Replit CEO Amjad Masad：一年收入增长 100 倍，究竟改变了什么？

简要描述Brief Description

Amjad Masad 谈到了 Replit 的营收增长、更简单的 AI 提示词、企业级防护措施、模型路由，以及自动驾驶公司成为可能的前景。Amjad Masad discusses Replit’s revenue growth, simpler AI prompts, enterprise safeguards, model routing and the possibility of self-driving companies.

目录Table of Contents

• 开场与介绍
  Opening and introduction
• 找到产品与市场的契合点
  Finding product-market fit
• 企业采用与更简单的提示词
  Enterprise adoption and simpler prompts
• 协作型与自驱型公司
  Collaboration and self-driving companies
• 代码质量与模型路由
  Code quality and model routing
• 竞争与一体化基础设施
  Competition and integrated infrastructure
• 采用前景与总结
  Adoption outlook and closing

开场与介绍Opening and introduction

我听你说过，不会编程反而能让你占据优势。我认为，那些已经用 AI 编程一段时间的人也处于劣势，因为最近几代 AI 模型（比如前沿模型）实际上更擅长处理非常简单的提示词。I heard you say that not knowing how to code can give you an advantage. I think people who have been coding with AI for a while are also at a disadvantage because most recent generations of AI model like the frontier are actually better with very simple prompts.

你觉得那个关键时刻是什么？就是你觉得你们已经实现了产品市场契合度的时候？当时我们大概有30个人在开发 Replit Agent，它确实是市场上第一个编程智能体。当时还没有任何编程智能体的先例，但我们一开始看到它在内部运行起来，就对它有了极大的信心。不过，那时候我们还不知道自己会在一年内实现收入增长100倍。What do you think was that pivotal moment that where you felt like you already hit that product market fit? The group of people about like 30 of us that were working on replet agent which is really the first coding agent on the market. There's no examples of coding agents at the time, but the moment we started seeing it work internally, we just had tremendous conviction in it. Now, still, we didn't know that we're going to 100x revenue in a year.

你觉得距离主流应用还有多远，才能让公司有信心地说：“好吧，我们这里有一些自动化反馈闭环。”我想说，大概……How far do you think we are from having mainstream adoption where companies can confidently say, "Okay, we have some automated feedback loops here." I would say like,

嗨，我是 Carlos，Product School 的 CEO，也是这档产品播客的主持人。今天的嘉宾是 Riplet 的 CEO Amjad Masad。公司成立 10 年了，他说前 8 年都只是在寻找产品市场契合度。后来他们推出了 Agent，一年内营收增长了 100 倍；如今他们拥有 5,000 万用户，估值达 90 亿美元，正朝着 10 亿美元营收的目标迈进。超过 75% 的用户不是工程师，而且他一开始就纠正了我：AI 领域没人有经常性收入，大家说的是营收运行率。接下来我们会聊这些话题：为什么他说聊天从来就不是关键；编程——不会编程如今反而成了一种优势；为什么他故意让自己的提示词变得越来越随意；以及自动驾驶公司，还有他为什么认为它会在明年年中出现。"Hey, this is Carlos, CEO at Product School and your host on the product podcast. My guest today is Amjad Masad, CEO of Riplet, 10 years in and he says the first eight were just finding product market fit. Then they shipped the agent 100x revenue in a year and now they're at 50 million users and a $9 billion valuation chasing a billion in revenue. Over 75% of those users are not engineers and he corrects me early on. Nobody in AI has recurring revenue. It's run rate revenue. Here are the things we'll cover. Why he says chat was never the thing. code is not knowing how to code is now an advantage. His prompts have gotten lazier on purpose. The self-driving company and why he thinks it's mid next year.

通过模型路由，以 40% 的成本实现前沿级性能。开始吧。AI 能帮助我们构思创意、起草计划，并在几分钟内启动工作。Frontier performance at 40% of the cost through model rooting. Let's get into it. AI helps us generate ideas, draft plans, and spin up work in minutes.

但更快并不一定意味着更好。当每个人都有自己的 AI 工具、自己的输出和自己的上下文时，就会造成碎片化、版本控制混乱、审查流程分散，决策各自并行，而非协同进行。在人与平台之间重新构建上下文，会耗费时间、削弱推进势头。这正是 Mural 发挥作用的地方。Mural 为团队提供共享的可视化画布，让大家汇聚工作成果。你可以直接在画布上生成结构化的起点，而不必在不同工具之间搬运输出。让所有上下文都集中在一处。兼容的 AI 智能体也可以与团队协作，带来它们熟悉的工具中的上下文。But faster doesn't necessarily mean better. When everyone has their own AI tools, their own outputs, and their own context, you get fragmentation, fractured version control, scattered review processes, decisions happening in parallel, not in concert. Rebuilding context between people and platforms costs you time and momentum. That's where Mural comes in. Mural gives teams a shared visual canvas to bring work together. You can generate structured starting points right on the canvas instead of moving outputs between tools. Keep all of your context in one place. And compatible AI agents can contribute alongside the team, bringing in context from the tools they already know.

工作的未来依然属于人类。了解更多信息，请访问 mural.co/mural-ai。Angel，欢迎你。感谢邀请我。The future of work is still human. Learn more at mural.co/mural-ai. Angel, welcome. Thanks for having me

感谢 Product Con 和产品播客。我 9 岁的儿子没能来到现场，但他让我代他说声谢谢。当然，这是因为他一直在 Replet 上编写电子游戏。to Product Con and to the product podcast. My 9-year-old son couldn't be here, but he asked me to say thank you. Of course, because he's been by coding some video games on Replet.

太棒了。现在电子游戏用上 AI 后变得特别出色，简直不可思议。我刚才其实就在一个展位上，我们有位销售工程师，他总是用 Replet 做电子游戏。他刚给我看了他做的 FIFA。我当时就说：“这比我小时候玩的 FIFA 还好。”而且他只用了一个提示词。That's awesome. Video games have gotten so good with AI. It's crazy. I was just actually on a at a booth, one of our sales engineers is like he's always making video games with Replet. He just showed me FIFA that he made. I'm like, "This is better than the FIFA I played growing up." And it was like one prompt.

找到产品与市场的契合点Finding product-market fit

哇。不过，也不是一切都那么顺利。你已经埋头苦干了10年，对吧？而最初的八年，可以说是在开始寻找产品市场契合度，对吧？Wow. Well, but not everything were rainbows and sunshines. You've been grinding for 10 years, right? And the first eight kind of were the beginning of finding product market fit, right?

最近发生了些什么？你觉得那个关键时刻是什么时候——也就是你觉得自己已经实现了产品市场契合度的时候？在创业公司的发展历程中，我们一直有这么一种想法：公司在 C 轮待两年，在 A 轮待两年，然后实现产品市场契合度，再从那时开始规模化发展。但我觉得，这种情况可能只是 SaaS 时代的现象。如果看看那些老牌企业，打造出有意义的东西大约需要五六七八年。即便是近些年，你看看 Notion、Figma，或者我们那个时期的一些同行，也花了不少时间才走到今天。所以我想，我之所以有耐心，是因为我觉得我们正乘着一些趋势前行，而这些趋势未来会变得越来越重要。So what's been happening? What do you think was that pivotal moment that where you felt like you already hit that product market fit? In the history of startups, we we've always had this idea that like you know companies like you spend two years in C, two years in A, you get product market fit and you scale from there. But I think that sort of was only like a SAS era phenomena. If you look at old businesses like it takes about five, six, seven, eight years to build something meaningful. And even recently when you look at businesses like notion or Figma or some of our peers from that era, it took him a while to get there. So I think like I've had the patience because I just felt like we are riding on certain trends that are going to become more and more important in the future.

其中一个是云计算，第二个是人工智能，第三个类似移动端，第四个类似协作，也算是未来的工作方式。One of them was cloud, two was AI, three was like mobile and four was like collaboration and kind of the future of work.

所以我们一直都很有信心。显然，有时候也会非常自我怀疑。但我们在开发 Replit Agent 时，多少已经意识到它代表着未来。当时公司正处于艰难时期：我们刚裁过员，因为花了很多钱，却没赚到钱。不过，我们这群大约 30 人的人正在开发 Replit Agent，它确实是市场上第一个编码智能体，当时还没有任何编码智能体的先例。可我们一看到它在内部开始发挥作用，就对它充满了信心。当然，那时我们也不知道一年后营收会增长 100 倍——没人能预测到这一点。So always had conviction. Obviously there are times when there's a lot of self-doubt. But when we were working on replet agent, we kind of knew it was the future. Like it was a rough time for the company. We had just done a layoff because we were spending a lot of money and not making any. But the group of people about like 30 of us that were working on replet agent which is really the first coding agent on the market there's no examples of coding agents at the time. But the moment we started seeing it work internally we just had tremendous conviction in it. Now still we didn't know that we're going to 100x revenue in a year that was like no one predicts that.

这确实很难预测，但我们知道那就是未来。几年后，你已经拥有超过 5000 万用户，估值达到 90 亿美元。It's really hard to predict but we knew it was the future. So a few years forward now you are with over 50 million users $9 billion valuation.

你们的目标是在今年年底实现 10 亿美元的年度经常性收入。进展如何？You're aiming for a billion dollars in revenue in annual recurring revenue by the end of this year. How is that going?

企业级应用的普及与更简单的提示词Enterprise adoption and simpler prompts

顺便说一句，在 AI 领域，没人用 ARR（年度经常性收入）这个说法。所以我们得习惯说 RR，也就是运行收入。不过，嗯，情况进展得不错。我觉得有几件事挺有意思的。我认为今年企业对 AI 的采用确实大幅推进了。回顾一下，从 GPT-3 出现以来，企业其实并没有怎么使用 AI；ChatGPT 的出现算是改变了这一点，后来又有了 Microsoft Copilot。但看看现在的大多数企业，大家用的都只是聊天工具。这里在大公司工作的大多数人，如果不是工程师——工程师通常处在技术前沿——就只能用聊天工具，或许再加上某种 RAG 系统之类的东西。不过今年，我们开始看到大型银行、金融机构、Visa、AMAX，以及我们的一些客户开始签约使用 Replit；政府也开始使用了，美国政府目前就是 Replit 的客户。By the way, no one is AI in AI has annual recurring revenue. So we need to get used to saying RR run revenue. But uh yeah, things are going well. I think there are a few things that uh are interesting. I think that enterprise adoption of AI has really advanced this year. So if you look at the last like you know since GPT3 enterprises were not really using AI chat GPT sort of started change that and then like Microsoft copilot but if you look at most enterprises today they just use chat most people here who work at large companies if you're not an engineer engineers you know are typically on the cutting edge but if you're not an engineer you just get access to chat and maybe some rag system or whatever But now this year we're starting to see like big banks sign up to Replet, big financial institutions, Visa, AMAX, some of our customers, governments, the US government is a customer of Replet right now.

我们终于开始看到 AI 如何改变工作以及我们的工作方式了，因为我不认为聊天本身会带来很大影响。之前大家有个很大的疑问：我们在 AI 上投入了这么多，却看不到成效。我不认为聊天是关键。我真的觉得，归根结底，代码才是关键。每个人都能开发软件、编写代码，还能借助智能体来完成工作，而大多数智能体本质上都是编程智能体。它对经济的影响将会非常具有变革性，而我们现在还处于早期阶段；但它的复利效应着实惊人。我想进一步了解这件事，因为你的用户中似乎有 75% 以上不是工程师，而且我听你说过，其实不懂编程反而可能是一种优势。It's a we're finally starting to see how AI could transform work and how we do work because I don't think chat really has a big impact. And there was like the this big question, oh we're investing so much in AI, we're not seeing impact. I don't think chat is a thing. I really think ultimately code is the thing. The idea that everyone can make software, can create code and can like work with agents and most agents are coding agents essentially to get their work done. That's quite transformers on the economy and we're in the early innings of that, but the compounding nature of it is quite astounding. I want to learn more about it because it seems like over 75% of your users are non-engineers and I heard you say that actually not knowing how to code can give you an advantage.

我觉得，那些已经用 AI 编程一段时间的人也处于劣势，因为最近几代 AI 模型——比如前沿模型——其实更擅长处理非常简单的提示词。随着时间推移，我的提示词也变得越来越随意。我用的技能文件之类的东西也少了，因为模型变得越来越强大。所以，你越是试图事无巨细地控制它们，效果就越差。你知道，硅谷有句老话，说微观管理不太好——这确实没错，对吧？比如，如果你有一位很有才华的工程师，就不该事无巨细地管着他。但大多数工程师的本能却是对 AI 进行微观管理。而那些没有这种本能的人，反而可能得到更好的结果，你现在已经开始看到这种现象了。I think people who have been coding with AI for a while are also at a disadvantage because most recent generations of AI model like the frontier are actually better with very simple prompts. My prompts have gotten lazier over time. I use sort of like less skill files, less so models are getting more and more capable. So the more you try to micromanage them, the worse they are. You know, there's like this wisdom in Silicon Valley that micromanagement is is not great, which is true, right? Like if you have a talented engineer, you shouldn't be micromanaging them. But like most engineers, their instinct is to micromanage the AI. Whereas someone who is not doesn't have that instinct might actually get better results and you're starting to see that.

我看到，使用 Replit Agent 可以启动多个子代理，对吧？接下来我想到的是，实际上该怎么调用、编排或监督它们呢？我不想说是事无巨细地管理，但至少作为人类用户，怎样才能对当前情况有比较清楚的了解？I saw that with replete agent you're able to spawn multiple sub aents right and the next thought that comes to that is how do you actually call it orchestrate or oversee I don't want to say micromanage but to make sure that at least you have a good sense of what's going on as a human user

所以，UI 显然需要提供相应功能，让你了解情况。比如使用多个并行 Agent 时，每个 Agent 都有自己的对话线程，你可以逐个查看它们的工作进展。Agent 也会提出问题，而且我们还有移动应用。你安装后，它就会给你发消息，比如：“嘿，我可能会超出预算”“我打算用这个新软件包”或者“我准备做这个重构”。这样你就能掌握情况，而 Agent 也会逐渐了解你的使用习惯。如果你完全不想操心，Agent 会慢慢适应这一点。但如果你是那种喜欢事无巨细地管理 AI 的工程师，那也完全没问题，Replit 会逐渐适应你的偏好。so the UI obviously needs to give you so you know with parallel agents we have like a thread for each one of them you can sort of like dig into each thread of work and see what's going on. Also, agents come back with questions and we have the mobile app. If you're install it, it'll like send you a message. It'll be like, hey, like I'm going to go over budget or I'm going to use this new package or I'm going to do this refactor. And so you have that sort of oversight and also the agent kind of learns your pattern of usage. And so if you're someone who is totally hands off, the agent like kind of learns that. But if you're an engineer who is micromanaging the AI and that's what you prefer, you know, more power to you and like replet will sort of adapt to that.

所以你最近提出了“自动驾驶公司”这个说法。企业如何学会学习？So you recently coined this term of the self-driving company. How can companies learn to learn?

协作与自驱型公司Collaboration and self-driving companies

所以我认为，学会学习具有一种复利效应，很大程度上就像我们生成的所有内容都可以重新回到上下文中。现在大多数公司的问题是，大多数人都在桌面端使用云端工具或聊天工具，而这些内容实际上并没有反馈到上下文中。在 Replet，我们的大部分 AI 使用都发生在 Slack 上，其中很多是在公开频道里进行的，所以一切都能相互关联、形成反馈。我们撰写的文档也会重新融入上下文，因此协作变得非常重要。我的意思是，我们花了很多时间琢磨如何在 Replet 上实现与 AI 协作，比如让多个人参与同一个项目。而各大实验室都没有把重点放在这方面。So I think there's a compounding nature of learning to learn very much like every everything we generate can go back into context. The problem now with most companies is most people are using cloud or chat on the desktop and that is actually not feeding back into context. At Replet most of our AI usage happens in Slack and a lot of it in public channels and so everything is self-referential. We write documents they kind of go back to the context and so collaboration becomes very important. I mean, we spent a lot of time figuring out how to do collaboration with AI on Replet, like having multiple people on the same project. None of the big labs are focused on that.

但我觉得那像是个错误。But I think that's like a mistake.

就像你希望的那样，我觉得眼下更重要的是，以更协作的方式来打造公司、开展工作，因为我们作为个人贡献者手头要做的事情会变少。新想法往往来自头脑风暴，来自在彼此想法的基础上继续推进。你几乎应该像经营开源社区那样来打造公司：开源社区可能会有点混乱，也没有一个集中的领导者，但大家都在彼此的成果之上继续构建，也都在相互学习。我认为，随着公司变得更加自主——许多工程工作、支持工作和运营工作都实现自主化——公司未来的运作方式也会改变。你必须思考，人类的角色是什么？归根结底，我认为就是了解客户想要什么，判断最值得打造的东西，做出重大的决策，大致确定目的地，然后相信公司能像自动驾驶一样自主运行，完成其余的工作。like you would want like I think it's more important right now to approach you know building companies more collaboratively and doing work more collaboratively because we're going to have less work on our plate to go do as individual contributors and where new ideas sort of emerge happens from brainstorming happens from building on each other's ideas you almost want to approach building a company like an open source community where in the open source community things might be a little bit chaotic and there's no centralized leader but you know everyone's building on top of each other's things everyone's learning from from one another and I think the future of how companies work as companies become more autonomous when a lot of the engineering is autonomous when the support is autonomous when a lot of the operations are autonomous you you have to ask what what is the role of the human and ultimately I think it is knowing what the customer want I think figuring out what's the best thing to build figuring out the major decisions kind of setting the destination and then trusting the self-driving autonomy of the company to do the rest.

对我来说，关键是能够在 Slack 中开始使用 Replet。我也看到你们与 Muse 或 Cloud Code 有类似的集成，所以我想了解一下，你们如何看待这类外部用户界面，以及它们如何增强协作。Unlock for me was to be able to start using Replet within Slack. And I see that you also have a similar integration with Muse or with with cloud code. So I'm curious to know how you're thinking about those type of external user interfaces as a way to enhance the collaboration.

是啊，我的意思是，我觉得我们都在试着摸索这应该是什么样子。我不认为有人已经弄清楚什么样的用户界面最好。我觉得操作系统才是正确的问题。某种程度上，我们都把 Slack 当作公司的操作系统来用，但它并不好用。它基本上就是个堆放所有文本的地方，而且人类用户要吸收所有内容已经变得非常困难。这就是为什么我们不得不越来越依赖智能体来总结越来越多的沟通内容，以及正在发生的事情。也许到某个时候，你会想要一种纯粹面向人的界面，因为我觉得智能体生成的很多内容，可以说是一连串的思维过程，你可能并不想费心去关注。Yeah, I mean I I think we're all sort of trying to discover what that looks like. I don't think anyone has figured out what's the best kind of user interface. I think operating system is the right question. I think we're all using Slack as an operating system in some ways for companies, but it is not a good one. It is basically dumping ground for all of text and it has become very hard for the human user to absorb everything which is why we're having to rely on agents more and more to summarize more more of the communication more of what's happening. you might want to at some point have like a human only sort of interfaces because I think a lot of the like a lot of the stuff that agents are generate are like kind of you can think of it as chains of thoughts that you might not want to worry about.

总之，这里有个关于可读性的问题，但我认为这是个非常开放的问题，而且如今最大的创业机会之一，就是弄清楚这到底意味着什么。对于技术用户，也就是工程师，我注意到一件事：你在博客上发表文章说，你能够提高代码的产出，同时不牺牲质量，也没有出现人们通常会预期的那种权衡——毕竟只是给火里添更多燃料。那么，你是怎么做到这一点的？你如何才能真正提高生产力和吞吐量，同时又不影响质量？So anyways, there there's a question of on legibility here, but I think it's a very open question and it's like one of the biggest startup opportunities today is figuring what that is out. And then for the technical user, for the the engineer, one of the things that I noticed is that when you publish on your blog that you were able to increase the output of your code through output without sacrificing quality and other maybe traditional trade-offs that you would expect as a result of just putting more gas into the fire. So how are you able to to to combine that so you can really increase that productivity and that throughout making the quality suffer?

代码质量与模型路由Code quality and model routing

所以在 vibe coding 这股风潮刚兴起时，Replet 可能是唯一一个奉行计算力至上的参与者。我们一直努力生成最好的软件、最安全的软件，也构建了市场上许多可以串联组合起来使用的东西。So early on when the whole vibe coding thing was happening, Replet was the probably the only player that was like compute maximalist. So we were always trying to generate the best software, the most secure and we like built a lot of the things you can string together in the market.

不过，就像我们内置了代码审查功能，也内置了安全代理，这让 Replit 稍微贵了一点、慢了一点，但你可以更信任它的结果。所以现在在 Replit 内部，我们都用 Replit 来构建 Replit。因此，我们内部比大多数公司都更放心地向设计师、甚至销售人员开放提交拉取请求。很多公司可能不愿意这么做，是因为仍然存在安全问题，也存在代码质量问题。如果你有非常完善的系统和防护措施，我认为大多数公司都会愿意向非工程师开放他们的 GitHub 仓库。But like we have built-in code review, we had built built-in security agents and it made replet a little more expensive, a little slower, but you can trust the results more. And so now internally at Replet, we all use replet to build replet. So internally we are a lot more comfortable than most companies opening pull requests to designers to even salespeople. The reason why a lot of companies might not want to open that up is because there's still like a safety issue. There's still like code quality issue. If you have really good systems and guard rails, I think most companies would want to open up the sort of get their GitHub repos to to non-engineers.

不过，这些护栏和系统是默认创建的吗？还是说公司需要专门搭建一些东西来确保质量？大公司需要这么做，我觉得小公司不用。不过现在在大公司里，我们已经开始这么做了——我的意思是，现在大家都在这么做——也就是采用 FDE 模式：我们会到客户那里，弄清楚他们的需求，并与他们合作，将他们的准则和风格指南编码进去。在很多情况下，银行和大型金融机构还涉及大量合规和监管问题，这些问题非常棘手。我敢肯定，在这些公司工作的人都知道，这是 AI 尚未得到大规模应用的一个重要原因。But so are those guard rails and systems created by default or do companies need to set up something just to make sure that the quality is there? Bigger companies need to to do that. I think smaller companies don't. But now with bigger companies, we started doing I mean everyone's doing it now, but the FDE model where we go in, we figure out the requirements and we work with them to encode their guidelines and style guides and in many cases in banks and big financial institutions there's a lot of compliance regulatory issues and those are very tough. And this is big reason why I'm sure a lot of people who work at these companies would know this is a big reason why AI has not seen tremendous adoption.

事情可能出错的地方实在太多了，所以，是的，它们需要多一些手把手的指导。你们的采用率也达到了……怎么说来着，财富500强企业中的80%到85%。There's so many ways in which things can can go wrong and so yeah they require a little bit of more handholding. You also have like what like 80 85% Fortune 500 adoption.

是的，按 PLG 的标准来看，这就像企业合同。规模小得多，但正在追赶。明白。我觉得另一个重要部分是模型路由，对吧？有些企业会有自己的标准，来决定团队有哪些选项。你们会如何处理这类路由？Yeah this is like PLG terms of like enterprise contracts. It's significantly less than that but it's catching up. Got it. I mean the other big piece I think is the model routing right like some of the enterprises will have their own criteria in terms of what are the options for their teams like how do you go about that type of routing?

是的，我们向客户承诺，对于任何给定任务，我们都能为你找到成本最低、效果最好的 token。因为过去三四年里，我们积累了大量使用数据，所以我们训练模型来判断需要什么级别的模型，不仅要看模型大小，也要考虑推理投入等因素。我们在网站上发布了基准测试结果，持续证明我们能以 40% 的成本实现前沿性能。因此，当你购买 Raplet 时，通常情况下——当然，大型企业和政府会有一些限制——我们希望客户信任我们，让我们来选择模型。我们和所有不同的服务提供商都签有零日数据保留协议，因为只要我们拥有这种自由，就能始终保持前沿性能，同时大幅降低成本。Yeah so we we promise our customers that we'll get you the cheapest token for like cheapest best token for any given task. So because we've accumulated a lot of data on usage over the past 3 4 years, we train models that can figure out what is level not just model size but also reasoning effort and so on. And so we've published benchmarks on our website showing that we can get frontier performance at 40% of the cost pretty consistently. So when you buy a raplet we sort of in most cases again there's like big enterprises and governments that have certain restrictions but in most cases we would want the customer to trust us with the model selection and we have zero day retention u contracts with all the different providers because if we have that freedom we're always going to be at frontier performance but also significantly cheaper.

竞争与综合基础设施Competition and integrated infrastructure

是的。我觉得这有点像一种市场动态：你与 OpenAI、Anthropic 合作，同时也可能被视为竞争对手，对吧？那么你如何应对这种二元关系？Yes. I think there's like a market dynamic situation where you are collaborating with OpenAI anthropic and at the same time you could be considered a competitor right so how do you navigate that dichconomy

你知道，我们一直都有这个问题。我们长期以来都是 Google Cloud 的客户，他们一直想和我们竞争，我记得从很早以前就是这样。他们有一个叫 IDX 的在线 IDE，在那之前还有别的东西，而且那些东西现在大概都已经没人用了。现在他们又推出了 Google Studio。我的意思是，这从来没怎么困扰过我。我看待这些大公司的方式是：有两三件事是他们绝不能输的，然后他们还会做一百件或一千件对他们来说没那么重要的事。you know we've always had this issue like we've been Google cloud customer for a long time they've been trying to compete with us ever since I remember like they had a like an online ID called like uh IDX and they had something before that and and they're probably all dead now and now now they have like the Google Studio. I mean, it never really bothered me. The way I view these big big companies is that there's like two or three things that they can't lose on and then they're going to do a hundred or a thousand things that are less important to them.

我的意思是，最初大家都在自己的平台上加入氛围编程功能时，很多投资者真的非常担心我们。你知道，我一直在说，我们只专注做一件事：成为创建软件的一站式平台，而平台的深度非常重要。比如面向消费者的使用场景，没错，任何人都可以在任何地方制作各种网站，你也可以让任何智能体来做。但如果你想在 Replit 上建立一家企业，或者运营一家企业，我认为我们仍然是最好的选择，因为我们提供了所有基础设施，也提供安全保障、合规与隐私保护等等。你知道，如果你在 Muse、Codex 之类的平台上构建网站，他们似乎会把网站交给 Cloudflare 这样的外部服务商托管。I mean initially when everyone was adding VIP coding to their platforms you know a lot of investors were really worried about about us and you know I kept saying that we just do this one thing which is we're one-stop shop for creating software and the depth of the platform is very important like the consumer use cases yeah anyone can make sort of any sort of website anywhere you can ask any agent to make that but if you want to build a business on replet or if you want to operate a business I think we're still best at that because we provide all the infrastructure we provide the security guarantees you know compliance privacy and so on. It doesn't seem like you know if you build a website on um you know Muse or Codex or whatever they send it to Cloudflare some external provider to like host it for you.

使用 Replet 时，所有东西都整合在一起，因此智能体可以访问整个环境，包括开发环境和生产环境，我们也能更好地控制。比如，信任 Replet 时，你只需要信任一方，而不必像现在这样信任三四家不同的服务提供商。With Replet it's all one thing and so the agent has access to the entire environment development and production and we also have better control like when you trust replet you only trust one player as opposed you're trusting like three or four different providers.

完全同意。我觉得，随着模型逐渐商品化，价值会被推向上游的应用层，而应用层更具差异化；此外，你也不必在基础设施建设上投入巨资。是的，我的意思是，这就是关键。我们的高级用户通常要么是创业者，很多时候独自打造价值数百万美元的企业；要么是企业员工，他们也在用 Replet 做出很了不起的成果。所以……Totally. I think as the mod is commoditized the the value got pushed upstream at the application layer has a more differentiator plus you do not have to do the heavy investments in building the infrastructure. Yeah, I mean that's that's the main thing. I mean, so you know, our power users tend to be either entrepreneurs who are like building, you know, multi-million dollar businesses many times solo and then like, you know, corporate employees that are like doing amazing things with Replet as well. So what

而且，而且这两组的共同点是，我不想管理基础设施。对。有人告诉我，微观管理和注重细节之间的区别，取决于你给对方多少自主权。对。and and the the common thing between these two groups is that I don't want to manage infra. Yeah. Someone told me that the difference between micromanagement and attention to detail is that depends on how much agency you give to the other person on the other end. Yeah.

采用前景与结语Adoption outlook and closing

总之，回到那家自动驾驶公司，我觉得这是个很迷人的概念，但听起来仍然很有未来感。你觉得我们距离它成为主流、让企业能够自信地说“好，我们这里已经有一些自动化反馈闭环了”，还有多远？我觉得到了明年年中，企业就能比较从容地运行智能体，让它们承担实际工作。现在，大多数智能体都运行在员工的笔记本电脑上。除了科技公司之外，真正把智能体用于实际工作流程的企业可能寥寥无几。所以我觉得到了明年年中，你会真切地感受到自己有了数字同事。我觉得过去几周，我们也开始看到这些 AI 助手被大规模采用，比如 News Instinct、Crockbot。这种超级周期会对你的业务产生什么影响？So anyway, going back to the self-driving company, I think that's a fascinating concept that still feels like futuristic like how far do you think we are from having mainstream adoption where companies can confidently say okay we have some automated feedback loops here? I would say like mid next year companies will be comfortably running agents doing real work. Right now most agents happen on employees laptops. Very few companies perhaps outside of tech that are using agents to do real workflows. So I think mid next year it'll feel like you really have digital co-workers. I think in the last few weeks we're also starting to see a massive adoption from these AI assistants like news instinct crockbot like how does that super cycle impact your business?

这有好的一面：更多人了解这些工具的威力后，就会要求自己的公司配备这些工具，或者把其中一些工具带进公司。也有棘手的一面：我觉得面向消费者的氛围编程已经不再是一个可行的市场了。我们确实从中赚过一些钱，但从一开始我就知道这种情况会发生。所以我一直觉得，我们应该向企业和商家收费，而不太应该向消费者收费。现在我们有免费方案——你也可以每月花20美元订阅 Rebot，然后一直写代码。呃，所以我们现在有一个免费……或者说不限量套餐。不过我觉得一切都挺好的。It is good in that more people knowing the power of these tools will demand their companies to have those tools or will bring some of these tools to their companies. It is challenging in that like I don't think consumer vibe coding is a viable market anymore and it's something we've made some money on but from the start I knew that was going to happen. So that's why I always thought that you know we should monetize enterprise and businesses and not really monetize consumer which is now we have a free we have a free like you subscribe to Rebot for $20 and you can just do code forever. Uh so we have like a free uh or like unlimited plan now. But I think it's all good.

越多人了解这些工具对他们的生活或工作能产生多大影响，采用速度就会越快，这对我们的业务有利。Like the more people understand how impactful these tools can be in their lives or their work, then adoption will happen faster and that's good for our business.

那我们就聊到这里吧。我只想说，如果一年后或者六个月后，我们能坐在彼此身边，说一句“还记得你当时说的话吗？”那就太棒了。是啊，这家自动驾驶公司正在得到广泛认可。Well, we're going to leave it here. I would just say that it would be awesome if one year from now or 6 months from now, we're sitting next to each other and we say, "Remember what you said?" Yes. There's so much adoption of this self-driving company.

我认为现在是活着的最佳时代之一。真的，有很多事情可以去创造。很多人都在试图让你相信，现在已经没有理由再创办初创公司或企业了。但这里有巨大的机遇，至少在未来两年里，这都是一个绝佳的时代。谢谢。当然。I think it's one of the best times to be alive. It's really there's a lot of things to build. A lot of people are trying to convince you that there's no reason to create startups or businesses anymore. There's tremendous opportunity and at least for the next two years, it's like a amazing time. Thank you. Of course.