How we built Grok Bot in a month

主持人 The ultimate vision of Grockbot is incredibly simple. You should have a team of AI bots that help you with your job and help you with your life. Grok Bot 的终极愿景其实非常简单。你应该有一支 AI bots 团队，帮你做工作，也帮你处理生活。

Roman Ugarte Grockpot 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. Grok Bot 是此刻世界上最热的 AI 产品。这是很高的门槛。争夺这个位置的竞争非常激烈。

主持人 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. 我们想做的，不只是给 developers 和 engineers 用的好产品。我们决定在内部拉起一支很小的团队，钻进洞穴里大约一个月，带着唯一目标：做出一款出色的 knowledge work 产品，把 agents 带给公司里其余的人。

Roman Ugarte It's been only 3 weeks since launch. I went to a rock meetup. There were hundreds of people there. Standing room only. It's very clear to me that you guys have built something very special. 上线才三周。我去了一场 Grok Bot meetup。现场有几百人，站着都挤满了。我非常清楚，你们做出了非常特别的东西。

主持人 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. 一旦你跳出「这是带了一组 connections 的 AI chat」，转而变成「这是一位带着电脑的同事」，你愿意交给 AI 去做的事情，上限就会被抬高。

Roman Ugarte You have this tweet, an AI that does 100% of the job feels categorically different from one that gets you 90% there. 你有这条 tweet：一个能把工作做完 100% 的 AI，和一个只能帮你做到 90% 的 AI，感觉是完全不同的类别。

主持人 What made me so excited to work on Grockbot 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. What is it that you think you did that is so different that made Grockbot so successful? It was two early decisions that at the time definitely did not feel obvious, but in hindsight I think are critical to what makes Grockbot work. 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 had a growth for the last 2 years. Most recently, he helped incubate Grockbot, a product that I am obsessed with. It has changed my life. I use it a 100 times a 让我如此兴奋去做 Grok Bot 的原因是：第一次在非 coding 任务上，我感觉自己真的可以把工作委托给 AI，不用再惦记，回来时它已经做完了。你觉得你们做了什么如此不同的事，让 Grok Bot 这么成功？是两个早期决定，当时完全不觉得显而易见，但事后看，我认为它们对 Grok Bot 能跑起来至关重要。今天的嘉宾是 Roman Ugarte。我会把开场说得很短，好直接进入正题。Roman 是 Cursor 的第 15 号员工。过去两年他负责 growth。最近，他帮忙孵化了 Grok Bot，这是一款我非常着迷的产品。它改变了我的生活。我每天用它一百次，

主持人 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 Grockbot. He's been part of the core team from early prototype until today. And we get into how it all started, where it's all going, and all the things that he and his team have learned since it launched just a few weeks ago. With that, I bring you Roman Ugarte. Roman, thank you so much for being here and welcome to the podcast. Thank you. It is great to be here. I am so excited to have you here. I am so hooked on Grockbot. I have it over here in my window. I have like 15 bots that I use every day, all the time. Uh I went to a meetup the other day, a Grockbot meetup. There were hundreds of people there. Standing room only. People sharing all the ways they're using Grockbot. It's very clear to me that you guys have 去做各种各样的事。我认为可以很有把握地说，它是此刻世界上最热、最令人兴奋的新 AI 产品。Roman 负责 Grok Bot 的产品。从早期原型到今天，他一直是核心团队的一员。我们会谈到这一切如何开始、将走向何处，以及上线才几周以来，他和团队学到了什么。下面有请 Roman Ugarte。Roman，非常感谢你来到这里欢迎来到这档播客。谢谢。很高兴来到这里。我非常兴奋你能来。我对 Grok Bot 已经上瘾了。它就开在我这边的窗口里。我大概有 15 个 bots，每天、随时都在用。前几天我去了一场 meetup，一场 Grok Bot meetup。现场有几百人，站着都挤满了。大家在分享自己用 Grok Bot 的各种方式。我非常清楚，你们

主持人 built something very special. It's very hard to break through the noise in the AI world. Uh Grockpot is the hottest AI product in the world right now. That is a very high bar. There's a lot of competition for that slot. I personally noticed I've moved a lot of my use cases from co-work and codeex into Grockpot just like just like very quickly which again feels like a really big deal and a very special moment. Uh and so I'm excited to talk about so many things. I want to understand how you guys did this, where this came from. Uh, where this is going, what you've learned about the journey so far. Um, first, nice job. Nice, nice work. This is very hard what you've done. 做出了非常特别的东西。在 AI 这个世界里，要冲出噪音非常难。Grok Bot 是此刻世界上最热的 AI 产品。这是很高的门槛。争夺这个位置的竞争非常激烈。我自己也注意到，我已经把很多原来在 Cowork 和 Codex 上的用例，很快就迁到了 Grok Bot，而这本身就感觉像一件大事，也是一个非常特别的时刻。所以我很兴奋，想谈很多事情。我想搞清楚你们是怎么做成的，这是从哪里来的，又会走向哪里，以及到目前为止你们从这段旅程里学到了什么。首先，干得好。真的，做得很好。你们做成的这件事非常难。

Roman Ugarte Thank you. I mean, I remember onboarding you uh by hand about a month ago, and I think you were skeptical at first. Uh, but we're very glad that you've been using it, and it's been great to see so many people um really take advantage of Grockpot. 谢谢。我记得大约一个月前，我还亲手帮你做 onboarding，当时你一开始是持怀疑态度的。但我们很高兴你一直在用，也很高兴看到这么多人真正把 Grok Bot 用起来。

主持人 I'm going to talk about that onboarding. 我会谈到那次 onboarding。

主持人 Uh that was a very interesting uh element of how this worked. Uh I actually remember in that onboarding I tried to you asked me to do like a let's try something and I was like okay try to come up with a tweet to promote my latest podcast episode. So I'm just like uh come up with a tweet to promote my last episode. That's it. And it was actually very good. It figured out what the hell last episode was how to promote it. So I actually remember in the moment being like wow this is really good. So let's actually start with origin story. 那是这件事能跑起来里很有意思的一环。我其实记得，那次 onboarding 里你让我试一下，我说好，那就试着写一条 tweet 来推广我最新一集播客。于是我就说：写一条 tweet 推广我上一集。就这样。结果其实非常好。它搞清楚了上一集到底是什么、该怎么推。所以我当时就记得自己在想：哇，这真的很好。那我们从起源故事开始。

主持人 Where did it start? What was kind of the original idea and when did the work on this begin? 它是从哪里开始的？最初的想法大概是什么？这项工作是什么时候启动的？

Roman Ugarte 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. Uh but what would that product look like for knowledge work? And we decided to kind of create this very small team internally. It was really just a handful of people uh to go off into a cave for about for about a month with the sole objective of build an amazing knowledge work product that brings agents to the rest of the 是的，它几乎是从一张白纸开始的，完全从零、从 scratch 做起。我觉得我们已经有很长时间感觉到，我们想做的不只是给 developers 和 engineers 用的好产品，而那正是我们起步的地方。而且我认为我们由此积累了很多直觉，知道怎样做出优秀的 agents、做出真正有用的产品。但这对 knowledge work 会是什么样的产品？我们决定在内部拉起一支很小的团队，其实就几个人，钻进洞穴里大约一个月，唯一目标就是：做出一款出色的 knowledge work 产品，把 agents 带给公司里其余的

Roman Ugarte company. And I think from the first line of code to when we released this prototype internally, it was only about a month. It was like a very quick um you know scrappy prototype that was pulled together. And I think in hindsight this would not have been possible if it had been I think a much bigger group. I think it took a small focused group that was completely isolated from the rest of the company. And I mean that literally. It was like a separate part of the office where this team sat. Um 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. Uh some things that maybe we'll talk about a bit later that were not obvious, were not really things that we'd done on other product surfaces before. And I think if it had been a very big group of people and we were kind of thinking about this 6 to 12 人。而且我认为，从第一行代码到我们在内部放出这个原型，大概只有一个月。那是一个很快、很 scrappy 的原型，硬拼出来的。事后看，如果当时是一个大得多的团队，这件事不可能做成。我觉得需要的是一支小而专注、完全和公司其他部分隔离开的小组。我说的是字面意义上的隔离。他们坐在办公室里单独的一块区域。还有私密的 Slack channels。目标是——事后看，这也是让我们能跑得这么快的很大一部分——我们每天需要做大量微观决策。有些事也许我们稍后会谈到，当时并不显而易见，也不是我们在其他产品表面上做过的事。我认为，如果当时是一大群人，而且我们想的是一个 6 到 12

Roman Ugarte monthlong vision, we just wouldn't have really gotten to the place that we ended up landing at. And so that was about a month from first line of code to here's a functional useful product that the core team is excited about. So then there was a moment of rolling this out across the company rolling this out across all the space act. Uh and so there was an all hands where we kind of shared the progress that had been made so far. There's this brand new product. 个月的愿景，我们根本到不了后来真正落地的那个位置。所以，从第一行代码到「这是一个核心团队已经很兴奋的、能用且有用的产品」，大约就是一个月。然后有一个时刻，是把它推向全公司，推向整个 SpaceXAI。于是有一场 all-hands，我们分享了到当时为止的进展。这是一款全新的产品。

Roman Ugarte We would love for you to use it. And I think what was most encouraging because at that point we were excited about it. I think we were using it constantly, but it's easy to use the thing that you built and you kind of understand the mechanics and what it's good for. And so this was a real pressure test with reality, like are people actually going to switch from other internal tools, other external tools to use Grockbot as their primary agent surface? Um, and in that first week after that all hands, um, I mean, I can't even tell you just the outcore of of love for Grogbot from people that maybe you wouldn't expect or from groups of the company that maybe you wouldn't expect. Uh, people who, you know, were daily driving Cheshy PT or like a chat interface switching all of their, you know, day-to-day agentic tasks over to Grockbot as like their primary surface for doing work. And so 我们很希望你们来用。最令人鼓舞的是——因为那时我们已经很兴奋了，也一直在用——但用自己做出来的东西很容易，你已经理解它的机制、知道它擅长什么。所以这是一次真正用现实来压测：人们会不会从其他内部工具、其他外部工具切过来，把 Grok Bot 当作他们主要的 agent 界面？而且在那场 all-hands 之后的第一周，我对你说都说不清，那些你可能想不到的人、你可能想不到的公司群体，对 Grok Bot 涌出了多大的喜爱。有些人日常在用 ChatGPT，或者某种 chat 界面，结果把他们日常的 agentic 任务全部切到了 Grok Bot，把它当成做工作的主界面。所以

Roman Ugarte the internal reception was was really extraordinary. um can tell some kind of funny stories from that that week or two period. Um and then once we saw I think 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. Uh and then that led to the the GA launch that we had a few weeks ago. This episode is brought to you by our season's presenting sponsor, Work OS. 内部反响真的非常惊人。那段一两周里，其实还有一些挺好笑的故事。然后一旦我们看到内部反响，就立刻切到：让我们把它准备好交给世界。要把它扩到数百万用户，还有大量工作要做。这才有了几周前的 GA 发布。本集由本季呈现赞助商 WorkOS 带来。

Roman Ugarte What do OpenAI, Anthropic, Cursor, Replet, Sierra, Clay, and hundreds of other winning companies all have in common? They are all powered by work OS. If you're building a product for the enterprise, you've felt the pain of integrating single signon, skim, arbback, audit, logs, and other features required by large companies. Work OS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SAS. OpenAI、Anthropic、Cursor、Replit、Sierra、Clay，以及另外几百家成功公司，有什么共同点？它们都由 WorkOS 提供动力。如果你在为企业做产品，你一定感受过接入 single sign-on、SCIM、RBAC、audit logs，以及大公司要求的其他功能有多痛。WorkOS 把这些成交拦路虎变成可直接接入的 APIs，是一个专为 B2B SaaS 打造的现代 developer platform。

Roman Ugarte Literally every startup that I'm an investor in that starts to expand up market ends up working with Work OS. And that's because they are the best. Whether you are seedstage startup trying to land your first enterprise customer or a unicorn expanding globally, work OS is the fastest path to becoming enterprise ready and unblocking growth. It's essentially Stripe for enterprise features. Visit works.com to get started or just hit up their Slack where they have actual engineers waiting to answer your questions. Work OS allows you to build faster with delightful APIs, comprehensive docs, and a smooth developer experience. Go to works.com to make your app enterprise ready today. Okay, so many questions. One that is really interesting here. So obviously there's anthropic openai. They went from they had this coding agent that they're like, "Holy this is a big opportunity." And then they're like, "Okay, people are using this for knowledge work. Let's build a knowledge 几乎每一个我投资的 startup，一旦开始向上市场扩张，最后都会和 WorkOS 合作。因为它们就是最好的。无论你是 seed 阶段、想拿下第一家企业客户的 startup，还是正在全球扩张的独角兽，WorkOS 都是最快变成 enterprise ready、打通增长的路径。它本质上就是企业功能界的 Stripe。访问 workos.com 开始使用，或者直接去他们的 Slack，那里有真正的工程师在等着回答你的问题。WorkOS 让你用令人愉快的 APIs、完整的文档和顺畅的开发体验，构建得更快。去 workos.com，今天就让你的应用变成 enterprise ready。好，问题很多。其中一个真的很有意思。显然有 Anthropic、OpenAI。它们从 coding agent 出发，觉得「天哪，这是一个巨大的机会」，然后发现人们在用它做 knowledge work，于是开始做 knowledge

Roman Ugarte work component." So there's co-work evolved out of that within the product and then codeex they've invested in let's make this useful for all kinds of things. Interestingly, you guys decided, okay, curs, we're not going to build this into cursor. We're gonna start something fresh. Was that was that just like obvious from the beginning? Okay, this is not going to work inside cursor the product. We need to start fresh. How like controversial was that decision? work 这一块。所以产品里演化出了 Cowork，然后 Codex 也在投入，让它能用于各种各样的事情。有意思的是，你们决定：好，Cursor，我们不把这个做进 Cursor。我们要从头做一个新东西。这从一开始就是显而易见的吗？好，这件事在 Cursor 这个产品里行不通，我们必须从头开始。这个决定当时有多有争议？

主持人 It was not obvious at all. I think you're completely right that that was one of those original decisions that uh 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 in this new thing I think has has contributed a lot to the success but there were a lot of discussions about you know cursor for 这一点都不显而易见。我觉得你完全说对了，那就是那些最初的决定之一，当时我们讨论了很多，我非常高兴我们落到了。现在这个选择。而且正如你说的，它是一款全新的产品，体验的每一个像素都由你控制，你对 knowledge work 会走向哪里有一套一致的愿景，而且全部装在这个新东西里，我认为这很大地贡献了它的成功。但当时也有很多讨论，比如 Cursor。

主持人 example and some of our coding products people use it for non-coding tasks all the time. Um, and you know, these coding agents are really excellent at some of these things, but you run into small paper cuts. Sometimes the product itself is kind of intimidating to nontechnical users. There's a brand association with these things. And so, I think we evaluated that path and I think we saw what maybe some of our competitors have been doing of this is all just one surface. You add new tabs for each new form factor and it feels a little cluttered and I think for users they can feel that that this was not a single consistent uh 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 以及我们的一些 coding 产品，人们其实一直在用它们做非 coding 任务。这些 coding agents 在其中一些事情上确实非常出色，但你会碰到一些小摩擦。有时产品本身对非技术用户有点吓人。这些东西还有品牌联想。所以我们评估过那条路，也看到了也许一些竞争对手在做的事：这全部就是一个界面。每一种新形态就加一个新 tab，感觉有点杂乱。而且我觉得用户能感觉到，这并不是对工作应该如何运转的单一、一致的愿景，而是三个不同的愿景挤在同一块屏幕上，你可以来回跳，但这有点像把组织架构图直接做成产品，用户对此的反应是负面的。所以我们决定，干脆完全从

主持人 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 botnative experience, but it's really important for people to just have like an amazingly simple and amazingly powerful experience. 零开始。看看从那里能走到哪里。也许会有一些非常好的机会，把人们从其他界面带到这种更 bot-native 的体验里，但对人们来说，真正重要的是先拥有一种极其简单、又极其强大的体验。

Roman Ugarte That is a really valuable lesson for people to take away here just that that is might be the solution instead of adding in complicated and existing AI product. So interestingly, Codex went the other direction and and it's like a different path and a different product,but it's interestingly they're like now we're going to make it one thing. So there, you know, there's many ways to make it work and it also feels like the path you take there will kind of lead you but maybe maybe we'll look back and be like that was not maybe the best idea. Something you mentioned that you did that is also really unique is this onboarding of early users. Uh I heard you and your team onboarded two to 300 people manually including me. Uh talk about why you thought that was necessary and what you learned from that 这是一个非常有价值的教训，大家可以带走：那也许才是解决方案，而不是往一个已经很复杂的现有 AI 产品里继续往里加。有意思的是，Codex 走了相反的方向，那是另一条路、另一款产品，。但有意思的是他们现在说：我们要把它做成一个东西。所以做成这件事有很多条路，而且你选的那条路也会把你带向某个方向，也许回头看我们会说，那也许不是最好的主意。你提到你们做的另一件也很独特的事，是对早期用户的 onboarding。我听说你和团队亲手 onboarding 了两三百人，包括我。谈谈你为什么觉得这有必要，以及你从中学到了什么，

Roman Ugarte experience and just like how long that period was of this kind of manual onboarding. I mean, you just learned so much and um the first few onboardings were pretty painful. I'm glad you got a good one, Lenny. Uh 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 uh where we were in that mode and onboarded a couple hundred people. Um and not only did we learn a lot about the product, I think we didn't really know uh I think sometimes with these products there's some group think of ways to use them. 还有这种人工 onboarding 大概持续了多久。我是说，你能学到的东西太多了。最开始几次 onboarding 挺痛苦的。很高兴你赶上了一次好的，Lenny。（笑）但也有一些相当粗糙，我们学到了很多。我觉得核心团队必须在场，必须坐在通话里二十分钟：电脑起不来，或者有人在 onboarding 里完全搞糊涂了。这样你一下通话就会想：这种事绝不能再发生。我们明天就得解决，因为明天我还要 onboarding 下一个人，必须更好。所以大概有两周时间我们处在那种模式，onboarding 了几百人。我们不仅对产品学到了很多，我觉得有时候这类产品里会有一种群体思维，大家都用差不多的方式去用。

Roman Ugarte And I think internally because people inside of SpaceX were just constantly sharing tips and tricks for how to use Grockbot, 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. Is there an example of that? So when we rolled out Grockbot 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 shortorthhand 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 而在内部，因为 SpaceXAI 的人一直在分享使用 Grok Bot 的 tips 和 tricks，一些模式开始出现，我们觉得它们对世界会有用，但我们并不确定，也绝对不想去诱导外面的世界。有例子吗？我们在内部推出 Grok Bot 时，大概有一两周，人们和产品交互的常见模式是：你会有 5 到 10 个 bots，每个 bot 你给不同的范围、不同的领域，它有点像不同工作泳道的速记。然后大概第二周末，我们开始在内部 Slack 里看到有人在推广自己的某个 bot，那个 bot 表现特别突出，他们把自己的主要私人助理，提拔成了自己的首席助理。然后他们。其实大部分时间都和这位首席助理说话，首席助理再把所有这些。

Roman Ugarte tasks to the other bots and would kind of manage the team. And there are some funny screenshots of people like actually telling their uh you know the bot they're promoting that they're promoted and the bot is asking if they get a raise and you know is their token budget higher all of these things. Um, and we kind of took note of that and I think more of the companies started to slightly shift in that direction, but it was not the majority of the company. People use this product in very different ways. And so in some of the onboarding sessions and just from the early access program in general, we really did not want to lead the witness and say, you know, create a chief of staff bot. Here's exactly the way that uh, you know, 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 任务分发给其他 bots，并管理这个团队。还有一些很好笑的截图：人们真的在告诉自己要提拔的那个 bot「你升职了」，那个 bot 会问自己有没有加薪，token budget 会不会更高，诸如此类。我们记下了这一点，公司里更多人也开始稍微往那个方向转，但这并不是公司里的大多数。人们用这款产品的方式非常不同。所以在一些 onboarding 场次里，以及从整个 early access 项目来看，我们真的不想诱导证人，去说：你要创建一个首席助理 bot，这就是那位首席助理管理其他 bots 的方式，然后看 early access 用户会不会？自己走到那里。而我们确实看到，很多人自己走到了。于是我们在产品里有了更明确一点的立场：这感觉是一个正在奏效的模式，是一个我们应该稍微鼓励的模式，但它不应该是一扇只能进不能出的。

Roman Ugarte door. And there were a few other examples of internal thesis that we really wanted to make sure, you know, would bear out in actual external usage without us imposing that in the product. 门。还有另外几个内部假设，我们非常想确认它们会在真实的外部使用中成立，而不是由我们在产品里强加。

主持人 Is there anything else there? Any uh examples come to mind? Yeah, I think another thing we really tried to pay attention to in the early onboardings um was just how much users wanted to see. And I think it is something a bit shocking or just different about Grockbot when you first start using it versus some of the other products that you mentioned. um where a lot of the internal mechanics of how Grockbot 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 know, 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 还有别的吗？有想到什么例子吗？有的，早期 onboarding 里我们很努力关注的另一件事，就是用户到底想看到多少。我觉得 Grok Bot 有一点让人吃惊，或者说和你提到的其他产品第一次用起来就不一样：Grok Bot 内部运转的很多机制并不会展示给用户。原因是，我们认为随着这些模型变聪明，就像你的同事一样，你不会要求他每一秒都汇报他按了哪些按钮、去了哪些网站，我觉得。

主持人 it's too much to ask your bots to do that, too. And I think it's honestly just overwhelming uh and can create more harm than good. And so we moved completely in the other direction of you send a message, you tell your bot to do something, it just starts doing it. It sends you progressive updates as it sees fit. And you just see that like typing indicator in the little green, you know, active uh active um circle kind of Slack like that it's 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 要求你的 bots 那样做也太多了。而且说实话，那只会让人应接不暇，带来的伤害可能大于好处。所以我们完全走到了另一个方向：你发一条消息，告诉 bot 去做某件事，它就开始做。它会在自己觉得合适的时候给你渐进更新。你看到的就是那个正在输入的指示，还有那个小小的绿色、活跃的圆点，有点像 Slack 那样，表示它是活跃的，它正在干活，很快会回来找你。但你看不到内部机制，看不到 tool calls，看不到它在自己电脑上的每一次点击。我们很想采取一个强硬立场：用户不需要看到所有这些机制。所以我们从那里起步。我们也确实收到一些反馈，比如：我很想看到我的 bot 的待办清单，我很想大致看到它怎样排优先级、在做什么。这是很好的反馈。但有用的是听到：

主持人 nobody wanted the like long stream of just text streaming out and chain of thought sequences. So that also gave us more uh confirmation that that was the right direction. the fact that you did two to 300 onboarding calls on a with a small team. I knew that I know the team grew uh 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. Uh do you feel like that's like that's the volume people need to do to figure out what actually needs to happen? Well, one thing to emphasize is the early access group is not necessarily just people that are highly influential taste makers. you know, you're in this category, Lenny, and we certainly wanted to get a lot of your feedback um just from being very close to many other products on the market and just being a 没有人想要那种长长的文字流不断涌出来，以及一串 chain of thought。这让我们更确认，那个方向是对的。你们用一支小团队做了两三百次 onboarding 通话。我知道团队后来变大了，但那是巨大的时间投入，也可以说是对构建的分心。显然它不是分心，显然它是成功的核心部分。你觉得人们需要做到那种体量，才能搞清楚真正该发生什么吗？有一点要强调：early access 群体并不一定只是那些影响力很大的 taste makers。你属于这一类，Lenny，我们当然很想拿到你的很多反馈，因为你非常贴近市场上许多其他产品，而且就是这些东西的

主持人 power user of these things, but we also wanted to get uh early access to kind of more unconventional profiles that we as a company had never really interacted with. So one example is uh there's a coffee shop owner that was a friend of a friend through the company who had heard about Grockbot and you know uh one day somebody on the core team had kind of shown them a demo of the test flight and got very excited and this coffee shop owner ended up being not only an amazingly uh an amazing power user of Grodbot but also a rich source of feedback for us. uh we have a very lively thread with with many many uh bugs that get identified or feature requests and it's a completely different use case of running a small business and so for example if you know the Shopify uh integration was a bit flaky or if it wasn't writing copy uh for products in power user。但我们也想把 early access 给到一些更非常规的画像，那是我们作为公司以前几乎没有接触过的。举个例子，有一位咖啡店老板，是公司里朋友的朋友，听说了 Grok Bot。有一天核心团队的人给他们看了 TestFlight 的 demo，对方非常兴奋。这位咖啡店老板后来不仅成了 Grok Bot 非常出色的 power user，也成了我们非常丰富的反馈来源。我们有一条非常热闹的 thread，里面有非常多被指出的 bugs 和功能请求，而这是一种完全不同的用例：经营一家小生意。所以比如说，如果 Shopify 集成有点不稳，或者它没有按某种特定方式为产品写

主持人 in a particular way we would get really rich feedback on that which is pretty different from the type of feedback we'd get from dog fooding this internally and so I think it was an important exercise for us to check our blind spots and say a this is going to be a very general product that is not just a thing that developers use. In fact, it is likely that this is most powerful for non-developers. We need to understand that group much better. And then B is we absolutely live in this kind of Silicon Valley AI bubble. Uh which I think is is a useful place to be to kind of push the frontier and push the future of 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 uh kind of business customer can interact with AI in a way that's useful. 文案，我们会拿到非常丰富的反馈，这和我们在内部 dogfooding 拿到的反馈很不一样。所以我觉得这对我们是一次重要的练习，用来检查盲点，并说：第一，这将是一款非常通用的产品，不只是 developers 用的东西。事实上，它很可能对非 developers 最有力量。我们需要远远更好地理解那群人。第二，我们绝对活在这种硅谷AI 泡沫里。我觉得待在那里是有用的，可以去推前沿、去推这些产品会怎样演化。但我们需要主动走出去，因为我觉得这样一款产品，有机会真正成为主流用户、主流商业客户与 AI 互动、并真正用得上的方式。

Roman Ugarte 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? 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. Wow. Okay. So, month of building the first thing, three weeks only of iterating and that and then it's been only three weeks since launch. It feels like it's it changed the world in 我们很快回到时间线，好把这件事看清楚。所以从第一行代码到内部 beta 是一个月，那之后发生了什么？从内部 beta 到公开发布大约三周，而录这期的时候，距离公开发布大约又过了三周。哇。好，所以第一个东西做了一个月，迭代只有三周，然后上线才三周。从我的视角看，它感觉像改变了世界。

Roman Ugarte my from my vantage point. So, wow. Okay. What most changed in those I don't know in those three weeks of internal beta, let's say. We unshipped a lot. Um, 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 uh, which was useful. We also were kind of putting pseudo developery like visibility tools into Grockbot instead of having like a separate observability pane uh 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 uh which was useful to debug issues and if you're building the product, you didn't want to go somewhere else to 所以，哇。好。在那三周内部 beta 里，变化最大的是什么？我们 unship 了很多东西。我真希望能给你看看，大概上线前两周时产品长什么样。那时我们意识到，核心团队有很多实验性功能，我们想拿到内部反馈，这是有用的。我们当时也把那种半开发者向的可见性工具塞进了 Grok Bot，而不是给那些东西单独做一个 observability 面板。所以比如说，我们有时确实会把模型的大量内部思考、它会存储的具体 memories，这些东西都暴露出来，这对 debug 问题有用；而且如果你在做这个产品，你也不想再跑到别的地方去。

Roman Ugarte 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 uh 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. Uh so that was one big push uh was unhip a lot of a lot of jank. Um, 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 把那些 context 拉回来。但我们必须非常激进地裁掉：用户在这个界面上绝对需要看到什么，什么不需要。我觉得这里还有更大的空间可以跑，这也是团队现在在专注的事：我们怎样能无情地简化这款产品，把用户不需要主动去想的任何东西都抽象掉。所以那是一个大推动：unship 掉大量粗糙的东西。然后那几周的第二个大推动，是让它就是能用。我觉得人们对 AI 想要的，不是一个有很多下拉菜单、很多花哨功能的东西，而只是：你描述一个对你有意义的任务，它就去做，然后带着完整的工作回来，或者带着一些东西回来让你

Roman Ugarte you to react to and then steer it in its kind of next cycle. Um, 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 uh when you know 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 your ability to make progress on that task. And so those few weeks we collected a really rich set of what are tasks that people actually are giving bot how can we quantify these things and how can we see week over week that across those categories of tasks that were hill climbing on very important dimensions to making that just work behind the scenes. 反应，再在下一轮循环里去引导它。所以要真正兑现这个承诺，其实不是很多功能产品路线图那种东西，而更像是在后端对五个非常重要的问题做 hill climbing。很多用户不会直接体验到这些，但当 bot 出去做事却点不准那个按钮，或者你的 bot出去做事却登不进一个网站，你的任务完全卡住、没法推进时，你完全能感觉到。所以那几周我们收集了一套非常丰富的材料：人们实际在给 bot 什么任务，我们怎样量化这些事，以及怎样按周看到，在那些任务类别上，我们正在对「让它在幕后就是能用」非常重要的维度做 hill climbing。

主持人 Is there an example one of those uh hills you were climbing that was kind of a technical breakthrough or technical challenge you overcame that really helped it just work? Yeah, one example was from rolling out Grockbot. One group inside of the company that was actually incredibly botpilled, so to speak, um was our go to market team was sales. And there are a bunch of tools that sales uses um that do not have wellsupported MCPs or APIs. And I think that's a lot 有没有？一个例子，那些你们在爬的山里，哪一座是某种技术突破，或者你们克服的技术。挑战，真正帮它做到了就是能用？有的，一个例子来自推出 Grok Bot。公司内部有一个群体其实非常 bot-pilled，可以说是我们的 go-to-market 团队，也就是销售。销售用的有一堆工具，并没有良好支持的 MCP 或 APIs。我觉得这正是

主持人 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 you know probably a list of of 10 or 20 of them of places where for whatever reason you know the mouse would just not have fine enough control to click on exactly that part of the Salesforce dashboard or something like that um that we would have to take back to the the core team working on really the infrastructure to say here's a very concrete case of where uh the agent not having this visibility into the browser or this visibility into the pixels on the screen is making it 让 bot 对这个群体产生前后巨大差别的原因：这些事他们没法可靠地交给另一款 AI 工具。过程中某个环节总会卡住。然后 bot 感觉像他们有了一个助理，或者说像他们给自己的私人团队招进了一个人。他们给它一台笔记本电脑，它就能跑起来。所以有一堆小事，大概有10 个或 20 个这样的地方：不管什么原因，鼠标就是没有足够精细的控制，点不到 Salesforce dashboard 上正好那一块，诸如此类。我们得把这些带回给真正在做基础设施的核心团队，说：这是一个非常具体的案例，agent 没有对浏览器的这种可见性，或没有对屏幕上像素的这种可见性，正在让这件事。

主持人 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 uh that was kind of behind the scenes kind of infrastructury and then the next day you would just get this outpour of you know 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 uh basically uh improvements seems like a big unlock. Uh I heard also the um I had Adam Ward on the podcast uh who's head of recruiting, head of hiring, basically head of talent. Uh I heard his team was like one of the top users of of uh Grockbot. Yes, the recruiting team um gave us a lot of great feedback. Anytime the product, especially in the early 变得不可能完成。而这比看着仪表盘上一个数字慢慢往上爬，要具体得多。它更像是新的工作块被解锁了，你会立刻感觉到反馈：你上线了一个幕后的、偏基础设施的改进，第二天就会收到销售团队涌来的喜爱和感谢，因为这个过去七天一直失败的 workflow 终于。能用了。这就是不断去找下一批要解锁的任务，然后把它们解决掉。所以 computer use 方面的改进，看起来是一个很大的解锁。我还听说——我请过 Adam Ward 上播客，他是 recruiting 负责人、hiring 负责人，基本上是人才负责人——我听说他的团队是 Grok Bot 使用最多的团队之一。是的，recruiting 团队给了我们很多很好的反馈。只要产品出问题，尤其是早期

主持人 days, if there was a little bug, we'd get a get a ping from um some folks on the recruiting team. Um yeah, I think the main use cases for recruiting that were particularly interesting uh was first it was incredibly valuable as a sourcing tool and I think one thing Adam talked about on the podcast with you uh and it's a big part of our hiring philosophy internally is be looking for a job being on the market is not a precondition for us trying to hire you. And in a lot of ways, um, you know, the best way to hire is really just look at the biggest problems at the company that needs someone to 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 那些天，哪怕一个小 bug，recruiting 团队的人就会 ping 我们。是的，我觉得 recruiting 特别有意思的主要用例，首先是它作为 sourcing 工具极其有价值。Adam 在和你那期播客里也谈到过，这也是我们内部 hiring 哲学的很大一部分：正在找工作、人在市场上，并不是我们尝试招你的前提。（笑）在很多方面，最好的招人方式，其实就是看公司里最大的、需要有人来拥有或带到下一层的问题。从全世界所有人里找出谁最合适，然后毫不留情地去追他们、说服他们加入。这从公司一开始就是很大一部分哲学。

主持人 the company. And so if that's your mindset, really the best recruiting work stream is not or workflows to automate are not, you know, here are a bunch of resumes, read through them, help sort them. The most useful thing is here's an entire universe of potential people. Help match that to this very concrete business problem or this very concrete role that we're recruiting for and help me get in touch with them. Help me get coffee with them. Let's just throw everything at it. And so there have been some cases of um really kind of uh unexpected ways of finding top talent that is is beyond even just you know looking on LinkedIn and trying to find uh 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 所以如果这是你的心态，真正最该自动化的 recruiting 工作流，并不是：这里有一堆简历，帮我读一遍、帮我筛选。最有用的是：这里是一整个人才宇宙。帮我把它匹配到这个非常具体的业务问题，或我们正在招的这个非常具体的角色，并帮我和他们取得联系。帮我和他们约咖啡。我们就把一切都砸上去。所以出现过一些非常出人意料的发现顶尖人才的方式，甚至超出了只是在 LinkedIn 上找有意思的人。比如：这篇论文的合著者是谁，而 PDF 在 Google Scholar 上不存在，只存在于这个会议网站。我要你每天早上去这个

主持人 conference website, download the PDFs. there are any new ones. You should find every new name that we've not yet tracked. You should add that name to a spreadsheet. You should do research. You should look at everybody at SpaceX, see if there's anyone directly connected. If so, you should send them a Slack message asking for an introduction. Like, it's those types of always on sourcing um 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. 会议网站，下载 PDF。如果有新的，你应该找出每一个我们还没追踪过的新名字。你应该把那个名字加进 spreadsheet。你应该做 research。你应该看遍 SpaceXAI 的每一个人，看有没有人直接认识。如果有，你应该给他们发一条 Slack 消息，请他们介绍。就是这类始终在线的 sourcing 用例，过去极其靠人工，而现在是那种AI 具有超能力的事情。我们的团队可以专注于拿下优秀候选人、和优秀候选人谈话，而不是去拉这些巨大的名单。

Roman Ugarte Wow, that is such a cool example. Uh, 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 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 uh team strategy for finding the best people and just turn it into a bot, holy moly, democratizing uh hiring. I want to come back to a few things. Okay. So, one is you made this point about unshipping. Such a 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 哇，这个例子太酷了。首先，马上就会有人把你刚才说的这段 transcript 丢进一个 bot，做出他们自己的版本，这很好。另一方面，我觉得你们可以把这个 bot 的模板卖十亿美元。如果我们基本上能把 Adam 团队找最优秀的人的策略，直接变成一个 bot，天哪，这就是把 hiring 民主化。我想回到几件事。好。第一件是你谈到的 unshipping。这是一个非常重要、我觉得人们容易忽略的点，因为 AI 不擅长告诉你该拿掉什么。它非常擅长说：好，这里还有更多想法、更多东西。而这件事在这档

Roman Ugarte 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? 播客里出现过很多次：那是一个很大的机会。那是人类继续非常重要、非常有价值的一大块空间：知道什么不该 ship、什么该砍、什么不该做。所以听到从原型到上线的内部演化里，很大一部分就是决定好，我们需要砍掉一堆东西，这非常有意思。还有要补充的吗？

主持人 Yeah. So, one thing we talk about internally is for anything that we're working on for Grockbot, what is the launch post? Like, what is the thing that we would actually tell users? And if it's not tweet, I imagine 有。我们内部会谈的一件事是对 Grok Bot 上我们在做的任何事：发布帖是什么？也就是我们真正会告诉用户的那句话是什么？如果那不是一条 tweet，我猜

Roman Ugarte launch tweet. And if it's not compelling, maybe we shouldn't be working on it. um if if it's not something that users will directly feel in the product and to take that even one step further um I think there is this old school software tendency to say things like Grockbot now has and when you think of completing that sentence it would be like a new button to press or it' be a new drop down or it' be a new integration that you can press plus and add and instead to reframe it as Grockbot can now which is is I a much more human way of kind of describing these capabilities. And I think it's 是发布 tweet。如果它不够打动人，也许我们就不该做它。如果它不是用户会在产品里直接感觉到的东西。再往前走一步，我觉得还有这种老派软件倾向，会说「Grok Bot 现在有了……」，你想把这句话补完，就会是一个新按钮、一个新下拉菜单，或一个你可以按加号加上的新集成。而我们要把它改写成「Grok Bot 现在能……」，这是一种更人性的方式来描述这些能力。而且我觉得它

Roman Ugarte forced us to think more in the frame of what are tools and and what are capabilities that we can give Grockbot, 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 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. Uh and so I think in the context of unshipping there have been a lot of Grockbot now has things uh 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 迫使我们更多地在这个框架里思考：我们能给 Grok Bot 什么工具、什么能力，而不是我们能往产品里加什么新东西。往产品里加东西不是目标。那不是推动这款产品向前、让它对更多人更有用的东西。让你的 bots 在幕后可靠地为你做真正有影响力的工作，而且就是能用，并给它们做到这一点的能力。那才是用户真正在乎的。所以在 unshipping 的语境里，有很多「Grok Bot 现在有了」的东西，我们后来意识到它们其实只是不需要像素的能力。能杀掉多少像素就杀掉多少。那些可以只是你的 bot 在幕后替你操作的东西，你不需要直接控制。我觉得一个例子是，我们很多竞争对手

Roman Ugarte you set up automations or routines is you go into a sidebar, you press plus, you select, you know, what the trigger event is. Uh you then select uh you know 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 for many things. We certainly have seen this in in the coding realm. And so I think what Grockbot 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 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. So, I tweeted about how much I love Grockbot when it launched and a lot of people replied. They're like, "Wait, can't you just do all this with codecs and co-work and you can technically 设置 automations 或 routines 的方式：你走进侧边栏，按加号，选择触发事件是什么，然后再选择之后该采取什么动作。你也许会用自然语言描述，但这非常笨拙，意味着人们不会为很多事情去设置很多 automations。我们在 coding 领域肯定见过这一点。所以我觉得 Grok Bot 对此的回应是：你应该只用自然语言定义 automations。你应该告诉你的 bot：请每天早上 8 点提醒我。然后它就该去做。你永远、永远不该看到那个创建 automation 的界面。所以这就是我们做的决定。现在平台上 99% 的 automations 都是这样建出来的。我觉得还有很多其他地方可以这样做。所以上线时我 tweet 了自己有多爱 Grok Bot，很多人回复说：等等，这些事你用 Codex 和 Cowork 不也能做吗？从技术上讲

Roman Ugarte everything as far as I know you can do with Grockbot 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 Grockbot so successful?" 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 Grockbot 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 据我所知，你能用 Grok Bot 做的一切，你也能用其他基础模型、那些 coding assistants 来做。所以我直接问你这个大问题：你觉得你们做了什么如此不同的事，让 Grok Bot 这么成功？我觉得是两个早期决定，当时完全不觉得显而易见，但事后看，我认为它们对 Grok Bot 能对人奏效至关重要。第一是：你永远不该去想 local 和 cloud，以及这些 workflows 跑在哪里。我的电脑必须醒着吗？如果我从手机上启动，它需要拴回家里的电脑吗？人们现在在试图理解这个

Roman Ugarte 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 uh I think haven't made that same decision and I think it it has a bunch of paper cuts as a result of it that users feel every day. I think the second decision was kind of to take that one step further of not only should this be an agent loop that kind of runs in the cloud and you can interact with in various ways. It's actually really runtime 住在哪里时，有太多粗糙的地方。我们很早就做了一个决定：这一切就该全部在 cloud 里。如果它在 cloud 里，而且是一个持久的同事、有自己的电脑，它能做自己的工作。你在任何地方和它交互，它都有同样的 state。这打开了很多非常好的机会：给你的 bot 发短信，从手机上启动它。未来，你应该能从任何地方给你的 bot 打电话，它应该能做真正的工作。这就像它是一个独立的实体而且它和你的设备分开存在。我觉得那是一个非常重要的决定，当前的产品我认为还没有做出同样的决定，因此有一堆小摩擦，用户每天都能感觉到。第二个决定是再往前走一步：这不仅应该是一个在 cloud 里跑、你可以用各种方式和它交互的 agent loop。真正重要的是

Roman Ugarte 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 wellsupported 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. Uh, 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. Uh, you don't have your own laptop. You're going to sit next to me. we're going to share 这些 bots 要有自己的电脑。一部分原因是我前面说的：有一堆任务并没有良好支持的 MCP 和 APIs。我们作为人类，并不是通过 MCP 和 APIs 做工作的。我们用电脑，我们点击像素，我们在输入框里打字。你的 bot 拥有这些基线能力也非常重要。但再往前走一步，我觉得我们正处在一个非常奇怪的时刻，回头看我们会说：我很惊讶很多人当时是这样和 AI 一起工作的——你在 onboarding 这些超级聪明的新同事、这些 AI bots，却让它们和你共用同一台电脑。这很疯狂。就像你在给团队招人，你说：今天是你第一天，我来给你 onboarding。你没有自己的笔记本电脑。你要坐在我旁边。我们要共用

Roman Ugarte 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 um you know a way to onboard them that's somewhat similar. And we've tried to push the product in that direction. 这台笔记本电脑，永远如此，还不断互相绊脚。你能拿到我的 credentials，我也能拿到你的 credentials。人们不这样做事，是有充分理由的。我觉得 bots 和未来这类 AI 同事，也需要一种多少类似的 onboarding 方式。我们一直在把产品往那个方向推。

主持人 That is so funny. Um 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. 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 Grockbot we had attempted or we had built in other 这太好笑了。（笑）你觉得其他公司为什么没这么做？我的猜测是，他们是在现有的 coding assistant 平台和方法上往上建，而这是一个相当大的转变。我觉得很大一部分归结于从零开始，以及那有多解放。我们自己也感受到了：Grok Bot 里的很多 primitives，我们曾经用其他

主持人 ways. Um you know cloud infrastructure we built for coding agents. um 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 uh 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 I think for good reason I think these are primitives that had already been getting attention 方式尝试过、建造过。比如我们为 coding agents 建过 cloud 基础设施。比如你可以给 agents 起名字、把它们当作独立实体来交谈。这也是我们在 developers 那边看到的模式，把特定的、有名字的 agents 带进 Slack。但我们没有试图把这些概念改装进某个新界面，或改装进现有界面——我觉得对很多公司来说那会是很强的默认选择——我们决定从零开始。我们决定把这些事真正做对：第一是面向 general knowledge work，那是新的受众；第二是面向我们现在所处的这个时点，模型已经非常有能力，如果你给它们正确的工具和正确的基础设施，它们能做很多。但这些想法里很多并不是我们这边的天才灵光。我觉得这是有道理的：这些 primitives 已经在获得关注

主持人 and product market fit by other products you know the open clause of the world um 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. 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. Uh, and I think a lot of that is what allowed the product to just work and click for so many people. So what I'm hearing here is the keys to success of what made this break out. A cloudbased 和 product-market fit，来自世界上那些 OpenClaw 一类的产品。我觉得我们从中拿了很多灵感，并试图把它产品化成一个更紧的界面，需要更少的 setup，也对更多人更可及。所以我觉得我们的竞争对手、以及其他在试图解决这类问题的工具，大家都看到了同一个机会。我们都看到了大量来自市场的反馈，但如果你困在现有范式里，如果你在那个现有范式里有很多沉没成本，要从零做一个新东西是非常痛苦的。我觉得正是这些，让这款产品对这么多人就是能用、一下就对上了。所以我听到的是，让这件事破圈的成功关键。一个基于 cloud 的

主持人 computer for every uh bot instead of locally. Uh a name 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 the 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. Um you mentioned OpenClaw obviously this is inspired by that which to me when I first used open claw I'm like holy this is the future how could we not have this and then the Hermes came out and everyone's been trying to build the open cloud 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 电脑给每一个 bot，而不是跑在本地。一个名字，也就是特定的 bot。顺便说，我们现在都在从 agents 转向 bots。干得好。感觉是你们把它推过了那个临界点。好，我们现在都是 bots 了。所以按任务、按用例一个 bot，这和一条 thread 对话、或一次性的 job 非常不同。然后感觉「就是能用」是核心的一部分，你也谈到了花了多久才走到「好，它现在真的很好用」那个位置。你提到了 OpenClaw，显然这从中受到了启发。我第一次用 OpenClaw 时就在想：天哪，这就是未来，我们怎么能没有这个。然后 Hermes 出来了，所有人都在试图做出那个对所有人都很容易用的 OpenClaw。你能再多说说 OpenClaw 和那个故事，怎样影响了你们思考

主持人 it? 这件事的方式吗？

Roman Ugarte 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, um it can get a lot of the way there in a lot of the places where people think AI is is dumb or uh maybe not as impactful um 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, you know, really kind of forced that question for many people. 可以。我觉得 OpenClaw 做对了两件大事。我们看到市场对 OpenClaw 的反应，自己也在用这款产品时，觉得非常兴奋。第一件是：模型真的很聪明，而且会继续更聪明。但即使在当前能力水平，如果你能给你的 bot 访问你用来做工作的那些工具，它就能在很多地方走完很大一段路——那些人们觉得 AI 很笨、或者没有承诺中那么有影响力的地方。我觉得其中很多，下游原因只是它被用错了方式。所以如果你给它访问大得多的一组东西，如果它能访问自己的电脑，你能走多远？我觉得 OpenClaw 真正把这个问题推到了很多人面前。

Roman Ugarte And then I think the second way open claw changed the mental model of of AI uh 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 Grockbot 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 然后我觉得 OpenClaw 改变 AI 心智模型的第二种方式，是真正把这些东西更多地看作同事、队友和人，更人格化一些，它是一个能访问你的生活、并能把你再往前延伸的帮手实体。所以我们拿了。其中很多，而我觉得 Grok Bot。也许往前延伸的是：第一，它必须非常容易 setup。那种黑客式的、家里挂着 VPN 加一台 Mac Mini 的搞法，显然扩不到数百万用户，显然也不会是企业利用这项技术的重要方式。所以我们非常想带着这一点去做一款出色的产品。第二，我觉得有很多

Roman Ugarte 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. Um, how can we make a Grockbot 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, you know, it's not incumbent on them to always be on the on the cutting edge of AI. And so that's really where we tried to to innovate. And I think there's still more room to go there. 地方、很多毛边要打磨掉，做出令人愉快的产品体验，让这些东西就是能用，并试图去掉 AI 的 power users 非常熟悉的一些抽象，比如 skills。我们怎样能让 Grok Bot 用户甚至不必知道 skill 是什么？他们永远不该去打一条 slash command。这些东西应该在后台被创建，作为 bots 能访问的有用 primitive，但对用户来说，你并不需要他们永远站在 AI 的最前沿。所以那才是我们真正试图去创新的地方。我觉得那里还有更多空间。

主持人 Uh, as you say that, I have my Mac Mini with my formerly alive OpenClaw on there. And, uh, that was an era and, uh, it's so awesome the work that it has inspired. I know it continues. I know there's still a lot of value to open cloud, 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 open claws. She's shut them all down and switched to Frogbot. That's a huge like it sounds funny, but that's actually a huge uh milestone of just how much things have shifted. Um, what's kind of the the vision for Grockbot? What's like where does this 你说到这，我这边就有一台 Mac Mini，上面曾经活着我的 OpenClaw。那是一个时代，它激发出的工作太棒了。我知道它还在继续。我知道 OpenClaw 仍然有很多价值。但当我看到 Claire Vo——她一直是 OpenClaw 最大的倡导者，它已经成了她生活、带孩子、做所有工作的核心部分——她刚刚把所有 OpenClaw 都切走了。她把它们全部关掉，切到了 Grok Bot。这听起来好笑，但这其实是一个巨大的里程碑，说明事情已经偏移了多少。Grok Bot 的愿景大概是什么？这会走向

主持人 go? What does this look like in the future? What's like the ideal platonic version of Grockbot? The ultimate vision of Grockbot 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 uh in building this is as we kind of get closer to this teammate future, how can we in every product decision we make think about this less from the perspective of a SAS product and more from the perspective of we're trying to 哪里？未来会长什么样？Grok Bot 理想的、柏拉图式的版本是什么？Grok Bot 的终极愿景其实非常简单：你应该有一支 AI bots 团队，帮你做工作，也帮你处理生活。而且它应该真的感觉像一支团队。应该真的感觉像自主的队友在帮你。你可以在各种方面引导他们。你不必微观管理他们。他们能访问做出出色、有雄心的工作所需的工具。我们在产品侧真正当作北极星的一件事是：随着我们更接近这种队友的未来，我们怎样能在每一个产品决策里，更少从 SaaS 产品的视角去想，而更多从我们在试图

主持人 build useful AI teammates. And so there have been a bunch of examples where we kind of have to push ourselves to be more like colleague pill in a way. We sometimes use that term where we're having a product debate about something. There are good arguments on one side. There are good arguments on another side. Both paths feel sensible. Like in product land, this maybe doesn't feel uh like there's a clear-cut answer. And then you zoom out a little bit and you remove yourself from the, you know, tech companiness of it all and you start thinking, how would a human do this? Like what would you want from your teammate in this exact situation? And oftentimes the answer is really clarifying and pretty unanimous. There's oftentimes not a lot of disagreement among the room of like how a human teammate you would prefer to work with in a certain way. And then once that answer is there, well then we just need to build it. And there are product 做出有用的 AI 队友这个视角去想。所以有一堆例子，我们得把自己往更 colleague-pilled 的方向推。我们有时会用这个词：我们在对某件事做产品辩论，一边有好论点，另一边也有好论点，两条路都感觉合理。在产品世界里，这也许感觉没有斩钉截铁的答案。然后你稍微拉远一点，你把自己从整件事的科技公司味里抽出来，开始想：一个人类会怎么做？在这个确切情境里，你希望从队友那里得到什么？很多时候答案非常澄清，也相当一致。房间里往往不会对「你更希望人类队友以某种方式工作」有很多分歧。一旦那个答案在了，那我们只需要把它做出来。而这会有产品上的

主持人 implications, there are model implications, there's a lot of things that need to go right to actually deliver on that experience. But in some ways it's not rocket science. Doesn't require you being a genius. you just need to ask the question of what would you want from a human teammate and can we push AI to behave in a similar way and so to give some examples of that I mean we've been thinking about what the right voice experience with uh these bots should be and I think in the context of a human for example we have a really good analog of a lot of times I'm slacking back and forth with a teammate we're sharing context and a lot of times it's just much simpler to get on a fiveminute huddle with them and just press huddle talk back and forth I share my screen. I show exactly what's on my mind. They share their screen. We hop off and then we continue async from there. And that's not really an experience that any AI product has gotten right right now. And it is deeply integral to the way that I think humans collaborate. And so we want to build 含义，有模型上的含义，有很多事情需要做对，才能真正兑现那种体验。但从某些方面说，这不是火箭科学。不需要你是天才。你只需要问：你希望从人类队友那里得到什么，我们能否把 AI 推向以类似方式行事。举一些例子：我们一直在想，和这些 bots 正确的语音体验应该是什么。我觉得在人类的语境里，我们有一个很好的类比：很多时候我和队友在 Slack 上来回聊、共享 context，很多时候更简单的是和他们开一个五分钟的 huddle，按一下 huddle，来回说。我分享屏幕，正好把我脑子里的东西展示出来。他们也分享屏幕。我们下线，然后从那里继续异步。而这并不是任何 AI 产品现在已经做对的体验。它深深嵌在我认为人类协作的方式里。所以我们想做

主持人 something like that. And there are a bunch of other examples of these like very clear patterns that just work uh that I think you should also feel when working with AI. 那样的东西。还有一堆其他例子，都是非常清楚、就是能用的模式，我觉得你和 AI 工作时也应该感觉到。

Roman Ugarte I love this term colleague build. uh such and it's come up so many times over the course of this chat already how that is uh kind of a throughine to making these decisions for example the computer example you gave is so good obviously people would have their own computer the naming piece is also a very important part of that a big question on my mind in the space and I'm so curious to get your take is the separation between work and personal do you think people will have two different assistants a work and a personal or do you think it'll be one 我喜欢 colleague-pilled 这个词。它在这次对话里已经出现了这么多次，它是做这些决策的一条贯穿线。比如说你给的电脑那个例子就非常好，显然人们会有自己的电脑；命名这一块也非常重要的一部分。我脑子里这个领域有一个大问题，我非常好奇你的看法：工作和私人之间的分离。你觉得人们会有两个不同的助理，一个工作、一个私人，还是会是一个？

主持人 when people think about a work product versus a consumer product. I think there's just a lot of baggage that comes from the last decade or two of horrible B2B software. Um, that leads to people seeing a product that is very simple in some ways. Chat GBT was like this. I think Grockbot 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, 当人们想到工作产品和消费产品时，我觉得有很多包袱来自。过去一二十年糟糕的 B2B 软件。这会让人们看到一款在某些方面非常简单的产品——ChatGPT 就是这样，我觉得 Grok Bot 也有很多这样的属性——就假定它不是工作产品，或假定它不是 power tool。而当你想到上一代的 power tool 时，

主持人 I in my head picture something a bit like Photoshop for example, where there are all of these different dials to turn very precisely. You know, the user of the tool is this kind of um you know, ultimate um cockpit flyer who knows exactly what all the knobs do and can like use them perfectly. And I think power tools of the future will actually be very different from that. Uh where it is mostly just intent being expressed and good steering on the part of the human and these AI tools abstract away all of the knobs. you should never see them unless you need to directly manipulate it which might happen and there should be a great affordance for that but ultimately it really is just working with a teammate and so the interface for that is quite conversational and so in a lot of ways Grockbot when you look at it like when I 我脑子里会想到有点像 Photoshop 那样的东西：有各种各样的旋钮要非常精确地拧。工具的用户是那种终极驾驶舱飞行员，确切知道所有旋钮做什么，并能完美地使用它们。而我觉得未来的 power tools 实际上会和那非常不同。大部分只是意图被表达出来，以及人类这边良好的引导，这些 AI 工具把所有旋钮都抽象掉。你永远不该看到它们，除非你需要直接操作——那也可能发生，而且应该有很好的 affordance——但最终它真的就是在和一位队友工作，所以那个界面相当对话化。所以在很多方面，Grok Bot 当你看着它，就像我

主持人 walk by someone's desk and I see Grockbot up on their computer for me for a split second I'm like oh are they on like a messaging app and it's like no they're you know this is actually the primary tool that they're using to do much of their work and so I think to question of are you going to have a different set of bots for your personal life and a different set of bots for your work life. Um I do think there will be a separation for many people. They want a separation between personal and and work life and I think that's I think that's great. I think that's important and I think there are a lot of common sense reasons why those things should be separate even from the perspective of of an enterprise. But I think our goal and the thing we're trying to build towards is Grockbot 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 Grockbot and focus on the higher leverage things. And then it should similarly be the way that you delegate a 走过某人的桌子，看到他们电脑上开着 Grok Bot，有一瞬间我会想：哦，他们是在用即时通讯应用吗？然后发现不是，这其实是他们用来做大部分工作的主工具。所以回到那个问题：你会不会有一套 bots 给私人生活，另一套 bots 给工作生活。我觉得对很多人会有分离。他们想要私人和工作生活之间的分离，我觉得那很好。我觉得那很重要。即使从企业的视角，也有很多常识理由说明这些事情应该分开。但我们的目标、我们在朝着去建的东西是：Grok Bot 应该成为你日常工作中很大一部分事情的方式。你应该能把其中很多委托给 Grok Bot，去专注更高杠杆的事。然后它同样应该成为你委托

主持人 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. 私人生活里很多低杠杆部分的方式。而这两件事其实并不是不同的问题集。在很多方面，产品形态和解决问题的方式几乎是一样的。所以我的直觉是，一款产品会是这两件事最好的形态。而这正是我们想做的。

Roman Ugarte Bam. That's a big TAM right there. Uh I love I love to hear it. Makes so much sense. Obviously the question is how do you avoid crosscontamination, you know, personal stuff somehow uh infiltrating exfiltrating stuff from work. Uh but feels like that's kind of okay. So what I'm hearing is that's the direction. The question is just how to do that and make people feel super safe. have kind of like the sock tube stuff in place and also just feel really fun. This episode is brought to you by Mercury. Radically different banking now with spend. I've been a Mercury customer for so many years now. I switched all my business 砰。那可是一个很大的 TAM。我很爱听这个。非常说得通。显然问题是怎样避免交叉污染，私人的东西不知怎么渗进去、又从工作里渗出来。但感觉那是可以解决的。所以我听到的是那就是方向。问题只是怎样做到，并让人感觉超级安全，把 SOC 2 这类东西就位，同时也感觉真的很好玩。本集由 Mercury 带来。彻底不同的 banking，现在有了 Spend。我做 Mercury 客户已经很多年了。我把所有生意上的

Roman Ugarte banking to Mercury and honestly I could not be happier. It's what online banking feels like when it's built by product people, not by bankers. And now with spend, you can give your team individual cards, set spending limits per person or per team, and have expense receipts automatically pulled in from Gmail or over text. You can even give your AI agents their own cards with their own limits and policies. Most founders start out the same way, one card used by everybody at the company. It works until it stops working. Someone goes over, a receipt disappears, you spend two days trying to figure out who spent what and why. Spend is expense management built directly into Mercury. All your team's cards, budgets, and reimbursements. All live in the same place as your business thinking. No chasing, no manual reviews, no end of month scramble. The result is a team that can move fast and a founder who is no longer the bottleneck. Learn banking 都切到了 Mercury，说实话再高兴不过。这就是由产品人而不是银行家做出来的线上 banking 该有的感觉。现在有了 Spend，你可以给团队每人一张卡，按人或按团队设置支出限额，费用收据会自动从 Gmail 或短信里拉进来。你甚至可以给你的 AI agents 它们自己的卡，带它们自己的限额和策略。大多数创始人起步都一样：一张卡给公司里所有人用。它能用，直到它不能用。有人超支了，一张收据消失了，你花两天去搞清楚谁花了什么、为什么。Spend 是直接做进 Mercury 的费用管理。团队所有的卡、预算和报销，都和你的业务账户活在同一个地方。不用追，不用手工审核，不用月底手忙脚乱。结果是团队能跑得快，创始人不再是瓶颈。了解更多

Roman Ugarte more and get signed up at mercury.com. Mercury is a fintech company, not an FDIC insured bank. Banking services provided to Choice Financial Group and column NA members FDIC. The IO card is issued by Patriot Bank and a member FDIC pursuant to a license from Mastercard International Incorporated. Let me ask a couple technical questions. Uh on the computer side, how how do how what's the simplest way to think about what you get as a part of your Grobot account? Is it like a VM that is running in the cloud with multiple login? Is it like a separate VM instance per bot? How do we understand that as much as you could share? Mhm. Yeah. I think to go back to the teammate frame of the product, um to kind of extend the analogy even further, if we were on a team together, you and me, um you know, 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 并在 mercury.com 注册。Mercury 是一家 fintech 公司，不是 FDIC 承保的银行。银行服务由 Choice Financial Group 和 Column NA 提供，它们是 FDIC 成员。该卡由 Patriot Bank 发行，该行是 FDIC 成员，依据 Mastercard International Incorporated 的许可。让我问几个技术问题。在电脑这一侧，作为 Grok Bot 账户的一部分，你得到的东西，最简单该怎么理解？它像是一台在 cloud 里跑的 VM，带多个登录？还是每个 bot 一个单独的 VM instance？在你能分享的范围内，我们该怎么理解？嗯。是的。回到产品的队友框架，把这个类比再延伸一点：如果我们在同一个团队，你和我，我觉得你必须手动接管我的电脑、开始点击东西、说你

Roman Ugarte doing this wrong, you should go here instead and type in manually. Hopefully is pretty close to zero. Hopefully that is not something uh you have to really do with 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. 这样做错了、你应该去这里、然后手动输入的次数，希望接近于零。希望那不是你对同事或队友真正必须做的事。同样，我觉得现在 computer use 已经不错，而且正在好得多。在很短的时间内，我觉得电脑这个概念会对用户完全抽象掉。你永远不该点进一台远程虚拟机。

Roman Ugarte You should never have to take control. Uh you know, if something if there's like a wasteful path and you have to kind of steer it into the correct path. Um, so in the medium term, I think the computer concept will be an important concept for users to have, but will not actually be something that they're interacting with. So I think the right way of thinking about Grockbot is it's a team of bots. It's a team of agents that are 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. Uh I think there are a lot of problems with that. I find myself copying and pasting between chats all the time. Um 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 uh 你永远不该必须接管。如果有一条浪费的路径，你必须把它引导到正确的路径。所以在中期，我觉得电脑这个概念对用户来说会是一个重要概念，但不会是他们真正在交互的东西。所以我认为理解 Grok Bot 的正确方式是：它是一支 bots 团队。它是一支为你做事的 agents 团队。至于它们能访问什么，它们能访问和你过去交互的很长一套 memory。所以我觉得当前有一种范式：你为每一个离散的工作单元新建一个 chat。我觉得那有很多问题。我发现自己总是在 chats 之间复制粘贴。我觉得那不是给工作分类分组的好方式。相反，就像在一个团队里，你有很好的方式去分组

Roman Ugarte 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 longived 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. uh at this meetup that I went to uh Shub who's on the I think grow to market team uh 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 Grockbot within Grockbot like the bot can run its own Grock bots and I know he was using it for testing and watching regressions and things like that but that's just like a mind 工作类别，也就是角色。你应该有角色，也就是你做的不同工作泳道，它应该向你学习，并随时间变得更聪明。所以我觉得非常关键的一点是：这些是长寿命的 agents。它们不是一次性的单个 session，这些 agents 会随时间变得更聪明。第二是，那些 agents 能访问你期望人类同事拥有的所有工具，也就是 APIs、MCPs。那很好，然后还有对它自己电脑的访问，它可以像你会做的那样自由操作。在我去的那场 meetup 上，Shub——我想是 go-to-market 团队的——演示了一件让所有人脑子炸开的事：因为每个 agent 里都有一台电脑，你可以在那台电脑上跑很多不同的东西。他在 Grok Bot 里跑 Grok Bot，也就是 bot 可以跑它自己的 Grok Bots。我知道他用它来做 testing、看 regressions 之类的，但那就是一个让思维

Roman Ugarte expanding idea and I'm curious how many levels you can go before the universe collapses on itself I do that one too. That one's actually a very useful thing to do is you download Grockbot for one of your bots. Mine is like a QA tester bot. Uh and that way if there's ever bug report or if we're kind of testing out a new a new build, for example, of the desktop app, I can just say, "Hey, here are 10 workflows that we need to make sure are getting better release after release. I want you to test it. I want you to write it to this notion document that has like an extensive list of all of the past tests that we've done of past client versions and compare them. And so I think once you start breaking out of this is AI chat with a set of connections which is I think where most people are conceptually now instead to this is a colleague with a computer and anything I would ask a colleague to do on a computer I can ask Arpot to do. It just 扩展开的想法。我很好奇能叠多少层，宇宙才会塌缩。我也会做那个。那其实是一件非常有用的事：你给自己的某个 bot 下载 Grok Bot。我的那个像是一个 QA tester bot。这样如果有 bug report，或者我们在测试一个新 build，比如说 desktop app 的新 build，我就可以说：嘿，这里有 10 个 workflows，我们需要确保它们变得更好，一个版本接一个版本。我要你去测。我要你写进这份 Notion 文档，里面有我们过去对各个 client 版本做过的所有测试的详尽清单，并做比较。所以我觉得，一旦你跳出「这是带了一组 connections 的 AI chat」——我觉得大多数人概念上现在还在那里——转而变成「这是一位带着电脑的同事，任何我会让同事在电脑上做的事，我都可以让 Grok Bot 去做」，它就只是

Roman Ugarte raises the ceiling I think of of what you would think to give to AI. Are there any other mindexpanding use cases or ways to use Grockbot that uh you've seen that or you use? Mhm. One pattern that I've seen from many users um that is simple but I think there's a lot of depth uh if you keep investing in making it better. And this is kind of where I can get kind of nerdy about optimizing my setup. um is Grockbot 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 抬高了你愿意交给 AI 去做的事情的上限。还有没有其他让思维扩展开的用例，或你见过、你自己在用的 Grok Bot 用法？嗯。我从很多用户那里看到的一个模式，很简单，但我觉得如果你持续投入把它做得更好，会有很多深度。而这有点是我会对优化自己的 setup 变得有点 nerdy 的地方。就是在某些方面把 Grok Bot 当成 infovore，大量吞食信息，把那部分从你自己的认知负荷里拿掉，给你平静，然后把重要的东西带到你面前。我觉得这件事的 V1 实现，很多人都

Roman Ugarte do is Grockbot sits on top of Slack and it sits on top of email and I tell it high level here's my role at the here's kind of what I care about. I want you to notify me in these cases. In these cases, you don't need to ping me directly, but you should include this in your daily roundup that I read every day. That's like the V1 implementation. I'm not sure what the V10 implementation is, but like maybe I'm at V3 or four,which is you can give these bots a complete fire hose of information. So I have mine hooked up to like every mention of Grockbot 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. Um, and I think 在做的是：Grok Bot 坐在 Slack 上面，也坐在 email 上面，我在高层面告诉它：这是我在公司的角色，这是我在乎的事。这些情况下我要你通知我。这些情况下你不必直接 ping 我，但你应该把它放进我每天读的 daily roundup。那就像 V1 实现。我不确定 V10 实现是什么，但也许我在 V3 或 V4，也就是你可以给这些 bots 一整条信息消防水带。所以我把自己的接到了 X 上每一次提到 Grok Bot，它在和我们的内部 context 交互。它在和 QA tester 交互，看能不能复现我们收到的任何 bugs 或反馈。我还接到了自己的消息服务，好快速对反馈采取行动、去联系人。而且我觉得

Roman Ugarte there's this just like always on kind of chief of staff entity that can preserve your focus on the things that actually matter, but is always like kind of surveilling to see if there's anything that should get your attention. And we've seen some funny cases of people actually giving their Grock bots, which I have not done this yet, but maybe soon, giving their Grock bots access uh 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 Grockbot, which is the type of thing that you only want to do if it's urgent and you really want to you want to trust uh that Grockbot, you know, does not have false positives. So far, those people have reported uh that that it's been very helpful and successful. But I think we're going to see more of that type of stuff um 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. This 这就像一个始终在线的首席助理实体，能保住你对真正要紧之事的专注，但又始终在监视，看有没有？什么该引起你注意。我们还看到一些好笑的例子：人们真的给他们的 Grok Bots——我还没这么做，但也许很快会——给他们的 Grok Bots 呼叫他们的能力。所以如果发生特别紧急的事。而他们在咖啡店或别的地方，他们会被 Grok Bot page。这种事你只想在真正紧急、而且你真的信任 Grok Bot 没有误报时才做。到目前为止，那些人反馈说这非常有帮助、也很成功。但我觉得我们会看到更多这类事：agent 或 bot 对你应该比你去找它更主动。我觉得那会是 AI 的下一次转变。这

Roman Ugarte touches on there's a number of things that I've been very impressed with watching your team operate. Uh 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 uh 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 uh 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 触及到我观察你们团队运转时非常印象深刻的几件事。一件是速度，我想谈，但另一件是你们意识到这是一个时刻，要去拿下大量市场份额，在有人——尤其是某个 foundation lab——出来说好，我们现在也有很棒的东西之前，尽可能多地拿下市场。所以看着你们发出去多少免费账户。也很聪明。还有对 use cases 的专注，非常聪明，因为这是如此新的东西，你打开它会想：我拿这干什么？于是有如此专注：好，这里有一堆人们用它做的事。然后 Twitter 上全是讨论，人们用模板的各种方式，非常说得通。就我能看出的这两个专注：尽快让尽可能多的人用上，直到有人说好——因为总会有人

Roman Ugarte around be like all right here's the next thing uh super smart and also the use case focus. Uh I know you were a goto market person at Kurser before this. Anything you want to share there about just the approach to the to go to market right now for getting this out there. 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 um just building practical AI that people use and I think we as a company have culturally really cared about not building demoware uh like building actually useful stuff in the world uh 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 出来说：好，这是下一个东西。非常聪明，还有对 use case 的专注。我知道你在这之前是 Cursor 的 go-to-market 的人。关于现在把这个推出去的 go-to-market 方法，你有什么想分享的吗？我觉得我们在 coding 上看到的模式，会和我们在 general knowledge work 上看到的有些相似。我觉得我们在 go-to-market 这一侧从中学到了很多，而且更一般地说，就是做出人们会用的实用 AI。我觉得我们作为公司，在文化上非常在乎不要去做 demoware，而要去做世界上真正有用的东西，并对此近乎着迷。有太多闪亮的东西、有趣的原型可以去做。但那和把这个交到

Roman Ugarte of millions of people and having it transform companies. So that's really I think culturally where we've we've always been focused. And so I think on the go to market side what we saw for coding um 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. Um people would kind of go home from work at at work, they were using a basic IDE. This is preAI. And then at home, they'd work on a side project and they'd be using cursor or they'd be using, you know, the latest and greatest AI coding tool. And that would give them an extreme amount of acceleration. It would feel like they were experiencing the future. And then they would come back to work and they 数百万人手里、并让它改变公司，是非常不同的问题。所以我觉得那才是我们在文化上一直聚焦的地方。所以在 go-to-market 这一侧，我们在 coding 上看到的是一个非常简单的模式：有一群 early adopter。这群 early adopter 会用这些 coding 工具，并把它们推到极限，而且他们大多是在个人项目上把它们推到极限。他们会在夜里和周末。我想的是大概 2023 年，更早一些。人们下班回家，在公司他们用的是一个基本的 IDE。那是 pre-AI。然后在家，他们做 side project，会用 Cursor，或用当时最新最好的 AI coding 工具。那会给他们极大的加速。感觉像他们在体验未来。然后他们回到公司，他们

Roman Ugarte 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 uh Grockbot controlling their home robot computer or home robot vacuum cleaner uh or Grockbot, you know, helping them save money on their Tesla charger negotiation. Like all of these fun use cases, but I think the next step is going to be this is not a consumer product. We think this is going to transform businesses. We think this is going to transform teams and it will be bots coming into teams and contributing really economically valuable work especially as they get much smarter. 会要求它。他们会说：我无法想象用别的方式工作。我现在感觉完全像在糖浆里走。这必须改变。我觉得对 knowledge work，我们会看到类似的模式：人们有时会在私人场景里真正感到 aha moment。我们现在在 X 上肯定已经看到很多：你看到所有这些例子，Grok Bot 在控制他们家里的机器人电脑，或家里的机器人吸尘器，或 Grok Bot 帮他们在 Tesla 充电谈判上省钱。都是这些有趣的 use cases。但我觉得下一步会是：这不是一款消费产品。我们认为这会改变企业。我们认为这会改变团队。会是 bots 走进团队，贡献真正有经济价值的工作，尤其是随着它们变得聪明得多。

Roman Ugarte And so on the go to market side, we're certainly um 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 uh 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 uh 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 Rockbot is the right primitive to create this switch to agents uh for the rest of the company outside of coding. And that's a place where we're quite focused right now. 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 所以在 go-to-market 这一侧，我们肯定在大力优先企业，思考的不只是和一个 bot 工作的单人用例，而是一个 bot 怎样在更广的团队里工作？一个 bot 怎样在真实的公司系统里工作——那些系统很复杂，有大量 context 和大量历史要理解？memory 在更广的组织里会是什么样，对比你在服务的单个个人？我觉得那里有很多未回答的问题。但我确实认为 Grok Bot 是正确的 primitive，好为 coding 之外公司其余的人，完成向 agents 的切换。那是我们现在相当聚焦的地方。沿着这条线，很明显你们都理解分发的力量，以及你需要既找到一款出色的产品，又把分发做对

Roman Ugarte because you know Grockpot's amazing, but the combination of how smart you guys have been with getting it out there in all these different ways is really impressive and I think that shows you what it takes these days to build something that's really successful. I want to ask about the brand of the different brands around uh 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 Grockbot, there's cursors 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 uh communicate about it correctly. 因为 Grok Bot 很出色，但你们用各种不同方式把它推出去有多聪明，这个组合真的令人印象深刻。我觉得这展示了如今要做出真正成功的东西需要什么。我想问一下围绕这款产品和这家公司的不同品牌，好让人们试着理解，因为我知道你们正在经历转型、收购、SpaceXAI，所有这些。所以有 Grok Bot，有 Cursor，是这样吗？谈谈这些产品，以及今天该怎样理解这些不同品牌，我知道它大概还会继续演化，好让我们能正确地谈论它。

主持人 Definitely. Yeah. Um I think there are three big pillars right now of SpaceX AI. So the first pillar is the coding product instead of products and right now that's Kerser and Grock build and I think we're big believers that having a professional work surface for developers and for the engineering part of the organization is going to be really critical and right now people use Grockbot 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 ware. We're big believers that that is going to require, you know, a product where every pixel is optimized for that end user. So, we're making big investments there. The second 当然。是的。我觉得 SpaceXAI 现在有三大支柱。第一根支柱是 coding 产品，或者说产品们，现在就是 Cursor 和 Grok Build。我们非常相信，为developers、为组织里的 engineering 部分拥有一个专业工作界面，会非常关键。现在人们有时会用 Grok Bot 去启动 cloud agents，或去 merge PRs，或做 QA，一堆工程相邻的任务。但最终当你在交付生产软件时，我们非常相信那会需要一款每一个像素都为那个终端用户优化的产品。所以我们在那里做大量投入。第二

主持人 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. And then third is the general model effort. Um we want to train the smartest models in the world um that are really capable. And I think one thing that somewhat distinguishes SpaceX AI from other AI labs um is I think our goal is less to build um you know chase super intelligence or some kind of vague aspirational ideal. uh 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 类是 general knowledge work，我们认为 bot 是朝那个方向非常令人兴奋的一步。还有很多工作要做：让它更有用，延伸到新的界面，真正感觉像一个你可以委托工作的 AI 队友，尤其是在公司和生意内部。所以那是第二根支柱。然后第三是通用模型方面的努力。我们想训练世界上最聪明的、真正有能力的模型。我觉得有一件事在某种程度上把 SpaceXAI 和其他 AI labs 区分开：我们的目标较少是去追逐超级智能，或某种模糊的、向往式的理想。目标其实非常实际，就是做出有用的 AI。我们在产品侧这样做，在模型侧也这样做。我觉得其中一部分也只是文化：为这些模型做贡献的这群

主持人 of people contributing to these models are engineers and people who um kind of came into the the model training effort from like a very applied mindset and I think that's what gets this company going and I think is is actually a slightly different direction from some of the other competitors out there. 人，是 engineers，是从非常应用的心态走进模型训练这件事的人。我觉得那才是让这家公司运转起来的东西，而且实际上和其他一些竞争对手是略微不同的方向。

Roman Ugarte Super interesting. Okay, there's a couple directions I want to go. One is you have this tweet that is uh 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. I think for me what made me so excited to work on Grockbot and contribute to it is it was the first 非常有意思。好，我想走几个方向。一个是你有这条 tweet，我想你把它 pin 了，或者也许是你最近一条tweet。如果人们去看你，它就在你的时间线上。这条 tweet 是：一个能把工作做完 100% 的 AI，和一个只能帮你做到 90% 的 AI，感觉是完全不同的类别。我已经显著更新了自己对 AI 能力的看法。再多说说这个。对我来说，让我如此兴奋去做 Grok Bot、为它做贡献的原因是：这是第一次

Roman Ugarte 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 and many many words have been said on that topic. Uh 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 a to a, you know, an input box, you hit enter, you watch all of these steps happen, you get an 在非 coding 任务上，我感觉自己真的可以把工作委托给 AI，不用再惦记，回来时它已经做完了。我觉得 engineers 已经有相当一段时间是这种感觉。大概一年、一年半，事情已经是那样。我是说，developer 的工作已经完全转变了。它和两年前已经认不出来，关于这个话题已经说了非常非常多话。但我觉得被低估的是：那种体验和大多数人此刻对 AI 的感觉、以及 AI 改变他们生活的方式，有多么不同。它看起来相当像人们大约两年前用 AI 的方式：你为一个任务新建一条 thread，打进一个输入框，按回车，看着所有这些步骤发生，得到一个

Roman Ugarte output, it's not quite right, you keep working on it. And Grockbot, I think, shortcircuits 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 um you know to a surprising extent uh and I think we're going to do a lot to to make it work much better and so I think what I was expressing in that was when you have a teammate that you only 90% trust uh 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 intervene and kind of steer it slightly. You're not that's not 90% task completion. You're still doing the thing 输出，不太对，你继续改。而 Grok Bot 我觉得把其中很多都短路掉了。当你第一眼看到第一个屏幕，你会想：哇，这明显不一样。看看它是不是真的能用，但这就是不一样。然后你给它一件事，它在令人吃惊的程度上能用。我觉得我们还会做很多，让它好用得多。所以我觉得我当时在表达的是：当你有一个你只 90% 信任的队友，你把事情交给他——幸好我在这里没有这种体验，因为我和很棒的人一起工作——但如果你把事情委托给某人，你心里想：我知道你在做的时候我还得惦记这件事，我知道它大概不会完全到位，我还得介入、稍微引导一下。那不是 90% 的任务完成。你仍然在做这件事。

Roman Ugarte and it feels that way and it's it's weighing on you in the same way versus like truly throwing a nook 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 Grockbot 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. 感觉也是那样，它以同样的方式压在你身上。对比真正给同事一个不看人传球：你能行。这是 context。出去跑。我很兴奋想看你做什么。那是不同的类别。我觉得人们每天和 Grok Bot 感受到的就是这类不看人传球：你就是信任它能做完，然后它做完了，那是一种非常神奇的体验。

主持人 Yeah, I have had that experience consistently. Um, okay. So, another element of how you all operate that has really impressed me and I've not seen this before is how fast you all move. So, I got added to this like Slack as you 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, uh, 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 what's the secret to how fast you all have been moving and how do you stay aligned moving that fast towards a vision of that you all want they all believe in 是的，我持续有过那种体验。好。你们运转方式里另一个真正让我印象深刻、而且我以前没见过的元素，是你们动得有多快。我在给反馈时被加进了某个 Slack，里面就是：好，那明天我们给你一些免费码去发。你可以明天做。我们明天就做这个。或者，我们要上线一个带模板的 marketplace。我们两天后上线。我就想：什么？我没有时间应付这个。你们怎么在所有这些事情进行的同时做到？这些东西不断在 ship，同时还保持一致、高质量，并且感觉清楚它是朝向一个特定愿景。所以这个问题大概有两部分：你们一直动得这么快的秘密是什么；以及你们怎么在动得这么快时，仍然对齐你们都想要、都相信的那个愿景，

主持人 and where you want it to go versus just like you know bandating it along the way 以及你们想让它去的地方，而不是一路打补丁？

Roman Ugarte 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. Um, and then now we're a part of of SpaceXi, 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 uh that everyone is fired up about and like and knows that that they need to execute on. Um, and you know, as companies grow, and we've had the fortune of hiring really great people from other companies that have gone through hyperrowth, things 是的，一件我非常高兴从未改变的事，是公司内部的那种 startup 感觉。作为背景，我最初加入 Cursor 时，我们大概 15 个人。我们扩到了超过一千人。然后现在我们是 SpaceXAI 的一部分，那是一个甚至更大的组织。而当你和这群极其有才华的人在一起时，成为其中一员就是如此有趣。每个人都以每小时一百英里的速度在动。你信任、深深信任每一个人去执行他们那部分。有一个清晰的愿景，每个人都为此兴奋，也知道自己需要去执行。而且你知道，随着公司变大——我们有幸从经历过超高速增长的其他公司招来了非常优秀的人——事情

Roman Ugarte 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 uh to say than to actually be. And, you know, fingers crossed this this continues to be true. I think it's really critical for our success if this continues to be true. Uh but even as we scaled it has always felt like that startup that kind of I I first joined. 会变慢，你不断告诉自己：我们仍然是 startup。我们仍然动得很快。但你其实没有。每个人都知道你没有。说起来比真正做到更容易。手指交叉，希望这继续为真。如果这继续为真，我觉得对我们的成功至关重要。但即使我们规模变大了，它一直感觉像我最初加入的那个 startup。

Roman Ugarte Um 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, uh, it's really been to enable that property in a way that I think some of our competitors and and other AI labs have gotten much bigger and you can feel it. Um, and I think us even as we scale there is that that startupy impulse that is is quite important to move quickly on these things. 而且我觉得如果你用人数或融资轮次来定义 startup，那些东西都没什么道理。定义 startup 的核心，正好就是你在描述的：那种赶工能量，事情有点混乱、有点无序。对很多人来说，那不是愉快的工作环境，但它有这些惊人的属性：你可以朝一个特定方向、在短时间内做出极端影响。而且你从一套系统里拿到的，真的就是你投入的。所以我觉得作为文化，作为组织，以及我们构建自己的方式，真正是为了启用那种属性。而我们的一些竞争对手和其他 AI labs 已经大得多，你能感觉到。即使我们在扩张，仍然有那种 startup 式的冲动，对在这些事情上快速行动相当重要。

主持人 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 if you were to look at cursor from the outside, you it shouldn't have worked. It shouldn't have uh lasted because one, it's in the most competitive market in the world competing against the fastest growing companies in history, open AAI and Anthropic. So that's one, it's like the comp competition is unlike anything 让我抓住这条线，让我。问你这个我一直期待问你的大问题。如果从外面看 Cursor，它本不该成功。它本不该撑下来。因为第一，它处在世界上竞争最激烈的市场，对手是历史上增长最快的公司，OpenAI 和 Anthropic。所以这是第一点：竞争不像任何人

主持人 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 Grockbot. To me, that feels like a core part of the success is uh quickly adjusting to reality and also building the best-in-class experience for a thing that also exists other places. Grockpot's a great example. You could do this other places, but it's the best-in-class experience. Cursor the ID, the best way to code. Uh so, so that's my question. Maybe I answered it, but what do you think has been core to 曾经经历过的。第二，它坐在那些平台之上来获得动力。而我作为局外人看到的是，让 Cursor 赢下来、有这次巨大的 exit、并继续成功的，是你们有多快调整去适应市场现实。从 autocomplete 起步，然后事情转到只是和 agents 对话，然后进入cloud，现在是 Grok Bot。对我来说，那感觉是成功的核心部分：快速调整去适应现实，同时为一件别处也存在的东西做出一流体验。Grok Bot 就是很好的例子。你在别处也能做这件事，但它是一流体验。Cursor 这个 IDE，最好的 coding 方式。所以这就是我的问题。也许我已经回答了，但你觉得什么是核心，让

主持人 Curser's ability to not just survive in this crazy competitive market, but uh do so incredibly well consistently for so long? Cursor 不仅在这个疯狂竞争的市场里活下来，而且持续如此出色、如此之久的能力？

Roman Ugarte 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. 很大一部分——这是一个模糊的回答——很大一部分我觉得是文化的下游：你设定的文化，你带进来的人，以及他们处理这些问题的方式。对我们来说，正如你所说，我们从未自满。

Roman Ugarte uh 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, uh 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 我们从未觉得自己已经赢了，永远都是下一件事。我觉得全公司有一种非常深的信念：AI 动得极快。我们的目标是把那些能力翻译成给客户的出色产品。但那些产品会变，它们需要在能力变强时赶上那个时刻。两年前赶上那个时刻的东西，和今天赶上那个时刻的东西完全不同。如果我们作为公司不能每六个月彻底重塑自己——最近感觉甚至比那更短，是对我们的优先级、核心产品、用户感受到的东西做非常显著的重塑——我们就会输。我觉得正是那种永远推向前沿的精神，从不认为已经结束、或我们已经赢了、或

Roman Ugarte that we've gotten it right. Uh, and just constantly updating our beliefs that has gotten us to where we are now. And to your point on the competitiveness of this space, I mean, one thing that I think is important to point out is AI coding has always been competitive from when cursor first 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. Um 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 uh 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 uh what has led us to invest in things like Rockblot for example. 我们已经做对了，以及不断更新我们的信念，把我们带到了现在这个位置。至于你说的这个领域的竞争性，有一点我觉得重要指出：从 Cursor 最初出现时，AI coding 就一直是竞争激烈的。当时的竞争对手是 Microsoft 和其他公司，大概十几二十家。而且我觉得值得注意的是，那些竞争对手现在没有一个站在 AI coding 的最前沿，很大一部分不是。因为他们做了错误的决定，或他们缺少资源，而是这种文化上无法快速行动、无法在时刻正在改变时去赶上那个时刻。所以我觉得那正好就是让我们去投入 Grok Bot 这类事情的原因。

主持人 Are there any uh core values just like specific ways you phrase this to kind of remind everyone of this is how we work? 有没有？什么核心价值观，就是。你们用来提醒所有人「我们就是这样工作」的特定说法？

Roman Ugarte 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 Grockbot I think we will feel the same thing uh 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 有。有两个价值观我发现自己经常回到。第一个是删除产品这个想法。我觉得它正好接回你现在说的：当你看 Cursor 过去的每一次迭代，甚至我觉得当你看 Grok Bot 过去的每一次迭代，我们都会有同样的感觉就是东西在消失，而不是新东西在被加上。那些脚手架式的、产品 overhang 式的东西被做进去，是因为模型还不够聪明、还不能自己去做。那些东西会随时间被拿掉。我们需要能坦然做出那种可能让一小部分用户、或内部一小部分人不高兴的艰难决定，去做更大的事：让产品简单，让产品

Roman Ugarte product powerful and adapt to where the future is going. So I think that's been very core. And then the second thing which ties back to the kind of pace of execution um is just do the thing uh which I find myself kind of repeating a lot um even as we've kind of grown as a company is it's on you know we're all in this boat together we want to win and if you see something that you think needs to happen you know this is not an ask for permission culture you go out and you fix the thing and you pull in the resources that you need to make it happen and I think that has made many people very successful here before and I think it's something we really share with with SpaceX AI as well 强大，并适应未来正在去的地方。所以我觉得那非常核心。第二件事接回执行的节奏，就是：把那件事做了。我发现自己经常重复这句话，即使我们作为公司已经变大了：我们都在这条船上，我们想赢。如果你看到某件你认为需要发生的事，这不是一个先请示的文化。你走出去，把那件事修好，并拉来你需要的资源让它发生。我觉得这已经让这里很多人非常成功。我觉得这也是我们和 SpaceXAI 真正共享的东西。

主持人 agency as uh you may have heard um so interesting one of the big questions that comes up and and uh and this might be my final question is around moes and a lot of people look at cursor is a really interesting example of they're in a market with technically maybe no moes but they've continued to win and succeed the two modes you think about with cursor is the data feedback loop of people autocompleting, learning what they're doing and training models based on that. So that's that's unique. The other is just best-in-class experience and being like a high g daily active user product and finding over time what works and what people need. What have agency，也许你听说过。非常有意思。一个经常出现的大问题——这也许是我最后一个问题——是关于护城河。很多人看 Cursor 是一个非常有意思的例子：他们处在一个技术上也许没有护城河的市场，却持续赢、持续成功。你想到 Cursor 的两个护城河，一个是数据反馈环：人们在 autocomplete，从他们在做的事里学习，并据此训练模型。那是独特的。另一个就是一流体验，成为一个高日活产品，并随时间发现什么有效、人们需要什么。你

主持人 you just learned and I guess any thoughts on Moes in this space that might be helpful for folks that are trying to figure this out for themselves? Yeah, there's a lot of talk about Moes 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 moes 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 刚刚学到了什么，以及关于这个领域里护城河的任何想法，可能会对那些试图自己搞清楚这件事的人有帮助？是的，关于护城河有很多讨论。现在是一个创办公司相当有意思的时刻。所以我能理解为什么这么多创始人在问自己这个问题，并试图向外投射 12 个月后、24 个月后，那感觉就像永恒。我会说，如果 Cursor 和这一代许多其他成功公司，当时想的是护城河，或者说试图从某张战略图、或某种更抽象的「公司该怎样运转」的观念往回推，我不认为那会创造出这个结果或。

主持人 this product. I think what really created the magic of cursor uh 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 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 这款产品。我觉得真正创造出 Cursor 魔力的，是对今天就做出一件有用之事的着迷。而且它不断是这种练习：你大概能看见世界三个月后、六个月后会去哪里，模型会更聪明，一件现在不可解的事终于会可解。我觉得 Cursor 有点像这个反复出现的 prompt：我们怎样能把那些东西拉到今天，即使这需要在上面做一点工程让它能用，或做很多工程让它能用。即使这需要以特定方式改变产品，好让用户能和这种新能力交互。我们怎样能把它提前，然后三个月后我们应该删掉那些东西，因为它会变成好用的、基本的、产品的最低常见配置，然后我们再去做从那时起三个月后的东西。然后就是

主持人 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. 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. Uh but I think that's really the place to play. 不断一遍又一遍地做那件事，我觉得这让用户真正信任我们，把他们的时间放进我们的产品，并信任我们在把东西带到下一个前沿、带到下一个未来。所以我非常鼓励很多创始人、或今天起步的人，更扎根于那个视角：我怎样能让一件现在不可能的事变成可能。用户会来找我。来用那个东西。我会把他们拉到下一个不可能的前沿，然后通过这一切，我会获得很多分发优势。我会获得数据优势。那里会有价值。但我觉得那才真正是该去玩的地方。

Roman Ugarte 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 modes piece. And if you can continue to do that, you'll find something which in cursor case ended up being a few things. 我爱这个回答。本质上，我在想的方式就是：做出人们着迷的东西。不要过度思考护城河那一块。如果你能持续那样做，你会找到某些东西，在 Cursor 的例子里最后是几件事。

主持人 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 modes are discovered, not planned ahead of time a lot of times. 而这其实最近在我做的另一期播客里也出现了。我不知道它会在这期之前还是之后出来。这个想法是：护城河很多时候是被发现的，而不是事先计划的。

Roman Ugarte Okay, let me actually ask you for Grockbot tips as an actual last question. Uh some people are going to be like, "Oh I got to try this thing. what all these what's all this excitement all about? Um 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. 好，让我真正问你要一些 Grok Bot 的 tips，作为实际的最后一个问题。有些人会想：哦，我得试试这个东西。所有这些兴奋到底是为了什么？对正在尝试的人，比如说对新人，会有什么建议，就是成功的关键；也许还有给已经在用的人的 power tip，让他们说哦原来我不知道。

主持人 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 Grockbot and they should do it. Um, and so what I would encourage for someone new who's like just downloading the app, you're looking at this this screen. Um, I think the first thing is give Grockbot 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 是的，我想远离那种特别黑客式的 pro tip，因为我觉得我们作为团队、作为公司的哲学是：那些东西真的不该存在。不该有所有这些疯狂的旋钮。你应该能把某件事委托给 Grok Bot，它们就该去做。所以对一个刚下载应用、正在看这个屏幕的新人，我会鼓励的是：第一件事，给 Grok Bot 它要成功所需的 context。就像你在给团队招人一样，对他们来说，能访问 Slack、你的 email、以及你每天都在用的公司记录，会非常有帮助。所以我会给它访问这些工具，然后我实际上会问

主持人 Grockbot 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. Um, and that was my big wow moment of feeling like no other AI tool in the past could have done those two things. It was not like draft an email. it was like do a chunk of work. And so I encourage people who are brand new to do it that way. And then for people who are not brand new, um I kind of am constantly finding new patterns for ways Grok Bot 它能为你做什么，让它去过一遍你最初接上的那些 connections。在我的例子里，也许是我给它我的 email，给它 Slack。我第一次 onboarding 时真的很吃惊。那时我们还没有任何 onboarding 屏幕。所以我给它的第一个任务大概是：过一遍我的 Slack，过一遍我的 email，建议大约五件你能从我盘子里拿走的事，以及你做那些事需要什么。它建议了五件，其中两件其实非常有帮助，我就立刻分出两个 bots 去解决那两件。那是我很大的 wow 时刻，感觉过去没有任何其他 AI 工具能做成那两件事。那不是「起草一封邮件」，那是「做一块工作」。所以我鼓励全新的人用那种方式去做。然后对不是全新的人，我不断在发现新的模式，关于我的 bots 怎样

主持人 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 Grockbots 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. Um, and so I would encourage power users to think about ways that Grockbot can actually write to like a a single store where you can organize a lot of its outputs much easier. 彼此交互、彼此协作。所以我一直在创建多一点的脚手架：这些 Grok Bots 产出的 artifacts 该住在哪里，以及它怎样能写到一个对我非常易读的地方。所以我有这些频繁的 digests，我每天读，它会推到一个 database，我可以非常容易地读。所以我会鼓励 power users 去想办法让Grok Bot 真正写到一个单一的 store，你可以在那里更容易地组织它的大量输出。

Roman Ugarte Damn, we need another episode of going deep on Gro Roman's Grockpot 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? 天哪，我们需要再来一集，深入讲 Roman 的 Grok Bot setup，那里面大概有太多私人敏感信息。我们没法展示，但没关系。这是一个惊人的 tip。Roman，在我们进入非常精彩的闪电轮之前，你还有什么想分享的，或还有什么想谈到的吗？

主持人 Nothing. Nothing else on my side. 没有。我这边没有别的了。

Roman Ugarte We covered so much ground. That was I can't believe that was only an hour and a halfish. Uh I felt like we 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? 我们覆盖了这么多。我不敢相信那大约只有一个半小时。感觉我们谈了很久，覆盖了我希望覆盖的一切。到这里，我们进入非常精彩的闪电轮。我有四个问题给你。你准备好了吗？

主持人 I am ready. 我准备好了。

Roman Ugarte What are two or three books that you find yourself recommending most to other people? 有哪两三本书，是你发现自己最常推荐给别人的？

主持人 Yeah. So, two two books for you. One is I love Kerbonagget. Uh, so Cat's Cradle has been a fun fun recommendation that and a copy that I bought many friends before. Um, and then second is The War of Art by Steven Presfield, uh, that I find myself frequently coming back to, even if it's just a page or two at a time. Um, and I'd recommend for anybody. 好。两本书给你。一本是我爱 Kurt Vonnegut。所以《猫的摇篮》一直是一个很好玩的推荐，我以前也给很多朋友买过一本。第二本是 Steven Pressfield 的《艺术之战》，我发现自己经常回到它，哪怕一次只读一两页。我会推荐给任何人。

Roman Ugarte 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. 《艺术之战》。太好了。它是一本很短的书，一旦你读了——它不是人们可能以为自己听到的《孙子兵法》。是的。

主持人 But it's the war of art. It's a play on that and it's about the uh the challenge of being creative and doing creating something new and how to overcome the resistance. Uh I love that recommendation. Uh next question. Favorite recent movie or TV show if you've had any time to watch any of these things. 而是 The War of Art。它是对那个名字的戏仿，讲的是作为创造者、去创造新东西的挑战，以及怎样克服阻力。我爱这个推荐。下一个问题。最近最喜欢的电影或剧集，如果你有时间看这些东西的话。

Roman Ugarte Yes. um 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 Yugarte which is like the only example of I think a Yugarte in the media. Um so Casablanca always a great rewatch. Um, and then on the TV side, um, I sometimes sneak in an episode of Monk, the detective show, uh, 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 有。最近。每年我都会重看《卡萨布兰卡》，那是我最喜欢的电影之一，而且碰巧里面有一个角色姓我的姓 Ugarte，大概是媒体里唯一一个Ugarte。所以《卡萨布兰卡》永远值得重看。然后在剧这一侧，我有时会偷偷看一集 Monk，那部侦探剧。那是我小时候和家人一起看的，现在我住在 San Francisco，又回来看了。它就是 90 年代末、2000 年代初拍摄时 San Francisco 那个时刻的很好快照，

Roman Ugarte shot. Um, that I I really enjoy. 我非常喜欢。

主持人 First Monk reference on the podcast. Okay. uh favorite or most interesting AI product right now. You can say Rockbot if you want, but if there's anything else, you get bonus points. 这档播客上第一次提到 Monk。好。此刻最喜欢或最有意思的 AI 产品。你可以说 Grok Bot，但如果有别的，你有加分。

Roman Ugarte Um I've always been a big AI semantic search nerd. I love any SEM search product, especially the kind of out of the ordinary ones. Um so I I was like a very early user of 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. 我一直是一个很大的 AI semantic search 爱好者。我爱任何 semantic search 产品，尤其是那种不寻常的。所以我当时是Metaphor 当时非常早期的用户，它后来变成了 Exa。我爱用 Exa 在互联网上做所有这些也许更奇怪的查询。但我看到很多人在做的例子，比如对 MoMA 的嵌入图像库做 semantic search，诸如此类。我玩那些总是非常开心。所以任何建在奇怪数据集上的 semantic search engine，我都爱。

主持人 And Exa in particular is one you'd recommend. 而 Exa 特别是你会推荐的。

Roman Ugarte I love Exa. Yeah. 我爱 Exa。是的。

主持人 Very cool. Okay. favorite life motto that you often come back to in work or in life. 非常酷。好。你在工作或生活里经常回到的人生座右铭？

Roman Ugarte Not as short as a single motto. Um but I love the desiderata which I don't know if you've read but um I have it on my on my door uh and I've had it since I was a teenager and everywhere I move I kind of paste it there and it's it's a very short poem but each line I just I find myself finding something new in it every time I read it and I find it really grounding. Roman, this was amazing. Uh what a what a point in time we're here right now at this moment in time of Grockbot of AI in general. Uh it's going to be really fun to revisit this in a year and be like, "Wow, we were so right and so wrong about so much." Uh thank you so much for doing this. I know it's a very busy time on your team right now. So I really appreciate you carving out a couple hours to chat. Um is there any place you want to point people to? 没有短到一句座右铭。但我爱 Desiderata，不知道你有没有读过。我把它贴在门上，从青少年起就有，每搬一次家我都会把它贴在那里。它是一首很短的诗，但每一行我都发现自己每次读都能从中发现新的东西，我觉得它非常能让人落地。Roman，这太棒了。我们正处在 Grok Bot、处在 AI 整体的这样一个时刻。一年后再回头看这一集，会非常有趣，我们会说：哇，我们对这么多事情既对得那么对，也错得那么错。非常感谢你做这一集。我知道你们团队现在非常忙。所以我非常感谢你抽出几个小时来聊。你有没有想指向人们去的地方？

Roman Ugarte Anything you want to plug other than check out Grockbot? Is that 除了去试试 Grok Bot，还有什么想推的吗？是那个吗？

主持人 Check out Grockbot? Of course. Um, and yeah, main thing would be please send feedback. I think we're in the very early innings of this still. I mean, we released a beta 3 weeks ago. Um, and a lot of the feedback that we've been getting from this early set of users is directly translating to what we built and how we build it. And so really appreciate um, all the input that people are giving. 去试试 Grok Bot？当然。主要的事是请发送反馈。我觉得我们仍然处在非常早期。我们三周前才发布了 beta。我们从这批早期用户拿到的很多反馈，正在直接翻译成我们做了什么、以及我们怎样去做。所以非常感谢人们给出的所有意见。

Roman Ugarte Nice job, Roman, and team. I know there's a whole team behind all this. Uh, Roman, thank you so much for being here. 干得好，Roman，还有团队。我知道这一切背后有一整支团队。Roman，非常感谢你来到这里。

主持人 Awesome. Thanks, Lenny. Bye everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennispodcast.com. See you in the next episode. 太好了。谢谢，Lenny。大家再见。非常感谢收听。如果你觉得这有价值，可以在 Apple Podcasts、Spotify 或你喜欢的播客应用上订阅本节目。也请考虑给我们评分或留下评论，那真的能帮助其他听众找到这档播客。你可以找到所有往期，或了解更多关于本节目的信息，请访问 lennyspodcast.com。下期见。