have mine hooked up to like every mention of Grok Bot ever on X and it's interacting with our internal context. It's interacting with the QA tester to like see if it can repro any bugs or feedback that we're getting. I've hooked up to my own kind of messaging services to like quickly act on feedback and reach out to people. And I think there's this just like always on kind of chief of staff entity that can preserve your focus on the things that actually matter, but is always like kind of surveilling to see if there's anything that should get your attention. And we've seen some funny cases of people actually giving their Grock bots, which I have not done this yet, but maybe soon, giving their Grock bots access the ability to page them. And so if something like super urgent happens and they're at a coffee or whatever, they get paged by Grok Bot, which is the type of thing that you only want to do if it's urgent and you really want to you want to trust that Grok Bot, you know, does not have false positives. So far, those people have reported that it's been very helpful and successful.

但我认为我们会看到更多这类东西，智能体或机器人实际上应该更主动地来找你，而不是你去找它。我认为这将是 AI 的下一个转变。

But I think we're going to see more of that type of stuff, where the agent or the bot should actually be more proactive to you than you reaching out to it. And I think that will be the next shift in AI.

这涉及很多方面，我在观察你们团队运作时印象非常深刻。一是速度，这个我想谈谈，但另一个是你们意识到这是一个抓住大量市场份额的时机，要尽可能多地占领市场，直到有人带着很棒的东西出现，尤其是某个基础模型实验室。所以看着你们发放这么多免费账户。还有对用例的关注，非常聪明，因为这是如此新颖的东西，你打开它，然后想，我该用它做什么？而你们如此专注于，好吧，这里有一堆人们用它做的事情，然后推特上有很多讨论，就像人们使用模板的所有方式。这非常合理，据我所知，这两个重点：尽可能快、尽可能多地让用户使用，直到有人说，好吧，你知道，因为总会有人带着下一个东西出现。超级聪明，还有用例关注。

This touches on a number of things that I've been very impressed with watching your team operate. One is speed, which I want to talk about, but the other is how you have an awareness that this is a moment in time to capture a lot of market share and really take as much of the market as you can before somebody comes around and, like, okay, now we got something awesome, especially one of the foundation labs. So watching just how many free accounts you guys are giving out. Also the focus on use cases, so smart, because it's such a novel thing and you open it up and it's like, what do I do with this? And there's such a focus on, okay, here's a bunch of things people do with it, and then there's all this talk on Twitter and just like all the ways people are using a template. Makes so much sense, just these two kind of focuses, from what I can tell: get as many people on it as possible as fast as possible until somebody's like, okay, you know, because someone's going to come around be like, all right, here's the next thing. Super smart, and also the use case focus.

我知道你之前在 Cursor 是负责市场推广的。关于现在如何推广这个产品，你有什么想分享的吗？

I know you were a go-to-market person at Cursor before this. Anything you want to share there about just the approach to the go-to-market right now for getting this out there?

我认为我们在编程领域看到的模式将与我们在通用知识工作中看到的有些相似，我认为我们在市场推广方面学到了很多，更普遍地说，就是构建人们使用的实用 AI。我认为我们作为一个公司，在文化上非常在意不构建演示软件，而是构建世界上真正有用的东西，并为此痴迷。有很多闪亮的东西和有趣的 prototypes 可以构建。但最终，这与让数百万人使用它并改变公司是非常不同的问题。所以，我认为这就是我们一直关注的文化。

I think the pattern we saw for coding will be somewhat similar to what we see for general knowledge work, and I think we've learned a lot from that on the go-to-market side and more generally just building practical AI that people use. And I think we as a company have culturally really cared about not building demoware, like building actually useful stuff in the world and kind of obsessing over that. And there are so many shiny objects and like fun prototypes to build. But ultimately that's a very different problem than getting this in the hands of millions of people and having it transform companies. So that's really, I think, culturally where we've always been focused.

所以我认为在市场推广方面，我们在编程领域看到的是一个非常简单的模式，就是有一群早期采用者。早期采用者会使用这些编程工具，真正把它们推到极限，而且他们大多是在个人项目上推到极限。他们会在晚上和周末这样做。我想的是 2023 年，你知道，更早的时候。人们下班回家——在工作中，他们使用的是基本的 IDE。这是 AI 之前。然后在家里，他们会做一个副项目，他们会使用 Cursor 或者使用最新最棒的 AI 编程工具。这会给他们带来极大的加速。感觉就像他们在体验未来。然后他们回到工作中，他们会要求它。他们会说：“我无法想象以其他方式工作。我现在感觉就像在糖浆里走路。这需要改变。”

And so I think on the go-to-market side, what we saw for coding was a very simple pattern, which was there was an early adopter crowd. The early adopter crowd would use these coding tools and really push them to the limits, and they would mostly push them to the limits on individual projects. They would on nights and weekends. I'm thinking like 2023, you know, kind of earlier. People would kind of go home from work—at work, they were using a basic IDE. This is pre-AI. And then at home, they'd work on a side project and they'd be using Cursor or they'd be using, you know, the latest and greatest AI coding tool. And that would give them an extreme amount of acceleration. It would feel like they were experiencing the future. And then they would come back to work and they would demand it. They would say, "I cannot picture working any other way than this. I feel like I'm completely walking through molasses right now. This needs to change."

我认为对于知识工作，我们将看到类似的模式，人们有时会在个人能力中真正感受到顿悟时刻。我认为我们现在在 X 上肯定看到了很多这样的例子。你看到所有这些例子，Grok Bot 控制他们的家用机器人电脑或家用机器人吸尘器，或者 Grok Bot 帮助他们通过谈判节省特斯拉充电器的费用。就像所有这些有趣的用例，但我认为下一步将是，这不是一个消费产品。我们认为这将改变企业。我们认为这将改变团队，机器人将进入团队并贡献真正有经济价值的工作，尤其是当它们变得更聪明时。

And I think for knowledge work, we're going to see a similar pattern of people really feeling the aha moment sometimes in a personal capacity. And I think we're certainly seeing a lot of this like on X right now. You see all these examples of Grok Bot controlling their home robot computer or home robot vacuum cleaner, or Grok Bot, you know, helping them save money on their Tesla charger negotiation. Like all of these fun use cases, but I think the next step is going to be this is not a consumer product. We think this is going to transform businesses. We think this is going to transform teams, and it will be bots coming into teams and contributing really economically valuable work, especially as they get much smarter.

所以在市场推广方面，我们肯定在优先考虑企业方面做出了巨大推动，不仅考虑与单个机器人合作的单人用例，还考虑机器人在更广泛的团队中如何工作？机器人在复杂的真实公司系统中如何工作，那里有很多上下文和很多历史需要理解？在更广泛的组织中，记忆看起来是什么样子，而不是你服务的单个个体？我认为那里有很多未解答的问题。但我确实认为 Rockbot 是创造这种向智能体转变的正确原语，适用于编程之外的公司其他部分。这就是我们现在非常关注的地方。

And so on the go-to-market side, we're certainly making a big push on prioritizing businesses and thinking about not just the single-player use case of working with a single bot, but how does a bot work inside of a broader team? How does a bot work inside of real company systems that are complicated and there's a lot of context and a lot of history to understand? What does memory look like in a broader organization versus a single individual you're catering to? And I think there are a lot of unanswered questions there. But I do think Rockbot is the right primitive to create this switch to agents for the rest of the company outside of coding. And that's a place where we're quite focused right now.

沿着这些思路，很明显你们都理解分销的力量，以及如何需要找到一个惊人的产品并正确进行分销，因为你知道 Grockpot 很棒，但你们在通过各种不同方式推广它方面的聪明才智组合真的令人印象深刻，我认为这向你展示了如今构建真正成功的东西需要什么。我想问一下围绕这个产品和公司的不同品牌，以便人们可以尝试理解，因为我知道你们正在经历过渡、收购、SpaceX 所有这些事情。所以有 Grok Bot，有 Cursor，是吗？所以谈谈这些产品和今天思考这些不同品牌的方式，我知道它可能会继续演变，以便我们能正确地沟通。

And along those lines, it's very clear you all understand the power of distribution and how you need to find both an amazing product and get distribution right, because you know Grockpot's amazing, but the combination of how smart you guys have been with getting it out there in all these different ways is really impressive, and I think that shows you what it takes these days to build something that's really successful. I want to ask about the brand of the different brands around this product and the company just so people can try to understand, because I know you're going through a transition acquisition SpaceX all these things. So there's Grok Bot, there's Cursor, is that—so talk about like the products and the way to think about these different brands today, and I know it'll probably continue to evolve just so we could communicate about it correctly.

当然。是的。我认为 SpaceX AI 现在有三大支柱。所以第一个支柱是编程产品，而不是产品，现在就是 Cursor 和 Grock build。我认为我们坚信，为开发人员和组织的工程部分提供一个专业的工作界面将非常关键。现在人们有时使用 Grok Bot 来启动云智能体或合并 PR 或进行 QA，一堆工程相关的任务。但最终，当你发布生产软件时，我们坚信那将需要一个每个像素都为最终用户优化的产品。所以我们正在那里进行大量投资。

Definitely. Yeah. I think there are three big pillars right now of SpaceX AI. So the first pillar is the coding product instead of products, and right now that's Cursor and Grock build. And I think we're big believers that having a professional work surface for developers and for the engineering part of the organization is going to be really critical. And right now people use Grok Bot sometimes to kick off cloud agents or to kind of merge PRs or to do QA, a bunch of engineering adjacent tasks. But ultimately when you're shipping production software, we're big believers that that is going to require a product where every pixel is optimized for that end user. So we're making big investments there.

第二个类别是通用知识工作，我们认为 bot 是朝着这个方向迈出的非常令人兴奋的一步。还有很多工作要做，使它更有用，扩展到新的界面，真正感觉像一个 AI 队友，你可以委托工作给它，尤其是在公司和企业内部。所以这算是第二个支柱。

The second category is general knowledge work, and we think bot is a really exciting step in that direction. There's a lot more work to do of making it more useful, extending it to new surfaces, it really feeling like an AI teammate that you can delegate work to, especially inside of companies and businesses. So that's kind of the second pillar.

然后第三个是通用模型努力。我们想要训练世界上最聪明的模型，真正有能力的。我认为 SpaceX AI 与其他 AI 实验室有所区别的一点是，我认为我们的目标不太是构建——你知道，追逐超级智能或某种模糊的抱负理想。

And then third is the general model effort. We want to train the smartest models in the world that are really capable. And I think one thing that somewhat distinguishes SpaceX AI from other AI labs is I think our goal is less to build—you know, chase super intelligence or some kind of vague aspirational ideal.

目标其实非常务实，就是打造有用的 AI。我们在产品侧这么做，也在模型侧这么做。我觉得其中一部分也是文化层面的——参与这些模型的人都是工程师，是从非常应用的思维进入模型训练工作的。我认为正是这一点推动着这家公司前进，而且我觉得这和外面一些竞争对手的方向略有不同。

The goal is actually very practical, which is to build useful AI. We do that on the product side, we do that on the model side. And I think part of that is also just cultural — the group of people contributing to these models are engineers and people who came into the model training effort from a very applied mindset. I think that's what gets this company going, and I think it's actually a slightly different direction from some of the other competitors out there.

非常有意思。好，我想往几个方向聊。一个是你发过一条推文——我记得你置顶了，或者可能是你最近的一条推文。如果大家去看你的主页，它就在上面。推文是这么写的：一个能完成 100% 工作的 AI，和一个只能帮你做到 90% 的 AI，感觉上是截然不同的。我已经大幅更新了我对 AI 能力的看法。多讲讲这个吧。

Super interesting. Okay, there's a couple directions I want to go. One is you have this tweet that is — I think you pinned it, or maybe it's your last tweet. It's up there in your timeline if people check you out. So the tweet is: an AI that does 100% of the job feels categorically different from one that gets you 90% there. I've significantly updated what I think AI is capable of. Say more about that.

对我来说，让我如此兴奋地投入 Grok Bot 并为之做贡献的原因是，这是第一次在非编程任务上，我感觉自己可以真正把工作委托给 AI，不用再去想它，等我回来时它已经做完了。我觉得工程师们感受到这一点已经有一段时间了。大概有一年、一年半了，事情一直是这样。我是说，开发者的工作已经彻底变了，和两年前相比已经面目全非，关于这个话题已经有太多太多的讨论。但我觉得被低估的是，这种体验和大多数人现在对 AI 的感受、以及 AI 改变他们生活的方式，差别有多大。大多数人用 AI 的方式和两年前很像：你为一个任务新建一个对话线程，在输入框里打字，按回车，看着所有步骤发生，得到一个输出，不太对，你继续改。而 Grok Bot 我觉得把其中很多环节都短路了。当你第一眼看到第一个界面时，你会想，哇，这明显不一样。看看它是不是真能用，但这确实不一样。然后你给它一个任务，它居然就做成了，程度令人惊讶。我觉得我们还会做很多事让它变得更好。所以我想在那条推文里表达的是：当你有一个只信任 90% 的队友时——幸运的是我在这里没有这种经历，因为我共事的人都很棒——但如果你把某件事委托给某人，而你心里清楚，在对方做的过程中你还得一直惦记着，你知道它大概不会做到位，你还得介入、稍微调整方向。那就不叫 90% 的任务完成度。你其实还在做这件事，感觉上也是如此，它同样压在你心上。而真正地把一个不看人传球甩给同事，说，交给你了，这是背景，放手去干，我很期待看到你的成果——那是另一个层次。我觉得人们每天在 Grok Bot 上感受到的就是这种不看人传球，你就是相信它能搞定，然后它真的搞定了，那是一种非常神奇的体验。

I think for me, what made me so excited to work on Grok Bot and contribute to it is it was the first time for non-coding tasks that I felt like I could truly delegate work to AI and not have to think about it, and I would come back and it's done. And I think engineers have been feeling this for quite some time. For maybe a year, a year and a half, things have been like that. I mean, the job of a developer has completely transformed. It is unrecognizable from what it was two years ago, and many, many words have been said on that topic. But I think it's underrated how different that experience is from what most people are feeling about AI right now and the way that AI has changed their lives. And it looks quite similar to the way that people would use AI like two years ago, where you create a new thread for a task, you type it into an input box, you hit enter, you watch all of these steps happen, you get an output, it's not quite right, you keep working on it. And Grok Bot, I think, short-circuits a lot of that. When you first lay eyes on the first screen, you're like, whoa, this is clearly different. Let's see if it actually works, but this is different. And then you give it something and it kind of works, you know, to a surprising extent. And I think we're going to do a lot to make it work much better. So I think what I was expressing in that was: when you have a teammate that you only 90% trust — and luckily I do not have the experience of here because I work with great people — but if you delegate something to someone and you're like, I know I'm going to have to be thinking about this while you're doing it, and I know it probably is not going to be quite there and I'm going to have to intervene and kind of steer it slightly. That's not 90% task completion. You're still doing the thing, and it feels that way, and it's weighing on you in the same way. Versus truly throwing a no-look pass to a colleague and being like, you got this. Here's the context. Go off and run. I'm excited to see what you do. That's a different category. And I think that's the type of thing that people feel with Grok Bot every day — are these no-look passes, and you just trust that it can get it done, and then it does, and it's just a very magical experience.

是啊，我一直在经历这种体验。好，那么你们运作方式中另一个让我印象深刻的点，是我以前没见过的，就是你们行动的速度。我在和一些同事给反馈的时候被拉进了一个 Slack，然后就是，好，要不——好，明天我们给你一些免费兑换码发出去。你明天就能做。我们明天做这个。或者，我们要上线一个带模板的市场。我们两天内上线。就是，什么？我都没时间了。你们在这么多事情同时进行的情况下，所有东西不断发布，同时还保持一致、高质量，并且让人感觉是在朝着一个明确的愿景走，你们是怎么做到的？所以这个问题大概有两部分。一是你们行动如此之快的秘诀是什么，二是你们如何在快速前进的同时保持对齐，朝着一个大家都想要、都相信、并且希望它去的愿景走，而不是一路打补丁？

Yeah, I have had that experience consistently. Okay, so another element of how you all operate that has really impressed me and I've not seen this before is how fast you all move. So I got added to this Slack as I was giving feedback with some folks, and it's just like, okay, how about — okay, tomorrow we're gonna give you some free codes to give out. You could do it tomorrow. We'll do this tomorrow. Or, we're going to launch a marketplace with templates. We're going to launch this in two days. It's just like, what? I don't have time for this. How do you guys, with all the things going on, all these things constantly shipping, and also staying consistent and high quality and feeling clear that it's towards a specific vision? So there's kind of two parts of this question. Just what's the secret to how fast you all have been moving, and how do you stay aligned moving that fast towards a vision that you all want, that you all believe in, and where you want it to go, versus just kind of band-aiding it along the way?

是的，有一件事我一直很高兴它从未改变，就是公司内部那种创业公司的感觉。作为背景，我最初加入 Cursor 时，我们大概 15 个人。后来我们扩张到一千多人。再后来我们成为 SpaceXAI 的一部分，那是一个更大的组织。当你身边是这么一群才华横溢的人时，身处其中真的非常有趣。每个人都在以每小时 100 英里的速度前进。你信任，你深深信任每个人都会把自己那部分做好。而且有一个清晰的愿景，大家都为之振奋，都知道自己需要去执行。你知道，随着公司成长——我们有幸从其他经历过超高速增长的公司招到了非常优秀的人——事情会慢下来，你会一直告诉自己，我们还是创业公司，我们行动还是很快，但其实并不是。而且所有人都知道并不是。这说起来比做起来容易。希望这能一直保持下去。我认为如果这能保持下去，对我们的成功至关重要。但即便在我们扩张的过程中，它一直感觉像是我最初加入时的那家创业公司。我觉得如果你用人数或融资轮次来定义创业公司，那些其实都没什么意义。定义创业公司的核心恰恰就是你描述的那种东西，就是这种手忙脚乱的能量，事情有点混乱、有点没条理。对很多人来说，那不是愉快的工作环境，但它有这些了不起的特性：你可以在短时间内朝某个特定方向产生极大的影响。而且一个系统里，你投入什么就真的会得到什么。所以我觉得作为一种文化、作为一个组织、以及我们构建自己的方式，我们一直在做的就是要让这种特性得以保持，而我觉得我们的一些竞争对手和其他 AI 实验室已经变得大得多，你能感觉得到。而我觉得我们即便在扩张，也仍然有那种创业公司的冲劲，这对快速推进这些事情非常重要。

Yeah, one thing I've been really happy has never changed is that startup feeling inside of the company. For context, when I joined Cursor originally we were about 15 people. We scaled to over a thousand. And then now we're a part of SpaceXAI, which is kind of an even bigger organization. And it's something that is just so fun to be a part of when you're around this group of incredibly talented people. Everyone's moving 100 miles an hour. You trust, you deeply trust everybody to execute on their part of the equation. And there's a clear vision that everyone is fired up about and knows that they need to execute on. And you know, as companies grow — and we've had the fortune of hiring really great people from other companies that have gone through hypergrowth — things slow down, and you kind of keep telling yourself, we're still a startup, we still move quickly, but you really don't. And everyone knows that you don't. And it's just easier to say than to actually be. And fingers crossed this continues to be true. I think it's really critical for our success if this continues to be true. But even as we scaled it has always felt like that startup that I first joined. And I think if you define a startup by number of people or by the funding round, none of those things really make any sense. The core thing that defines a startup is exactly what you're describing, which is this kind of scramble energy of things are kind of chaotic and kind of disorganized. And for a lot of people, that's not a pleasant working environment to be in, but it has these amazing properties of you can make extreme impact in a particular direction in a short amount of time. And you really do get out of a system what you put in. And so I think as a culture, I think as an organization and the way we construct ourselves, it's really been to enable that property in a way that I think some of our competitors and other AI labs have gotten much bigger and you can feel it. And I think us, even as we scale, there is that startupy impulse that is quite important to move quickly on these things.

让我顺着这条线追问，问你一个我一直很期待问的大问题。如果你从外部看 Cursor，它本不该成功。它本不该活下来，因为第一，它身处世界上最激烈的竞争市场，对手是历史上增长最快的公司，OpenAI 和 Anthropic。

Let me pull on this thread and let me ask you this big question that I've been looking forward to asking you. If you were to look at Cursor from the outside, it shouldn't have worked. It shouldn't have lasted, because one, it's in the most competitive market in the world, competing against the fastest growing companies in history, OpenAI and Anthropic.

所以，第一，竞争是前所未有的。第二，它建立在那些平台之上来驱动。作为一个局外人，我看到的是，让 Cursor 胜出、实现大规模退出并持续成功的原因，是你们适应市场现实的速度。从自动补全开始，然后转向与智能体对话，再进入云端，现在是 Grok Bot。对我来说，这感觉是成功的核心部分：快速适应现实，同时为在其他地方也存在的东西打造一流的体验。Grok Bot 就是个很好的例子。你可以在其他地方做这个，但这是最好的体验。Cursor 这个 IDE，是最好的编程方式。所以，这就是我的问题。也许我已经回答了，但你认为 Cursor 能够在这个疯狂竞争的市场中不仅生存下来，而且长期持续表现如此出色的核心是什么？

So that's one, it's like the competition is unlike anything anyone's ever experienced. Two, it sits on top of those platforms to power it. And what I've seen as an outsider is what has allowed Cursor to win and have this massive exit and continue to succeed is how quickly you all adjust to the reality of the market. Started as autocomplete and then things moved on to just talking to agents and then into the cloud and now Grok Bot. To me, that feels like a core part of the success is quickly adjusting to reality and also building the best-in-class experience for a thing that also exists other places. Grok Bot's a great example. You could do this other places, but it's the best-in-class experience. Cursor the IDE, the best way to code. So, so that's my question. Maybe I answered it, but what do you think has been core to Cursor's ability to not just survive in this crazy competitive market, but do so incredibly well consistently for so long?

我的意思是，这其中很多，答案可能有点模糊，但我认为很多都源于文化，以及你设定的文化、你引进的人以及他们处理这些问题的方式。对我们来说，正如你所说，我们从未自满。我们从未觉得自己赢了，始终关注下一件事，而且整个公司都深信 AI 发展极其迅速。我们的目标是将这些能力转化为为客户打造的出色产品。但这些产品会变化，它们需要随着能力增强而顺应时代。两年前顺应时代的东西与今天完全不同。如果我们作为一家公司不能每六个月彻底重塑自己——最近甚至感觉更短，比如对我们的优先级、核心产品、用户体验进行非常重大的重塑——我们就会输。我认为正是这种始终推动自己站在前沿、从不认为已经结束或已经赢了或已经做对了的精神，以及不断更新我们的信念，才让我们走到了今天。关于这个领域的竞争，我想指出的一点是，从 Cursor 刚出现时起，AI 编程就一直是竞争激烈的。当时的竞争对手是微软和其他公司，大概有 10 到 20 家。值得注意的是，这些竞争对手现在都没有站在 AI 编程的最前沿，很大程度上不是因为他们做出了错误决定或缺乏资源，而是因为文化上无法快速行动、无法随着时代变化而改变以顺应时代。所以我认为，这正是促使我们投资像 Grok Bot 这样的东西的原因。

I mean, a lot of this, and it's a fuzzy answer, a lot of this, I think, is downstream from culture and the culture that you set and the people that you bring in and the way that they approach these problems. And I think for us, exactly as you said, we have never been complacent. We've never felt like we've won and it's always been about the next thing and I think there's been a really deep belief across the company that AI is moving incredibly quickly. Our goal is to translate those capabilities into amazing products for customers. But those products are going to change and they need to meet the moment as the capabilities get stronger. And what met the moment two years ago is completely different than what's meeting the moment today. And if we as a company can't completely reinvent ourselves every six months, which recently it's felt even shorter than that of kind of complete like very significant reinventions of our priorities, the core product, what users feel, we're going to lose. And I think it's that spirit of always pushing to be on the frontier, never thinking it's over or that we've won or that we've gotten it right. And just constantly updating our beliefs that has gotten us to where we are now. And to your point on the competitiveness of this space, I mean, one thing that I think is important to point out is AI coding has always been competitive from when Cursor first kind of came to be. And at the time the competitors were Microsoft and others and a handful of maybe 10 or 20 companies. And I think it's notable that none of those competitors are at the forefront of AI coding right now in large part not because of any incorrect decisions that they made or any lack of resources on their part but this cultural inability to move quickly and to change to meet the moment as the moment's changing. And so I think that's exactly what has led us to invest in things like Grok Bot for example.

有没有一些核心价值观，就像你用来提醒大家我们是这样工作的具体表述？

Are there any core values just like specific ways you phrase this to kind of remind everyone of this is how we work?

是的，有两个价值观我经常回顾。第一个是“删除产品”的理念，我认为这正好与你刚才说的相呼应：当你回顾 Cursor 的每一个过去版本，甚至 Grok Bot 的每一个过去版本，我想我们都会有同样的感觉——不是增加新东西，而是去掉那些因为模型还不够聪明、无法自己完成而搭建的脚手架式产品悬垂。这些东西会随时间被移除，我们需要乐于做出可能让一小部分用户或内部一小部分人不高兴的艰难决定，以实现更大的目标：让产品简单、强大，并适应未来的方向。所以我认为这非常核心。第二个与执行速度有关，就是“动手做”，我发现自己经常重复这句话，即使公司已经成长。意思是，我们都在同一条船上，我们想赢，如果你看到你认为需要发生的事情，这不是一个需要请求许可的文化，你出去解决问题，并拉入你需要的资源来实现它。我认为这已经让这里许多人非常成功，而且我认为这也是我们与 SpaceX AI 真正共享的东西。

Yeah, two values that I find myself coming back to quite a bit. The first one is this idea of deleting the product and I think it exactly ties back to what you're saying right now where when you look at every past iteration of Cursor for example but even I think when you look at every past iteration of Grok Bot I think we will feel the same thing is things going away not new things getting added but you know these scaffolding product overhang style things that get built in because the models have not yet gotten smart enough to just do it themselves. Those things will get moved away over time and we need to feel comfortable making kind of hard decisions that might upset a small set of users or a small set of us internally to do the bigger thing of make the product simple, make the product powerful and adapt to where the future is going. So I think that's been very core. And then the second thing which ties back to the kind of pace of execution is just do the thing which I find myself kind of repeating a lot even as we've kind of grown as a company is it's on you know we're all in this boat together we want to win and if you see something that you think needs to happen you know this is not an ask for permission culture you go out and you fix the thing and you pull in the resources that you need to make it happen and I think that has made many people very successful here before and I think it's something we really share with with SpaceX AI as well

可能你已经听说过“能动性”。所以有趣的是，出现的一个大问题——这可能是我最后一个问题——是关于护城河的。很多人把 Cursor 看作一个非常有趣的例子：他们所在的市场从技术上讲可能没有护城河，但他们持续获胜并取得成功。你想到的 Cursor 的两种模式是：人们自动补全的数据反馈循环，了解他们在做什么并基于此训练模型。所以这是独特的。另一个就是一流的体验，成为一个高日活用户产品，并随着时间的推移发现什么有效、人们需要什么。你学到了什么？我想，关于这个领域的护城河，你有什么想法可能对试图自己弄清楚这个问题的人有帮助？

Agency as you may have heard. So interesting one of the big questions that comes up and and this might be my final question is around moats and a lot of people look at Cursor as a really interesting example of they're in a market with technically maybe no moats but they've continued to win and succeed the two modes you think about with Cursor is the data feedback loop of people autocompleting, learning what they're doing and training models based on that. So that's unique. The other is just best-in-class experience and being like a high g daily active user product and finding over time what works and what people need. What have you just learned and I guess any thoughts on moats in this space that might be helpful for folks that are trying to figure this out for themselves?

是的，关于护城河有很多讨论，现在确实是创办公司的有趣时刻。所以我能理解为什么这么多创始人会问自己这个问题，并试图预测 12 个月后、24 个月后的情况，感觉就像永恒。我想说，如果 Cursor 和许多其他这个时代的成功公司当初考虑护城河，或者试图从某种战略图或更抽象的公司运作方式倒推，我不认为会创造出这样的结果或产品。我认为真正创造 Cursor 魔力的是对今天构建有用东西的痴迷，而且我认为这不断是一种练习：你可以看到世界在三个月后、六个月后会走向何方，模型会变得更聪明，现在无法解决的问题最终会变得可解决。我认为 Cursor 有点像是这种反复出现的提示：我们如何能把那些东西拉到今天，即使需要在上面做一些工程或大量工程才能让它工作。即使需要以特定方式改变产品，以便用户能够与这种新能力互动。

Yeah, there's a lot of talk about moats and it is a pretty interesting moment in time to be starting a company. So, I can understand why so many founders are kind of asking themselves that and trying to project out 12 months from now, 24 months from now, it just feels like an eternity. I will say that I think if Cursor and many other successful companies of this kind of vintage I think if they had thought about moats slash kind of tried to work backwards from some strategy diagram or like you know a maybe more abstract notion of how a company should work. I don't think that would have created this outcome or this product. I think what really created the magic of Cursor was an obsession with building a useful thing today and I think it was constantly this exercise of you can kind of see where the world is going three months from now six months from now models are going to get smarter a thing that isn't solvable now is finally going to be solvable and I think Cursor was a little bit this recurring prompt of how could we pull that stuff to today even if it requires a little bit of engineering on top to make it work or a lot of engineering on top to make it work. Even it requires changing the product in a specific way so that a user can interact with this new capability.

我们怎么把它往前推？然后三个月后，我们应该把那些东西全删掉，因为它会变得很好、很基础，你知道，就是产品的起码底线。然后我们再为接下来的三个月打造新东西。就是不断地这样重复。我认为这让用户真正信任我们，把他们的时间投入到我们的产品里，并相信我们在把东西带向下一个前沿、下一个未来。所以我真的鼓励很多创始人或今天刚起步的人，更扎根于这个视角：我怎么能让现在不可能的事变成可能？用户会来找我用那个东西。我会把他们拉向下一个不可能的前沿。然后通过这一切，我会获得很多分发优势。我会获得数据优势。那里会有价值。但我认为那才是真正该玩的地方。

How can we bring that forward? And then three months from now we should delete all that stuff because it'll just be good and basic, you know, common bare minimum of the product. And then we'll build the thing for three months from then. And it was constantly just doing that over and over again. I think that led to users really trusting us and placing their time inside of our product and trusting that we were kind of bringing things to this next frontier and to the next future. And so I would really encourage many founders or people starting out today to be more grounded in that perspective of: how can I make something that is not possible now possible? Users are going to come to me to use that thing. I'm going to pull them to the next impossible frontier. And then through all of that, I'm going to gain a lot of distribution advantages. I'm going to gain data advantages. There will be value there. But I think that's really the place to play.

我喜欢这个回答。本质上，我的理解就是：打造一个人们痴迷的东西。不要过度思考模式那部分。如果你能持续这样做，你会找到一些东西——在 Cursor 的例子里，最终是好几样东西。

I love that answer. Essentially, the way I'm thinking about it is just build something people are obsessed with. Don't overthink the modes piece. And if you can continue to do that, you'll find something which in Cursor's case ended up being a few things.

这个其实最近在我做的另一个播客里也提到了。我不知道它会在这次之前还是之后播出。就是「模式往往是事后发现的，而不是提前规划好的」这个想法。

And that came up actually recently on another podcast I did. I don't know if it'll come out before or after this. This idea that modes are discovered, not planned ahead of time a lot of times.

好，那作为最后一个问题，让我问问你 Grok Bot 的使用建议。有些人会想：「哦，我得试试这个东西。这么多兴奋点到底是为什么？」对于正在尝试的人，比如说新手，你会给什么建议——就像「这是成功的关键」，也许再给已经上手的人一些高级技巧，让他们觉得「哇，我都不知道还能这样」。

Okay, let me actually ask you for Grok Bot tips as an actual last question. Some people are going to be like, "Oh, I got to try this thing. What's all this excitement all about?" What would be some advice for folks that are trying out, let's say for people that are new to it, just like here's some keys to success, and maybe some power tips for someone that's already with it and just like, "Oh wow, I didn't know that."

是的，我想避开那些超级取巧的高级技巧，因为我认为我们团队和公司的理念是：这些东西本就不该存在。不该有这些疯狂的旋钮。你应该能把某件事委托给 Grok Bot，它就该去做。所以对于刚下载应用的新手，你看着这个屏幕，我想第一件事是给 Grok Bot 提供它成功所需的上下文。就像你给团队新人做入职一样，让他们能访问 Slack、你的邮箱和你每天用的公司记录，会非常有帮助。所以我会给它访问这些工具的权限，然后我实际上会问 Grok Bot 它能为你做什么，让它去梳理你最初设置的那些连接。在我的例子里，可能是给它我的邮箱，给它 Slack。我第一次上手时真的很惊讶。这是——当时我们还没有任何引导界面。所以我给它的第一个任务就是：翻我的 Slack，翻我的邮箱，建议五件你能帮我分担的事，以及你需要什么才能做到。它建议了五件，其中两件真的很有用，我立刻分出了两个机器人去解决那两件事。那是我最大的「哇」时刻，感觉过去没有任何 AI 工具能做到那两件事。那不是「起草一封邮件」，而是「完成一块工作」。所以我鼓励全新用户这样做。而对于不是新手的人，我一直在不断发现我的机器人之间互动和协作的新模式。所以我一直在搭建一个更像脚手架的东西，规定 Grok Bot 创建的这些产物应该放在哪里，以及它如何写到一个对我来说非常易读的地方。所以我有一些每天阅读的频繁摘要，它会推送到一个数据库，我可以很容易地读。所以我鼓励高级用户思考 Grok Bot 如何能写到一个单一的存储里，让你能更容易地组织它的许多输出。

Yeah, I want to stay away from the super hacky pro tip stuff because I think our philosophy as a team and as a company is that those things really shouldn't exist. There shouldn't be all these crazy knobs. You should be able to delegate something to Grok Bot and they should do it. And so what I would encourage for someone new who's just downloading the app, you're looking at this screen. I think the first thing is give Grok Bot the context it needs to be successful. So, in a similar way as if you were onboarding someone to your team, it'd be really helpful for them to have access to, you know, Slack and your email and the company records that you use every single day. So, I'd give it access to the tools and then I would actually ask Grok Bot what it can do for you and let it kind of go through those connections that you've initially set up. In my case, it might be I give it my email, I give it Slack. And I was really surprised when I was first onboarding. This is—we didn't have any onboarding screens at this time. So this was kind of the first task I gave it: go through my Slack, go through my email and suggest like five things that you can take off of my plate and what it would take for you to do that. And I suggested five and like two of them were actually really helpful and I just immediately spun off two bots to solve those two. And that was my big wow moment of feeling like no other AI tool in the past could have done those two things. It was not like draft an email. It was like do a chunk of work. And so I encourage people who are brand new to do it that way. And then for people who are not brand new, I kind of am constantly finding new patterns for ways that my bots can interact with each other and can collaborate with each other. And so I've been creating a bit more of a scaffold of kind of where these artifacts that Grokbots create should live and how it can write to a place that's very legible to me. So I have like these frequent digests that I read every day and it kind of pushes to a database and I can just read it very easily. And so I would encourage power users to think about ways that Grok Bot can actually write to like a single store where you can organize a lot of its outputs much easier.

天哪，我们需要再做一期深入探讨 Roman 的 Grok Bot 配置的节目，那里面大概有太多私密敏感信息了。我们没法展示，但没关系。这是个很棒的建议。Roman，在我们进入非常激动人心的闪电轮之前，你还有什么想分享或想提到的吗？

Damn, we need another episode of going deep on Roman's Grok Bot setup, which probably has way too much private sensitive information. We couldn't show it, but that's okay. That's an amazing tip. Roman, is there anything that you wanted to share or anything else you wanted to touch on before we get to our very exciting lightning round?

没有了。我这边没有别的了。

Nothing. Nothing else on my side.

我们覆盖了太多内容。那真是——我简直不敢相信那只有大约一个半小时。感觉我们聊了很久，涵盖了我希望涵盖的一切。那么，我们来到了非常激动人心的闪电轮。我有四个问题问你。准备好了吗？

We covered so much ground. That was—I can't believe that was only an hour and a halfish. I felt like we've been talking for ages and covered everything I was hoping to cover. With that, we've reached our very exciting lightning round. I've got four questions for you. Are you ready?

准备好了。

I am ready.

你最常向别人推荐的两三本书是什么？

What are two or three books that you find yourself recommending most to other people?

好。给你两本书。一本是我喜欢库尔特·冯内古特。所以《猫的摇篮》一直是个有趣的推荐，我以前买过很多本送给朋友。第二本是史蒂文·普雷斯菲尔德的《艺术之战》，我发现自己经常回头翻，哪怕一次只读一两页。我推荐给任何人。

Yeah. So, two books for you. One is I love Kurt Vonnegut. So Cat's Cradle has been a fun recommendation, and a copy that I bought many friends before. And then second is The War of Art by Steven Pressfield, that I find myself frequently coming back to, even if it's just a page or two at a time. And I'd recommend for anybody.

《艺术之战》。太棒了。它是一本很短的书，一旦你读了——它不是《孙子兵法》，人们可能以为听到的是那个。是的。

War of Art. Incredible. It's like such a short book and it's like once you read it and it's not The Art of War, which is what people might think they're hearing. Yes.

但它是《艺术之战》。是对那个的戏仿，讲的是创造和创造新事物的挑战，以及如何克服阻力。我喜欢这个推荐。下一个问题。

But it's The War of Art. It's a play on that and it's about the challenge of being creative and creating something new and how to overcome the resistance. I love that recommendation. Next question. Favorite recent movie or TV show if you've had any time to watch any of these things.

如果你有时间看的话，最近最喜欢的电影或电视节目是什么？

Favorite recent movie or TV show if you've had any time to watch any of these things.

有。最近。我每年都会看一遍《卡萨布兰卡》，那是我最喜欢的电影之一，而且它碰巧有一个角色和我同姓，Ugarte，我想这是媒体里唯一一个 Ugarte 的例子。所以《卡萨布兰卡》总是值得重看。电视方面，我有时会偷偷看一集《神探阿蒙》，那部侦探剧，是我小时候和家人一起看的，现在我住在旧金山，又回来看它。它很好地捕捉了 90 年代末、2000 年代初拍摄时的旧金山。我非常喜欢。

Yes. Recently. So every year I do a watch of Casablanca, which is one of my favorite movies and it incidentally also has a character with my last name, Ugarte, which is like the only example of I think a Ugarte in the media. So Casablanca always a great rewatch. And then on the TV side, I sometimes sneak in an episode of Monk, the detective show, which was one that I watched kind of as a kid with my family and I've come back to now that I live in San Francisco. And it's just a great moment in time snapshot of San Francisco in the late 90s, early 2000s when it was shot. That I really enjoy.

这是播客上第一次提到《神探阿蒙》。好。现在最喜欢或最有趣的 AI 产品。你想说 Grok Bot 也行，但如果有别的，你会得到加分。

First Monk reference on the podcast. Okay. Favorite or most interesting AI product right now. You can say Grok Bot if you want, but if there's anything else, you get bonus points.

我一直是个 AI 语义搜索迷。我喜欢任何语义搜索产品，尤其是那些不寻常的。所以我当时是很早的 Metaphor 用户，它后来变成了 Exa。

I've always been a big AI semantic search nerd. I love any semantic search product, especially the kind of out of the ordinary ones. So I was like a very early user of Metaphor at the time, which became Exa.

我喜欢用 Exa 来做这些，也许是在互联网上更奇怪的查询，但我看到很多例子，人们构建像语义搜索，你知道，嵌入图像存储的 MoMA 或类似的东西。我总是玩得很开心。所以，任何语义搜索引擎，像奇怪的数据集，我都喜欢。

And I love using Exa to do all of these maybe more strange queries over the internet, but I see a lot of examples of people building like semantic search over, you know, an embedded image store of the MoMA or kind of things like that. And I always have so much fun playing with those. So, anything semantic search engine over like a weird data set, I love.

特别是 Exa 是你推荐的。

And Exa in particular is one you'd recommend.

我喜欢 Exa。是的。

I love Exa. Yeah.

非常酷。好的。你经常在工作或生活中回归的最喜欢的人生格言。

Very cool. Okay. favorite life motto that you often come back to in work or in life.

不像单个格言那么短。嗯，但我喜欢《Desiderata》，我不知道你是否读过，但嗯，我把它贴在我的门上，嗯，我从青少年时期就有了，每次搬家我都会把它贴在那里，它是一首非常短的诗，但每一行，我只是，每次读它我都会发现新的东西，我觉得它真的很接地。

Not as short as a single motto. Um but I love the desiderata which I don't know if you've read but um I have it on my on my door uh and I've had it since I was a teenager and everywhere I move I kind of paste it there and it's it's a very short poem but each line I just I find myself finding something new in it every time I read it and I find it really grounding.

Roman，这太棒了。嗯，我们现在正处于 Grok Bot、AI 的这个时间点。嗯，一年后回顾这个会很有趣，然后说，‘哇，我们在很多方面既对又错。’嗯，非常感谢你做这个。我知道你们团队现在非常忙。所以我真的很感激你抽出几个小时来聊天。嗯，有没有什么地方你想让人们去？除了查看 Grok Bot，还有什么你想推荐的？是吗

Roman, this was amazing. Uh what a what a point in time we're here right now at this moment in time of Grok Bot of AI in general. Uh it's going to be really fun to revisit this in a year and be like, "Wow, we were so right and so wrong about so much." Uh thank you so much for doing this. I know it's a very busy time on your team right now. So I really appreciate you carving out a couple hours to chat. Um is there any place you want to point people to? Anything you want to plug other than check out Grok Bot? Is that

查看 Grok Bot？当然。嗯，是的，主要的是请发送反馈。我认为我们仍处于非常早期的阶段。我的意思是，我们 3 周前发布了测试版。嗯，我们从早期用户那里得到的很多反馈直接转化为我们构建的内容以及我们如何构建它。所以真的很感激嗯，人们给出的所有输入。

Check out Grok Bot? Of course. Um, and yeah, main thing would be please send feedback. I think we're in the very early innings of this still. I mean, we released a beta 3 weeks ago. Um, and a lot of the feedback that we've been getting from this early set of users is directly translating to what we built and how we build it. And so really appreciate um, all the input that people are giving.

干得好，Roman 和团队。我知道这背后有一整个团队。嗯，Roman，非常感谢你来到这里。

Nice job, Roman, and team. I know there's a whole team behind all this. Uh, Roman, thank you so much for being here.

太棒了。谢谢，Lenny。大家再见。

Awesome. Thanks, Lenny. Bye everyone.

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