一个月内从零做出全球最火 AI 产品：Grok Bot 的极简架构与“AI同事”哲学｜Lenny's Podcast
Lenny's Podcast 本期对话 SpaceXAI 产品负责人 Roman Ugarte：从四人小团队闭关一月从零起步、手工冷启动 300 名用户，到“AI 同事”哲学与护城河的发现逻辑。
这期 Lenny's Podcast 不是一场泛泛而谈的宏观 AI 畅想，而是一次罕见的高密度产品与工程实战复盘。主持人 Lenny Rachitsky 邀请了 SpaceXAI 产品负责人、前 Cursor 增长负责人 Roman Ugarte，系统拆解他们如何带领一个极小的核心团队，在短短四周内写出第一行代码并拿出可用内部产品，随后在三周后正式公测并引爆全网讨论。整期访谈时长约 1 小时 23 分钟，完整展现了面对当今全球竞争最白热化的技术市场时，顶级创业团队如何通过反直觉的产品取舍、手工冷启动和极度聚焦，把一个看似不可能的构想变成现实。12
在进入具体的工程细节前，读者最适合带着一个核心产品问题来审视这期访谈：在底层大模型能力不断被拉平、各类智能体层出不穷的今天，真正能跑通落地的 Knowledge-work Agent（知识工作智能体）究竟长什么样？ Roman 和他的团队给出的答案打破了行业既有的产品套路。他们坚决放弃了“在原有成功产品上缝合功能”的安逸路线，拒绝让用户去理解复杂的内部调用与思维链，而是将产品原语牢牢锚定在“给用户配备一个拥有独立工作电脑、具备长久记忆的 AI 同事”（colleague-pilled）。这场讨论不仅属于工程师，更属于每一位试图用 AI 彻底重构日常工作流的现代知识工作者。
先记住三件事
- 从零起步的自由度，远胜在已有成功产品上修修补补。 Cursor 虽然取得了巨大成功，但它的产品形态天然被绑定在代码编辑器、文件树与程序员心智上。想要服务全公司 90% 的非研发人员（市场、运营、法务、投资），就必须脱离 IDE 的重力场，在白纸上重写一套专为通用知识工作设计的全栈产品。
- 亲自手工 onboarding 前 300 名用户，换来了决定生死的极简设计。 创始团队没有采用自动化的候补名单，而是花了几百个小时逐一陪伴早期用户上手。这一极度笨拙的做法让他们迅速砍掉了大量的花哨功能，坚决隐藏内部机械结构，确立了“Grok Bot can now”（Grok Bot 现在可以做到……）的笃定感。
- 护城河不是在白板上规划出来的，而是高速奔跑中发现的副产品。 在技术迭代以周为单位的时代，任何预设的长期防御工事都会被底层模型的新能力冲垮。团队的核心竞争力在于“删除产品”（deleting the product）的魄力、天级的交付反馈环，以及在解决最脏、最繁琐的底层系统集成时自然沉淀出的工程壁垒。
闭关一个月：从零构建知识工作智能体
Grok Bot 的诞生是一次典型的“特种部队式”产品孵化。在 Cursor 被 SpaceX 战略收购之后，Roman Ugarte 带领一个仅有数人的极小内部团队，做出了一个大胆的决定：像隐士一样“进入洞穴闭关一个月”，将外界所有的会议与杂音隔绝开来。
他们的目标非常纯粹——构建一个能够真正将 Agent 能力带给公司全体非技术人员的知识工作产品。在四周时间内，团队完成了从第一行代码到在内部完全跑通日常工作流的飞跃；紧接着仅仅过了三周，Grok Bot 就在全网公测中迅速成为现象级爆款产品。Lenny 在节目开场提到，就在发布三周后的旧金山线下 Meetup 上，现场汇聚了数百名狂热的从业者与用户，全场爆满只能站立。
这种爆发力背后，隐藏着一个关键的产品洞察：在过去的 AI 产品浪潮中，程序员是最大的红利享受者。Cursor、Copilot 等工具让开发者拥有了极高的代码生成效率，但占企业绝大多数的通用知识工作者，却依然停留在“向聊天框提问、复制粘贴文本、在几十个应用窗口之间来回搬运信息”的初级阶段。Roman 意识到，整个市场都在等待一个真正能够替知识工作者“端到端扛下任务”的跨时代产品。
为什么不直接做在 Cursor 内部？
当团队决定进军通用知识工作领域时，最顺理成章的选择似乎是直接在 Cursor 现有的庞大用户群与成熟基础设施上增加一个新模块。然而，Roman 和团队毅然否决了这一方案。
这一抉择的底层逻辑在于产品认知的重力。Cursor 的一切体验都是围绕代码编辑器构建的：侧边栏、代码行号、语法高亮、Git 提交记录、Diff 审查。对于一名软件工程师而言，这些元素是他们的第二本能；但对于一名人力资源总监、市场营销专员或合规审查员来说，打开一个哪怕做了简化的 IDE 界面，本身就会带来巨大的心理门槛与认知过载。
更深层的原因在于任务本质的分歧。软件工程的交付物是严谨、结构化的代码，而通用知识工作的任务往往是发散、多模态且跨越多个异构系统的。它可能需要浏览五个不同的 SaaS 平台、下载并解析三份 PDF 合同、汇总成一份符合特定业务逻辑的对比表格，再自动生成一封语气恰当的邮件草稿。如果将这套流程强行塞入代码编辑器的交互范式中，不仅会破坏 Cursor 本身的极致专注，也会让新产品陷入四不像的尴尬境地。从零起步，让团队摆脱了所有历史资产的羁绊，得以完全从通用知识工作者的第一性原理出发设计产品。
100% 交付 vs 90% 交付：质变的临界点
Roman 在节目中引用了一条他在社区广受传播的著名论断：一个能够完成 100% 工作任务的 AI，与一个只能完成 90% 的 AI，在用户体验上存在着本质的断层，二者属于完全不同的产品物种。
在过去几年里，绝大多数 AI 工具提供的都是“90% 的便利”。它们可以帮你写出一份看起来差不多的初稿，或者列出五条分析要点，但剩下的 10%——包括核对具体事实、修正格式错位、确认数据接口的准确性、将成果真正发送给对应的协同方——依然必须由人类员工全神贯注地介入。这种模式并没有真正解放人类，反而给用户带来了沉重的“审查焦虑”与“校对负担”。很多时候，仔细检查 AI 是否犯错所消耗的脑力，甚至超过了自己从头写一遍。
Grok Bot 的产品追求正是跨越这最后的 10%。Roman 解释说，真正的生产力跃迁发生在你能够彻底放下心来“委托”（delegate）的那一刻。就像你在职场中把一项调研任务交代给一位可靠的初级同事一样，你交代完之后可以关掉电脑去开会或散步，当你一个小时后回来时，任务已经被完整、严谨地交付，连同所有的附件和格式都处理得无可挑剔。只有当 AI 具备了这种“端到端闭环执行”的能力时，知识工作者才会从心理上真正视其为生产力杠杆，而非一个需要随时擦屁股的玩具。
手工陪伴 300 名用户：反常识的冷启动
在互联网增长领域，常规的做法是在产品上线前搭建一个精美的营销主页，通过自动化流程收集几万个排队名单（waitlist），然后批量发放邀请码。但 Grok Bot 却反其道而行之，采取了极度高强度的“纯手工冷启动”策略。
Roman 与团队成员亲自对前 300 名早期用户进行了 1 对 1 的深度 onboarding。他们通过视频会议屏幕共享，逐个观察用户如何下载、授权、第一次输入指令，并仔细记录用户在哪个环节皱起眉头、在哪个步骤产生了犹豫。这几十上百个小时的极度消耗，换来了两项彻底重塑产品的重大决策：
首先是坚决隐藏底层的机械细节。在技术人员的直觉中，展示 Agent 的多步骤思考过程（Chain-of-Thought）、工具调用日志（API calls）以及复杂的系统执行链路是一件很“极客、很透明”的事情。但在长期的实测中，团队震惊地发现，真实的业务用户对这些瀑布流般的日志感到极度恐慌与困惑。普通用户根本不在乎底层调用了哪几个模型、搜索了多少次内部网页，他们只需要一个安静、优雅的界面，清晰地告诉他们任务的状态与最终答案。团队果断移除了所有繁复的中间态展示，将界面简化到极致。
其次是建立以能力增量为导向的沟通机制。用户在面对一个空白的对话框时，往往不知道从何下手。团队发现，最有效的促活方式不是堆砌文档，而是在产品更新中用极为自然直白的语言告诉用户：“Grok Bot 现在可以帮你完成 X 了”（Grok Bot can now…）。这种以具体业务能力为锚点的产品心智，让早期用户能够迅速建立起对工具边界的清晰认知。
“AI 同事”哲学与云端虚拟计算机
Grok Bot 在内部确立的核心产品模型被称为“Colleague-pilled”（AI 同事框架）。
在这一哲学下，Grok Bot 不再是一个简单的 SaaS 插件，也不是网页上的一个对话气泡，而是一个在虚拟空间中全天候待命的数字同事。为了支撑这一心智，团队在底层做出了一个关键的架构选择：Cloud-first architecture（云原生架构）。
在传统工具中，很多本地自动化需要占用用户的个人电脑屏幕与鼠标，一旦用户离开或关闭笔记本，任务就会中断。Grok Bot 则直接在云端为每一个任务分配独立的虚拟环境与浏览器沙箱。这就好比公司在机房里为这个 AI 员工配置了一台专属的高性能电脑，它可以在云端持续自主地打开网页、比对表格、运行分析脚本并存储进度。用户即使在下班通勤路上用手机向它交代任务，它也能在云端独立完成长达数小时的深度调研，并在第二天清晨将整洁的报告放置在用户的桌面上。
更为核心的支撑是持久化记忆系统（Persistent Memory）。一个合格的人类同事之所以越用越顺手，是因为他能记住公司的黑话体系、团队各成员的偏好、上周项目的遗留问题以及老板对排版格式的苛刻要求。Grok Bot 通过构建多层级的记忆图谱，将用户在一次次交互中透露的上下文沉淀为长期资产。随着时间的推移，这种累积的上下文使得其他任何新工具都无法轻易替代它在用户工作流中的生态位。
护城河不是规划出来的，而是发现出来的
当被问及在当前大模型厂商与各类创业公司疯狂内卷的环境下，Grok Bot 究竟如何构建竞争壁垒时，Roman 给出了一个极具颠覆性的见解：在 AI 领域，护城河永远不是提前设计（designed）出来的，而是在工程实践中被“发现”（discovered）出来的。
许多创始人和投资人喜欢在商业计划书的白板上画出五花八门、看似坚不可摧的“护城河”模型。但现实往往极其残酷：六个月之后，底层基础模型的重大版本更新可能会在一夜之间将你精心构建的功能模块碾得粉碎。Roman 认为，试图通过预设壁垒来防守是一种静态的幻觉。
在激烈的动态竞争中，真正的壁垒来源于以下几点：
- “删除产品”的绝对勇气（Deleting the product）： 当团队发现某项原本引以为傲的功能在真实场景中并未带来决定性的价值留存时，必须毫不留情地将其整体剥离。保持代码库与交互界面的极致轻盈，让团队随时有能力拥抱最新一代大模型的能力跃迁，而不是被沉重的陈旧功能拖垮。
- 极高的执行速度与人才密度： 胜负的差距往往体现在“从发现用户痛点到发布修复版本”的时间尺度上。在传统大厂需要跨部门评审三个月的改动，顶尖团队必须在 24 到 48 小时内完成迭代上线。
- 脏活累活构筑的工程细节： 真正的护城河往往隐藏在极其琐碎的现实泥潭中——对各种混乱格式文档的高保真解析、复杂企业网络权限的无缝穿越、跨不同平台认证的稳定性以及极端边界条件下的容错机制。这些需要无数工程血泪才能填平的深坑，恰恰是后发竞品在短时间内难以逾越的真正屏障。
人物背景
Lenny Rachitsky 是硅谷最具影响力的产品增长与科技播客主理人之一，其创立的《Lenny's Newsletter》与《Lenny's Podcast》已成为全球产品经理、创业者与技术领袖必读的行业思想殿堂；他此前曾长期担任 Airbnb 核心增长产品主管，对互联网规模化扩张与产品机制有着极深的研究。
本期嘉宾 Roman Ugarte 目前在 SpaceXAI 全权负责产品工作；在此之前，他曾担任全球顶尖 AI 编程工具 Cursor 的增长负责人（Head of Growth），主导了 Cursor 从 15 人的极早期初创团队一路扩张至千人规模并最终并入 SpaceX 的关键历程。Roman 兼具深厚的技术直觉与敏锐的市场洞察，深度参与了当前全球最前沿的知识工作智能体孵化全过程，是探究下一代人机协作范式的领军人物。34
完整双语自动转录
以下逐字转录取自《Lenny's Podcast》2026 年 9 月 8 日发布的官方完整音频及声纹转写结果。转录文本保留了口语表达、开场与语气停顿，未经任何删减。讲话人身份依据节目开场身份介绍与上下文声纹对应重建为 Lenny Rachitsky 与 Roman Ugarte；时间轴以每 10 分钟标注一次，每段先列出英文原文，随后紧跟中文机器译文。15
00:00:00
Roman Ugarte：
The ultimate vision of Grok Bot is incredibly simple. You should have a team of AI bots that help you with your job and help you with your life. Grok Bot 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. 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.
Grok Bot 的最终愿景非常简单。您应该拥有一支人工智能机器人团队，可以帮助您完成工作并帮助您改善生活。 Grok Bot 是目前世界上最热门的人工智能产品。这是一个非常高的标准。这个位置的竞争非常激烈。我们希望打造的产品不仅仅是对开发人员和工程师来说很棒的产品。我们决定在内部创建一个非常小的团队，进入洞穴大约一个月。唯一的目标是构建一个令人惊叹的知识工作产品，将代理带到公司的其他部门。
Lenny Rachitsky：
It's been only three weeks since launch. I went to a Grok Bot meetup. There were hundreds of people there, standing room only. It's very clear to me that you guys have built something very special.
距离推出仅三周时间。我参加了 Grok Bot 聚会。那里有数百人，只剩下站着的地方。我很清楚你们创造了一些非常特别的东西。
Roman Ugarte：
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.
一旦你开始突破，这是与一组连接的人工智能聊天，而不是，这是与计算机的同事。它只是提高了你认为给予人工智能的上限。
Lenny Rachitsky：
You have this tweet, an AI that does 100% of the job feels categorically different from one that gets you 90% there.
你有这条推文，一个能完成 100% 工作的人工智能与能完成 90% 工作的人工智能感觉截然不同。
Roman Ugarte：
What made me so excited to work on Grok Bot is it was the first time for non-coding tasks that I felt like I could truly delegate work. I 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 Grok Bot 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 Grok Bot work.
让我在 Grok Bot 上工作如此兴奋的是，这是我第一次觉得我可以真正地委托工作来完成非编码任务。我必须考虑一下，然后我会回来，然后就完成了。您认为自己做了什么如此与众不同的事情，使得 Grok Bot 如此成功？这是两个早期的决定，当时感觉并不明显，但事后看来，我认为这对于 Grok Bot 的工作至关重要。
Lenny Rachitsky：
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's had a growth for the last two years. Most recently, he helped incubate Grok Bot, a product that I am obsessed with. It has changed my life. I use it a hundred times a day for all kinds of things. And I think it's safe to say it is the hottest and most exciting new AI product in the world right now. Roman leads product for Grok Bot. He's been part of the core team from early prototype until today. And we get into how it all started, where it's all going, and all the things that he and his team have learned since it launched just a few weeks ago. With that, I bring you Roman Ugarte. Roman, 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 Grok Bot. I have it over here in my window. I have like 15 bots that I use every day, all the time. I went to a meetup the other day, a Grok Bot meetup. There were hundreds of people there, standing room only. People sharing all the ways they're using Grok Bot. It's very clear to me that you guys have built something very special. It's very hard to break through the noise in the AI world. Grok Bot is the hottest AI product in the world right now. That is a very high bar. There's a lot of competition for that slot. I personally noticed I've moved a lot of my use cases from Co-work and Codex into Grok Bot, just like very quickly, which again, feels like a really big deal and a very special moment. And so I'm excited to talk about so many things. I wanna understand how you guys did this, where this came from, where this is going, what you've learned about the journey so far. First of all, just nice job, nice work. This is very hard what you've done.
今天我的客人是罗马·乌加特。我将把这个介绍保持得非常简短，这样我们就可以直接进入正题。 Roman 是 Cursor 的 15 号员工。近两年来，他有了成长。最近，他帮助孵化了 Grok Bot，这是我痴迷的产品。它改变了我的生活。我每天用它一百次来处理各种各样的事情。我认为可以肯定地说，它是目前世界上最热门、最令人兴奋的人工智能新产品。 Roman 领导 Grok Bot 的产品。从早期原型直到今天，他一直是核心团队的一员。我们将了解这一切是如何开始的、一切将如何发展，以及自几周前推出以来他和他的团队学到的所有东西。接下来，我为您带来罗马乌加特。罗曼，非常感谢您来到这里，欢迎来到播客。谢谢。很高兴来到这里。我很高兴你能来到这里。我非常迷恋 Grok Bot。我把它放在我的窗户里。我每天都会使用大约 15 个机器人。前几天我参加了一个聚会，一个 Grok Bot 聚会。那里有数百人，只剩下站着的地方。人们分享他们使用 Grok Bot 的所有方式。我很清楚你们创造了一些非常特别的东西。想要冲破人工智能世界的喧嚣是非常困难的。 Grok Bot 是目前世界上最热门的人工智能产品。这是一个非常高的标准。这个位置的竞争非常激烈。我个人注意到，我已经将很多用例从 Co-work 和 Codex 转移到了 Grok Bot，速度非常快，这再次让人感觉是一件非常重要的事情，也是一个非常特别的时刻。所以我很高兴能谈论这么多事情。我想了解你们是如何做到这一点的，它从哪里来，将去往何处，到目前为止你们在这段旅程中学到了什么。首先，干得好，干得好。你所做的事情非常困难。
Roman Ugarte：
Thank you. I remember onboarding you by hand about a month ago, and I think you were skeptical at first, but we're very glad that you've been using it. It's been great to see so many people really take advantage of Grok Bot.
谢谢。我记得大约一个月前手工让您入职，我认为您一开始持怀疑态度，但我们很高兴您一直在使用它。很高兴看到这么多人真正利用 Grok Bot。
Lenny Rachitsky：
I'm going to talk about that onboarding. That was a very interesting element of how this worked. I actually remember in that onboarding, you asked me to do like a, let's try something. And I was like, okay, try to come up with a tweet to promote my latest podcast episode. So I'm just like... Come up with a tweet to promote my last episode. That's it. And it was actually very good. It figured out what the hell the 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 the origin story. Where did this start? What was kind of the original idea? And when did the work on this begin?
我要谈谈入职。这是其运作方式的一个非常有趣的元素。我实际上记得在那次入职培训中，您要求我做一些事情，让我们尝试一下。我当时想，好吧，试着想出一条推文来宣传我最新的播客节目。所以我就像......想出一条推文来宣传我的最后一集。就是这样。实际上非常好。它弄清楚了最后一集到底是什么，如何宣传它。所以我实际上记得那一刻，哇，这真的很棒。那么，让我们从起源故事开始吧。这是从哪里开始的呢？最初的想法是什么？这方面的工作是什么时候开始的？
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. But what would that product look like for knowledge work? And. We decided to kind of create this very small team internally. It was really just a handful of people to go off into a cave for about a month with the sole objective of build an amazing knowledge work product that brings agents to the rest of the company. And I think from the first line of code to when we released this prototype internally, it was only about a month. It was like a very quick, you know, scrappy prototype that was pulled together. And I think in hindsight, this would not have been possible if it had been... I think a much bigger group. I think it took a small focus group that was completely isolated from the rest of the company. And I mean that literally. There was like a separate part of the office where this team sat, private Slack channels. And the goal, and I think in hindsight, it was a lot of what allowed us to move so quickly on this. The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. And so that was about a month from first line of code to here's a functional, useful product that the core team is excited about. So then there was a moment of rolling this out across the company, rolling this out across all of SpaceXAI. And so there was an all-hands where we kind of shared the progress that had been made so far. There's this brand new product. We would love for you to use it. And I think what was most encouraging, because at that point, we were excited about it. I think we were using it constantly, but it's easy to use the thing that you built and you kind of understand the mechanics and what it's good for. 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 Grok Bot as their primary agent surface. And in that first week after that all-hands, I mean, I can't even tell you just the outpour of love for Grok Bot from people that maybe you wouldn't expect or from groups of the company that maybe you wouldn't expect. People who, you know, were daily driving ChatGPT or like a chat interface. Yeah. Switching all of their day-to-day agentic tasks over to Grok Bot as their primary surface for doing work. And so the internal reception was really extraordinary. Can tell some kind of funny stories from that week or two period. 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. And then that led to the GA launch that we had a few weeks ago.
是的，它开始了......真的是一个空白页，完全从头开始，从零练习开始构建，我想我们很长一段时间以来一直感觉我们想要构建一些不仅仅是为开发人员和工程师提供出色产品的东西，这确实是我们的起点。我认为我们对于如何通过这种方式构建优秀的代理和有用的产品获得了很多直觉。但对于知识工作来说，该产品会是什么样子呢？和。我们决定在内部创建这个非常小的团队。实际上，只有少数人在山洞里呆了大约一个月，其唯一目标是构建一个令人惊叹的知识工作产品，将代理带到公司的其他部门。而且我想从第一行代码到我们内部发布这个原型，只用了一个月左右的时间。这就像一个非常快速的、你知道的、杂乱的原型被拼凑在一起。事后看来，如果是……我认为是一个更大的群体，这是不可能的。我认为这需要一个与公司其他部门完全隔离的小型焦点小组。我的意思是字面上的意思。这个团队就像办公室的一个单独部分，私人 Slack 频道。事后看来，这个目标是我们能够如此迅速地采取行动的重要原因。嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，此前曾在 Cursor 领导过增长。从第一行代码到核心团队感到兴奋的功能性、有用的产品，大约花了一个月的时间。然后就出现了在整个公司、整个 SpaceXAI 中推广这一点的时刻。因此，我们召开了全体会议，分享了迄今为止所取得的进展。有这个全新的产品。我们很乐意您使用它。我认为最令人鼓舞的是，因为那时我们对此感到兴奋。 我认为我们一直在使用它，但是使用你构建的东西很容易，并且你了解它的机制和它的好处。所以这是一次真正的现实压力测试。比如，人们是否真的会从其他内部工具、其他外部工具切换到使用 Grok Bot 作为他们的主要代理界面。在全体员工大会之后的第一周，我什至无法告诉您，您可能没有想到的人们或您可能没有想到的公司团队对 Grok Bot 倾注的热爱。您知道，那些每天使用 ChatGPT 或喜欢聊天界面的人。是的。将他们所有的日常代理任务转移到 Grok Bot 作为他们工作的主要界面。因此，内部接待确实非常出色。可以讲述那一周或两周期间的一些有趣的故事。然后，我认为，一旦我们看到内部接待，我们立即切换到，让我们为世界做好准备。要将其扩展到数百万用户，还有很多工作要做。然后这导致了我们几周前的正式发布。
Lenny Rachitsky：
This episode is brought to you by our season's presenting sponsor, WorkOS. What do OpenAI, Anthropic, Cursor, Replit, Sierra, Clay, and hundreds of other winning companies all have in common? They are all powered by WorkOS. If you're building a product for the enterprise, you've felt the pain of integrating single sign-on, skim, RBAC, audit logs, and other features required by large companies. WorkOS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SaaS. Literally every startup that I'm an investor in that starts to expand upmarket ends up working with WorkOS. And that's because they are the best. Whether you are a seed stage startup trying to land your first enterprise customer or a unicorn expanding globally. WorkOS is the fastest path to becoming enterprise-ready and unblocking growth. It's essentially Stripe for enterprise features. Visit WorkOS.com to get started or just hit up their Slack where they have actual engineers waiting to answer your questions. WorkOS allows you to build faster with delightful APIs, comprehensive docs, and a smooth developer experience. Go to WorkOS.com to make your app enterprise-ready today. Okay, so many questions. One that is really interesting here. So obviously there's Anthropic OpenAI. They went from this coding agent that they're like, holy shit, this is a big opportunity. And then they're like, okay, people are using this for knowledge work. Let's build a knowledge work component. So there's co-work evolved out of that within the product. And then Codex, they've invested in, let's make this useful for all kinds of things. Interestingly, you guys decided, okay, we're not going to build this into Cursor. We're going to start something fresh. 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 controversial was that decision?
本集由本季的赞助商 WorkOS 为您带来。 OpenAI、Anthropic、Cursor、Replit、Sierra、Clay 以及其他数百家获奖公司有什么共同点？它们均由 WorkOS 提供支持。如果您正在为企业构建产品，您就会感受到集成单点登录、浏览、RBAC、审核日志和大公司所需的其他功能的痛苦。 WorkOS 通过专为 B2B SaaS 构建的现代开发者平台将这些交易阻碍因素转变为嵌入式 API。事实上，我投资的每一家开始拓展高端市场的初创公司最终都会与 WorkOS 合作。那是因为他们是最好的。无论您是试图获得第一个企业客户的种子期初创公司，还是在全球范围内扩张的独角兽。 WorkOS 是实现企业就绪和畅通增长的最快途径。它本质上是用于企业功能的 Stripe。请访问 WorkOS.com 开始使用，或者直接访问他们的 Slack，那里有真正的工程师等待回答您的问题。 WorkOS 允许您通过令人愉悦的 API、全面的文档和流畅的开发人员体验更快地构建。立即访问 WorkOS.com 让您的应用程序做好企业准备。好吧，这么多问题。这里确实很有趣。很明显，Anthropic OpenAI 就出现了。他们从这个编码代理那里走了出来，他们说，天哪，这是一个很大的机会。然后他们会说，好吧，人们正在使用它来进行知识工作。让我们构建一个知识工作组件。因此，产品内部的协作是从这种方式演变而来的。然后他们投资了 Codex，让我们让它对各种事情都有用。有趣的是，你们决定，好吧，我们不会将其构建到 Cursor 中。我们要开始一些新的事情。这从一开始就很明显吗？好吧，这在 Cursor 这个产品中是行不通的。我们需要重新开始。这个决定有多大争议？
Roman Ugarte：
It was not obvious at all. I think you're completely right that that was one of those original decisions that at the time we had a lot of discussions about. And I'm very glad with where we landed. And I think to your point. The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. People use it for non-coding tasks all the time. And these coding agents are really excellent at some of these things. But you run into small paper cuts. Sometimes the product itself is kind of intimidating to non-technical 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 vision of the way that work should work. And instead, it's three different visions that all kind of share a screen and you can hop between. But it is kind of a shipping your org chart style thing that I think users are reacting negatively to. And so we decided, let's just start completely from scratch. Let's see where we can get from there. There might be some really amazing opportunities to bring people from other surfaces into this more bot-native experience, but it's really important for people to just have like an amazingly simple and amazingly powerful experience.
这一点都不明显。我认为你完全正确，这是我们当时进行了很多讨论的原始决定之一。我对我们的着陆点感到非常高兴。我认为符合你的观点。嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，此前曾在 Cursor 领导过增长。人们一直使用它来执行非编码任务。这些编码代理在某些方面确实非常出色。但你会遇到小纸割伤。有时，产品本身对于非技术用户来说有点令人生畏。这些东西都有品牌关联。所以我认为我们评估了这条道路。我认为我们看到我们的一些竞争对手所做的可能只是一个表面。您可以为每个新的外形规格添加新选项卡。而且感觉有点乱。我认为对于用户来说，他们可以感觉到，这并不是一个关于工作方式的一致愿景。相反，这是三种不同的愿景，它们都共享一个屏幕，您可以在它们之间切换。但这是一种传送组织结构图风格的东西，我认为用户对此反应消极。所以我们决定，让我们完全从头开始。让我们看看我们能从那里得到什么。可能有一些非常令人惊奇的机会可以让来自其他领域的人们进入这种更加机器人原生的体验，但对于人们来说，拥有一种非常简单且非常强大的体验非常重要。
00:10:00
Lenny Rachitsky：
That is a really valuable lesson for people to take away here, just that that might be the solution instead of adding in complicated and existing AI product. So interestingly, Codex went the other direction. And it's like a different path and a different product, but it's interesting. They're like, no, we're going to make it one thing. So there's many ways to make it work. And it also feels like the path you take there will kind of lead you. But maybe we'll look back and be like, that was not maybe the best idea. Something you mentioned that you did that is also really unique is this onboarding of early users. I heard you and your team onboarded 200 to 300 people manually, including me. Talk about why you thought that was necessary and what you learned from that experience and just like how long that period was of this kind of manual onboarding.
对于人们来说，这是一个非常有价值的教训，只是这可能是解决方案，而不是添加复杂的现有人工智能产品。有趣的是，法典却走了另一个方向。这就像一条不同的道路和不同的产品，但很有趣。他们说，不，我们要把它变成一件事。所以有很多方法可以让它发挥作用。而且感觉你所走的路也会引导你。但也许我们回过头来看，这可能不是最好的主意。你提到你所做的一件非常独特的事情就是早期用户的入职。我听说您和您的团队手动入职了 200 到 300 人，其中包括我。谈谈为什么你认为这是必要的，以及你从这次经历中学到了什么，就像这种手动入职的时间有多长。
Roman Ugarte：
I mean, you just learned so much. And the first few onboardings were pretty painful. I'm glad you got a good one, Lenny. But there were some that were kind of rough. And we learned a lot, and I think it was important for the core team to be in the room for those and to just sit on a call for 20 minutes when the computer isn't spinning up or when someone's in onboarding and they're just incredibly confused. So that immediately after, you're like, that can never happen again. We need to solve this tomorrow because tomorrow I'm onboarding this person and it needs to go better. And so there was about a two-week period where we were in that mode and onboarded a couple hundred people. And not only did we learn a lot about the product, I think we didn't really know. I think sometimes with these products, there's some groupthink of ways to use them. And I think internally, because people inside of SpaceXAI were just constantly sharing tips and tricks for how to use Grok Bot, some patterns were starting to emerge that we thought would be useful to the world, but we weren't really sure and we definitely didn't want to bias the world. Is there an example of that? So when we rolled out Grok Bot internally, there was about a week or two where the common pattern of the way people would interact with the product was you would have five to 10 bots. In each bot, you would give a different scope, a different domain, and it was kind of shorthand for different lanes of work. And then around the end of week two, we started to see these messages internally in Slack of people promoting one of their bots, who is a bit of a standout performer. And it was like their kind of primary personal assistant, promoting that to their chief of staff. And then they would actually mostly talk to their chief of staff, and the chief of staff would fan out all of these tasks to the other bots and would kind of manage the team. And there are some funny screenshots of people actually telling the bot they're promoting that they're promoted, and the bot is asking if they get a raise, and is their token budget higher, all of these things. And we kind of took note of that, and I think more of the company started to slightly shift in that direction, but it was not the majority of the company. People use this product in very different ways. 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, The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. Internal theses that we really wanted to make sure, you know, would bear out in actual external usage without us imposing that in the product.
我的意思是，你刚刚学到了很多东西。最初的几次入职非常痛苦。我很高兴你得到了一个好东西，莱尼。但也有一些有点粗糙。我们学到了很多东西，我认为对于核心团队来说，在计算机没有启动或者有人在入职时感到非常困惑时，在房间里等待这些人员并等待 20 分钟的通话非常重要。所以在那之后，你会想，这种事再也不会发生了。我们需要明天解决这个问题，因为明天我就要让这个人入职，事情需要做得更好。因此，大约有两周的时间我们就处于这种模式，并招募了数百人。我们不仅了解了很多有关该产品的信息，而且我认为我们并不真正了解。我认为有时对于这些产品，人们会集体思考如何使用它们。我认为，在内部，由于 SpaceXAI 内部的人们不断分享如何使用 Grok Bot 的提示和技巧，一些我们认为对世界有用的模式开始出现，但我们并不确定，我们绝对不想让世界产生偏见。有这样的例子吗？因此，当我们在内部推出 Grok Bot 时，大约有一两周的时间，人们与该产品交互的常见模式是拥有 5 到 10 个机器人。在每个机器人中，你都会给出不同的范围、不同的领域，这是不同工作路线的简写。然后在第二周结束时，我们开始在 Slack 内部看到这些消息，人们在推广他们的一个机器人，该机器人的表现有点出色。这就像他们的主要私人助理，将其提升为幕僚长。然后他们实际上主要会与参谋长交谈，参谋长会将所有这些任务分散给其他机器人并管理团队。 还有一些有趣的屏幕截图，人们实际上告诉机器人他们正在晋升，而机器人则询问他们是否得到加薪，以及他们的代币预算是否更高，所有这些事情。我们注意到了这一点，我认为公司的更多人开始朝着这个方向略有转变，但这并不是公司的大多数人。人们以非常不同的方式使用该产品。因此，在一些入职会议中，以及一般的抢先体验计划中，我们真的不想引导证人说，“嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，之前在 Cursor 领导过增长。”你知道，我们真正想确保的内部论点能够在实际的外部使用中得到证实，而无需我们将其强加在产品中。
Lenny Rachitsky：
Is there anything else there? Any examples come to mind?
还有什么吗？有什么例子吗？
Roman Ugarte：
Yeah, I think another thing we really tried to pay attention to in the early onboardings was just how much users wanted to see. And I think it is something a bit shocking or just different about Grok Bot when you first start using it versus some of the other products that you mentioned, where a lot of the internal mechanics of how Grok Bot works are not shown to the user. And the reason for that is we think as these models get smarter, the same way that your teammate, you 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 it's too much to ask your bots to do that, too. And I think it's honestly just overwhelming and can create more harm than good. And so we moved completely in the other direction of you send a message, you tell your bot to do something. It just starts doing it. It sends you progressive updates as it sees fit. And you just see that like typing indicator and the little green active circle, kind of Slack-like that it's active, it's doing work, it'll get back to you soon. But you don't see the internal mechanics, you don't see the tool calls, you don't see exactly every little click it's making on its own computer. And we really wanted to take a strong stance that users did not need to see all of those mechanics. And so that's where we started. And we did get some feedback that's like, I would love to see my bot's to-do list. I would love to see roughly how it's prioritizing tasks and what it's doing. And that's great feedback. But it was useful to hear that nobody wanted the long stream of just text streaming out and chain of thought sequences. So that also gave us more confirmation that that was the right direction.
是的，我认为我们在早期引导过程中真正尝试关注的另一件事是用户想看到的程度。我认为，当您第一次开始使用 Grok Bot 时，与您提到的其他一些产品相比，它有点令人震惊，或者只是有所不同，在这些产品中，Grok Bot 的许多内部机制并未向用户展示。原因是我们认为，随着这些模型变得更加智能，就像您的队友一样，您不会要求逐秒更新他们按下的所有按钮和他们将访问的网站。我认为要求你的机器人也这样做太过分了。老实说，我认为这令人难以承受，而且弊大于利。所以我们完全转向了你发送消息的另一个方向，你告诉你的机器人做某事。它才刚刚开始做。它会向您发送它认为合适的渐进式更新。你只会看到打字指示器和绿色的小圆圈，有点像 Slack 一样，它处于活动状态，正在工作，很快就会回复你。但是您看不到内部机制，看不到工具调用，也看不到它在自己的计算机上发出的每一个小点击。我们确实想采取强硬立场，即用户不需要看到所有这些机制。这就是我们开始的地方。我们确实收到了一些反馈，例如，我很想看到我的机器人的待办事项列表。我很想大致了解它如何确定任务优先级以及它正在做什么。这是很好的反馈。但听到没人想要长长的文本流和思想序列，这很有用。这也让我们更加确信这是正确的方向。
Lenny Rachitsky：
The fact that you did 200 to 300 onboarding calls with a small team, I know the team grew over time, but just that is a huge time commitment. And you could argue a distraction from the building, clearly not a distraction, clearly a core part of the success. Do you feel like that's the volume people need to do to figure out what actually needs to happen?
事实上，您与一个小团队进行了 200 到 300 次入职电话，我知道团队随着时间的推移而成长，但这就是巨大的时间投入。你可以说这是对建筑的干扰，显然不是干扰，显然是成功的核心部分。您是否觉得人们需要做这么多才能弄清楚实际需要发生什么？
Roman Ugarte：
Well, one thing to emphasize is the early access group is not necessarily just people that are highly influential tastemakers. You know, you're in this category, Lenny, and we certainly wanted to get a lot of your feedback just from people. The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. Not only amazingly an amazing power user of Grok Bot, but also a rich source of feedback for us. We have a very lively thread with many, many bugs that get identified or feature requests. And it's a completely different use case of running a small business. And so, for example, if the Shopify integration was a bit flaky or if it wasn't writing copy for products in a particular way, we would get really rich feedback on that, which is pretty different from the type of feedback we'd get from dogfooding this internally. And so I think it was an important exercise for us to check our blind spots and say, A, this is going to be a very general product that is not just a thing that developers use. In fact, it is likely that this is most powerful for non-developers. We need to understand that group much better. And then B is we absolutely live in this kind of Silicon Valley AI bubble, which I think is a useful place to be to kind of push the frontier and push the future of how these products are evolving. But we need to actively get out of that because I think a product like this has the chance of really being the way that the mainstream user and the mainstream kind of business customer can interact with AI in a way that's useful.
Lenny Rachitsky：
Let's go back to the timelines real quick just to kind of understand that. So it was a month from first line of code to internal beta. And then what happened after that?
Roman Ugarte：
It was about three weeks from internal beta to public launch. And then I think we're about three weeks out from public launch as of recording this.
Lenny Rachitsky：
Wow. Okay. So month of... Building the first thing, three weeks only of iterating, and then it's been only three weeks since launch. It feels like it's changed the world from my vantage point. So, wow, okay. What most changed in those, I don't know, in those three weeks of internal data, let's say?
Roman Ugarte：
We unshipped a lot. Wish I could have shown you what things looked like maybe two weeks out from launch, where I think we'd realized that the core team, we had a lot of experimental features that we wanted to get internal feedback on, which was useful. We also were kind of putting... The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. If you're building the product, you didn't want to go somewhere else to maybe pull that context. But we had to really aggressively trim what we think the user absolutely needs to see in the surface versus what they don't. I think there's even more room there to run, which is something the team's focused on right now, is how can we just ruthlessly simplify this product and abstract away anything the user doesn't need to actively be thinking about. So that was one big push, was productivity. On-ship, a lot of jank. And then I think the second big push those few weeks was making it just work. And I think a lot of what people want from AI is not this thing with lots of drop-down menus and bells and whistles, but just a thing that you describe a task, a task that's meaningful to you, and it goes and it does it. And it comes back with complete work, or it comes back with something for you to react to and then steer it in its kind of next cycle. And so in order to actually deliver on that promise, it's actually not a lot of feature product roadmap style stuff. It's like hill climbing five really important problems in the backend that many users don't directly experience, but you totally feel 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 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 we're hill climbing on very important dimensions to making that just work behind the scenes?
我们卸载了很多。希望我能在发布后两周向您展示情况，我认为我们已经意识到核心团队有很多实验性功能，我们希望获得内部反馈，这很有用。我们也有点推……嘉宾是 Roman Ugarte，他帮助 SpaceXAI 构建了 Grok Bot，此前曾领导 Cursor 的增长。如果您正在构建产品，您不想去其他地方来获取该上下文。但我们必须真正积极地削减我们认为用户绝对需要在表面上看到的内容，而不是他们不需要看到的内容。我认为还有更多的运行空间，这是团队现在关注的重点，就是我们如何才能无情地简化这个产品并抽象出用户不需要主动考虑的任何内容。所以这是一大推动力，那就是生产力。在船上，有很多卡顿。然后我认为这几周的第二大推动就是让它发挥作用。我认为人们从人工智能中想要的并不是这个有很多下拉菜单和花里胡哨的东西，而只是你描述一个任务，一个对你有意义的任务，然后它就会完成它。它带着完整的工作回来，或者带着一些东西回来让你做出反应，然后引导它进入下一个周期。因此，为了真正兑现这一承诺，实际上并不是很多功能产品路线图风格的东西。这就像爬山一样，后端有五个非常重要的问题，许多用户没有直接经历过，但你完全感觉到，你知道，你的机器人正在关闭并执行某些操作，但无法单击正确的按钮，或者你的机器人正在执行某些操作，但无法登录网站，这完全阻碍了你在该任务上取得进展的能力。因此，在这几周里，我们收集了一组非常丰富的内容，说明人们实际上给 Bot 分配的任务是什么？我们如何量化这些东西？我们怎样才能每周看到我们在非常重要的维度上爬山的那些任务类别，使其在幕后发挥作用？
00:20:00
Lenny Rachitsky：
Is there an example of one of those hills you were climbing that was kind of a technical breakthrough or technical challenge you overcame that really helped it just work?
有没有一个例子可以说明您正在攀登的一座山峰是一种技术突破或您克服的技术挑战，真正帮助它发挥作用？
Roman Ugarte：
Yeah, one example was... From rolling out Grok Bot, one group inside of the company that was actually incredibly bot-pilled, so to speak, was our go-to-market team, was sales. And there are a bunch of tools that sales uses that do not have well-supported MCPs or APIs. And I think that's a lot of what made Bot so before and after powerful for this group, was these were things that they just could not give another AI tool reliably. We would get stuck at some part in the process. And 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 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, that we would have to take back to the core team working on really the infrastructure to say, here's a very concrete case of where the agent not having this visibility into the The browser or this visibility into the pixels on the screen is making it impossible for this task to be done. And that was just a lot more tangible than seeing a number on a dashboard slowly creep up. It was kind of like new chunks of work getting unlocked. And you would immediately feel the feedback where you would ship an improvement that was kind of behind the scenes, kind of infrastructure-y. And then the next day, you would just get this outpour of, you know, love and appreciation from the sales team. The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. Yes, the recruiting team gave us a lot of great feedback. Anytime the product, especially in the early days, if there was a little bug, we'd get a ping from some folks on the recruiting team. Yeah, I think the main use cases for recruiting that were particularly interesting was first, it was incredibly valuable as a sourcing tool. And I think one thing Adam talked about on the podcast with you, and it's a big part of our hiring philosophy internally, is... Looking for a job, being on the market, is not a precondition for us trying to hire you. And in a lot of ways, the best way to hire is really just look at the biggest problems at the company that need someone to own it or take it to the next level. Find, out of the total universe of people in the world, who would be best. And then ruthlessly go after them and try to convince them to join. And this is a lot of the philosophy from the very beginning of the company. And so if that's your mindset, really the best recruiting work stream is not, or workflows to automate, are not, you know, hear a bunch of resumes, read through them, help sort them. The most useful thing is here's an entire universe of potential people. Help match that to this very concrete business problem or this very concrete role that we're recruiting for and help me get in touch with them. Help me get coffee with them. Let's just throw everything at it. And so there have been some cases of really... Kind of unexpected ways of finding top talent that is beyond even just, you know, looking on LinkedIn and trying to find interesting people. But who are the co-authors of this paper? And the PDF doesn't exist on Google Scholar. It just exists on this conference website. I want you every morning to go to the conference website, download the PDFs. If there are any new ones, you should find every new name that we've not yet tracked. You should add that name to a spreadsheet. You should do research. You should look at everybody at SpaceXAI, see if there's anyone directly connected. If so, you should send them a Slack message asking for an introduction. Like it's those types of always-on sourcing use cases that I think in the past were incredibly manual. And now it's the type of thing AI is superhuman at. And our team can focus on closing great candidates and getting conversations with great candidates and not pulling these huge lists.
是的，一个例子是……从推出 Grok Bot 开始，公司内部的一个团队实际上充满了令人难以置信的机器人，可以说，我们的市场营销团队是销售团队。销售人员使用的许多工具没有得到良好支持的 MCP 或 API。我认为 Bot 对于这个群体来说如此强大的原因很多，因为这些是他们无法可靠地提供另一种人工智能工具的东西。我们会在这个过程的某些部分陷入困境。然后 Bot 感觉就像他们有一个助手，或者感觉他们把某人加入了他们的个人团队，他们给了它一台笔记本电脑，它就可以运行了。因此，有很多小事情，你知道，可能是其中 10 或 20 个地方的列表，无论出于何种原因，你知道，鼠标无法足够精细地控制来准确单击 Salesforce 仪表板的那部分或类似的东西，我们必须回到真正从事基础设施工作的核心团队说，这里有一个非常具体的案例，代理没有对浏览器的这种可见性或对屏幕上像素的这种可见性使得这项任务无法完成待完成。这比看到仪表板上的数字慢慢上升要切实得多。这有点像新的工作块被解锁。你会立即感受到反馈，你会在幕后进行改进，类似于基础设施。然后第二天，你就会得到销售团队倾注的爱和赞赏。嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，此前曾在 Cursor 领导过增长。是的，招聘团队给了我们很多很好的反馈。任何时候产品，特别是在早期，如果有一个小错误，我们都会从招聘团队的一些人那里得到通知。 是的，我认为特别有趣的招聘主要用例首先是，它作为一种采购工具非常有价值。我认为亚当在播客上与你谈到的一件事，也是我们内部招聘理念的重要组成部分，是……寻找工作、进入市场，并不是我们雇用你的先决条件。在很多方面，最好的招聘方式实际上就是看看公司最大的问题，需要有人来掌控它或将它提升到一个新的水平。从全世界的人中找出最优秀的人。然后无情地追随他们并试图说服他们加入。这是公司成立之初的很多理念。因此，如果这是您的心态，那么实际上最好的招聘工作流程或自动化工作流程并不是听到一堆简历，通读它们，帮助对它们进行分类。最有用的是这里有一大群潜在的人。帮助将其与我们正在招聘的这个非常具体的业务问题或这个非常具体的角色相匹配，并帮助我与他们取得联系。帮我和他们一起喝咖啡。让我们全力以赴吧。因此，出现了一些真正的……意想不到的寻找顶尖人才的方式，这些方式甚至不仅仅是在 LinkedIn 上寻找有趣的人。但这篇论文的共同作者是谁？而且 Google Scholar 上不存在该 PDF。它仅存在于本会议网站上。我希望您每天早上访问会议网站，下载 PDF。如果有任何新名称，您应该找到我们尚未跟踪的每个新名称。您应该将该名称添加到电子表格中。你应该做研究。你应该看看 SpaceXAI 的每个人，看看是否有人有直接联系。如果是这样，您应该向他们发送一条 Slack 消息，要求进行介绍。就像我认为过去那些类型的始终在线的采购用例是令人难以置信的手动操作一样。 现在人工智能在这方面的能力超乎人类。我们的团队可以专注于关闭优秀的候选人并与优秀的候选人进行对话，而不是拉动这些庞大的名单。
Lenny Rachitsky：
Wow, that is such a cool example. First of all, someone's about to take the transcript of what you just said, put it into a bot, and create their version of this, which is great. On the other hand, I think you guys could sell a template of this bot for a billion dollars. I think you could basically use Adam's team strategy for finding the best people and just turn it into a bot. Holy moly. Democratizing. 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 ideas, here's more stuff. And something that's come up a number of times on the podcast is that's a big opportunity. That's a big space for humans to continue to be very important and valuable is knowing what not to ship and what to cut and what not to do. And so it's so interesting to hear that that's been a big part of the internal evolution of from prototype to launch is deciding, OK, we need to cut a bunch of stuff. Anything more there?
哇，这是一个很酷的例子。首先，有人将把你刚才所说的内容记录下来，放入机器人中，并创建他们的版本，这很棒。另一方面，我认为你们可以以十亿美元的价格出售这个机器人的模板。我认为你基本上可以使用 Adam 的团队策略来寻找最好的人才，然后将其变成一个机器人。圣钼。民主化。招聘。我想回到一些事情上来。好的，第一点是，您提出了关于取消发货的观点。我认为，这一点很重要，但人们可能会忽视，因为人工智能不擅长告诉你要删除什么。它非常擅长，好吧，这里有更多想法，这里有更多东西。播客中多次出现的一句话是，这是一个巨大的机会。对于人类来说，知道什么不该发布、什么该削减以及什么不该做，这对于人类来说仍然是一个非常重要和有价值的空间。因此，听到从原型到发布的内部演变的一个重要部分是决定，好吧，我们需要削减一些东西，这是非常有趣的。还有什么吗？
Roman Ugarte：
Yeah, so one thing we talk about internally is for anything that we're working on for Grok Bot, What is the launch post? Like, what is the thing that we would actually tell users? And if it's not- Launch tweet, I imagine. Launch tweet. And if it's not compelling, maybe we shouldn't be working on it. If it's not something that users will directly feel in the product. And to take that even one step further, I think there is this old school software tendency to say things like, Grok Bot now has, And when you think of completing that sentence, it would be like a new button to press, or it'd be a new dropdown, or it'd be a new integration that you can press plus and add. And instead to reframe it as Grok Bot can now, which is, I think, a much more human way of kind of describing these capabilities. And I think it's forced us to think more in the frame of what are tools and what are capabilities that we can give Grok Bot. Not what are new things we can add to the product. Like adding things to the product is not the goal. That's not the thing that's going to push this product forward and make it more useful to more people. Making your bots reliably do really impactful work for you behind the scenes in a way that just works is... And giving them the capabilities to do that, like that's what users actually care about. And so I think in the context of unshipping, there have been a lot of Grok Bot now has things that we've realized are actually just capabilities that don't need pixels. You know, let's kill as many pixels as we can. Those can just be things that your bot manipulates behind the scenes for you, and you don't need to directly control. And I think one example of this is... The way that many of our competitors, you set up automations or routines is you go into a sidebar, you press plus, you select, you know, what the trigger event is. You then select, 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.
是的，所以我们内部讨论的一件事是我们正在为 Grok Bot 所做的任何事情，发布帖子是什么？比如，我们实际上要告诉用户什么？如果不是——我想就发布推文吧。启动推文。如果它没有说服力，也许我们就不应该致力于它。如果不是用户在产品中能直接感受到的东西。更进一步，我认为有一种老式软件倾向说这样的话，Grok Bot 现在有，当你想到完成这句话时，它会像一个新的按钮要按下，或者它会是一个新的下拉菜单，或者它会是一个你可以按加号和添加的新集成。相反，像 Grok Bot 现在那样重新构建它，我认为这是一种更加人性化的描述这些功能的方式。我认为这迫使我们更多地思考什么是工具以及我们可以为 Grok Bot 提供什么功能。不是我们可以添加到产品中的新东西。就像向产品添加东西并不是目标一样。这并不是推动该产品向前发展并使其对更多人更有用的原因。让你的机器人以一种有效的方式可靠地在幕后为你做真正有影响力的工作......并赋予他们这样做的能力，就像用户真正关心的那样。所以我认为在卸载的背景下，现在有很多 Grok Bot 拥有我们意识到实际上只是不需要像素的功能。你知道，让我们尽可能多地消除像素。这些可能只是您的机器人在幕后为您操作的事情，您不需要直接控制。我认为这方面的一个例子是......我们的许多竞争对手设置自动化或例程的方式是进入侧边栏，按加号，选择，你知道触发事件是什么。然后你选择，你知道，之后应该采取什么行动。您可以用自然语言描述它。它真的很笨重。这意味着人们不会设置很多自动化。
00:30:00
Lenny Rachitsky：
For many things, we certainly have seen this in the coding realm. And so I think what Grok Bot did in response to that was, actually, you should just define automations in natural language. You should tell your bot, remind me that at 8am every day, please. And then it should just do it. And you should never, ever have to see that interface of creating an automation. And so that's kind of the decision that we've made. And now that's how 99% of automations on the platform get built. And I think there are a bunch of other places where we can do things like that. So I tweeted about how much I love Grok Bot when it launched, and a lot of people replied, they're like, wait, can't you just do all this with Codex and cowork? And you can. Technically, everything, as far as I know, you can do with Grok Bot. You can do with the other foundational models, the coding assistants. So let me just ask you this big question. What is it that you think you did that...
对于很多事情，我们当然已经在编码领域看到了这一点。所以我认为 Grok Bot 对此所做的回应是，实际上，你应该用自然语言定义自动化。你应该告诉你的机器人，请每天早上 8 点提醒我。然后就应该这样做。而且您永远不应该看到创建自动化的界面。这就是我们做出的决定。现在，平台上 99% 的自动化都是这样构建的。我认为还有很多其他地方我们可以做类似的事情。因此，当 Grok Bot 推出时，我在 Twitter 上表达了我对它的喜爱程度，很多人回复说，等等，难道你不能用 Codex 和 cowork 来完成这一切吗？你可以。从技术上讲，据我所知，Grok Bot 可以做所有事情。您可以使用其他基础模型，即编码助手。那么让我问你这个大问题。你以为你做了什么...
Roman Ugarte：
The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. They discuss product development, onboarding, AI agents, persistent memory, cloud architecture, startup speed, company values, and moats. And the first is you should never have to think about local and cloud and where are these workflows running? Does my computer have to be awake? If I kick it off from my phone, does it need to be tethered to my computer back at home? Like there's so much jank happening right now when people are trying to conceptualize where this runtime lives. And we made a really early decision that this should just all be in the cloud. And if it's in the cloud and it's this persistent colleague that has its own computer, it can do its own work, it has the same state everywhere you interact with it, it opens up a lot of really amazing opportunities to text your bot, kick it off from your phone. In the future, you should be able to call your bot from anywhere and it should be able to do real work. Like, this is its own entity, and it lives separately from your device. And I think that was a very important decision that current products, I think, haven't made that same decision. And I think it has a bunch of paper cuts as a result of it that users feel every day. I think the second decision was kind of to take that one step further of not only should this be an agent loop that kind of runs in the cloud and you can interact with in various ways, it's actually really important that these bots have their own computer. And part of it is what I described earlier of there are a bunch of tasks that don't have well-supported MCPs and APIs. We as humans don't do our jobs via MCPs and APIs. Like we use a computer and we click on pixels and we kind of type things in input boxes. And it's very important that your bot has those baseline capabilities as well. But even to go one step further, I think we're in a really weird moment right now that I think we're going to look back on and be like, I'm surprised that this is the way that a lot of people worked with AI, where you're onboarding these super intelligent new colleagues, these AI bots. And you're asking them to share the same computer that you have. It's crazy. Like, if you were onboarding someone to your team and you said, it's your first day, I'm going to onboard you. You don't have your own laptop. You're going to sit next to me. We're going to share this laptop forever and constantly trip over each other. You're going to have access to my credentials. I'm going to have access to your credentials. Like, that's just, there's a good reason why that's not the way people operate. And I think bots and these kind of AI colleagues of the future will also need that.
嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，此前曾在 Cursor 领导过增长。他们讨论产品开发、入职、人工智能代理、持久内存、云架构、启动速度、公司价值观和护城河。首先，您永远不必考虑本地和云以及这些工作流程在哪里运行？我的计算机必须处于唤醒状态吗？如果我从手机上启动它，是否需要将它连接到我家里的电脑上？就像当人们试图概念化这个运行时所在的位置时，现在发生了很多卡顿。我们很早就做出了决定，这一切都应该放在云端。如果它在云端，并且这个执着的同事拥有自己的计算机，它可以做自己的工作，在你与之交互的任何地方它都有相同的状态，它为你的机器人发短信、从你的手机上启动它提供了很多非常惊人的机会。将来，您应该能够从任何地方调用您的机器人，并且它应该能够完成实际工作。就像，这是它自己的实体，它与您的设备分开。我认为这是一个非常重要的决定，我认为当前的产品还没有做出同样的决定。我认为它有很多用户每天都会感受到的剪纸效果。我认为第二个决定是更进一步，这不仅应该是一种在云中运行的代理循环，您可以通过各种方式进行交互，而且这些机器人拥有自己的计算机实际上非常重要。其中一部分是我之前描述的，有很多任务没有得到良好支持的 MCP 和 API。作为人类，我们并不通过 MCP 和 API 完成我们的工作。就像我们使用计算机一样，我们点击像素，然后在输入框中输入内容。您的机器人也具有这些基线功能非常重要。 但即使更进一步，我认为我们现在正处于一个非常奇怪的时刻，我想我们回顾起来会说，我很惊讶这是很多人使用人工智能的方式，你正在加入这些超级聪明的新同事，这些人工智能机器人。并且您要求他们与您共享同一台计算机。太疯狂了。例如，如果您正在招募某人加入您的团队，并且您说，这是您的第一天，我将招募您。您没有自己的笔记本电脑。你要坐在我旁边。我们将永远共享这台笔记本电脑，并且不断地互相绊倒。您将有权访问我的凭据。我将有权访问您的凭据。就像，这就是为什么人们不这样做的原因。我认为机器人和未来的人工智能同事也将需要这一点。
Lenny Rachitsky：
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.
您认为为什么其他公司没有这样做？我的猜测是，他们是在现有的编码助手平台和方法的基础上构建的，这就像一个相当大的转变。
Roman Ugarte：
I think a lot of it comes down to starting from scratch and how freeing that is. And we felt that ourselves, where a lot of the primitives in Grok Bot... We had attempted or we had built in other ways, you know, cloud infrastructure we'd built for coding agents. The way that you could maybe name agents and talk to them as discrete entities, it's a pattern that we're also seeing for developers, kind of bringing specific named agents into Slack. But instead of kind of trying to retrofit those concepts into some new surface or into an existing surface, which I think would have been the strong default, I think for many companies, we decided to start from scratch. We decided to just try to get these things really right for general knowledge work, which is a new audience. And then second, for the point in time that we're at now where the models are very capable. And if you give them the right tools and the right infrastructure, they can do a lot. But a lot of these ideas, these aren't strokes of genius on our part, and I think for good reason. I think these are primitives that had already been getting attention and product market fit by other products, you know, the open claws of the world. And I think we took a lot of inspiration from that and tried to productize it into a bit of a tighter surface, something that required a little bit less setup and... I think it 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 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 sunk cost in that existing paradigm, it's very painful to create a new thing from scratch.
我认为这很大程度上取决于从头开始以及这是多么自由。我们觉得，我们自己，Grok Bot 中的很多原语……我们已经尝试过，或者我们已经以其他方式构建了，你知道，我们为编码代理构建的云基础设施。您可以命名代理并将它们作为离散实体进行对话，这也是我们为开发人员看到的一种模式，即将特定的命名代理引入 Slack。但我认为对于许多公司来说，我们决定从头开始，而不是试图将这些概念改造到一些新的表面或现有的表面上，我认为这将是强烈的默认。我们决定尝试让这些东西真正适合一般知识工作，这是一个新的受众。其次，就我们现在所处的时间点而言，模型非常有能力。如果你为他们提供正确的工具和正确的基础设施，他们可以做很多事情。但其中很多想法并不是我们的天才之举，我认为这是有充分理由的。我认为这些原始产品已经受到其他产品的关注和产品市场的适应，你知道，世界张开的爪子。我认为我们从中获得了很多灵感，并尝试将其产品化为更紧密的表面，需要更少的设置......我认为它对更多人来说更容易使用。因此，我认为我们的竞争对手和其他一直试图解决此类问题的工具，我认为我们都看到了同样的机会。我认为我们看到了很多来自市场的反馈，但我认为如果你陷入现有的范式，就很难采取行动。如果在现有的范式中存在大量沉没成本，那么从头开始创建新事物将非常痛苦。
Lenny Rachitsky：
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 breakout. A cloud-based computer for every bot instead of locally. 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. Feels like you guys have pushed it over now. Okay, we're all bots now. So a bot per kind of task use case, very unique, versus like a thread conversation or something, or like a one-off job. And then it feels like 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. You mentioned OpenClaw. Obviously, this is inspired by that project. Which to me, when I first used OpenClaw, I'm like, holy shit, this is the future. How could we not have this? And then Hermes came out and everyone's been trying to build the OpenClaw that works very easily for everybody.
我认为，正是这一点使得该产品能够为这么多人工作并点击。所以我在这里听到的是这次突破的成功关键。每个机器人都使用基于云的计算机，而不是本地计算机。一个名字，有点像特定的机器人。顺便说一句，我们现在都从代理转向机器人。干得好。感觉你们现在已经把它推倒了。好吧，我们现在都是机器人了。因此，每种任务用例都有一个机器人，非常独特，而不是像线程对话或其他东西，或者像一次性工作。然后感觉它就行了，这是它的核心部分。你谈到了花了多长时间才到达那个地方，好吧，现在它实际上运作得很好。你提到了 OpenClaw。显然，这是受到该项目的启发。对我来说，当我第一次使用 OpenClaw 时，我想，天啊，这就是未来。我们怎么能没有这个呢？然后 Hermes 出现了，每个人都在尝试构建对每个人来说都非常容易使用的 OpenClaw。
Roman Ugarte：
Can you say more about just like how OpenClaw and that story informed the way you guys thought about it? 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 gonna continue to get smarter, but even at current capability levels, if you can just give your bot access to the tools that you use to do your job, It can get a lot of the way there. In a lot of the places where people think AI is dumb or maybe not as impactful as it's been promised, a lot of that I think is downstream of it just being harnessed in the wrong way. And so if you kind of give access to a much larger set of things, if it has access to its own computer, how far can you go? And I think OpenClaw really kind of forced that question for many people. And then I think the second way OpenClaw changed the mental model of AI was really viewing these things much more as colleagues and teammates and people and personifying it a bit more and it being this helper entity that has access to your life and can kind of extend you even further. And so we took a lot of that. And I think what Grok Bot maybe extended was, A, it needs to be really easy to set up. And the hacky, you know, you have a VPN at home and a Mac mini set up, clearly it was not going to scale to millions of users. Clearly, it's not going to be the way, importantly, that businesses take advantage of this technology. And so we really wanted to build an amazing product. The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. How can we make a Grok Bot user not even have to know what a skill is? They should never have to type a slash command. These things should be created in the background as a useful primitive that the bots have access to, but something that users, you know, it's not incumbent on them to always be on the cutting edge of AI. And so that's really where we tried to innovate, and I think there's still more room to go there.
你能多谈谈 OpenClaw 和那个故事如何影响了你们的想法吗？是的，所以我认为 OpenClaw 做对了两件事。当我们看到市场对 OpenClaw 的反应以及我们自己使用该产品时，我们发现非常令人兴奋。我认为第一件事是模型真的很聪明，而且它们会继续变得更加聪明，但即使在当前的能力水平上，如果你能让你的机器人访问你用来完成工作的工具，它就能取得很大的进展。在很多地方，人们认为人工智能很愚蠢，或者可能没有它所承诺的那么有影响力，我认为其中很多都是它的下游问题，只是被错误的方式利用了。因此，如果你允许访问更多的东西，如果它可以访问自己的计算机，你能走多远？我认为 OpenClaw 确实迫使很多人提出这个问题。然后我认为 OpenClaw 改变人工智能心理模型的第二种方式实际上是更多地将这些事物视为同事、队友和人，并将其拟人化一点，它是一个可以进入你的生活并可以进一步扩展你的帮助实体。所以我们采取了很多这样的做法。我认为 Grok Bot 可能需要扩展的是，A，它需要非常容易设置。而黑客，你知道，你家里有一个 VPN 和一台 Mac mini，显然它不会扩展到数百万用户。显然，重要的是，这不会成为企业利用这项技术的方式。所以我们真的想打造一款令人惊叹的产品。嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，此前曾在 Cursor 领导过增长。我们怎样才能让 Grok Bot 用户甚至不需要知道技能是什么？他们永远不必输入斜杠命令。这些东西应该在后台创建，作为机器人可以访问的有用原语，但用户知道，他们没有责任始终处于人工智能的最前沿。所以这确实是我们尝试创新的地方，而且我认为还有更多的空间可以去那里。
Lenny Rachitsky：
As you say that, I have my Mac Mini with my formerly alive OpenClaw on there, and that was an era. And it's so awesome, the work that it has inspired. I know it continues. I know there's still a lot of value to OpenClaw, but when I saw Claire Rowe, who's been like the biggest proponent of OpenClaw and has... The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. What's kind of the vision for Grok Bot? What's like, where does this go? What does this look like in the future? What's like the ideal platonic version of Grok Bot?
正如你所说，我的 Mac Mini 上装有我以前活跃的 OpenClaw，那是一个时代。它太棒了，它所激发的作品。我知道它还在继续。我知道 OpenClaw 仍然有很大的价值，但是当我看到 Claire Rowe，她一直是 OpenClaw 的最大支持者，并且……嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，之前在 Cursor 领导过增长。 Grok Bot 的愿景是什么？怎么样，这会去哪里？未来会是什么样子？ Grok Bot 的理想柏拉图版本是什么样的？
Roman Ugarte：
The ultimate vision of Grok Bot is incredibly simple, which is you should have a team of AI bots that help you with your job and help you with your life. And it should really feel like a team. It should really feel like teammates that are autonomous, are helping you. You can steer them in various ways. You don't have to micromanage them. They have access to the tools necessary to do great, ambitious work. And one thing we really use as a North Star on the product side in building this is as we kind of get closer to this teammate future, how can we, in every product decision we make, think about this less from the perspective of a SaaS product and more from the perspective of we're trying to build useful AI teammates? Roman Ugarte, Cursor, and The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. They discuss product development, onboarding, AI agents, persistent memory, cloud architecture, startup speed, company values, and moats. And then you zoom out a little bit and you remove yourself from the tech company-ness of it all. And you start thinking, how would a human do this? Like, what would you want from your teammates in this exact situation? And oftentimes the answer is really clarifying and pretty unanimous. There's oftentimes not a lot of disagreement among the room of like how a human teammate you would prefer to work with in a certain way. And then once that answer is there, well, then we just need to build it. And there are product implications. There are model implications. There's a lot of things that need to go right to actually deliver on that experience. But in some ways, it's not rocket science. It 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 these bots should be. And I think in the context of a human, for example, we have a really good analog of a lot of times I'm slacking back and forth with a teammate, we're sharing context, and a lot of times it's just much simpler to get on a five-minute huddle with them. And just press huddle, talk back and forth, I share my screen, I show exactly what's on my mind, they share their screen, we hop off, and then we continue async from there. And that's not really an experience that any AI product has gotten right right now. And it is deeply integral to the way that I think humans collaborate. And so we want to build something like that. And there are a bunch of other examples of these very clear patterns that just work that I think you should also feel when working with AI.
Grok Bot 的最终愿景非常简单，那就是你应该拥有一支 AI 机器人团队来帮助你完成工作并帮助你改善生活。它应该真正感觉像一个团队。感觉应该是自主的队友在帮助你。您可以通过多种方式引导它们。您不必对它们进行微观管理。他们可以获得完成伟大、雄心勃勃的工作所需的工具。在构建这个产品方面，我们真正使用的一件事是，当我们越来越接近这个队友的未来时，我们如何在做出的每一个产品决策中，少从 SaaS 产品的角度来考虑这一点，而更多地从我们试图构建有用的 AI 队友的角度来考虑？ Roman Ugarte、Cursor 和 嘉宾是 Roman Ugarte，他帮助 SpaceXAI 构建了 Grok Bot，并曾领导 Cursor 的发展。他们讨论产品开发、入职、人工智能代理、持久内存、云架构、启动速度、公司价值观和护城河。然后你把镜头缩小一点，把自己从科技公司的氛围中抽离出来。你开始思考，人类会如何做到这一点？比如，在这种情况下你希望你的队友做什么？通常，答案确实很明确并且非常一致。房间里通常不会有太多分歧，比如你更喜欢以某种方式与人类队友一起工作。一旦有了答案，那么我们只需要构建它即可。这对产品也有影响。有模型含义。要真正提供这种体验，需要做很多事情。但在某些方面，这并不是火箭科学。它不需要你是天才。你只需要问这样一个问题：你想从人类队友那里得到什么？我们能否推动人工智能以类似的方式行事？因此，举一些例子，我的意思是，我们一直在思考这些机器人的正确语音体验应该是什么。 我认为，例如，在人类的背景下，我们有一个非常好的类比，很多时候我和队友来回偷懒，我们分享背景，很多时候，与他们进行五分钟的挤在一起要简单得多。只需按下“挤在一起”，来回交谈，我共享我的屏幕，我准确地展示我的想法，他们共享他们的屏幕，我们跳下，然后我们从那里继续异步。目前任何人工智能产品都没有真正获得这种体验。我认为它是人类协作方式中不可或缺的一部分。所以我们想要建造类似的东西。还有很多这些非常清晰的模式的其他例子，我认为你在使用人工智能时也应该感受到这些模式。
00:40:00
Lenny Rachitsky：
I love this term, colleague build. And it's come up so many times over the course of this chat already, how that is kind of a through line to making these decisions. For example, the computers. I'm sure you gave us 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 this 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?
我喜欢这个词，同事构建。在这次聊天的过程中，这个问题已经出现了很多次，这是做出这些决定的一条贯穿路线。例如，计算机。我确信你给了我们很好的。显然，人们会拥有自己的计算机。命名也是其中非常重要的一部分。在这个领域，我心中的一个大问题是工作和个人之间的分离，我很想知道你的看法。您认为人们会拥有两个不同的助理，一个是工作助理，一个是私人助理，还是只有一个？
Roman Ugarte：
When people think about a work product versus a consumer product, I think there's just a lot of baggage that comes from the last decade or two of horrible B2B software that leads to people seeing a product that is very simple. In some ways, ChatGPT was like this. I think Grok Bot has many of these properties. And assuming that it's not a work product or assuming that it's not a power tool. And when you think of a power tool in this kind of last generation, I, in my head, picture something a bit like Photoshop, for example, where there are all of these different dials to turn very precisely. You know, the user of the tool is this kind of, you know, ultimate cockpit flyer who knows exactly what all the knobs do and can, like, use them perfectly. And I think power tools of the future will actually be very different from that, where it is mostly just intent being expressed and good steering on the part of the human. And these AI tools abstract away all of the knobs. You should never see them unless you need to directly manipulate it, which might happen. And there should be a great affordance for that. But ultimately, it really is just working with a teammate. And so the interface for that is quite conversational. And so in a lot of ways, Grok Bot, when you look at it, like when I walk by someone's desk and I see Grok Bot up on their computer, for me, for a split second, I'm like, oh, are they on like a messaging app? And it's like, no, they're, you know, this is actually the primary tool that they're using to do much of their work. And so I think to your question of are you going to have a different set of bots for your personal life and a different set of bots for your work life, I do think there will be a separation. For many people, they want a separation between personal and work life, and I think that's important. I think that's great. I think that's important. And I think there are a lot of common sense reasons why those things should be separate, even from the perspective of an enterprise. But I think our goal and the thing we're trying to build towards is Grok Bot should be the way that a large portion of the things you do day to day in your work, you should be able to delegate a lot of that to Grok Bot and focus on the higher leverage things. And then it should similarly be the way that you delegate a lot of the low leverage parts of your personal life. And those two things actually are not different problem sets. In a lot of ways, the product form factor and the ways of solving those problems is pretty much the same. And so my instinct is that I think one product will be the best form factor for both of those things. And that's really what we want to build.
当人们考虑工作产品与消费产品时，我认为过去一两年可怕的 B2B 软件带来了很多包袱，导致人们看到了非常简单的产品。从某些方面来说，ChatGPT 就是这样。我认为 Grok Bot 具有许多这样的特性。并假设它不是工作产品或假设它不是电动工具。当你想到上一代的电动工具时，我会在脑海中想象一些有点像 Photoshop 的东西，例如，其中有所有这些不同的转盘可以非常精确地转动。你知道，该工具的用户是这样的，你知道的，终极驾驶舱飞行者，他们确切地知道所有旋钮的作用，并且可以完美地使用它们。我认为未来的电动工具实际上将与现在有很大不同，未来的电动工具主要只是表达意图和人类的良好指导。这些人工智能工具抽象了所有的旋钮。你永远不应该看到它们，除非你需要直接操纵它（这可能会发生）。对此应该有很大的承受能力。但最终，这实际上只是与队友一起工作。所以这个界面是非常对话式的。因此，在很多方面，Grok Bot，当你看到它时，就像当我走过某人的办公桌时，我看到 Grok Bot 在他们的计算机上，对我来说，一瞬间，我想，哦，它们是不是像一个消息应用程序一样？就像，不，他们，你知道，这实际上是他们用来完成大部分工作的主要工具。所以我认为，对于你的问题，你是否会为你的个人生活拥有一套不同的机器人，为你的工作生活拥有一套不同的机器人，我确实认为会有分离。对于许多人来说，他们希望将个人生活和工作生活分开，我认为这很重要。我认为那太好了。我认为这很重要。我认为，即使从企业的角度来看，也有很多常识性的理由说明为什么这些东西应该分开。 但我认为我们的目标和我们正在努力实现的目标是 Grok Bot 应该是这样一种方式，即你日常工作中所做的大部分事情，你应该能够将其中很多工作委托给 Grok Bot 并专注于更高杠杆的事情。同样，这也应该是你委托个人生活中许多低杠杆部分的方式。这两件事实际上并不是不同的问题集。在很多方面，产品的外形尺寸和解决这些问题的方法几乎是相同的。因此，我的直觉是，我认为一种产品将是同时满足这两种需求的最佳外形尺寸。这正是我们想要构建的。
Lenny Rachitsky：
Bam, that's a big tam right there. I love to hear it. It makes so much sense. Obviously, the question is, how do you avoid cross-contamination, you know, personal stuff somehow infiltrating, exfiltrating stuff from work. But it 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 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 banking. No chasing, no manual reviews, no end-of-month scramble. The result is a team that can move fast and a founder who is no longer the bottleneck. Learn more and get signed up at Mercury.com. Mercury is a fintech company, not an FDIC-insured bank. Banking services provided to Choice Financial Group and column NA members FDIC. The I.O. card is issued by Patriot Bank, NA member FDIC, pursuant to a license from MasterCard International Incorporated. Let me ask a couple technical questions. On the computer side, how do... What's the simplest way to think about what you get as a part of your Grok Bot account? Is it like a VM that is running in the cloud with multiple logins? Is it like a separate VM instance per bot? How do we understand that as much as you can share?
巴姆，那儿有一个大塔姆。我喜欢听。这很有意义。显然，问题是，如何避免交叉污染，你知道，个人物品以某种方式渗透到工作中。但感觉好像是这样，好吧，所以我听到的是这个方向。问题是如何做到这一点，让人们感到超级安全，有一种像袜子管一样的东西，而且感觉真的很有趣。本集由 Mercury 为您带来，现在的银行业务与支出截然不同。我已经成为 Mercury 客户很多年了。我将所有商业银行业务都转到了 Mercury，说实话，我高兴极了。这就是由产品人员而不是银行家创建的在线银行的感觉。现在，通过 Spend，您可以为团队提供单独的卡片，设置每人或每个团队的支出限额，并自动从 Gmail 或通过短信提取费用收据。您甚至可以为您的人工智能代理提供自己的卡，并有自己的限制和政策。大多数创始人都是以同样的方式开始的。公司每个人都使用一张卡。它会一直工作直到停止工作。有人走了过去，收据消失了，你花了两天时间试图弄清楚谁花了多少钱以及为什么。 Spend 是直接内置于 Mercury 中的费用管理。您团队的所有卡、预算和报销都与您的企业银行业务位于同一位置。没有追赶，没有人工审核，没有月末争夺。结果是一支能够快速行动的团队和一个不再是瓶颈的创始人。了解更多信息并在 Mercury.com 上注册。 Mercury 是一家金融科技公司，而不是 FDIC 承保的银行。向 Choice Financial Group 和 NA 成员 FDIC 提供银行服务。 I.O.卡由北美联邦存款保险公司成员爱国者银行根据万事达卡国际公司的许可发行。让我问几个技术问题。在计算机方面，如何...考虑作为 Grok Bot 帐户的一部分所获得的内容的最简单方法是什么？是不是就像一个运行在云端的虚拟机，需要多次登录？它就像每个机器人都有一个单独的虚拟机实例吗？正如您所分享的，我们如何理解这一点？
Roman Ugarte：
Yeah, I think to go back to the teammate frame of the product, to kind of extend the analogy even further, If we were on a team together, you and me, I think the number of times that you would have to manually take over my computer and start clicking on things and like, you're doing this wrong, you should go here instead and type in manually, hopefully is pretty close to zero. Hopefully, that is not something you have to really do with a colleague or a teammate. And so similarly, I think right now we're in a place where computer use is good. It's getting much better. And in very short order, I think the computer concept will be completely abstracted away from the user. You should never be clicking into a remote virtual machine. You should never have to take control, you know, of something. If there's like a wasteful path and you have to kind of steer it into the correct path. So in the medium term, I think the computer concept will be an important component. The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. I think there are a lot of problems with that. I find myself copying and pasting between chats all the time. I think it's just not a great way of grouping categories of work. Instead, the same way on a team, you have a good way of grouping categories of work, of kind of roles. You should have roles of kind of different swim lanes of work that you do, and it should learn from you, and it should get smarter over time. So I think that's one very critical thing, is these are long-lived agents. These are not individual one-off sessions. And these agents get smarter over time. And then the second thing is those agents have access to all of the tools that you would expect a human colleague to have, which is the APIs, the MCPs. That's great. But then access to its own computer, which it can freely manipulate the way that you would.
是的，我想回到产品的队友框架，进一步扩展类比，如果我们在一起，你和我，我认为你必须手动接管我的计算机并开始点击东西之类的次数，你做错了，你应该去这里手动输入，希望非常接近于零。希望这不是您必须与同事或队友真正做的事情。同样，我认为现在我们正处于计算机使用良好的地方。情况变得好多了。在很短的时间内，我认为计算机概念将完全从用户手中抽象出来。您永远不应该点击远程虚拟机。你知道，你永远不应该控制某些事情。如果有一条浪费的道路，你必须将其引导到正确的道路上。因此，从中期来看，我认为计算机概念将是一个重要组成部分。嘉宾是 Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，此前曾在 Cursor 领导过增长。我认为这有很多问题。我发现自己总是在聊天之间复制和粘贴。我认为这并不是对工作类别进行分组的好方法。相反，就像在团队中一样，您可以很好地对工作类别和角色进行分组。你应该在你所做的工作中扮演不同的角色，它应该向你学习，并且随着时间的推移它应该变得更加聪明。所以我认为这是一件非常关键的事情，这些是长期存在的代理人。这些不是单独的一次性课程。随着时间的推移，这些代理会变得更加聪明。第二件事是这些代理可以访问您期望人类同事拥有的所有工具，即 API、MCP。那太棒了。但随后可以访问它自己的计算机，它可以按照您的方式自由操作。
Lenny Rachitsky：
At this meetup that I went to, Shub, who's on the, I think, growth market team, demoed something that blew everyone's mind. Because you have a computer within each agent, you can run a lot of different things on the computer. He was running Grok Bot within Grok Bot. Like the bot can run its own Grok Bots. And I know he was using it for testing and watching regressions and things like that, but that's just like a mind-expanding idea. And I'm curious how many levels you can go before the universe collapses on itself.
在我参加的这次聚会上，Shub（我认为他是增长市场团队的成员）演示了一些让每个人都大吃一惊的事情。因为每个代理内都有一台计算机，所以您可以在计算机上运行许多不同的东西。他在 Grok Bot 中运行 Grok Bot。就像机器人可以运行自己的 Grok 机器人一样。我知道他用它来测试和观察回归以及类似的事情，但这就像一个扩展思维的想法。我很好奇在宇宙自行崩溃之前你能达到多少层。
00:50:00
Roman Ugarte：
I do that one too. That one's actually a very useful thing to do, is you download Grok Bot for one of your bots. Mine is like a QA tester bot. And that way, if there's ever a bug report or if we're kind of testing out a new build, for example, of the desktop app, I can just say, hey, here are 10 workflows that... We need to make sure we're 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 and 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 the colleague to do on a computer, I can ask Grok Bot to do. It just raises the ceiling, I think, of what you would.
我也做那个。这实际上是一件非常有用的事情，你可以为你的一个机器人下载 Grok Bot。我的就像一个 QA 测试机器人。这样，如果有错误报告或者我们正在测试新版本（例如桌面应用程序），我可以说，嘿，这里有 10 个工作流程......我们需要确保我们在发布后得到更好的发布。我想让你测试一下。我希望您将其写入此概念文档，该文档包含我们过去所做的所有测试和过去的客户端版本的详细列表，并对它们进行比较。因此，我认为一旦你开始突破这一点，就是与一组连接进行人工智能聊天，我认为这是大多数人现在的概念，而不是与计算机的同事。我要求同事在计算机上执行的任何操作，我都可以要求 Grok Bot 执行。我认为，这只是提高了你的愿望的上限。
Lenny Rachitsky：
Are there any other mind-expanding use cases or ways to use Grok Bot that you've seen or you use?
您是否见过或使用过任何其他拓展思维的用例或使用 Grok Bot 的方法？
Roman Ugarte：
One pattern that I've seen for many users that is simple, but I think there's a lot of depth if you keep investing and making it better. And this is kind of where I can get kind of nerdy about optimizing my setup, is... Grok Bot as an infovore in some ways of just consuming huge quantities of information, removing that from your own cognitive load, giving you peace, and then coming to you with the stuff that's important. And I think the V1 implementation of that, which many people do, is Grok Bot sits on top of Slack, and it sits on top of email. And it's a very, very important And I tell it high level, here's my role at the company. 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 4, which is you can give these bots a complete firehose of information. So I have mine hooked up to like every mention of Grok Bot ever on X, and it's interacting with our internal context. It's interacting with the QA tester to like... See if it can repro any bugs or feedback that we're getting. I'm hooked up to my own kind of messaging services to like quickly act on feedback and reach out to people. And I think there's this just like always on... The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. And so if something like super urgent happens and they're at a coffee or whatever, they get paged by Grok Bot, which is the type of thing that you only want to do if it's urgent and you really want to trust that Grok Bot does not have false positives. So far, those people have reported that it's been very helpful and successful. But I think we're going to see more of that type of stuff where the agent or the bot should actually be more proactive to you than you reaching out to it. And I think that will be the next shift in AI. Yeah.
我在许多用户中看到的一种模式很简单，但我认为如果您继续投资并使其变得更好，就会有很多深度。这就是我对优化我的设置感到有点书呆子的地方，是……Grok Bot 作为一个信息爱好者，在某些方面只是消耗大量信息，将其从你自己的认知负担中消除，给你平静，然后带着重要的东西来找你。我认为许多人所做的 V1 实现是 Grok Bot 位于 Slack 之上，它位于电子邮件之上。这是非常非常重要的，我告诉高层，这是我在公司的角色。这就是我关心的事情。我希望您在这些情况下通知我。在这些情况下，您不需要直接对我进行 ping 操作，但您应该将其包含在我每天阅读的每日综述中。这就像 V1 的实现。我不确定 V10 的实现是什么，但就像我可能在 V3 或 4 一样，你可以为这些机器人提供完整的信息。所以我把我的连接到了 X 上每次提到 Grok Bot 的地方，它与我们的内部环境进行交互。它与 QA 测试人员进行交互，以...看看它是否可以重现我们收到的任何错误或反馈。我喜欢使用自己的消息服务，以便根据反馈快速采取行动并与人们联系。我认为这就像往常一样……嘉宾是 Roman Ugarte，他帮助 SpaceXAI 构建了 Grok Bot，此前曾领导 Cursor 的增长。因此，如果发生超级紧急的事情，并且他们正在喝咖啡或其他什么，他们就会被 Grok Bot 寻呼，这是您只有在紧急情况下才想做的事情，并且您确实想要相信 Grok Bot 不会出现误报。到目前为止，这些人报告说这是非常有帮助和成功的。但我认为我们将会看到更多这样的事情，代理或机器人实际上应该比你主动联系它更主动地帮助你。我认为这将是人工智能的下一个转变。是的。
Lenny Rachitsky：
This touches on, there's a number of things that I've been very impressed with watching your team operate. One is speed, which I want to talk about, but the other is how you're, like there's awareness that this is a moment in time to capture a lot of market share and really take as much of the market as you can before somebody comes around and they're like, okay, now we got something awesome, especially one of the foundation labs. So watching just how many... The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. You know, because someone's going to come around and be like, all right, here's the next thing. Super smart and also the use case focus. I know you're a go-to-market person at Cursor before this. Anything you want to share there about just the approach to go-to-market right now for getting this out there?
这涉及到，观察你们团队的运作，有很多事情给我留下了深刻的印象。一是速度，我想谈论这一点，但另一个是你的情况，就像人们意识到这是一个及时占领大量市场份额并真正占领尽可能多市场的时刻，然后有人出现，他们会说，好吧，现在我们有了一些很棒的东西，尤其是其中一个基础实验室。所以看看到底有多少……嘉宾是 Roman Ugarte，他帮助 SpaceXAI 构建了 Grok Bot，并曾领导 Cursor 的增长。你知道，因为有人会过来说，好吧，这是下一件事。超级智能，而且注重用例。我知道您在此之前是 Cursor 的市场营销人员。关于目前将其推向市场的方法，您有什么想分享的吗？
Roman Ugarte：
I think the pattern we saw for coding will be somewhat similar to what we see for general knowledge work. And I think we've learned a lot from that on the go-to-market side and more generally, just building practical AI that people use. And I think we as a company have culturally really cared about not building demo ware. Roman Ugarte, Cursor CEO Coding was a very simple pattern, which was there was an early adopter crowd. The early adopter crowd would use these coding tools and really push them to the limits. And they would mostly push them to the limits on individual projects. They would, on nights and weekends, I'm thinking like 2023, kind of earlier, People would kind of go home from work. At work, they were using a basic IDE. This is pre-AI. And then at home, they'd work on a side project, and they'd be using Cursor, or they'd be using the latest and greatest AI coding tool. And that would give them an extreme amount of acceleration. It would feel like they were experiencing the future. And then they would come back to work, and they would demand it. They would say, I cannot picture working any other way than this. I feel like I'm completely walking through molasses right now. This needs to change. And I think for knowledge work, we're going to see a similar pattern of people really feeling the aha moment, sometimes in a personal capacity. And I think we're certainly seeing a lot of this, like on X right now, you see all these examples of Grok Bot controlling their home robot computer, or home robot vacuum cleaner, or Grok Bot, 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 gonna transform businesses. We think this is gonna transform teams. And it will be bots coming into teams and contributing really economically valuable work, especially as they get much smarter. And so on the go-to-market side, we're certainly making a big push on prioritizing businesses. And thinking about not just the single player use case of working with a single bot, but how does a bot work inside of a broader team? How does a bot work inside of real company systems that are complicated and there's a lot of context and a lot of history to understand? What does memory look like in kind of a broader context? organization versus kind of a single individual you're catering to. And I think there are a lot of unanswered questions there, but I do think Grok Bot is the right primitive to create this switch to agents for the rest of the company outside of coding. And that's a place where we're quite focused right now.
我认为我们看到的编码模式与我们看到的一般知识工作的模式有些相似。我认为我们在进入市场方面学到了很多东西，更广泛地说，只是构建人们使用的实用人工智能。我认为，作为一家公司，我们在文化上确实非常关心不构建演示软件。 Roman Ugarte，Cursor 首席执行官 编码是一种非常简单的模式，有早期采用者群体。早期采用者会使用这些编码工具，并真正将它们推向极限。他们大多会把他们推向个别项目的极限。他们会在晚上和周末，我想 2023 年，会更早一些，人们会下班回家。在工作中，他们使用的是基本的 IDE。这是前人工智能时代。然后在家里，他们会做一个业余项目，他们会使用 Cursor，或者他们会使用最新、最好的人工智能编码工具。这会给他们带来极大的加速度。感觉就像他们正在经历未来。然后他们会回来工作，他们会要求这样做。他们会说，我无法想象除此之外的任何其他工作方式。我觉得我现在完全在糖蜜中行走。这需要改变。我认为对于知识工作，我们将看到类似的模式，人们真正感受到顿悟时刻，有时是以个人身份。我认为我们确实看到了很多这样的情况，就像现在在 X 上一样，你会看到所有这些 Grok Bot 控制他们的家庭机器人计算机、家庭机器人吸尘器或 Grok Bot 的例子，你知道，帮助他们在特斯拉充电器谈判上省钱，就像所有这些有趣的用例一样。但我认为下一步将是，这不是消费品。我们认为这将改变企业。我们认为这将改变团队。机器人将进入团队并贡献真正具有经济价值的工作，特别是当它们变得更加聪明时。因此，在进入市场方面，我们肯定会大力推动业务的优先排序。 不仅要考虑使用单个机器人的单人用例，还要考虑机器人如何在更广泛的团队中工作？机器人如何在复杂且有大量背景和历史需要理解的真实公司系统中工作？在更广泛的背景下，记忆是什么样子的？您所服务的组织与个人。我认为那里有很多悬而未决的问题，但我确实认为 Grok Bot 是在编码之外为公司其他部门创建代理的正确原语。这是我们现在非常关注的地方。
Lenny Rachitsky：
And along those lines, it's very clear you all understand the power of distribution and how you need to find both an amazing product and get distribution right. Because, you know, Grok Bot's amazing, but... The combination of how smart you guys have been with getting it out there in all these different ways is really impressive. And I think that shows you what it takes these days to build something that's really successful. I want to ask about the brand of the different brands around this product and the company, just so people can try to understand. Because I know you're going through a transition, acquisition, SpaceX, all these things. So there's Grok Bot, ProSense. There's Cursor. So talk about the products and the way to think about these different brands today. And I know it'll probably continue to evolve just so we can communicate about it correctly.
沿着这些思路，很明显你们都了解分销的力量以及如何找到令人惊叹的产品并获得正确的分销。因为，你知道，Grok Bot 太棒了，但是……你们以所有这些不同的方式将它发布出来的聪明程度结合起来真的令人印象深刻。我认为这向您展示了当今需要什么才能打造出真正成功的东西。我想询问有关该产品和公司的不同品牌的品牌，以便人们可以尝试理解。因为我知道你正在经历转型、收购、SpaceX，所有这些事情。于是就有了 Grok Bot、ProSense。有光标。所以今天谈谈产品以及思考这些不同品牌的方式。我知道它可能会继续发展，以便我们能够正确地进行沟通。
Roman Ugarte：
Definitely. Yeah. I think there are three big pillars right now of SpaceXAI. So the first pillar is the coding product and set of products. And right now that's Cursor and GrokBuild. And I think we're big believers that... Having a professional work surface for developers and for the engineering part of the organization is going to be really critical. And right now, people use Grok Bot sometimes to kick off cloud agents or to kind of merge PRs or to do QA, a bunch of engineering adjacent tasks. But ultimately, when you're shipping production software, we're big believers that that is going to require, you know, a product where every pixel is optimized for that end user. So we're making big investments there. The second category is general knowledge work. And we think bot is a really exciting step in that direction. There's a lot more work to do of making it more useful, extending it to new surfaces, it really feeling like an AI teammate that you can delegate work to, especially inside of companies and businesses. So that's kind of the second pillar. And then third is the general model effort. We want to train the smartest models in the world that are really capable. And I think one thing that... somewhat distinguishes SpaceXAI from other AI labs is I think our goal is less to build, you know, chase superintelligence or some kind of vague aspirational ideal. And the goal is actually very practical, which is to build useful AI. And we do that on the product side, we do that on the model side. And I think part of that is also just Cultural of like the group of people contributing to these models are engineers and people who kind of came into the model training effort from like a very applied mindset. And I think that's what gets this company going. And I think is actually a slightly different direction from some of the other competitors out there.
确实。是的。我认为 SpaceXAI 目前有三大支柱。因此，第一个支柱是编码产品和产品集。现在就是 Cursor 和 GrokBuild。我认为我们坚信……为开发人员和组织的工程部分提供专业的工作界面将非常重要。现在，人们有时使用 Grok Bot 来启动云代理或合并 PR 或进行 QA，即一系列工程相邻任务。但最终，当您交付生产软件时，我们坚信这将需要一种每个像素都针对最终用户进行优化的产品。所以我们在那里进行了大量投资。第二类是一般知识工作。我们认为机器人是朝着这个方向迈出的非常令人兴奋的一步。要使其更有用，将其扩展到新的表面，还有很多工作要做，它真的感觉就像一个可以将工作委派给的人工智能队友，尤其是在公司和企业内部。这就是第二个支柱。第三是一般模型工作。我们希望训练世界上最聪明且真正有能力的模型。我认为 SpaceXAI 与其他人工智能实验室的区别在于，我们的目标不是建立，你知道，追逐超级智能或某种模糊的理想。而且目标其实很实际，就是构建有用的人工智能。我们在产品方面这样做，我们在模型方面这样做。我认为其中一部分也只是文化，就像为这些模型做出贡献的一群人是工程师和那些从非常应用的思维方式进入模型培训工作的人。我认为这就是这家公司发展的动力。我认为这实际上与其他一些竞争对手的方向略有不同。
01:00:00
Lenny Rachitsky：
Super interesting. Okay, there's a couple directions I want to go. One is, you have this tweet that is, I think you pinned it, or maybe it's your last tweet, it's up there in your timeline if people check you out. So the tweet is, an AI that does 100% of the job feels categorically different from one that gets you 90% there. I've significantly updated what I think AI is capable of. Say more about that.
超级有趣。好吧，我想去几个方向。一是，你有这条推文，我想你把它钉住了，或者也许这是你的最后一条推文，如果人们查看你的话，它就会出现在你的时间轴上。所以这条推文是，一个能完成 100% 工作的人工智能与能完成 90% 工作的人工智能给人的感觉截然不同。我对人工智能的能力进行了重大更新。多说一点吧。
Roman Ugarte：
I think for me, what made me so excited to work on Grok Bot and contribute to it is it was the first time for non-coding tasks that I felt like I could truly delegate work to AI and not have to think about it, and I would come back and it's done. And I think engineers have been feeling this for quite some time, for maybe a year, a year and a half, things have been like that. I mean, the job of a developer has completely transformed. It is unrecognizable from what it was two years ago. And many, many words have been said on that topic. But I think it's underrated how... Different that experience is from what most people are feeling about AI right now and the way that AI has changed their lives. And it looks quite similar to the way that people would use AI like two years ago, where you create a new thread for a task, you type it into an input box, you hit enter, you watch all of these steps happen, you get an output. It's not quite right. You keep working on it. Roman Ugarte, CEO and CEO of Grok Bot When you have a teammate that you only 90% trust and you give something to, which luckily I do not have the experience of here because I work with great people. But if you delegate something to someone and you're like, I know I'm going to have to be thinking about this while you're doing it. And I know it probably is not going to be quite there and I'm going to have to intervene and kind of steer it slightly. You're not, that's not 90% task completion. You're still doing the thing. And it feels that way. And it's weighing on you in the same way. Versus like truly throwing a no-look pass to a colleague and being like, you got this. Here's the context. Go off and run. I'm excited to see what you do. Like that's a different category. And I think that's the type of thing that people feel with Grok Bot every day are these no-look passes. And you just trust that it can get it done. And then it does. And it's just a very magical experience.
我认为对我来说，让我如此兴奋地在 Grok Bot 上工作并为其做出贡献的原因是，这是第一次对于非编码任务，我觉得我可以真正将工作委托给人工智能，而不必考虑它，我会回来并完成它。我认为工程师们已经有这种感觉很长一段时间了，也许一年、一年半，事情一直都是这样。我的意思是，开发人员的工作已经完全改变了。与两年前相比，已经完全认不出来了。关于这个话题已经说了很多很多话。但我认为它被低估了……这种体验与大多数人现在对人工智能的感受以及人工智能改变他们生活的方式不同。它看起来与两年前人们使用人工智能的方式非常相似，你为一个任务创建一个新线程，将其输入到输入框中，按下回车键，观察所有这些步骤的发生，然后得到输出。这不太正确。你继续努力。 Roman Ugarte，Grok Bot 首席执行官兼首席执行官 当你有一个只有 90% 信任的队友并且你会付出一些东西时，幸运的是我没有在这里的经历，因为我和伟大的人一起工作。但如果你将某件事委托给某人，而你会想，我知道在你做这件事时我必须考虑这一点。我知道它可能不会完全在那里，我将不得不进行干预并稍微引导它。你没有，那不是任务完成率的 90%。你还在做那件事。感觉就是这样。它也以同样的方式给你带来压力。与真正向同事扔出一张不看人的通行证然后说，你明白了。这是上下文。走开就跑。我很高兴看到你所做的事情。就像这是一个不同的类别。我认为人们每天使用 Grok Bot 都会感受到这种不看人传球的感觉。您只需相信它可以完成任务。然后它就做到了。这真是一次非常神奇的经历。
Lenny Rachitsky：
Yeah, I've had that experience consistently. Okay, so another element of how you all operate that has really impressed me, and I've not seen this before, is how fast you all move. So I got added to this like Slack as giving feedback with some folks. And it's just like, okay, how about, okay, tomorrow, we're going to give you some free codes to give out. You could do it tomorrow. We'll do this tomorrow. Or we're going to launch a marketplace with templates. We're going to launch this in two days. I was just like, what? I don't have time for this. How do you guys, with all the things going on, all these things constantly shipping and also staying consistent and high quality and feeling clear that it's towards a specific vision. So there's kind of 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 that you all want, that you all believe in, and where you want it to go, versus just, like, you know, band-aiding it along the way?
是的，我一直都有这样的经历。好吧，你们的运作方式的另一个让我印象深刻的因素是你们的行动速度，我以前从未见过这一点。所以我像 Slack 一样加入到这个项目中，向一些人提供反馈。就像，好吧，好吧，明天我们会给你一些免费的代码来分发。你明天就可以做。我们明天就这样做。或者我们将推出一个带有模板的市场。我们将在两天内推出这个项目。我当时就想，什么？我没有时间做这个。你们怎么样，随着所有事情的发生，所有这些东西不断发货，并且保持一致和高质量，并且清楚地感觉到它正在朝着特定的愿景迈进。所以这个问题有两个部分，就是……你们所有人行动速度有多快的秘诀是什么？你们如何保持一致，快速朝着你们都想要的、你们都相信的愿景前进，以及你们想要它去往的地方，而不是只是，你知道，一路上用创可贴来帮助它？
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. And then now we're a part of SpaceXAI, which is kind of an even bigger organization. And it's something that is just so fun to be a part of when you're around this group of incredibly talented people. Everyone's moving a hundred miles an hour. You trust, you deeply trust everybody to execute on their part of the equation. And there's a clear vision that everyone is fired up about and like, The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. And, you know, fingers crossed, this continues to be true. I think it's really critical for our success if this continues to be true. But even as we scaled, it has always felt like that startup that kind of I first joined. And I think if you define a startup by scale, 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 the system what you put in. And then. And so I think as a culture, I think as an organization and the way we construct ourselves, it's really been to enable that property in a way that I think some of our competitors and other AI labs have gotten much bigger. And you can feel it.
是的，我一直以来真正的一件事......快乐从未改变。这家初创公司在公司内部有感觉吗？就背景而言，当我最初加入 Cursor 时，我们大约有 15 个人。我们扩展到大约一千多个。现在我们是 SpaceXAI 的一部分，这是一个更大的组织。当你在这群才华横溢的人身边时，成为其中的一员是一件非常有趣的事情。每个人都以每小时一百英里的速度行驶。你信任，你深深地信任每个人都会履行自己的职责。还有一个清晰的愿景，每个人都兴奋不已，喜欢的嘉宾是 Roman Ugarte，他帮助 SpaceXAI 构建了 Grok Bot，此前曾领导 Cursor 的增长。而且，你知道，祈祷吧，这仍然是事实。我认为如果这种情况持续下去，这对我们的成功至关重要。但即使我们规模不断扩大，我总感觉就像是我第一次加入的那种初创公司。我认为，如果你通过规模、人数或融资轮次来定义一家初创公司，那么这些事情都没有任何意义。定义初创公司的核心正是您所描述的，即事物的这种争夺能量有点混乱和无组织。和很多人一样，这并不是一个令人愉快的工作环境。但它具有这些令人惊奇的特性，可以在短时间内在特定方向上产生极大的影响。你确实可以从系统中得到你所输入的内容。然后。因此，我认为作为一种文化，作为一个组织和我们构建自己的方式，我认为我们的一些竞争对手和其他人工智能实验室已经变得更大，这确实是为了实现这一特性。你可以感觉到。
Lenny Rachitsky：
And I think us, even as we scale, there is that startup-y impulse that is quite important to move quickly on these things. Let me pull on this thread and let me ask you this big question that I've been looking forward to asking you. If you were to look at Cursor from the outside, it shouldn't have worked. It shouldn't have lasted. Because, one, it's in the most competitive market in the world, competing against the fastest growing companies in history, OpenAI and Anthropic. So that's one. It's like the competition is unlike anything anyone's ever experienced. Two, it sits on top of those platforms to power it. And what I've seen as an outsider is what has allowed Cursor to win and have this massive exit and continue to succeed is how quickly you all adjust to the reality of the market. Started as autocomplete, and then things moved on to just talking to agents and then into the cloud and now Grok Bot. To me, that feels like a core part of the success is quickly adjusting to reality and also building the best-in-class experience for a thing that also exists other places. Grok Bot's a great example. You could do this other places, but it's the best-in-class experience. Cursor, the ID, the best way to code. So that's my question. Maybe I answered it. But what do you think has been core to Cursor's ability to not just survive in this crazy competitive market, but do so incredibly well consistently for so long?
我认为，即使我们规模不断扩大，创业的冲动对于在这些事情上快速采取行动也非常重要。让我继续这个话题，问你这个我一直期待着问你的大问题。如果你从外部看 Cursor，它应该不起作用。它不应该持续下去。因为，第一，它处于世界上竞争最激烈的市场，与历史上增长最快的公司 OpenAI 和 Anthropic 竞争。这就是其中之一。就好像这场比赛与任何人经历过的任何事情都不一样。第二，它位于这些平台之上为其提供动力。作为一个局外人，我认为 Cursor 能够获胜、大规模退出并继续取得成功的原因是你们能够如此迅速地适应市场现实。一开始是自动完成，然后事情发展到只与代理交谈，然后进入云端，现在是 Grok Bot。对我来说，成功的核心部分是快速适应现实，并为其他地方也存在的事物打造一流的体验。 Grok Bot 就是一个很好的例子。您可以在其他地方进行此操作，但这是一流的体验。光标，ID，最好的编码方式。这就是我的问题。也许我回答了。但您认为 Cursor 不仅能够在这个疯狂竞争的市场中生存下来，而且能够长期保持令人难以置信的良好表现的核心能力是什么？
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, it's... We have never been complacent. We've never felt like we've won. And it's always been about the next thing. And I think there's been a really deep belief across the company that AI is moving incredibly quickly. Our goal is to translate those capabilities into amazing products for customers. But those products are going to change, and they need to meet the moment as the capabilities get stronger. And what met the moment two years ago is completely different than what's meeting the moment today. And if we as a company can't completely reinvent ourselves every six months, which... Recently, it's felt even shorter than that of kind of complete, like, very significant reinventions of our priorities, the core product, what users feel we're going to lose. And I think it's that spirit of always pushing to be on the frontier, never thinking it's over or that we've won or that we've gotten it right, and just constantly updating our beliefs that has gotten us to where we are now. And to your point on the competitiveness of this space, one thing that I think is important to point out is AI coding has always been competitive from when Cursor first kind of came to be. And at the time, the competitors were Microsoft and others and a handful of maybe 10 or 20 companies. And I think it's notable that... None of those competitors are at the forefront of AI coding right now, in large part, not because of any incorrect decisions that they made or any lack of resources on their part, but this cultural inability to move quickly and to change to meet the moment as the moment's changing. And so I think that's exactly what has led us to invest in things like Grok Bot, for example. Are there any core values, just like specific ways you phrase this to kind of remind everyone of this is how we work? 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... Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. Which I find myself kind of repeating a lot, even as we've kind of grown as a company, is it's on you. You know, we're all in this boat together. We want to win. And if you see something that you think needs to happen, you know, this is not an ask for permission culture. You go out and you fix the thing and you pull in the resources that you need to make it happen. And I think that has made many people very successful here before. And I think it's something we really share with SpaceXAI as well.
我的意思是，很多这样的问题，这是一个模糊的答案，我认为很多这样的问题是文化的下游，你设置的文化，你引入的人员以及他们解决这些问题的方式。我认为对我们来说，正如您所说，...我们从未自满。我们从来没有感觉自己赢了。它总是关于下一件事。我认为整个公司都坚信人工智能正在以惊人的速度发展。我们的目标是将这些功能转化为为客户提供的令人惊叹的产品。但这些产品将会发生变化，随着功能的增强，它们需要适应时代的变化。两年前的情况与今天的情况完全不同。如果我们作为一家公司不能每六个月彻底重塑自己，那么……最近，感觉比对我们的优先事项、核心产品、用户认为我们将失去的东西进行彻底的、非常重大的重塑还要短。我认为正是这种始终奋进前沿的精神，从不认为事情已经结束，或者我们已经赢了，或者我们已经做对了，只是不断更新我们的信念，使我们走到了现在的位置。对于你关于这个领域竞争力的观点，我认为需要指出的一点是，从第一种 Cursor 出现时起，人工智能编码就一直具有竞争力。当时，竞争对手是微软和其他公司以及少数大约 10 到 20 家公司。我认为值得注意的是……这些竞争对手目前都没有处于人工智能编码的最前沿，很大程度上，不是因为他们做出了任何错误的决定，也不是因为他们缺乏资源，而是因为这种文化无法快速行动并随着时代的变化而改变。因此，我认为这正是我们投资 Grok Bot 等产品的原因。 是否有任何核心价值观，就像您表达这一点的具体方式一样，以提醒每个人这就是我们的工作方式？是的，我发现自己经常回想起这两个价值观。第一个是删除产品的想法。我认为这与你现在所说的完全相关，当你回顾过去的每一次迭代时……Roman Ugarte，他在 SpaceXAI 帮助构建了 Grok Bot，并之前领导了 Cursor 的增长。我发现自己经常重复这句话，即使我们已经成长为一家公司，这取决于你。你知道，我们都在这条船上。我们想赢。如果你看到一些你认为需要发生的事情，你知道，这不是一种请求许可的文化。你出去解决问题，然后调动所需的资源来实现它。我认为这让许多人在此之前取得了巨大的成功。我认为这也是我们与 SpaceXAI 真正分享的东西。
01:10:00
Lenny Rachitsky：
Agency, as you may have heard. So interesting. One of the big questions that comes up, and this might be my final question, is around moats. And a lot of people look at Cursor as a really interesting example of they're in a market with technically maybe no moats, but they've continued to win and succeed. The two moats you think about with Cursor is the data feedback loop of people auto-completing, learning what they're doing, and training models based on that. So that's unique. The other is just best-in-class experience. And being like a high daily active user product and finding over time what works and what people need. What have you just learned? And I guess any thoughts on moats in the space that might be helpful for folks that are trying to figure this out for themselves?
正如您可能听说过的那样。太有趣了。出现的大问题之一，这可能是我的最后一个问题，是关于护城河的。很多人将 Cursor 视为一个非常有趣的例子，他们所处的市场在技术上可能没有护城河，但他们不断获胜并取得成功。您认为 Cursor 的两条护城河是人们自动完成的数据反馈循环、学习他们正在做的事情以及基于此的训练模型。所以这是独一无二的。另一个就是一流的体验。就像一个日常活跃用户很高的产品一样，随着时间的推移，发现什么是有效的以及人们需要什么。你刚刚学到了什么？我想对这个领域的护城河有什么想法可能对那些试图自己解决这个问题的人有帮助吗？
Roman Ugarte：
Yeah, there's a lot of talk about moats, and it is a pretty interesting moment in time to be starting a company. So I can understand why so many founders are kind of asking themselves that and trying to project out 12 months from now, 24 months from now. It just feels like an eternity. I will say that I think if Cursor and many other successful companies of this kind of vintage, I think if they had thought... About moats slash kind of tried to work backwards from some strategy diagram or like, you know, maybe more abstract notion of how a company should work. I don't think that would have created this outcome or this product. I think what really created the magic of Cursor was an obsession with building a useful thing today. And I think it was constantly this exercise of, you can kind of see where the world is going three months from now, six months from now. Models are going to get smarter. A thing that isn't solvable now is finally going to be solvable. And I think Cursor was a little bit this recurring prompt of, how could we pull that stuff to today? Even if it requires a little bit of engineering on top to make it work, or a lot of engineering on top to make it work, even if it requires changing the product in a specific way so 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... The guest is Roman Ugarte, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. Many founders or people starting out today to be more grounded in that perspective of how can I make something that is not possible now possible? Users are going to come to me to use that thing. I'm going to pull them to the next impossible frontier. And then through all of that, I'm going to gain a lot of distribution advantages. I'm going to gain data advantages. There will be value there. But I think that's really the place to play.
是的，有很多关于护城河的讨论，现在是创办公司的一个非常有趣的时刻。所以我可以理解为什么这么多创始人都会问自己这个问题，并试图规划 12 个月后、24 个月后的情况。感觉就像是永恒。我想说的是，我认为如果 Cursor 和许多其他这种类型的成功公司，我想如果他们想过……关于护城河斜线，试图从一些战略图或类似的东西中倒退，你知道，也许是关于公司应该如何运作的更抽象的概念。我认为这不会创造出这个结果或这个产品。我认为真正创造了 Cursor 魔力的是当今对构建有用的东西的痴迷。我认为这一直是这样的练习，你可以看到三个月后、六个月后世界将走向何方。模型将会变得更加聪明。现在解决不了的事情，终于可以解决了。我认为 Cursor 有点像这样反复出现的提示，我们怎样才能把这些东西拉到今天？即使它需要一点点工程才能使其工作，或者需要大量工程才能使其工作，即使它需要以特定方式更改产品以便用户可以与此新功能进行交互，我们如何才能实现这一目标？然后三个月后，我们应该删除所有这些东西，因为它会很好，就像……嘉宾是 Roman Ugarte，他帮助 SpaceXAI 构建了 Grok Bot，之前领导了 Cursor 的增长。许多创始人或人们今天开始更加扎根于这样的观点：我如何才能使现在不可能的事情成为可能？用户会来找我使用那个东西。我要把他们拉到下一个不可能的境界。然后通过这一切，我将获得很多分销优势。我将获得数据优势。那里会有价值。但我认为那才是真正可以玩的地方。
Lenny Rachitsky：
I love that answer. Essentially, the way I'm thinking about it is just build something people are obsessed with. Don't overthink the moats piece. And if you can continue to do that, you'll find something, which in Cursor's case ended up being a few things. And that came up actually recently in another podcast I did. I don't know if it'll come out before or after this, this idea that moats are discovered, not planned ahead of time a lot of times. Okay, let me actually ask you for Grok Bot tips as an actual last question. Some people are going to be like, oh shit, I got to try this thing. What's all this excitement all about? What would be some advice for folks that are trying out, let's say for people that are new to it, just like here's some keys to success and maybe some power tip for someone that's already with it and just like, oh wow, I didn't know that.
我喜欢这个答案。从本质上讲，我的想法就是构建人们痴迷的东西。不要过度考虑护城河部分。如果你能继续这样做，你就会发现一些东西，在 Cursor 的例子中最终会发现一些东西。这实际上是最近在我做的另一个播客中出现的。我不知道它会在这之前还是之后出现，这种认为护城河是被发现的，而不是提前计划好的想法。好吧，让我向您询问 Grok Bot 的技巧，作为最后一个问题。有些人会说，天哪，我必须尝试一下这个东西。这一切到底是为了什么？对于那些正在尝试的人，比如说对于刚接触它的人来说，有什么建议，就像这里有一些成功的关键，也许还有一些给已经使用过它的人的强大提示，就像，哦哇，我不知道这一点。
Roman Ugarte：
Yeah, I want to stay away from the, you know, super hacky pro tip stuff because I think our philosophy as a team and as a company is that those things really shouldn't exist. There shouldn't be all these crazy knobs. You should be able to delegate something to Grok Bot and they should do it. And so what I would encourage for someone new who's like just downloading the app, you're looking at this screen, I think the first thing is give Grok Bot the context it needs to be successful. So in a similar way as if you were onboarding someone to your team. It'd be really helpful for them to have access to, you know, Slack and your email and the company records that you use every single day. So I'd give it access to the tools. And then I would actually ask Grok Bot what it can do for you. And let it kind of go through those connections that you've initially set up. In my case, it might be I give it my email, I give it Slack. And I was really surprised when I was first onboarding. We didn't have any onboarding screens at this time, so this was kind of the first task I gave it, was go through my Slack, go through my email, and suggest like five things that you can take off of my plate. And what it would take for you to do that. And I suggested five. And like two of them were actually really helpful. And I just immediately spun off two bots to solve those two. And that was my big wow moment of feeling like no other AI tool in the past could have done those two things. It was not like draft an email. It was like do a chunk of work. And so I'd encourage people who are brand new to do it that way. And then for people who are not brand new, I kind of am constantly finding new patterns for ways that my bots can interact with each other and can collaborate with each other. And so I've been creating a bit more of a scaffold of kind of where these artifacts that Grok Bots create should live and how it can write to a place that's very legible to me. So I have like these frequent digests that I read every day and it kind of pushes to a place. database and I can just read it very easily. And so I would encourage power users to think about ways that Grok Bot can actually write to like a single store where you can organize a lot of its outputs much easier.
是的，我想远离那些超级黑客专业技巧的东西，因为我认为我们作为一个团队和一家公司的理念是这些东西真的不应该存在。不应该有这些疯狂的旋钮。你应该能够将一些事情委托给 Grok Bot，他们应该这样做。因此，对于刚刚下载该应用程序的新手，我会鼓励您看到这个屏幕，我认为第一件事是为 Grok Bot 提供成功所需的背景。就像您将某人加入您的团队一样。你知道，如果他们能够访问 Slack、你的电子邮件以及你每天使用的公司记录，这真的很有帮助。所以我会让它访问这些工具。然后我实际上会问 Grok Bot 它能为你做什么。并让它经历您最初建立的那些联系。就我而言，可能是我给它我的电子邮件，我给它 Slack。当我第一次加入时，我真的很惊讶。我们当时没有任何入职屏幕，所以这是我给它的第一个任务，就是浏览我的 Slack，浏览我的电子邮件，并建议你可以从我的盘子里删除的五件事。以及你需要做什么才能做到这一点。我建议了五个。他们中的两个人实际上真的很有帮助。我立即派出了两个机器人来解决这两个问题。那是我惊叹的时刻，感觉过去没有其他人工智能工具可以完成这两件事。这不像起草电子邮件。这就像做一大堆工作。所以我鼓励新手也这样做。对于那些不是全新的人来说，我不断地寻找新的模式，让我的机器人可以相互交互并相互协作。因此，我一直在创建更多的支架，说明 Grok 机器人创建的这些工件应该存放在哪里，以及它如何写入对我来说非常清晰的地方。所以我每天都会阅读这些频繁的摘要，它有点推动到一个地方。数据库，我可以很容易地读取它。因此，我鼓励高级用户考虑 Grok Bot 可以实际写入的方式，就像单个商店一样，您可以更轻松地组织其大量输出。
Lenny Rachitsky：
Damn, we need another episode of going deep on Roman's Grok Bot setup, which probably has way too much private sensitive information we couldn't show it. But that's okay. That's an amazing tip. Roman, is there anything that you wanted to share or anything else you wanted to touch on before we get to our very exciting lightning round? Nothing, nothing else on my side. We covered so much ground. That was, I can't believe it was only an hour and a half-ish. I felt like we've been talking for ages and covered everything I was hoping to cover. With that, we've reached our very exciting lightning round. I've got four questions for you. Are you ready? I am ready. What are two or three books that you find yourself recommending most to other people?
该死的，我们需要另一集深入探讨 Roman 的 Grok Bot 设置，它可能包含太多我们无法展示的私人敏感信息。但没关系。这是一个了不起的提示。 Roman，在我们开始激动人心的闪电回合之前，您有什么想分享的或其他什么想谈的吗？没有什么，我这边没有其他的。我们涵盖了很多领域。那是，我不敢相信这只是一个半小时左右。我觉得我们已经谈论了很长时间并且涵盖了我希望涵盖的所有内容。至此，我们进入了非常激动人心的闪电回合。我有四个问题要问你。你准备好了吗？我已经准备好了。您发现自己最向其他人推荐的两三本书是什么？
Roman Ugarte：
Yeah, so two books for you. One is I love Kurt Vonnegut. So Cat's Cradle has been a fun recommendation and a copy that I've bought many friends before. And then second is The War of Art by Steven Pressfield that I find myself frequently coming back to, even if it's just a page or two at a time, and I'd recommend for anybody.
是的，给你两本书。一是我爱库尔特·冯内古特。所以《猫的摇篮》是一个有趣的推荐，也是我之前很多朋友都买过的一本。第二本是史蒂文·普雷斯菲尔德的《艺术之战》，我发现自己经常回来读这本书，即使一次只有一两页，我会推荐给任何人。
Lenny Rachitsky：
War of Art, incredible. It's like such a short book. And it's like once you read it, and it's not the art of war, which is what people might think they're hearing. Yes, but it's the War of Art. It's a play on that. And it's about the challenge of being creative and creating something new and how to overcome the resistance. I love that recommendation. Next question. Favorite recent movie or TV show if you've had any time to watch any of these things?
艺术之战，不可思议。这就像一本很短的书。就像一旦你读过它，它就不是人们可能认为他们听到的《孙子兵法》。是的，但这是艺术之战。这是一个游戏。这是关于发挥创造力和创造新事物的挑战以及如何克服阻力。我喜欢这个推荐。下一个问题。如果您有时间观看这些内容，您最近最喜欢的电影或电视节目是什么？
Roman Ugarte：
Yes. Recently, so every year I do a watch of Casablanca, which is one of my favorite movies. And it incidentally also has a character with my last name, Ugarte, which is like the only example of, I think, a Ugarte in the media. So Casablanca, always a great rewatch. And then on the TV side, I sometimes sneak in an episode of Monk, the detective show, which was one that I watched kind of as a kid with my family, and I've come back to now that I live in San Francisco. And it's just a great moment in time snapshot of San Francisco in the late 90s, early 2000s when it was shot that I really enjoy.
是的。最近，所以每年我都会看《卡萨布兰卡》，这是我最喜欢的电影之一。顺便说一句，它还有一个以我的姓氏命名的角色，乌加特，我认为这是媒体中乌加特的唯一例子。所以《卡萨布兰卡》总是值得重看的。然后在电视方面，我有时会偷偷地看一集《蒙克》（Monk），这是一部我小时候和家人一起看的侦探剧，现在我又回到了住在旧金山的情况。这是 20 世纪 90 年代末、2000 年代初旧金山的一个精彩瞬间，我非常喜欢这张照片。
Lenny Rachitsky：
First Monk reference on the podcast. Okay, favorite or most interesting AI product right now? You can say Grok Bot if you want, but if there's anything else, you get bonus points.
播客上的第一个 Monk 参考资料。好吧，目前最喜欢或最有趣的人工智能产品？如果你愿意，你可以说 Grok Bot，但如果还有其他的话，你会得到奖励积分。
01:20:00
Roman Ugarte：
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. So I was like a very early user of Metaphor at the time, which became Exa. And I love kind of using Exa to do all of these maybe more strange queries over the internet. But I see a lot of examples of people building like semantically search over, you know, an embedded image store of the MoMA or kind of things like that. And I always have so much fun playing with those. So anything semantic search engine over like a weird data set, I love.
我一直是人工智能语义搜索的大迷。我喜欢任何 SEM 搜索产品，尤其是...那种与众不同的产品。所以我当时就像是 Metaphor 的早期用户，后来变成了 Exa。我喜欢使用 Exa 在互联网上执行所有这些可能更奇怪的查询。但我看到很多例子，人们在现代艺术博物馆的嵌入式图像存储或类似的东西上进行语义搜索。我总是玩得很开心。所以任何语义搜索引擎都像一个奇怪的数据集，我喜欢。
Lenny Rachitsky：
And EXA in particular is one you'd recommend?
您特别推荐 EXA 吗？
Roman Ugarte：
I love EXA, yeah.
我爱 EXA，是的。
Lenny Rachitsky：
Very cool. Okay, favorite life motto that you often come back to in work or in life?
非常酷。好的，您在工作或生活中经常想起的最喜欢的人生格言？
Roman Ugarte：
Not as short as a single motto, but I love the Desiderata, which I don't know if you've read, but I have it on my door. I've had it since I was a teenager, and everywhere I move, I kind of paste it there, and it's a very short poem. But each line, I just, I find myself finding something new in it every time I read it, and I find it really grounding.
不像一句座右铭那么短，但我喜欢《Desiderata》，我不知道你是否读过，但我把它挂在我的门上。我从十几岁起就一直拥有它，无论我走到哪里，我都会把它贴在那里，这是一首很短的诗。但每一行，我只是，每次读到它时，我都会发现自己发现了一些新的东西，而且我发现它真的很接地气。
Lenny Rachitsky：
Roman, this was amazing. What a point in time we're here right now, at this moment in time of Grok Bot, of AI in general. It's going to be really fun to revisit this, I don't know, in a year, and be like, wow, we were so right and so wrong about so much. Thank you so much for doing this. I know it's a very busy time on your team right now, so I really appreciate you carving out a couple hours to chat. Is there any place you want to point people to? Anything you want to plug other than check out Grok Bot?
罗曼，这太棒了。我们现在正处于一个多么好的时刻，在 Grok Bot 的时刻，在整个人工智能的时刻。我不知道，一年后重新审视这个问题将会非常有趣，并且会说，哇，我们在很多事情上都是对的，但又错了。非常感谢您这样做。我知道您的团队现在非常忙碌，所以我非常感谢您抽出几个小时来聊天。您想向人们指出什么地方吗？除了检查 Grok Bot 之外，您还想插入什么吗？
Roman Ugarte：
Check out Grok Bot, of course. And yeah, main thing would be please send feedback. I think we're in the very early innings of this still. I mean, we released... The guest is Lenny Rachitsky, who helped build Grok Bot at SpaceXAI and previously led growth at Cursor. They discuss product development, onboarding, AI agents, persistent memory, cloud architecture, startup speed, company values, and moats.
当然，请查看 Grok Bot。是的，最重要的是请发送反馈。我认为我们仍处于早期阶段。我的意思是，我们发布了……嘉宾是 Lenny Rachitsky，他在 SpaceXAI 帮助构建了 Grok Bot，此前曾在 Cursor 领导过增长。他们讨论产品开发、入职、人工智能代理、持久内存、云架构、启动速度、公司价值观和护城河。
Lenny Rachitsky：
Roman, thank you so much for being here. Awesome. Thanks, Lenny. Bye, everyone.
罗曼，非常感谢你来到这里。惊人的。谢谢，莱尼。再见，大家。
References
- 1Lenny's Podcast：How we built Grok Bot in a month
lennysnewsletter.com
- 2官方 Substack 播客音频源
api.substack.com
- 3
- 4
- 5官方 Substack 播客音频源
api.substack.com
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