SpaceXAI Roman Ugarte：一个月做出 Grok Bot

Roman Ugarte

Grok Bot 的终极愿景其实极其简单：你应该有一支 AI bot 团队，既帮你干活，也帮你生活。

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.

Lenny Rachitsky

Grok Bot 是眼下世界上最热的 AI 产品——这个标准极高，竞争这个位置的产品很多。

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.

Roman Ugarte

我们想做的不只是给开发者和工程师的好产品。我们决定在内部拉一支很小的团队，进「洞穴」大约一个月，唯一目标是：做一个出色的知识工作产品，把智能体带给公司其余的人。

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 build an amazing knowledge work product that brings agents to the rest of the company.

Lenny Rachitsky

公开发布才三周。我去过一场 Grok Bot meetup，几百人，站无无。很明显你们做出了特别的东西。

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.

Roman Ugarte

一旦你跳出「这是带一堆连接的 AI 聊天」，改成「这是一个有电脑的同事」，你愿意交给 AI 的天花板就会抬高很多。

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.

Lenny Rachitsky

你有一条推文：一个能把工作做到 100% 的 AI，和只把你带到 90% 的 AI，感觉是完全不同的品类。

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

Roman Ugarte

让我这么兴奋做 Grok Bot 的原因是：第一次在非编码任务上，我感觉真能把工作委托给 AI，不用再想，回来时已经做完了。

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.

Lenny Rachitsky

你觉得你们做对了什么、才让 Grok Bot 这么成功？

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

Roman Ugarte

是早期两个决策——当时一点都不显而易见，事后看却是 Grok Bot 能成立的关键。

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.

Lenny Rachitsky

今天嘉宾是 Roman Ugarte。开场我会尽量短，好直接进入正题。Roman 是 Cursor 第 15 号员工，过去两年负责 Growth；最近他参与孵化了 Grok Bot——我超级沉迷，每天用上百次，各种事都交给它。可以说它是眼下世界上最热、也最让人兴奋的新 AI 产品。Roman 负责 Grok Bot 的产品，从早期原型到现在一直是核心团队的一员。我们会聊它怎么开始、往哪走，以及公开发布几周以来团队学到了什么。下面请出 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.

Lenny Rachitsky

Roman，非常感谢你来，欢迎上播客。

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

Roman Ugarte

谢谢。很高兴来。

Thank you. It is great to be here.

Lenny Rachitsky

我太沉迷 Grok Bot 了。窗口里就开着，大概有 15 个 bot 天天在用。那天去的 meetup 几百人站满。AI 世界里很难破圈，而 Grok Bot 是眼下最热的 AI 产品——标准极高。我自己也很快把很多用例从 Cowork 和 Codex 迁到了 Grok Bot，这感觉是大事。我想搞清楚你们怎么做到的、从哪来、往哪去、目前学到了什么。先说一句：干得漂亮，这很难。

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. 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. I personally noticed I’ve moved a lot of my use cases from Cowork and Codex into Grok Bot just very quickly, which again feels like a really big deal. First, nice job. This is very hard what you’ve done.

Roman Ugarte

谢谢。我记得大约一个月前亲手给你做 onboarding，你一开始还有点怀疑。很高兴你一直在用，也高兴看到这么多人真正把 Grok Bot 用起来。

Thank you. 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.

Lenny Rachitsky

那个 onboarding 很有意思。我记得你让我试一件事，我说：帮我写一条推文推广最新一集播客。就这一句。结果它搞清楚上一集是什么、怎么推，当时我就觉得：哇，真的很好。那从起源故事开始——最初想法是什么，什么时候开工？

I’m going to talk about that onboarding. I actually remember in that onboarding I tried something — you asked me to do a let’s try something and I was like okay try to come up with a tweet to promote my latest podcast episode. And it was actually very good. It figured out what the last episode was, how to promote it. So let’s actually start with origin story. Where did it start? What was the original idea and when did the work on this begin?

Roman Ugarte

一开始真的是白纸一张、从零构建。我们很久就觉得：不能只做给开发者和工程师的好产品——那是我们起步和积累智能体直觉的地方——但知识工作产品该长什么样？于是决定拉一支很小的内部团队，真的就几个人，进洞穴大约一个月，唯一目标是做出把智能体带给公司其余人的出色知识工作产品。

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 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 build an amazing knowledge work product that brings agents to the rest of the company.

Roman Ugarte

从第一行代码到内部放出可用原型，大概只有一个月——非常快、很糙的原型拼起来。事后看，如果人多得多，这不可能。需要的是完全隔离、高度聚焦的小组——我是字面意思：办公室单独一块区域、私有 Slack 频道。每天要做大量微观决策，有些在别的产品面上从没做过；如果是大群人、盯着六到十二个月愿景，根本到不了我们最后落到的地方。

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 scrappy prototype that was pulled together. And I think in hindsight this would not have been possible if it had been 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 thinking about this 6 to 12 month long vision, we just wouldn’t have really gotten to the place that we ended up landing at.

Roman Ugarte

所以大约一个月：从第一行代码到核心团队兴奋的、能用的产品。然后是在全公司、整个 SpaceXAI rollout。有一场 all hands 分享进展：这是全新产品，希望你们用。那时我们自己天天在用，但用自己建的东西容易；真正压测是：别人会不会从内部工具、外部工具切过来，把 Grok Bot 当主智能体界面？

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 of SpaceXAI. And so there was an all hands where we 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, we were using it constantly, but it’s easy to use the thing that you built and you understand the mechanics and what it’s good for. 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?

Roman Ugarte

All hands 后第一周，爱意爆发——来自你可能想不到的人、想不到的团队。天天开 ChatGPT 或聊天界面的人，把日常智能体任务全切到 Grok Bot。内部反响非常惊人。看到内部反应后，我们立刻切换成：准备面向世界，扩到数百万用户还有很多活——然后就到了几周前的 GA 发布。

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 like 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. 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.

Lenny Rachitsky

问题很多。有意思的一点：Anthropic、OpenAI 有编码智能体，发现知识工作机会后，在产品里长出 Cowork，Codex 也在往全能用扩展。你们却决定：不把这东西建进 Cursor，要从头新开。一开始就显而易见「Cursor 里搞不定」吗？这个决定有多争议？

Okay, so many questions. One that is really interesting here. So obviously there’s Anthropic, OpenAI. They had this coding agent and then they’re like, okay, people are using this for knowledge work. Let’s build a knowledge work component. So there’s Cowork 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? How controversial was that decision?

Roman Ugarte

一点都不显而易见。那是最早那些决策之一，当时讨论很多，我很庆幸落点是现在这样。全新产品、你控制体验的每个像素、对知识工作走向有一致愿景、全装在这个新东西里——这对成功贡献很大。但确实有很多讨论：Cursor 和一些编码产品，人们本来就经常拿来做非编码任务；编码智能体在这些事上很强，但会碰到小纸割伤，产品本身对非技术用户有时偏吓人，还有品牌联想。

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 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.

Roman Ugarte

我们评估过那条路，也看到有些竞品在做：全是一个界面，每种形态加新 tab，感觉有点乱；用户能感觉到这不是单一一致的「工作该怎么做」愿景，而是三个愿景共一个屏、可以跳来跳去——有点像把组织架构图直接 ship 出去，用户会负面反应。所以我们决定完全从零开始，看能走到哪。也许将来有很棒的机会把人从别的界面带进更 bot-native 的体验，但关键是先有一个简单到极致、又强大到极致的体验。

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 like an amazingly simple and amazingly powerful experience.

Lenny Rachitsky

这对很多人很有价值：也许解法不是往已有复杂 AI 产品里加东西。有意思的是 Codex 走了另一边，现在又想合成一件事——路径很多，走哪条会把你带到不同地方，也许回头看又会说未必最好。

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 and 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 are 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.

Lenny Rachitsky

你提到一件也很独特的事：早期用户 onboarding。听说你和团队亲手 onboarding 了两三百人，包括我。为什么觉得有必要？学到了什么？这段手动 onboarding 大概多久？

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 300 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.

Roman Ugarte

你学到的东西太多了。前几次 onboarding 相当痛苦——Lenny 你那次还好。但有些很糙，我们学了很多。核心团队必须在场：电脑起不来、有人 onboarding 时完全懵，就干坐通话二十分钟——挂了立刻觉得「这绝不能再发生，明天就要修，因为明天还要给下一个人 onboarding」。大约两周，我们以那种模式 onboarding 了几百人。

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.

Roman Ugarte

不只学产品：这类产品有时会有群体思维式的用法。SpaceXAI 内部大家不断分享 tips，一些模式开始成形，我们觉得对外可能有用，但不确定，也绝不想先给外部用户定调。

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 SpaceXAI 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.

Lenny Rachitsky

有例子吗？

Is there an example of that?

Roman Ugarte

内部 rollout 后大约一两周，常见交互是：你有五到十个 bot，每个给不同 scope、不同领域，像不同工作泳道的缩写。大约第二周末，Slack 里开始有人「提拔」某个表现突出的 bot——把它从私人助理升成首席幕僚，然后主要跟首席幕僚说话，由它把任务扇出给其他 bot、管理团队。还有人真的告诉 bot「你升职了」，bot 问有没有加薪、token 预算会不会更高——很好笑。我们记下了；公司里更多人往那方向挪一点，但不是多数——用法很散。

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 is a bit of a standout performer — and it was like their kind of 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 like actually telling their bot 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 company started to slightly shift in that direction, but it was not the majority of the company. People use this product in very different ways.

Roman Ugarte

所以在部分 onboarding 和整个 early access 里，我们真的不想诱导证人：说「去建一个首席幕僚 bot，它该这样管别的 bot」。想看 early access 用户会不会自己走到那。确实很多人自己走到了。于是产品上我们有了更有观点的取：这模式管用，可以稍微鼓励，但不应是单向门。还有一些内部 thesis，我们也想确认能在真实外部用法里成立，而不是我们先写进产品。

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, you know, 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 theses that we really wanted to make sure would bear out in actual external usage without us imposing that in the product.

Lenny Rachitsky

还有别的例子吗？

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

Roman Ugarte

早期 onboarding 里我们还很注意：用户到底想看到多少。Grok Bot 跟你提的那些产品相比，一上手就有点震惊或不同——很多内部机制不展示给用户。原因是：模型更聪明时，你不会要求队友秒级汇报每个按键、每个网站；对 bot 这样要求也太多了，而且压倒性，害大于利。

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.

Roman Ugarte

所以我们完全走到另一边：你发消息、让 bot 做事，它就开始做；它觉得合适时发进度更新；你只看到打字指示器和像 Slack 那样的绿色活跃圆点——它在干活，很快回来。看不到内部机制、工具调用、在自己电脑上每一次点击。我们坚定认为用户不必看这些。有人反馈想看 bot 的 to-do、大致优先级——很好；但没人想要长长的文本流和思维链序列，这也更确认方向对。

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 like 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 like 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.

Lenny Rachitsky

小团队做两三百次 onboarding 通话——我知道团队后来长大了——时间投入巨大，有人会说是从「建」上分心。显然不是分心，是成功核心。你觉得要摸清该做什么，就得这个量级吗？

The fact that you did two to 300 onboarding calls with a small team — I know 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?

Roman Ugarte

要强调：early access 不全是高影响力口味制造者。Lenny 你属于这类，我们当然想要你的反馈——你贴近市场上很多产品、又是重度用户。但我们也想覆盖公司以前几乎没接触过的非常规画像。例子：一位咖啡店老板，公司朋友的朋友，听说了 Grok Bot；有人给看了 TestFlight demo，他很兴奋，后来不仅是惊人的重度用户，还是丰富反馈源——很长的 bug/需求线程，用例完全是经营小生意。Shopify 集成不稳、商品文案写法不对，反馈都很实在，跟内部 dogfood 很不一样。

Well, one thing to emphasize is the early access group is not necessarily just people that are highly influential taste makers. 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 kind of 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 TestFlight 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. 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 dogfooding this internally.

Roman Ugarte

这对我们是重要练习：一、这是非常通用的产品，不只给开发者——事实上对非开发者可能最强，我们必须更懂那群人；二、我们绝对活在硅谷 AI 泡泡里——推前沿有用，但必须主动走出去，因为这种产品有机会真正成为主流用户、主流商业客户有用的 AI 交互方式。

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 kind of business customer can interact with AI in a way that’s useful.

Lenny Rachitsky

快速回到时间线。第一行代码到内部 beta 一个月，之后呢？

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?

Roman Ugarte

内部 beta 到公开发布大约三周；录制时距公开发布大约三周。

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.

Lenny Rachitsky

哇。一个月做出第一版，只迭代三周，发布又才三周。从我的视角像改变了世界。

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.

Lenny Rachitsky

那大约三周内部 beta 里，变最多的是什么？

What most changed in those — I don’t know — in those three weeks of internal beta, let’s say.

Roman Ugarte

我们 unship 了很多。真希望能给你看发布前两周的样子：核心团队塞了很多想拿内部反馈的实验功能；也把偏开发向的可见性工具塞进 Grok Bot，而不是单独可观测面板——比如有时会暴露很多模型内部思考、具体存了哪些记忆，对调试有用，建产品的人不想去别处拉上下文。但我们必须非常激进地砍：用户在界面上绝对需要看到什么、不需要看到什么。还有更大空间——团队现在正盯着：如何无情简化，把用户不必主动想的东西全抽象掉。一大推力就是 unship 大量 jank。

We unshipped a lot. I wish I could have shown you what things looked like maybe two weeks out from launch where I think we’d realized that the core team, we had a lot of experimental features that we wanted to get internal feedback on which was useful. We also were kind of putting pseudo-developer-y like visibility tools into Grok Bot instead of having like a separate observability pane for those things. So for example, we actually did expose sometimes a lot of the internal thinking of the models and the specific memories it would store and all of these things which was useful to debug issues and if you’re building the product, you didn’t want to go somewhere else to maybe pull that context. But we had to really aggressively trim what we think the user absolutely needs to see in 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 is 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 was unship a lot of a lot of jank.

Roman Ugarte

那几周第二大推力是让它「就是能用」。很多人要的不是一堆下拉和花活，而是：描述一件对你有意义的任务，它去做，带回完整结果，或带回让你反应、再驾驭下一轮的东西。兑现这个承诺，其实不是功能路线图那类活，而是后端爬五六个重要问题的山——用户不直接看见，但 bot 点不对按钮、登不上网站、任务彻底卡住时，你完全感觉得到。

And then I think the second big push those few weeks was making it just work. And 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 that you describe a task, a task that’s meaningful to you and it goes and it does it and it comes back with complete work or it comes back with something for you to react to and then steer it in its kind of 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.

Roman Ugarte

那几周我们收集了一套很丰富的：人们实际交给 bot 什么任务、怎么量化、怎么按周看这些类别在「就是能用」的关键维度上在爬坡。

And so those few weeks we collected a really rich set of what are tasks that people actually are giving bot, how can we quantify these things and how can we see week over week that across those categories of tasks that we’re hill climbing on very important dimensions to making that just work behind the scenes.

Lenny Rachitsky

有没有一座山是技术突破或硬挑战，真正帮它「就是能用」？

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

Roman Ugarte

例子：公司里有一组人其实非常 bot-pilled——go-to-market、销售。销售用的很多工具没有良好 MCP 或 API。对这群人，bot 前后差别巨大：以前没法可靠交给别的 AI，会卡在某步；有了 bot 像多了个助理、像给个人团队 onboarding 了一个人、发了台笔记本就能跑。有一长串十到二十个小点：比如鼠标精度不够点不准 Salesforce 仪表盘某处。我们会带回基础设施团队：这是非常具体的案例——智能体对浏览器/屏幕像素没这种可见性，任务就做不成。这比看仪表盘数字慢慢爬更可感：解锁新一块工作；背后基础设施改进一 ship，第二天销售团队就会涌来感谢——卡了七天的流程终于通了。不断找下一座要解锁的任务山再解决。所以 computer use 改进是大解锁。

Yeah, one example was from rolling out Grok Bot. One group inside of the company that was actually incredibly bot-pilled, 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 bot so before-and-after powerful for this group was these were things that they just could not give another AI tool reliably. We would get stuck at some part in the process. Then 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 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 outpouring 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. So, computer use basically improvements seems like a big unlock.

Lenny Rachitsky

我请过 Adam Ward——负责招聘/人才。听说他的团队是 Grok Bot 顶级用户之一。

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.

Roman Ugarte

是，招聘团队给了很多好反馈。早期产品有点小 bug，就会收到招聘同学的 ping。特别有意思的主用例首先是 sourcing：Adam 跟你聊过，也是我们内部招聘哲学的一大部分——「正在找工作、在市场上」不是我们尝试招你的前提。很多时候最好的招人方式是：看公司最大、需要人拥有或带到下一阶段的问题；在全世界潜在人选里找谁最合适；然后无情追、说服加入。这从公司一开始就是哲学。

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 being 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.

Roman Ugarte

有了这种心态，最该自动化的不是「一堆简历帮我读、排序」；最有用的是：这里有一整宇宙潜在人选，帮我对上这个非常具体的业务问题或岗位，帮我联系、约咖啡——全力砸上去。有些找顶尖人才的方式出人意料，不只是扫 LinkedIn：这篇论文的共同作者是谁？PDF 不在 Google Scholar，只在某个会议网站上——我要你每天早上去会议站下 PDF，有新的就找出我们还没追踪的新名字，加进表格，做研究，看 SpaceXAI 里有没有直接认识的人，有就 Slack 求介绍。这类 always-on sourcing 过去极手工，现在是 AI 超人类擅长的；团队可以专注关单、开对话，而不是拉巨型名单。

And so if that’s your mindset, really the best recruiting workstreams 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. If 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 SpaceXAI, 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.

Lenny Rachitsky

太酷了。一方面马上有人会把你刚说的塞进 bot 做自己的版本——很好。另一方面你们几乎能把 Adam 团队的策略做成模板 bot 卖十亿美元。民主化招人啊。

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.

Lenny Rachitsky

我想回到几点。你讲 unship——很多人会忽略，因为 AI 很会给你「再加更多」，不会告诉你该拿掉什么。播客里反复出现：知道不 ship、该砍、不该做什么，是人类继续重要的大空间。从原型到上线，内部演化一大块是决定砍一堆东西。还有要补充的吗？

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 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 of from prototype to launch is deciding okay we need to cut a bunch of stuff. Anything more there?

Roman Ugarte

我们内部会问：任何在做的 Grok Bot 工作，发布帖是什么？真正会对用户说什么？如果不是一条让人想发的 launch tweet——如果不够有说服力——也许就不该做。如果用户在产品里直接感觉不到，也不该做。再往前一步：老派软件倾向说「Grok Bot now has」——补完这句往往是新按钮、新下拉、新集成、点加号挂上。我们改成「Grok Bot can now」——更像人在描述能力。这逼我们想：能给 Grok Bot 什么工具和能力，而不是能往产品里加什么新东西。加东西不是目标，那不会把产品推向更多人更有用；让 bot 在背后可靠地做出有影响的工作、并给它们做到这件事的能力——用户才在乎。

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 — 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.

Roman Ugarte

所以在 unship 语境下，很多「Grok Bot now has」其实只是不需要像素的能力——能杀多少像素就杀多少，让 bot 在背后操纵，用户不必直接控。例子：很多竞品设自动化/例程是进侧栏、按加号、选触发、再选动作，也许再用自然语言描述——很笨重，所以人很少设。编码领域我们也见过。Grok Bot 的回应是：用自然语言定义自动化——告诉 bot「每天早上八点提醒我」，它就该做；你永远不该看到「创建自动化」那个界面。现在平台上 99% 的自动化是这样建的。还有很多地方可以这样做。

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 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.

Lenny Rachitsky

我发推说有多爱 Grok Bot，很多人回：等等，这些用 Codex 和 Cowork 不也能做吗？据我所知，技术上 Grok Bot 能做的，别的基础模型和编码助手也能做。那大问题：你觉得你们做对了什么、才让 Grok Bot 这么成功？

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 Codex and Cowork 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?

Roman Ugarte

我认为是早期两个决策——当时绝不显而易见，事后看却是关键。第一：你永远不该去想本地还是云、工作流跑在哪、电脑要不要醒着、手机上踢出去要不要拴着家里电脑——现在人们概念化 runtime 住哪时，纸割伤太多了。我们很早决定：全在云里。在云里、又是有自己电脑的持久同事，它能自己干活，你在哪交互状态都一样——于是可以给 bot 发短信、从手机启动；未来你该能在任何地方打电话给 bot，它能做真工作。它是独立实体，活在设备之外。这个决策很重要；现有产品很多没做同样决定，用户天天感觉得到纸割伤。

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.

Roman Ugarte

第二步更进一步：不只是云端跑的智能体循环、可用多种方式交互——这些 bot 必须有自己的电脑。一部分是前面说的：很多任务没有良好 MCP/API；人类工作也不是靠 MCP/API——我们用电脑、点像素、在输入框打字。bot 也需要这些基线能力。再往前：我们处在一个回头会觉得奇怪的时刻——你在 onboarding 超级聪明的新同事、AI bot，却让它们跟你共用同一台电脑。疯狂。如果第一天 onboarding 某人：你没有自己的笔记本，永远坐我旁边共用、不断绊倒对方，凭证互相看得见——有很好的理由人类不这么干。未来的 bot、AI 同事也需要某种类似的 onboarding 方式。我们在把产品往那推。

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. And we’ve tried to push the product in that direction.

Lenny Rachitsky

太好笑了。

That is so funny.

Lenny Rachitsky

你觉得别的公司为什么没这么做？我猜是在现有编码助手平台上建，这是很大的转向。

Why do you think the other companies didn’t do this? My guess is they were building off of their existing coding assistant platform and approach and this was like a pretty big shift.

Roman Ugarte

很多归结为从零开始有多解放——我们自己也感受到。Grok Bot 里很多原语我们以前用别的方式试过或建过：编码智能体的云基础设施；给智能体命名、当离散实体对话——开发者侧也在出现，比如把具名智能体带进 Slack。但我们没有强默认地把这些概念硬塞进新界面或旧界面，而是从零开始，尽量为通用知识工作——新受众——以及模型已经很强的当下做对：给对工具和基础设施，它们能做很多。这些点子不是我们的天才一闪；OpenClaw 一类产品已经在拿关注和产品市场契合。我们大量受启发，想产品化成更紧的界面、少一点 setup、对更多人更可及。

I think a lot of it comes down to starting from scratch and how freeing that is and we felt that ourselves where a lot of the primitives in Grok Bot we had attempted or we had built in other ways. You know cloud infrastructure we built for coding agents. The way that you could maybe name agents and talk to them as discrete entities. It’s a pattern that we’re also seeing for developers kind of bringing specific named agents into Slack. But instead of kind of trying to retrofit those concepts into some new surface or into an existing surface, which I think would have been the strong default I think 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 — these aren’t strokes of genius on our part and I think for good reason I think these are primitives that had already been getting attention and product market fit by other products, you know the OpenClaws of the world. And 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 I think was more accessible to more people.

Roman Ugarte

竞品和其他在解同类问题的工具，大家看见的机会差不多、市场反馈也差不多；但若困在旧范式、沉没成本很大，从零做新东西很痛。我认为正是这些让产品对很多人「就是能用、就是对上了」。

And 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. I think we’re seeing a lot of those — the 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 kind 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.

Lenny Rachitsky

所以我听到的破圈钥匙：每个 bot 一台云电脑而不是本地；具名的、按任务/用例的 bot——顺便说，我们好像都从 agents 改口叫 bots 了，干得漂亮，感觉是你们推过去的；再就是「就是能用」，以及你们花多久才到那。

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 named kind of like specific bot. And by the way, there’s this like we’re all moving from agents to bots now. Nice job. Like feels like you guys have pushed it over now. Okay, we’re all bots now. So a bot per kind of task use case — very unique versus like a thread conversation or something or like a one-off job. And then it feels like there’s it just works was a core part of this and you talked about how long it took to get to that place of like okay now it actually works really well.

Lenny Rachitsky

你提到 OpenClaw——显然受启发。我第一次用 OpenClaw 就觉得：这就是未来，怎么能没有。后来 Hermes 出来，人人想做「对所有人都好用的 OpenClaw」。OpenClaw 那条故事怎么塑造你们的想法？

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 just like how OpenClaw and that story informed the way you guys thought about it?

Roman Ugarte

OpenClaw 做对了两件大事，我们看市场反应、自己用时都很兴奋。第一：模型已经很聪明、还会更聪明；但即使在当前能力，只要给 bot 你用来干活的那些工具，很多地方人们觉得 AI「笨」或没承诺那么有影响——往往是 harness 用错了。给更大工具集、给自己的电脑，能走多远？OpenClaw 把这个问题狠狠推到很多人面前。

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 do — 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’s just being harnessed in the wrong way. And so if you kind of 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 kind of forced that question for many people.

Roman Ugarte

第二：OpenClaw 改变了对 AI 的心智模型——更把这些东西看成同事、队友、人，拟人一点，是能接触你生活、把你延伸得更远的帮手实体。我们拿了很多；Grok Bot 延伸的是：一、必须极易 setup——家里 VPN 加 Mac mini 那套黑客式显然扩不到百万用户，也显然不是企业用这技术的方式，所以要按那个标准建出色产品；二、很多毛边要磨平，做成愉悦体验、让它就是能用，并去掉 AI 重度用户熟悉的抽象——比如 skills。怎么让 Grok Bot 用户甚至不必知道 skill 是什么、永远不必打斜杠命令——这些在后台作为 bot 可用的有用原语创建，而不是要求用户永远站在 AI 刀刃上。我们想创新的是这块，还有空间。

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 and personifying it a bit more and it being this helper entity that has access to your life and can kind of extend you even further. And so we took a lot of that and I think what Grok Bot maybe extended was A it needs to be really easy to set up and the hacky you know 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 importantly that businesses take advantage of this technology and so we really wanted to build an amazing product with that in mind and then second is I think there are a lot of places, 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.

Lenny Rachitsky

你说这话时，我旁边还有曾经活着的 OpenClaw 的 Mac Mini——那是一个时代，它激发的工作太棒了，OpenClaw 仍有价值。但我看到 Claire Vo——OpenClaw 最大拥趸之一，已经成她和孩子生活、工作的核心——她把所有 OpenClaw 关掉，全切到 Grok Bot。听起来好笑，其实是巨大里程碑，说明风向转了多少。

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 — it’s like 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 — like it sounds funny, but that’s actually a huge milestone of just how much things have shifted.

Lenny Rachitsky

Grok Bot 的愿景大致是什么？未来长什么样？柏拉图理想版是什么？

What’s kind of the vision for Grok Bot? What’s like where does this go? What does this look like in the future? What’s like the ideal platonic version of Grok Bot?

Roman Ugarte

终极愿景极其简单：你该有一支 AI bot 团队，帮你工作、也帮你生活；而且真要感觉像团队——自主的队友在帮你，你可以多种方式驾驭，不必微观管理，它们有做大事所需的工具。产品侧我们当北极星用的是：越靠近这种队友未来，每个产品决策越少从 SaaS 产品视角、越多从「我们在建有用的 AI 队友」视角想。

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. 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 SaaS product and more from the perspective of we’re trying to build useful AI teammates.

Roman Ugarte

有很多例子逼我们更「colleague-pilled」——我们有时用这词。产品争论双方都有好理由，产品视角未必有斩钉截铁答案；然后你退一步，脱掉科技公司那套，问：人类会怎么做？这种情况下你希望队友怎样？答案往往很澄清、很一致——房间里对「你更想怎样跟人队友协作」常常没多少分歧。答案有了，就去建。有产品含义、模型含义，很多东西要对齐才能兑现；但某种程度上不是火箭科学，不必当天才——问你会希望人类队友怎样，再把 AI 往那推。

And so there have been a bunch of examples where we kind of have to push ourselves to be more like colleague-pilled 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 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.

Roman Ugarte

举例：我们在想跟这些 bot 怎样做语音体验。人类这边有很好的类比：很多时候跟队友 Slack 来回共享上下文，更简单是开五分钟 huddle，按一下、来回说，共享屏幕，展示脑子里的东西，下线再异步继续。目前几乎没有 AI 产品做对这件事，而它深深嵌在人类协作方式里。我们想建类似的东西。还有一堆「就是管用」的清晰模式，跟 AI 协作时也该感觉得到。

And so to give some examples of that I mean we’ve been thinking about what the right voice experience with 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 five-minute 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 that I think you should also feel when working with AI.

Lenny Rachitsky

我太爱「colleague-pilled」这个词——整场对话的贯穿线。你举的电脑例子特别好：人当然该有自己的电脑；命名也很重要。我脑子里有个大问题——

I love this term colleague-pilled. Such — and it’s come up so many times over the course of this chat already how that is kind of a throughline 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 —

Lenny Rachitsky

——工作和个人要不要分开？你觉得人会有两个助手——工作和生活各一个——还是一个？

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?

Roman Ugarte

人们想「工作产品」vs「消费产品」时，带着过去一二十年糟糕 B2B 软件的很多包袱——看到 ChatGPT、Grok Bot 这种某种意义上很简单的产品，就假定它不是工作产品、不是专业工具。上一代专业工具在我脑海里像 Photoshop：一堆精密旋钮，用户是终极驾驶舱飞行员，知道每个旋钮干什么。未来的专业工具会很不一样：大多是表达意图、人做良好驾驭，AI 把旋钮抽象掉——除非你需要直接操纵（那时也该有很好的 affordance），否则永远不该看见。本质上就是跟队友协作，界面相当会话化。

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. That leads to people seeing a product that is very simple in some ways. ChatGPT 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 ultimate 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. 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.

Roman Ugarte

很多时候我走过别人工位看到 Grok Bot，有一瞬间会想：他们是不是在用消息应用？其实那是他们做大量工作的主工具。所以：会不会有一套个人生活 bot、一套工作 bot？我认为很多人会分开——想要个人与工作分离，这很好、很重要，从企业视角也有很多常识原因该分开。但我们想建的是：Grok Bot 应成为你日常大量工作可委托出去的方式，你专注更高杠杆的事；同样也成为你委托个人生活里低杠杆部分的方式。这两件事问题集其实没那么不同，产品形态和解法很大程度上一样。我的直觉是：一个产品会是两者最好的形态——那正是我们想建的。

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 — this is actually the primary tool that they’re using to do much of their work and so I think to the 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. I do think there will be a separation for many people. They want a separation between personal and work life and 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 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.

Lenny Rachitsky

Bam，TAM 很大。很说得通。问题是怎么避免交叉污染——个人东西渗进工作、或反过来。感觉方向是那样，关键是怎么做、让人超级安心，有 SOC 2 一类东西，也真的好玩。

Bam. That’s a big TAM right there. I love to hear it. Makes so much sense. Obviously the question is how do you avoid cross-contamination, you know, personal stuff somehow infiltrating — exfiltrating stuff from work. 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 SOC 2 stuff in place and also just feel really fun.

Lenny Rachitsky

几个技术问题。电脑这边：Grok Bot 账号里你「得到」的最简单理解是什么？云里一台多登录的 VM？每个 bot 单独实例？能分享多少就说多少。

Let me ask a couple technical questions. On the computer side, how — what’s the simplest way to think about what you get as a part of your Grok Bot 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?

Roman Ugarte

回到队友框架，把类比再伸一点：如果我们在同一队，你需要手动接管我的电脑、开始点、说「你做错了、去这儿、手动打」——希望次数接近零。那不该是跟人队友常做的事。同样，现在 computer use 已经不错、还在变得更好；很快「电脑」概念会完全对用户抽象掉——你永远不该点进远程虚拟机、永远不必接管；如果有浪费路径，你驾驭回正确路径。中期「电脑」对用户仍是重要概念，但不是他们真正交互的东西。

Yeah. I think to go back to the teammate frame of the product, to kind of 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 know, 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. You know, if something — 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.

Roman Ugarte

正确理解 Grok Bot：是一支 bot 团队、一支为你干活的智能体。它们能访问很长的、与你过往互动的记忆。当前范式是每个离散工作单元开新聊天——问题很多，我老在聊天间复制粘贴，也不是好的工作归类方式。团队上你会按角色、泳道归类工作；这些角色应向你学习、随时间更聪明。关键之一：它们是长寿智能体，不是一次性会话，且越来越聪明。第二：它们有你期望人类同事有的全部工具——API、MCP 很好，再加上自己的电脑，可像你一样自由操纵。

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.

Lenny Rachitsky

那场 meetup 上，go-to-market 的 Shub 演示把大家惊呆了：每个智能体里有电脑，你可以跑很多东西——他在 Grok Bot 里跑 Grok Bot，bot 可以跑自己的 Grok Bot，用来测试、看回归。好奇能嵌几层宇宙才塌。

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 Grok Bots 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.

Roman Ugarte

我也那么干。其实很有用：给某个 bot 下载 Grok Bot——我有个 QA 测试 bot——有 bug report 或测新桌面版时，我可以说：这里有十个工作流，每个 release 都要更好；去测，写到这份 Notion，里面有过去客户端版本的详尽测试清单，做对比。一旦你跳出「这是带一堆连接的 AI 聊天」——我觉得多数人概念上还在那——改成「这是有电脑的同事，凡是我会让同事在电脑上做的，我都能让 Grok Bot 做」，交给 AI 的天花板就抬高了。

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 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 Grok Bot to do. It just raises the ceiling I think of what you would think to give to AI.

Lenny Rachitsky

还有别的打开脑洞的用法吗？你见过或自己在用的？

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

Roman Ugarte

很多人用的一个模式简单但越投入越有深度——我会对优化自己的 setup 有点 geek：某种意义上把 Grok Bot 当 infovore，吞掉海量信息，从你认知负荷里拿掉，给你安宁，再把重要的带给你。V1 很多人做的是：Grok Bot 坐在 Slack 和邮件上，我告诉它我的角色、我在乎什么；这些情况通知我，那些情况不必直接 ping，但放进我每天读的日报。

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 — is 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 — 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.

Roman Ugarte

我不确定 V10 是什么，也许我在 V3 或 V4：你可以给这些 bot 完整的信息消防水带。我的接上了 X 上每一次提到 Grok Bot，跟内部上下文互动，跟 QA 测试员互动看能不能复现反馈里的 bug；也接到我自己的消息服务，好快速行动、联系人。这是始终在线的首席幕僚实体：保住你对真正重要事的注意力，同时一直在「监视」有没有该引起注意的事。还有人真的给 Grok Bot 呼叫权限——我还没做，也许很快——超紧急时在咖啡店被 Grok Bot page。只有紧急、且你信任它几乎没有假阳性时才敢这么干；到目前那些人说很有帮助。我们会看到更多：bot 该比你主动找它更主动找你——那会是 AI 下一轮转变。

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 Grok bots — which I have not done this yet, but maybe soon — giving their Grok 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 trust that Grok Bot does not have false positives. So far, those people have reported that it’s been very helpful and successful. 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.

Lenny Rachitsky

这碰到我看你们团队运作很佩服的几点：一是速度；二是你们清楚这是抢市场份额的时间窗口——在别人、尤其基础实验室拿出很强的东西之前，尽量多占。看你们发多少免费账号、多聚焦用例——这东西很新，打开就问「我能干嘛」，所以「人们都在干这些」和 Twitter 上的模板讨论特别聪明。你以前在 Cursor 做 go-to-market，关于现在怎么把这东西推出去，有想分享的吗？

This touches on there’s 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 like there’s 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 like 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. 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.

Roman Ugarte

我认为编码侧见过的模式，会多少类似地出现在通用知识工作；我们在 go-to-market 和更广义「建人们真用的实用 AI」上学了很多。公司文化上我们很在乎不建 demoware——建世界上真正有用的东西，并为此执着。闪亮物体和好玩原型太多，但那跟把产品交到百万人手里、改造公司，是完全不同的问题。文化上我们一直盯着后者。

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.

Roman Ugarte

Go-to-market 上，编码侧模式很简单：早期采用者把编码工具推到极限——多半是个人项目、夜晚周末。想 2023 年更早：白天上班用基础 IDE，这是前 AI；回家做 side project 用 Cursor 或最新 AI 编码工具，感觉极度加速、像在体验未来；回公司就要求：我没法想象再用别的方式，现在像在糖浆里走，必须改。知识工作也会类似：aha 时刻有时先出现在个人场景——X 上现在就能看到 Grok Bot 控家里机器人吸尘器、帮谈 Tesla 充电价之类好玩用例。下一步是：这不是消费产品，我们认为它会改造企业、改造团队——bot 进入团队做真正有经济价值的工作，尤其它们变得更聪明时。

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 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. 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 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.

Roman Ugarte

所以 go-to-market 上我们在大力优先企业：不只单人跟单个 bot 的单人模式，而是 bot 如何在更广团队里工作、如何进入复杂、有大量上下文和历史的公司系统；组织级记忆 vs 服务单人记忆长什么样。未解问题很多，但我认为 Grok Bot 是让公司其余部分——编码之外——切到智能体的正确原语，我们现在很聚焦这里。

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 kind of a broader organization versus kind of a single individual you’re catering to? And I think there are a lot of unanswered questions there. But I do think Grok Bot 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.

Lenny Rachitsky

而且很明显你们懂分发的力量：既要惊人产品，也要把分发做对。Grok Bot 本身很强，再加上你们各种把它推出去的聪明方式，说明现在要做出真正成功的东西需要什么。

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 Grok Bot’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.

Lenny Rachitsky

想问品牌——产品周围、公司周围不同品牌，好让人说对。我知道你们在经历收购、SpaceX 等过渡。有 Grok Bot，有 Cursor——今天该怎么理解这些产品和品牌？知道还会演化，只是想当下沟通正确。

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.

Roman Ugarte

当然。我认为 SpaceXAI 现在有三大支柱。第一是编码产品/产品线——现在是 Cursor 和 Grok Build。我们坚信：给开发者、给工程组织一块专业工作界面会非常关键。现在人们有时用 Grok Bot 启动云智能体、合并 PR、做 QA 等工程相邻任务；但最终要 ship 生产软件，我们相信需要每个像素都为那个终端用户优化的产品。所以我们在大力投入。

Definitely. Yeah. I think there are three big pillars right now of SpaceXAI. So the first pillar is the coding product — instead of products — and right now that’s Cursor and Grok 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.

Roman Ugarte

第二类是通用知识工作，我们认为 bot 是很令人兴奋的一步；还有很多活：更有用、扩展到新界面、真正感觉像可委托工作的 AI 队友——尤其在公司和企业里。这是第二支柱。

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.

Roman Ugarte

第三是通用模型努力——我们想训练世界上最聪明、真正有能力的模型。SpaceXAI 跟其他 AI 实验室略有区别的一点：目标不那么是追逐超级智能或某种模糊理想；目标非常务实——建有用的 AI。产品侧做、模型侧也做。文化上也是：参与这些模型的很多人是工程师，带着很应用的心态进入模型训练。我认为这驱动公司，也跟一些竞品方向略有不同。

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 SpaceXAI from other AI labs is I think our goal is less to build — chase superintelligence or some kind of vague aspirational ideal — and the goal is actually very practical which is to build useful AI and we do that on the product side, we do that on the model side and I think part of that is also just cultural of like the group of people contributing to these models are engineers and people who kind of came into the model training effort from like a very applied mindset and I think that’s what gets this company going and I think is actually a slightly different direction from some of the other competitors out there.

Lenny Rachitsky

超级有意思。

Super interesting. Okay, there’s a —

Lenny Rachitsky

——几个方向想聊。一是你有条推文，好像 pinned 或时间线很靠上：一个能把工作做到 100% 的 AI，和只把你带到 90% 的 AI，感觉是完全不同的品类。我显著更新了自己对 AI 能力的看法。多说一点。

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.

Roman Ugarte

对我来说，让我这么兴奋做并贡献 Grok Bot 的是：第一次在非编码任务上，我感觉真能把工作委托给 AI，不用再想，回来已经做完。工程师大概已经感觉这大约一到一年半了——开发者的工作跟两年前完全不可同日而语，这方面说了很多。但被低估的是：这种体验跟大多数人现在对 AI、以及 AI 改变他们生活的方式，差别有多大。多数人用法仍很像两年前：为任务开新线程，打进输入框，回车，看步骤，拿输出，不太对，继续改。Grok Bot 短路了很多：第一眼界面就觉得「这明显不一样，看看是不是真管用」——然后你给它东西，它在惊人程度上管用。我们还会大力让它更好。

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 kind of 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 to a surprising extent and I think we’re going to do a lot to make it work much better.

Roman Ugarte

那条推想表达的是：如果你只有 90% 信任某个队友——幸好我这里没有，因为同事很强——你把事交给对方时心里想「我知道自己还得一边想着这件事，大概还差一点，我得介入稍稍驾驭」——那不是 90% 任务完成，你仍在干这件事，它同样压着你。真正像无视线传球给同事：「你行的，这是上下文，去跑，我很期待你做出什么」——那是另一品类。我认为人们每天在 Grok Bot 上感觉到的就是这种 no-look pass：你相信它能做完，它也做完了，非常魔法。

And so I think what I was expressing in that was when you have a teammate that you only 90% trust and you give something to — which 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 like probably is not going to be quite there and I’m going to have to intervene and kind of steer it slightly. You’re not — 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 like 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. Like 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.

Lenny Rachitsky

对，我持续有这种体验。

Yeah, I have had that experience consistently. Okay. So, another —

Lenny Rachitsky

——你们运作方式另一点让我印象深刻、以前没见过的是有多快。我被加进一个给反馈的 Slack，就是：好，明天给你们一批免费码可以发出去；或者我们要上模板 marketplace，两天后上。我就：什么？我没时间跟。你们事情那么多还不断 ship，又保持一致、高质量、清楚指向特定愿景。问题两半：快的秘诀是什么？以及这么快怎么对齐到大家都信的愿景，而不是一路打补丁？

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 like 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 — 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 like 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 — they all believe in and where you want it to go versus just like you know band-aiding it along the way?

Roman Ugarte

我很高兴一件从未变的事：公司里的创业感。背景：我加入 Cursor 时大约 15 人，扩到超过一千；现在又是更大的 SpaceXAI 组织的一部分。跟一群极强的人在一起，人人每小时跑一百英里，你深深信任每个人执行自己那一块，有清晰愿景，人人兴奋并知道必须执行——特别好玩。

Yeah one thing I’ve been really happy has never changed is that startup feeling inside of the company and for context when I joined Cursor originally we were about 15 people. We scaled to about 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 like and knows that they need to execute on.

Roman Ugarte

公司长大时——我们有幸招了很多经历过超增长公司的强人——事情会变慢，你不断告诉自己「我们还是创业公司、还很快」，但其实并不快，人人都知道并不快，说比做容易。手指交叉希望这继续为真——对我们成功至关重要。但即使规模变大，一直感觉像我当初加入的那种创业公司。如果你用人数或融资轮定义创业公司，那些都不成立；核心定义正是你说的那种 scramble 能量：有点乱、有点无序——很多人会觉得不舒服——但它有惊人属性：短时间能在特定方向产生极端影响，系统回报你投入多少。作为文化、作为组织、我们怎么构建自己，一直是在启用这种属性；一些竞品和其他 AI 实验室变大很多，你能感觉到。我们即使扩张，那种创业冲动对快速做事仍相当重要。

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, you know, it’s easier to say than to actually be. And, you know, 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 kind of I first joined. And I think if you define a startup by number of people or by like the funding round like 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 like 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.

Lenny Rachitsky

让我拽住这根线，问我一直想问的大问题——

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 —

Lenny Rachitsky

——从外面看 Cursor，它「本不该成」「本不该撑住」：一、处在世界最卷市场，对手是史上增长最快的公司 OpenAI 和 Anthropic，竞争强度前所未见；二、它又坐在这些平台之上用它们的能力。作为局外人，我觉得 Cursor 能赢、有巨大 exit、继续成功，是因为你们多快调整适应市场现实：从 autocomplete，到跟智能体对话，到云，再到 Grok Bot。核心似乎是快速对齐现实，并为别处也存在的东西做出最佳体验——Grok Bot 是例子，别处也能做，但这是最佳体验；Cursor IDE 是最好的编码方式。也许我已经答了，但你觉得 Cursor 能在这么疯的竞争里不仅存活、还持续极好表现，核心是什么？

if you were to look at Cursor from the outside, you — 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. 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?

Roman Ugarte

很多——答案有点模糊——来自文化：你定下什么文化、带进什么人、他们怎么对待问题。对我们来说，正像你说的：我们从不自满，从不觉得已经赢了，永远盯着下一件事。全公司有很深的信念：AI 动得极快，我们的目标是把能力翻译成给客户的惊人产品；但产品会变，必须在能力变强时对上那个时刻。两年前对上时刻的东西，跟今天完全不同。如果我们作为公司不能每六个月——最近感觉更短——彻底重塑优先级、核心产品、用户感受，我们就会输。正是永远推向前沿、从不觉得结束或赢了或做对了、不断更新信念，把我们带到现在。

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.

Roman Ugarte

说到竞争：AI 编码从 Cursor 出现起就一直很卷——当时对手是 Microsoft 等，大概十到二十家公司。值得注意的是：那些竞品现在都不在 AI 编码前沿——很大程度上不是因为做错决策或缺资源，而是文化上无法快速移动、无法在时刻变化时对上时刻。正是这让我们投资 Grok Bot 这类东西。

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.

Lenny Rachitsky

有没有核心价值观——具体怎么表述——提醒大家：我们就是这样工作的？

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

Roman Ugarte

有两个我常回到的。第一是「删除产品」——正好接上你刚才说的。看 Cursor 每一代过去迭代，我认为看 Grok Bot 每一代过去迭代也会一样：东西在消失，不是新东西在加——那些因为模型还不够聪明、不能自己做而建的脚手架、产品 overhang，会随时间移走。我们需要舒服做可能让一小撮用户或内部人不高兴的硬决定，去成全更大的事：让产品简单、强大，适配未来走向。这非常核心。

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.

Roman Ugarte

第二件接上执行节奏：just do the thing——即使公司长大我仍常重复。我们在同一条船上，想赢；如果你看见该发生的事，这不是请示许可文化——你出去修，拉你需要的资源做成。这让很多人在这里很成功，也是我们跟 SpaceXAI 真正共享的东西。

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 SpaceXAI as well.

Lenny Rachitsky

Agency——你也许听过。有意思。

Agency as you may have heard. So interesting —

Lenny Rachitsky

——常出现的大问题，也许是最后一个：护城河。很多人觉得 Cursor 很有意思：技术上或许没有护城河的市场，却持续赢。常想到的两个：数据反馈环——人们 autocomplete，学习他们在干什么，据此训练模型；以及最佳体验、高日活，随时间发现什么管用。你学到了什么？对这个空间护城河有什么想法，可能帮到在想自己护城河的人？

one of the big questions that comes up and this might be my final question is around moats and a lot of people look at Cursor is 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 moats 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 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?

Roman Ugarte

护城河谈得很多；现在创业是很有意思的时刻，我理解为什么很多创始人问自己、试图投影十二个月、二十四个月后——感觉像永恒。我会说：如果 Cursor 和很多同代成功公司当初从护城河、从战略图或更抽象的「公司该怎么运作」反推，我不认为会创造出这个结果或这个产品。真正创造 Cursor 魔法的，是执着于今天建有用的东西——不断是：你能看见世界三四个月、六个月后模型会更聪明，现在不可解的事终于可解；Cursor 像反复提示：怎么把那东西拉到今天，哪怕需要上面加一点或很多工程，哪怕需要改产品形态让用户能交互新能力。怎么带到今天，然后三个月后删掉那些脚手架，因为它会变成产品的基本底线；再为再往后三个月建——不断重复。用户因此信任我们，把时间放在产品里，信任我们在把东西带到下一前沿。

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. 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 like basic you know common bare minimum of the product and then we’ll build the thing for 3 months from then and then it was constantly just doing that over and over again that I think led to users really trusting us and placing you know their time inside of our product and trusting that we were kind of bringing things to this next frontier and to the next future.

Roman Ugarte

所以我会鼓励今天起步的很多创始人更落地：怎么让现在不可能的事变得可能；用户会为那个来；我把他们拉到下一个不可能的前沿；在这过程中我会获得分发优势、数据优势，会有价值——但那才是该玩的地方。

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.

Lenny Rachitsky

太爱这个回答。我的理解是：建让人沉迷的东西，别过度想护城河；你能持续做，就会发现东西——Cursor 案例里发现了几样。另一集播客里也出现过：护城河很多时候是发现的，不是事先规划的。

I love that answer. Essentially, like the way I’m thinking about it is just build something people are obsessed with. Don’t overthink the moats piece. And if you can continue to do that, you’ll find something which in Cursor case ended up being a few things. And that that came up actually recently on another podcast I did. I don’t know if it’ll come out before after this. This idea that moats are discovered, not planned ahead of time a lot of times.

Lenny Rachitsky

好，真正最后一个问题：Grok Bot tips。有人会想「我得试试，热闹到底怎么回事」。对新用户的成功钥匙？对已经在用的人有什么 power tip？

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 tip for someone that’s already with it and just like oh wow I didn’t know that.

Roman Ugarte

我想避开超级黑客式 pro tip——团队和公司哲学是那些东西本不该存在。不该有一堆疯狂旋钮；你该能把事委托给 Grok Bot，它们就去做。对新下载 app、盯着屏幕的人：第一件事是给 Grok Bot 成功所需的上下文。类似 onboarding 新人：最好能访问 Slack、邮件、你每天用的公司记录。给它工具，然后真的问 Grok Bot 它能为你做什么，让它扫一遍你刚接上的连接。我的例子：给邮件、给 Slack。第一次 onboarding——那时还没有任何 onboarding 屏——我给的第一个任务是：扫我的 Slack 和邮件，建议五件你能从我盘子里拿走的事、以及你需要什么才能做。它建议了五个，其中两个真的很有帮助，我立刻开出两个 bot 去解决。那是大 wow：过去没有别的 AI 工具能做那两件——不是起草邮件，是做一块工作。鼓励全新用户这样开始。

Yeah I want to stay away from the you know 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 like 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 was 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.

Roman Ugarte

对不是全新的人：我不断发现 bot 之间互动协作的新模式。我在建更多脚手架——Grok Bot 产出的工件该住哪、怎么写到对我很可读的地方。我有每天读的频繁 digests，推到数据库，很容易读。鼓励重度用户想：Grok Bot 怎么写到单一存储，好更容易组织大量输出。

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 Grok Bots 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.

Lenny Rachitsky

该死，我们需要另一集深挖 Roman 的 Grok Bot setup——大概有太多私密敏感信息不能展示，但没关系，这 tip 太棒了。Roman，闪电轮前还有想分享或想碰的吗？

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?

Roman Ugarte

我这边没有了。

Nothing. Nothing else on my side.

Lenny Rachitsky

覆盖了这么多，难以置信只有大约一个半小时。感觉聊了好久，想盖的都盖了。到了非常精彩的闪电轮。四个问题，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?

Roman Ugarte

准备好了。

I am ready.

Lenny Rachitsky

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?

Roman Ugarte

两本。一是我爱 Kurt Vonnegut，《猫的摇篮》是好玩的推荐，也买给过很多朋友。二是 Steven Pressfield 的《战争艺术》，我常回来翻一两页，谁我都推荐。

Yeah. So, two books for you. One is I love Kurt Vonnegut. So Cat’s Cradle has been a fun recommendation that 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.

Lenny Rachitsky

《战争艺术》太棒了。很短，读完就懂——不是人们可能听错的《孙子兵法》，是 play on that，关于创造、做出新东西、如何克服阻力。爱这个推荐。下一题：最近喜欢的电影或剧——如果还有时间看的话。

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. But it’s the war of art. It’s a play on that and it’s about the challenge of being creative and doing 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.

Roman Ugarte

有。每年我会重看《卡萨布兰卡》——最爱电影之一，碰巧还有个跟我姓一样的角色 Ugarte，大概是媒体里唯一的 Ugarte。所以《卡萨布兰卡》永远值得重看。剧方面，有时会偷看一集侦探剧《Monk》——小时候跟家人看，现在住旧金山又回来看；它是上世纪九十年代末、本世纪初旧金山的很好时间胶囊，我很享受。

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.

Lenny Rachitsky

播客上第一次有人提 Monk。好。现在最爱或最有意思的 AI 产品——可以说 Grok Bot，但若有别的给加分。

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.

Roman Ugarte

我一直是 AI 语义搜索 geek，爱任何语义搜索产品，尤其非寻常的。我是当时 Metaphor（后来成了 Exa）的很早用户，爱用 Exa 做各种对互联网更怪的查询；也看到有人在 MoMA 嵌入图像库之类奇怪数据集上做语义搜索，玩起来总是很开心。所以任何在怪数据集上的语义搜索引擎我都爱。

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. And I love kind of 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 semantically 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.

Lenny Rachitsky

尤其会推荐 Exa？

And Exa in particular is one you’d recommend.

Roman Ugarte

爱 Exa。对。

I love Exa. Yeah.

Lenny Rachitsky

很好。工作或生活中常回到的人生座右铭？

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

Roman Ugarte

不是短到一句座右铭。我爱 Desiderata——不知道你读过没有——我从青少年起就贴在门上，每次搬家都贴上。很短的诗，但每一行每次读都发现新东西，非常 grounding。

Not as short as a single motto. But I love the Desiderata which I don’t know if you’ve read but I have it on my door and I’ve had it since I was a teenager and everywhere I move I kind of paste it there and 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.

Lenny Rachitsky

Roman，太棒了。我们正处在 Grok Bot、以及整个 AI 的这个时间点上。一年后再回看会很好玩：哇，我们对了这么多、也错了这么多。非常感谢你来做这集——我知道团队现在极忙，你能腾出几小时聊天我很感激。有想让人去的地方吗？除了试试 Grok Bot，还有想推的吗？

Roman, this was amazing. What a point in time we’re here right now at this moment in time of Grok Bot of AI in general. 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. 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. Is there any place you want to point people to? Anything you want to plug other than check out Grok Bot? Is that —

Roman Ugarte

当然试试 Grok Bot。主要是：请发反馈。我们仍在很早期——beta 三周前才放。早期用户的反馈直接翻译成我们建什么、怎么建。非常感谢大家给的输入。

Check out Grok Bot? Of course. 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. 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 all the input that people are giving.

Lenny Rachitsky

Roman 和团队干得漂亮——我知道背后有一整支团队。Roman，非常感谢你来。

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

Roman Ugarte

太好了。谢谢 Lenny。大家再见。

Awesome. Thanks, Lenny. Bye everyone.