Vercel CEO Guillermo Rauch 谈如何为 Agents 构建互联网
- Vercel 的使用曲线已从以人为节奏的云采用,转向以机器为节奏的部署:用了约10年才达到10亿次部署,之后10个月又增加了15亿次。 Agent 驱动的部署占比从年初的3%升至60%。节目以一轮3亿美元的 F 轮融资和93亿美元估值开场,Molly O’Shea 同时援引 The Information 的数据称,Vercel 年化收入达到6亿美元。
- Rauch 最激进的判断是,廉价代码和个性化软件可能吞噬传统 SaaS 的大片市场,同时提升部署基础设施的价值。 他所说的“致命组合”是:企业可以“买下 Vercel 作为平台,然后再也不用买软件”,转而生成面向具体领域的应用。Salesforce、SAP 这类系统可能继续存在,但越来越像无界面化的权威数据源,而不是员工需要访问的界面。
- 互联网的下一代界面将是 Agent 对 Agent,这要求企业以机器原生的形式开放信息、能力和交易。 AEO 和可搜索的文字稿依然重要,但 Rauch 认为这些还不够:产品必须支持 MCP、Machine Payments Protocol 和 Universal Commerce Protocol 等协议。Vercel 已经看到 Agent 在其市场中购买 BrowserBase 等服务,而且“完全不需要人工介入”。
- 自主性既创造了 Agent 时代的基础设施需求,也带来了最具定义性的安全风险。 Agent 能够写代码、部署、浏览、交易,并在更长时间内追逐模糊目标,推动算力需求“垂直增长”;但同样的资源调度能力也让它们容易遭受提示词注入,并具备寻找软件漏洞的能力。Rauch 预计,接下来“几年会很艰难”:防御与攻击 token 将展开竞争,企业则需要加固沙箱和人类编写的代码。
- 开放模型已经从一种意识形态偏好,变成 Vercel 所测量 token 流量的多数来源。 Rauch 表示,Vercel AI Gateway 上80%的 token 流向开放模型;年初时,Vercel 的网络主要由 OpenAI、Anthropic 和 Google 占据。企业可以把前沿智能留给规划,把更便宜的开放模型用于执行,并通过“一行代码”切换供应商。
- 前沿实验室仍有需求,但 Rauch 认为,留存和经济模式的持久性,而不是基准测试的绝对领先,才是投资者尚未解决的问题。 当领先模型可能在几周内更换时,客户表现出“零忠诚度”;免费补贴、虚构的 token 规模,以及存疑的零数据保留声明,也让 AI 的部分市场像加密货币“来得容易、去得也快”的阶段。不过他仍然保留判断:如果真正差异化的智能具备可持续的经济模型,就能留住客户。
- 工程正在变成跨 Agent 的资本配置,但 Rauch 既反对盲目的 vibe coding,也不接受人类判断已经无关紧要的说法。 他的原则是“拒绝不理解”:人应该指挥 Agent、检查其成果、验证关键系统,并决定哪些工作值得消耗 token。Vercel 目前招聘看重的是“接管大批 Agent”的能力、技术好奇心和真正的人类沟通能力——证明工作的含义,已经超越了交付一个由 AI 生成的小型 Demo。
1. Agent 驱动的部署将10年压缩为10个月
Rauch 创办 Vercel,起点只是一个简单的挫败感:即便是有经验的开发者,要交付一个安全、高性能、可扩展的应用,也仿佛需要先拿到“云计算博士学位”。因此公司的创立前提是“让交付变得简单”,并将一次部署定义为向应用发布的每一次变更。
Vercel 花了约10年才达到10亿次部署,之后仅用10个月又增加了15亿次。部署构成也同样剧烈变化:年初,编程 Agent 只贡献了3%的部署;如今“60%由 Agent 驱动”,用 Rauch 的话说,就是“机器人告诉其他机器人该做什么”。
编程模型也许在生成算法方面已经“超越人类”,但 Rauch 的基础设施逻辑从一个约束出发:“代码不会自行产生任何作用。”它必须在某处被构建、加固并部署。Vercel 已经成为病毒式实验以及 OpenAI、Meta 等公司应用的目的地,有时还会直接体现在默认的
.vercel.app域名上。财务背景与使用量拐点相互印证,但节目对数据来源进行了明确区分:节目提到 Vercel 的3亿美元 F 轮融资和93亿美元估值,O’Shea 则援引报道称其年化收入为6亿美元、客户约485,000名。Rauch 对客户增长的解释是:“现在是 Agent 在做选择,而且它们选对了。”
2. 多年前做出的开源选择,变成了面向机器的分发渠道
Rauch 在阿根廷学习编程时,开发软件是专有的,而且贵到他买不起;大多数使用手册又都是英文。他部分是为了学习代码才自学英语,之后在寻找免费工具和托管服务时接触到开源。这段经历塑造了 Vercel 的信念:开发者工具——如今也包括 Agent 工具——应该“免费且开放”。
因此,Vercel 花了11年发布框架、文档和运营知识。随着模型开始基于公开信息训练并检索公开信息,这种开放变成了商业优势:“关于你的信息越多,它们能访问你的内容以及你定义的规则越多,这个 Agent 就越好。”Rauch 认为,这既是“正向因果”,也是一门好生意。
这种姿态也延伸到 Vercel 的运营体系: “iterate to greatness”(持续迭代,直到卓越)、“dig deep”(深挖)、透明,以及公开工作。Rauch 还把常规数据与“anecdata”结合起来——客户反馈、X 上的讨论、直觉和市场氛围——因为在 AI 领域,“棋盘每两周就会重新洗牌”,上季度的表格本身已经不够用。
3. 人类监督正从敲代码转向管理智能
Rauch 的原则是“拒绝不理解”。一种做法是告诉 Agent 要构建什么,从不检查成果,直接按下发布键;而他偏好的方式——包括对自己的孩子——是使用 AI,但理解 AI 做了什么。他现在越来越多地阅读代码,并要求 Agent 向他解释自己的选择。
最接近现有的职位描述是工程经理:组织执行、排除障碍、检查工作、运行基准测试、执行 QA,并带回一线反馈。最好的经理依然理解工程、热爱工程,因此 Rauch 并不认为监督 Agent 就等于可以变成技术文盲。
他区分普通的“系统”和负责敏感数据、关键基础设施、安全或国家安全的大写“系统”(Systems)。Vibe coder 有其合理位置,但事关重大的系统需要由 Agent 驱动的工程师、验证机制,以及防止 Agent 发布“垃圾”或意外把“你的数据扔到整个世界”的安全措施。
4. 企业必须为 Agent 重建互联网,而不只是向 Agent 做营销
旧互联网把页面和以像素为中心的界面从机器交付给人类。Agent 访问 Vercel 时,不需要人类访客看到的动态渐变;它需要的是“直接信号”——精确的商业信息和可调用的能力。Rauch 对这一转变的概括是:“为 Agent 而建,由 Agent 驱动。”
O’Shea 提出一个 Bot 检测难题:如果一切都是 Bot,还剩下什么需要检测?Rauch 的回答划出了一个重要区别:企业需要 Bot 情报。它们应该知道来访的是 ChatGPT、Claude、Grok、编程 Agent 还是爬虫,这些 Agent 是否成功,以及每类 Agent 应该获得哪些上下文信息。
搜索和 AEO 依然必要,因为模型存在训练截止时间,也会通过网页搜索获取最新信息。Rauch 对 O’Shea 业务的具体建议是发布播客文字稿,这样未来有人提出“ Molly 说过某某什么?”时,系统就能检索到她真正说过的内容。但只有信息还不够,产品本身也必须具备 Agent 化运行能力。
MCP 让服务可以告诉 Agent 它们能够使用哪些工具;Vercel 的 MCP 暴露了部署软件、列出项目等功能。Rauch 还提到 Machine Payments Protocol 和 Universal Commerce Protocol:能够“说” Agent 协议的企业,可以绕过更慢的浏览器导航,直接开放交易能力。
5. 个性化软件挑战 SaaS 界面,但保留权威数据系统
Rauch 可以让一个基于 Slack 的 Agent 为客户会议做准备:调取 Salesforce 活动、支持问题和账户背景。他本人从不访问 Salesforce;Agent 负责访问,再根据问题、用户和使用熟练程度,生成合适的界面。
Rauch 不认同未来会由不断膨胀的“最大公约数软件”套装主导。他把 Vercel 称作一家“yes-code 公司”:如果 Agent 让代码事实上变得免费,企业就可以生成适配自身工作流的工具。他刻意采取极端表达:“你买 Vercel 作为平台,然后再也不用买软件。”
O’Shea 提出“无头 Salesforce”的框架,Rauch 对此进行了限定。生成的软件依然需要权威数据:客户历史、联系人、会议记录和支持工单必须存放在某处。Salesforce、SAP 及类似支柱系统可能仍是关键数据基础设施,即使 Agent 用新的应用和上下文可视化取代了它们固定的界面。
6. 更长时间的自主运行,让有用的 Agent 变成开放式安全主体
Rauch 认为,与早期 ChatGPT 相比,最大的变化在于自主性。ChatGPT 需要人类主导循环——提问、接收答案、再次提问;而 Agent 把这个循环放进系统内部,并被训练得能够在没有干预的情况下“越来越久、越来越久、越来越久”地运行。
好处是无需操心的资源调度能力:让 Agent 找到 Molly 的邮箱并发送生日祝福,40分钟后,它可能已经搜索了网页、Crunchbase 和 YouTube 评论。用户只看到任务已经完成,而看不到中间那一连串动作。
同一条行动链也制造了风险。隐藏在 YouTube 评论中的恶意指令,可能重新引导一个正在使用用户 token、工具和资源的 Agent。核心问题变成:为了完成任务,哪些行动是被允许的?又该如何阻止外部信息改写任务本身?
Vercel 正在提供一种类似“面向 Agent 时代的内网”的企业基础设施,让 Codex、Claude Code 等系统能够在内部部署。其模型中立立场为企业提供了安全性和模型选择权:针对具体任务,企业可以选择表现最好的供应商,而不必把技术栈绑定在某一家实验室上。
7. 编程能力也让 Agent 成为异常强大的黑客
Agent 对软件规则的理解足以写出软件,也就足以破坏这些规则。Rauch 表示,许多企业还没有解决 Agent 安全问题,而一些所谓的沙箱实际上只是能访问“整个该死世界”的电脑。真正受控的环境,必须能够在 Agent 主动寻找逃逸路径时仍然把它困住。
Vercel 发起了100万美元挑战,邀请全世界攻击其沙箱。Rauch 表示,最终只有一名高水平安全研究员借助“一支 Agent 大军”取得进展;这一发现暴露出一个关键 Linux 漏洞,Vercel 正在处理,并与行业同行共享。这里的限定很重要:这是成熟的人类专业能力经过 Agent 放大后的结果,不是一个孩子随手要求 Claude 去黑什么东西。
Rauch 预计,短期内防御者与攻击者之间会展开“4个好 token 对4个坏 token”的竞争,因为双方将获得相近的智能。他反对出于网络安全原因封禁开放模型,因为开放模型的防御能力,正来自制造攻击风险的同一种通用智能。他的预测仍然谨慎:基础设施必须加固,未来几年会“很艰难”。
更长期的出路是可验证代码。Rauch 正在探索证明系统,让永不疲倦的 Agent 生成可以被证明“几乎在数学意义上”正确的软件。他提到一份 OpenAI 的数学证明,其代码对数学家来说都很难解析,并据此认为,机器生成的软件可能走向一种人类很少能在大规模实践中实现的确定性。
8. Agent 让基础设施需求垂直增长,但质量仍是护城河
旧的算力周期受人类限制:一个下午写几个文件,部署一次,然后等待人们访问。如今,Agent 生成并部署代码,其他 Agent 再浏览和使用由此产生的服务。这一复合循环解释了 Rauch 为什么认为基础设施需求正在“垂直增长”,以及 Vercel 网络为何每天都在创下新的利用率纪录。
他没有声称已经看到需求上限。医疗、教育和个人 Agent 的渗透率仍然很低;即便是给孩子做的一个“很粗糙”的数学应用,在他看来也最终会变成个性化 Agent。更有价值的活动意味着算力、能源、网络和网络安全领域的需求都会增加。
沙箱本质上是发给 Agent 的一台云电脑,类似员工使用的笔记本电脑。Rauch 认为,Vercel 进入这一市场时已经有11年相关经验,因为每次部署本来就需要安全的云算力来构建代码。对于廉价的新云厂商报价,他的答案是质量:不可靠或不安全的基础设施也许能快速上线,但要维护它,需要“用一生去承诺”。
9. 开放模型赢得流量,前沿实验室则对抗商品化
Vercel 的 AI Gateway 汇聚了专有模型和开放模型,让 Rauch 能够观察 token 需求。年初,Vercel 的网络主要由 OpenAI、Anthropic 和 Google 占据;他特别认可 Gemini 在企业客户中的价格性能平衡。如今,他表示,网络上80%的 token 来自开放模型。
尽管一直支持开源,Rauch 过去仍认为开放编程模型不可用。中国实验室改变了他的看法:他特别点名 Kimi“好得惊人”,同时保留了它并非在每项基准或执行任务上都获胜这一限制。他的解读是,大量企业工作——他推测或许占流量的80%——并不需要“Albert Einstein”级别的智能。
一种常见架构是让最强模型负责制定计划,再把执行工作——将计划转成代码、指令或操作——交给更便宜的开放模型。供应商因此变成可替换模块;切换一个供应商只需“一行代码”。未来,自动路由也许会根据上下文和所需智能水平进行选择,而不再要求用户先挑选模型。
O’Shea 以 Bending Spoons 据报99%使用开放模型为例追问:前沿实验室还剩下什么?Rauch 的答案不是它们会消失,而是客户忠诚度很弱:基准测试领先可能只维持几周,运行在他 MacBook Air 上的小型 Qwen 等本地模型正在进步,而免费补贴、制造出来的 token 规模,以及存疑的零数据保留声明,都让客户留存难以判断。只要智能和经济性都能成立,前沿模型仍然有需求。
10. 工程正在变成跨 Agent 集群的资本配置
Rauch 说,他和 DHH 曾经热爱的那个开发者世界——为人类双手优化的精美代码——“已经不是现在的游戏了”,这要求人经历一次“自我消亡”。Rust 体现了这种逆转:它僵硬、晦涩的编译器让人类痛苦,但 Agent 可以消化这种摩擦;Rauch 预计,Agent 将更快地生成更安全的代码。
人类不会消失的任务,是决定什么值得投入。Rauch 将 Marc Andreessen 所说的“最后一份工作是风险投资人”改写成“资本配置者”:每个人拥有相同的墙上时钟时间,但如今可以调度能够调查、构建和执行的 token。创造力、优先级排序和工具选择仍然稀缺。
Vercel 的招聘标准也随之改变。静态简历本来就不如工作成果有说服力;如今,即便是一个 vibe-coded Demo 也不够。Rauch 希望找到能够“接管大批 Agent”、搭建软件工厂的人,同时还要能真实沟通、赢得客户信任,并通过好奇心和提示词不断提升技术熟练度。
Mercedes 的迁移项目是他的证明:一个 Agent 在5分钟内完成了从旧平台迁移到 Vercel 的第一版重写;Rauch 表示,过去这项工作需要数月。O’Shea 补充说,咨询公司可能要花1年。“贴近代码或贴近客户”如今变成贴近客户的代码——前置部署团队现在可以直接执行迁移。
11. 最终的运营原则是打好基础,从健康到流动算力
当被问及如何在经营一家约800人的公司、同时抚养6个孩子的情况下保持个人状态时,Rauch 拒绝在基础问题尚未解决前进行最后一公里优化。他的拳击教练给出的经验是:“先把饮食调整好,吃干净、完整的食物,甚至出去走走”;他还会做引体向上、轻度有氧,不喝酒,并和孩子一起练巴西柔术。
他把同样的纪律应用于 Vercel:忽略流行但分散注意力的事物,贴近客户痛点,保持产品可靠。他给客户的指标是“迭代速度,而不是速度”——速度可能只是原地打转,而迭代速度代表随着市场变化进行调整的能力。
在他看来,Serverless 并没有消亡,反而因为 Agent 生成的软件不可能全部持续运行而变得更有必要。Vercel 将下一章称为“流动算力”:容量“像液体一样流动”,在函数、网站、沙箱和 Agent 之间随流量扩张、在闲置时收缩。Rauch 预计,它将“定义下一个10年”。
完整逐字稿
Vercel recently raised $300 million in a Series F funding round. It brings the cloud company's valuation to $9.3 billion.
Vercel seems to be winning. You guys are at a $9.3 billion valuation. The Information reported you guys at $600 million in annualized revenue.
When you're a developer or a company of any size, you can deploy these agents and make your business more efficient. We started out the year with 3% of deployments on Vercel coming from coding agents. Now 60% are agentic.
Oh my God.
It took us about 10 years to get to a billion deployments, and then in the next 10 months, we've added another 1.5 billion deployments. So what took us 10 years, we've now surpassed in just a few months.
Almost every other thing I see on X every day is just a Vercel deployment. Sometimes you see the largest companies in the world deploying on Vercel, including companies like OpenAI and Meta. Agents are now making the choices, and they're choosing right. The lethal combination there is that you buy Vercel as the platform, and then you never have to buy software again.
G, welcome to Sorcery.
Thanks for having me.
Well, thanks for having me in your really cool studio.
We're here in San Francisco, on the seventh floor of the Vercel headquarters.
I mean, this is insane. You have multiple studios in here—
Yeah.
—as well. I was talking to your crew before, and you have this acronym of, like, you have to do everything at the best. What is that?
Well, we have a couple of company values. One is ITG: iterate to greatness.
Mm-hmm.
So once upon a time, recording out of Vercel was not this good. We're always iterating to greatness. The other one is "dig deep." Whether you get a customer complaint or you find a bug, go as deep as humanly and agentically possible.
Say more about that.
When I started Vercel, I was a framework and dev tools builder.
Mm-hmm.
My passion has always been: can I build a better hammer? Can I build a better power drill, but for software developers?
Back when I was a kid in Argentina, I would be given a project. This is kind of fun: I started out doing freelance gigs as a software developer. Any time I would be given a job, I would do the job, and I would also build my own tools to do the job, for two reasons. One is that I loved it, and the other one is that with each incremental job, I would be able to do it more easily and faster. In fact, it ended up being true. My lifetime has been about creating better tools. When I started the company, the first tool that became super, super popular was Next.js.
Mm-hmm.
We created the framework that almost everybody in the world has now used to build modern web experiences. But I also see the company itself as a product, and the best products are built with the best tools and the best frameworks.
Over the years, people have asked me a lot, "What is your role at the company these days?" I tell them, "I do a little bit of everything. I do QA, I talk to customers, et cetera," but I invest a lot in the machinery that powers the company itself—the machinery that yields innovation in the future.
I think one of the key constituents of this framework of how I run the company is our values and our mission statement—the classic things. We put quite a bit of effort into who we are and what our values are.
Is this how you became and continue to be very popular on the internet? Nick and I were talking about this, but you are a celebrity.
I'm a nerd celebrity of sorts. But I'll tell you, one of my personal values is transparency and working in public. A lot of my personal traits have permeated through the company as well: open source, open models, building in public, transparency.
Mm-hmm.
The reason I think I've had success communicating with people over the internet is that I just tell it like it is. People have asked me if I have ghostwriters for my X posts. I also spend a lot of time with young founders. Another value of mine and of our family is giving back.
Mm-hmm.
I spend a lot of time trying to give back to the ecosystem, and I invest in a lot of young founders. Almost every week I get, "Who writes the tweets for you?"
Really?
"Can I hire a firm?" I tell them, "Look, it's just..." It sounds like the worst advice because it's so simple, which probably makes it good advice. Just be yourself. Tell your story, share your truth, and don't overthink it too much. I think that's how some of the bangers have happened online.
But you go viral very constantly. Do you check your X analytics? I know I'm going off on a tangent, but I'm curious now.
No, no—
I—
I do, actually, for the sake of... Another, maybe, toxic trait of mine is that I'm constantly scrutinizing products: how fast they load, how well they represent the UI, whatever.
The only reason I've spent a lot of time in X analytics is that I know the engineer at X who worked on that feature, and I've given him a bunch of feedback. But you kind of feel it. You don't need analytics.
This is another—this is not really a value, but an operating principle of mine: you have to be mindful of the data and the anecdata, especially when running a business in a fast-moving market like AI.
Mm-hmm.
You can't just go off, like, "Oh, yeah, the last quarter's little spreadsheet that the data analysts put together." We were talking before about how every 2 weeks the board is getting reshuffled, and so you have to marry the anecdata, the vibes, and the instincts with what you're seeing from the arithmetic of your business.
I try to go off how I feel, how people feel, and, you know, you do have to adapt and move really fast in this world. I think what's proven really valuable to Vercel has been that we have a mission about enabling builders and enabling people to ship what's next. That means we constantly have to be rethinking and reinventing who we are, how we work, and so I think there's a sense of almost working in real time with the world and having this real-time conversation.
Based on that real-time conversation, you inform your next move.
I don't know if you'd be surprised or not, but when I've had these interviews—and I've interviewed many different CEOs and investors—a lot of them are getting their news and their pulse on what's going on in the AI industry just from X alone.
Yeah.
You'd think it'd be somewhere else, but it's like, no—
Yeah, you would think it's their research teams—
Yeah.
—and there are large enterprises with technical advisors to the CEO who write them reports and memos prior to meetings. But no, a lot of us are just in that global conversation, making our contributions, and then seeing how customers react.
So Vercel does play a role in this. You aggregate and distribute some of that data, but you've also mentioned before that we're in the middle of an exponential—or the exponential. What does that mean?
Yeah. For context, Vercel got really popular because of how easy we made it for anybody on the planet to ship an application.
When I started the company over 10 years ago—almost 11 now—if you sat down, even as an experienced software developer, and you wanted to put an app out into the world that really performed, was secure, and scaled, it was like a PhD that you had to take on cloud computing.
Mm.
At the time, I realized, hey, if it's hard for me to ship an app—and I've been studying the blade since I was pretty much 10 years old in Argentina, programming day in and day out—and if it was so hard for me to ship an app, I couldn't even fathom an enterprise trying to figure out cloud computing, frameworks and tools, shipping pipelines, and all of that.
I started a company with that simple premise: make it easy to ship. It took us about 10 years to get to a billion deployments. Deployment is one of my favorite words. Every time you ship a change to your app, that's a deployment.
In the next 10 months, we've added another 1.5 billion deployments. So what took us 10 years, we've now surpassed in just a few months.
The reason for this is that, one, shipping has gotten easier. Not easier in the sense that the code is actually pretty damn hard, but now we have coding agents writing the code, and I think nobody ever saw that coming.
The people building the AI, the people close to the AI, think what's been the supersonic tsunami is that the machines have taken over. They're better than us at figuring out these algorithms and this code, but they need to ship that stuff somewhere.
When you write the code... Code is kind of a funny thing. I remember telling people that another one of my internal principles is: code is a liability.
Code can have vulnerabilities. Code is how you could delete stuff. You can leak customer data. You have to treat code with responsibility.
Now these coding agents are superhuman at writing the most amazing code. But again, code doesn’t do anything on its own. It needs to live somewhere. It needs to be deployed.
Vercel has emerged as the place, this universal field, where all of the coding agents are plugging into and pushing their code out so that it can be used by anybody. You probably are using Vercel every day of your life, because when you see things on X go viral, it now makes me quite proud to see this. It took us so long to build it, but almost every other thing I see on X every day is just a Vercel deployment.
Sometimes you can tell because, by default, we give people a domain name. It’s like “.vercel.app.” Sometimes you see the largest companies in the world deploying on Vercel, including companies like OpenAI and Meta.
We’ve been at this juxtaposition of all of this, which, to your point, has given us a very unique lens into what’s happening. Not only are we seeing all of the activity coming from the coding agents, we’re also distributing the tokens on the internet.
A lot of companies and developers are coming to us to get their AI tokens, and we offer every model under the planet. You can get OpenAI, Anthropic, open models, closed models, and proprietary models. We’ve emerged as this index that tells you where AI is going.
Are you still coding?
Yes. Now we can get into hot-take territory. One of my tweets that went viral the other day, I called it “Reject Non-Understanding.”
What do I mean by rejecting non-understanding? There are 2 schools of thought today. On one hand, you can tell your AI agent to do whatever, and you don’t even look at what it’s doing. You press a button, ship it, and it ships it to Vercel or wherever.
There’s another route, which is the one that I recommend to my children. I was up doing math homework with one of my children last night. It’s to use the AI, but also understand what it’s doing.
Now, you asked specifically, “Do I write the code?” I read code. What this means is that I’m asking the AI more and more to explain back to me what it did, which is a little bit of the job.
I’ve compared it to being an engineering manager. The engineering manager at any big tech firm in Silicon Valley over the last 10 or 20 years has also been a subject of debate, but for the most part, they help their engineers get organized, help them execute, and get blockers out of the way.
Obviously, the best engineering managers are amazing engineers themselves. Occasionally, they write code. Sometimes they write code to test out what you did and poke holes. Sometimes they might write a little benchmark. Sometimes they may do QA of the final product. Sometimes, in collaboration with the product manager, they might bring feedback from the field.
They’re looking out for you so that you don’t make mistakes. I think the role that most people are now taking with these coding agents is that of an engineering manager.
Again, the best engineering managers that I’ve ever worked with, first of all, love code. They love writing it, understanding it, and so on. I still do it. I also shipped something this weekend that you could call a proof system, a mechanism by which we can make sure that the AI doesn’t ship slop and doesn’t yeet your data out into the world by mistake.
I purposefully read lots of the code. I wrote down a lot of the examples, because there’s a lot of sensitivity around code. AI and code will run more and more of our lives, whether we like it or not.
Formula 1—there was a massive event because they had to ship a software update into the cars, and the drivers were complaining. You realize these moments make you think, “Holy shit, these Formula 1 cars are being run by code.” How the engine works is determined by code.
You’re going to go to the hospital, and all of those systems are run by code. It’s so important that we take these AI safety issues, the quality of the code we produce, and how we verify it extremely seriously.
To be honest about this, how many people—or what percentage of other companies or employees in companies—are actually doing that? I’ve heard people say they don’t even know how to read their code anymore because they don’t know what the coding agent is making.
I’ll tell you a wild stat first. We started out the year with 3% of deployments on Vercel coming from coding agents. Now, 60% are agentic.
Oh my God.
More and more of the software of the world is just robots telling other robots what to do. You can think of it as robots that take in English and yeet out code for other robots to run.
Of that 60%, it’s hard to say, but I will tell you there’s a really cool thing happening right now. When I was a kid in Argentina, I had to work so hard just to write my first line of code.
First of all, a lot of software for writing code was proprietary and financially impossible for me to purchase. I couldn’t pay for it; I couldn’t afford it. Second, most of the manuals were written in English.
It’s a little thing, but most of the world doesn’t speak English. At the time, I had to teach myself English as a way of teaching myself how to code. I had all of these obstacles in the way.
Then I taught myself English, and I had to get around all of these problems: How do I get software for free? How do I host it for free? And all of these things.
That led me to open source and the big epiphany that has defined Vercel: The tools that developers and agents should use should be free and open, so that everybody in the world can learn. It’s such a simple thing.
When you think about why Vercel has emerged as this coding-agent favorite, it’s because over the past 11 years, we’ve open-sourced everything we know. It turns out that when the models get trained, the more information there is about you, and the more they can access your content and the rules that you’re defining, the better it is for the agent.
It was positive karma that we put out into the world, and it’s also good for business. Essentially, what’s happening that’s really good is that if you were to say, “I want to ship my first line of code today. I want to ship my first app. I want to ship my first idea,” you don’t have to go through the troubles that I had to go through.
That’s miraculous, and I want that to continue to happen. I don’t want to be the guy who says, “You have to understand every line of code and every precise mathematical principle behind these systems.”
But I can tell you, perhaps as another hot take, there are systems, and then there are capital-S Systems. There are the systems that are going to run and host our data, our most critical infrastructure, our security, and our national security.
I do think that there’s a place for agentic-powered engineers, and there’s a place for vibe coders, which is the term that the industry has given to the more playful, “Let me just yeet out whatever from the AI” type of behavior.
To unpack and go deeper into this era of exponential growth, you’ve been running Vercel for almost 11 years now—the birthday is in November. Can you explain those shifts and how they’ve impacted developers, their workflow, and their workday? How has it also impacted you as a business and what you offer them? You’ve now had to open the kimono to multiple different kinds of new products to keep up.
Totally. In the beginning of time, there was the web, and it was made out of pages and human-centric interfaces. You open up a website or an application, and you’re the one consuming. It’s machine to human.
The era that we’re going into now is more agent to agent. Imagine a place where you can deploy interfaces for agents.
A simple example is when an agent goes to vercel.com. I don’t give it the fancy experience. People should go to vercel.com; they’re going to see this beautiful triangle with a gradient. Our engineers and our agents carefully chiseled this beautiful animation.
I don’t give the agent that. The agent doesn’t care. The agent wants straight signal. What we give the agent—and this is a Vercel Cloud capability—is highly precise information about our business that the agent needs to learn.
So you’re creating your website now for agents?
Correct. We’re helping everybody in the world make this transformation as fast as they can, because if they don’t make that transformation, they’re going to be left out of the most exciting economic opportunity of our times.
Mm-hmm.
More and more of the traffic on the internet will be agents doing things for us.
I’ll give you a very simple example. If you ask Muse to build you a website, it’ll use Vercel. It can go off and say, “I’m going to visit Vercel, get some information about how to build software, and then build something for this user.”
I need to present my best face to that agent and to the many, many other agents that are going to…
And this is true for every business, right? The example that’s super top of mind for people is DoorDash, a customer of Vercel, just shipping an agent where you can ask for a burrito over text message. You could argue it’s a gimmick. Actually, some people will use it, whatever. The key point is that this is an agentic interface.
There are going to be people talking to an agent, and then that agent will go and talk to DoorDash. Funny enough, a lot of the internet was built to block bots, which is kind of nuts. A lot of websites are saying, “Oh, you know what?” They’re using technology that was built for a different era that actually says, “No, no, no, this is a bot. I don’t want this traffic.”
Vercel is taking the opposite posture. We’re saying, “No, no, no. The moment is now to help every business in the world retool themselves for agents. For agents and by agents.”
That’s a really good point. I just put out this interview that I did with John Collison of Stripe at the BrowserBase Navigate conference. We were also talking about this before, but they’re the browser for agents to browse the internet—or the connector for agents to browse the internet.
I was talking to John Collison about this, and John said, “Why do we need bot detection anymore?” Everything’s a bot. What are we detecting?
What you do need, and what we provide, is bot intelligence. It’s so important to know if the bot is having a good experience, which is kind of nuts to think about, right?
The transformation that Vercel made is to go from developer experience—which was our first customer, a developer—to now the agentic developer experience. It’s very important that you understand, “Okay, am I getting ChatGPT on my website?”
Yeah.
Because I want ChatGPT on my website. I want it to get the best possible information. I want it to get contextual information. People are not just distributing static information on the internet; they’re also distributing capabilities. You also want to expose your tools, your products, and your services to the agents.
We partner with Stripe and Shopify to offer agents the ability to transact. Another astonishing fact about the Vercel business is that we see agents now purchasing our services. One of the most popular tools in the Vercel toolset is a capability that helps agents buy stuff from our marketplace. For example, if an agent needs to buy a web browser, it can purchase BrowserBase through the Vercel Marketplace.
I’m enabling that transaction end to end without any human intervention. It’s like the agent is visiting the virtual Vercel shelf and saying, “Oh, I need that.” Then I say, “Okay, it’s this much.”
What’s really important for business owners is that you need to have this intelligence about what’s happening with all of these agents: Grok, ChatGPT, Claude, the coding agents, and even the search engine crawlers.
Because one important thing that people need to know is that models are getting trained all the time, but they have certain cutoffs in training. When ChatGPT first came out and you would ask it, “Hey, ChatGPT, what day is it?” it would say, “Oh, it’s 3 years ago,” or something like that, right?
What we have done as an industry is give the agent the ability to search the internet. It’s still very important for businesses to be really good at putting out their content. In fact, I’ll give you an example. When you put out your podcasts and your shows, you want to make sure that there’s a transcript as well.
When an agent—I’m not even going to say “I,” because I’m not going to be doing it—when I say to my agent, “Hey, what did Molly say about so-and-so?” if you basically fed the internet with that information, you’re going to be there more readily available to the agent. This is true for basically every business online.
That's why we have a newsletter. Subscribe to sorcery.vc.
Yes.
Um, no, that’s a really good point. To talk about that shift, we had SEO, which was really important before. Then we went into the age of chatbots, or that kind of thing, chat logs, and we had GEO. I don’t know what happened with that. Are you saying we need a new thing for agents? What would that be?
It’s not just giving them the information. That’s sort of what AEO is about, which I think is really, really important. It’s also that you have to make sure that your product runs agentically, that the agents can use it.
The fundamental protocol—or programming language, we can call it—when the internet first came around was hypertext. It delivered HTML, which some older people in the audience might recall as MySpace codes. The internet for humans was HTML. The internet of agents is new protocols.
One is called MCP, which basically allows you to say, “Hey, agents, these are all the tools that you can use from my service.” For example, the Vercel MCP says, “Here’s how you deploy software. Here’s how you list your projects.” We’re creating a presentation of Vercel that is very ergonomic for the agent.
There are new protocols also emerging. For example, one is the Machine Payments Protocol, or the Universal Commerce Protocol. These are going to be the ones that you mentioned: web browsers.
When I ask my agent, “Hey, go and purchase the same thing that I purchase every month,” or, “Hey, go and get me this really cool…” I take a photo of this. “Go get me this really cool microphone,” it can go and browse a website. Some companies will be out there saying, “Hey, agent, you can just buy it far more quickly in a more streamlined fashion because I’m speaking your language. I’m speaking your protocol.”
I think what we’re going to see over the next few years is a complete transformation of every product and every service toward this. By the way, you see this even from the largest enterprises. I recently spoke at the Salesforce conference.
Salesforce was built as a product that was awesome for humans. You go and see your list of contacts, your CRM. It’s that vision of a pixel-centric interface for humans.
Nowadays, the way that we work at Vercel is that I can go into my agent, which we deploy on Slack, and say, “Hey, tell me about Molly and how frequently she deploys on Vercel, because I’m going to have a meeting with her and I’m her account executive. Give me a quick report on some of the problems that she’s reported.” I never actually went to Salesforce.
Right.
I just went to the agent, and the agent went to Salesforce. What we’re helping companies figure out is, first, how do you build agents so that you can streamline your operations?
Almost everything we do at Vercel, we do with agents, so I don’t have to learn these 20 different tools. You may think, “How big of a change is that?” What I can tell you is that agents are so much easier to use. It’s such a disruption of how products are built.
It’s such a disruption of the Silicon Valley ethos, even, because you would go to any company in Palo Alto, and they would be designing interfaces for humans. They would all be gathered together in a room, and the whiteboard would say, “Okay, what does G have to see when he wants to prepare for a meeting?” “Well, let’s put Molly’s profile picture up here and a list of 5 support tickets over here.”
It was very fixed in time and space, and it was decided basically by a product design team somewhere in the world. At Vercel, we have an agent that helps prepare our Salesforce and our customer support teams.
The interfaces are more generative. If I’m asking about an individual, it renders a profile of that individual. If I’m asking about a company, it gives me more contextual information about that company.
We’re going more and more into a world that, if you’ve watched “Minority Report,” feels more like the information is just coming to you depending on everything: context, your level of experience. I may not want to give a beginner sales development representative the same kind of sophistication that I’m going to give my finance team when I give them an outlook of our business.
These are all things that agents can solve for that websites, traditional pages, and pixels could not solve for. We’re helping this new generation of software be easy to build and ship to these companies.
There are 2 questions I want to ask off of that. One is, what does the end state of the agent era look like? I had Chenxi from Merge on a couple of months ago.
Yeah.
She’s a huge fan. She loves Marc Benioff. She’s a huge fan of Salesforce, and when she saw them go headless, she was like—
Yeah.
“He sees the future.” He’s seeing beyond what no one’s really going to need to go into their Salesforce. They can just interact with it and use it headless.
We’re seeing this now, as you’re saying, with agents, Shopify, and Stripe. Someone was talking about this on X: the agent is buying directly from the brand, so it’s not going to Amazon.
Yeah.
So, maybe that's helpful for small businesses.
Yeah.
What does this end state look like?
Well, I'll tell you my super-opinionated point of view: I almost take the opposite stance. We were talking about your Bending Spoons thing that went viral. I don't believe in aggregating piles and piles of software and having what you could think of as lowest-common-denominator software.
I believe in a future of personalized software. Vercel makes it possible for you to prompt with your coding agent and generate software that's perfect for you. You can build the podcast's schedule and note-taking app, and an agent that fits just your needs.
But most importantly for enterprises, their ROI on creating tools that are domain-specific is much, much, much greater. In fact, there was this entire category of SaaS that you could call no-code, and I'm on the opposite end of the spectrum. I'm a yes-code company because I'm now saying coding agents basically make the code free.
So why not buy—well, the lethal combination there is that you buy Vercel as the platform, and then you never have to buy software again because you can just generate it to your needs. So where do the Salesforces and SAPs of the world fit in?
Well, software needs data. I can generate the most beautiful meeting prep, report, or any of these awesome things that you can deploy on Vercel—websites, applications, agents—but they need to get their data from somewhere. I think the sources of record—the place where customer history lives, where contacts live, where my meeting notes live, where my support tickets live—are critical data infrastructure.
I'm not going to call it software because you used the word headless. What does headless mean? Headless means that we no longer go to the head ourselves. The agent can go and get the data out of the system and then either create new software, create new visualizations of the data, et cetera.
In a way, the entire world of software is changing, and in a way, I think some of the fundamental pillars will still be there.
This episode is brought to you by Brex, my favorite. You become what you spend on, and I refuse to spend my time on work that shouldn't exist. Expense reports, receipt chasing, and manual closes. The companies building what's next, from Vercel, OpenAI, Anthropic, Granola, and Deepgram all made the same call. They all run on Brex. Brex is the intelligent finance platform that combines cards, expenses, and banking into a single stack with agentic finance built in. AI agents that handle expenses automatically enforce policy before spend happens and close your books in minutes. That's why Sorcery runs on Brex, so I can spend time on building and not busy work. It's time to get Brex AF. Learn more at brex.com/sorcery. That's B-R-E-X.com/S-O-U-R-C-E-R-Y. Bye. From handshake to signature faster, Harvey, the AI platform built for legal work, is trusted by 80% of the AM Law 100 and over 20% of the Fortune 500. Learn more today at harvey.ai. That's harvey.ai. AI needs more than chips. It needs power, land, and infrastructure. Zone develops next-generation data center campuses, partnering with AI companies, site developers, and technology leaders to bring compute online faster and at scale. Zone is building the foundation of the AI frontier. Visit zonefrontier.com to learn more. That's zonefrontier.com to learn more.
As you've seen these different value-aggregation buckets of where infrastructure is going, how have you oriented the business around that to capture that value?
Infrastructure is extremely valuable. It has this compounding value and return because when you enable anybody to ship and make source code free, essentially, that code has to be deployed to some infrastructure.
The other thing that's really, really important in this age is security and creating guardrails for what the agents can do. The infrastructure to support agents is extremely vital. Vercel has created new services purpose-built to secure and contain the agents.
A good example is that now everybody can create software. How do you prevent this software from accidentally going out into the internet if it's supposed to be internal to your organization? We created an enterprise platform where you can plug in Codex, Claude Code, and all of these systems, and then securely deploy.
Some people might remember the term intranet, where you basically had an internet that's just for your company, right? We built that for the agent era.
Another really important primitive is the news that went viral around OpenAI hacking Hugging Face. What happened there is that they had this agent, and the agent was given a goal. In the pursuit of that goal, agents—for better and for worse—will do whatever it takes to fulfill their mission.
They're like a soldier whose frontal lobe has been removed, and they're like, "Let's go, go, go, go, go." People will come to appreciate this capability because when you deploy these enterprise agents, when you build your own agents, you're going to realize that now they can act autonomously for longer.
In fact, if I were to summarize what has changed about the world since ChatGPT to today, it's autonomy. With ChatGPT, we had to be in the loop: "Hey, ChatGPT, tell me this. All right, now tell me that. All right, now tell me this." We put that in a loop, and now we call that the agent, and we're training them to go for longer and longer and longer.
What can happen is that you say, "Hey, agent, go and close this sale," and the agent can take a very open definition of that. They're so resourceful, and they're being optimized to fulfill their mission and to go for a very, very long time without intervention, because that's also a better user experience.
If I say, "Find me Molly's email because I need to send her a happy birthday note," the agent can say, "I'll do whatever it takes to find this email and send her the note." Forty minutes later, it tells me, "Oh, I did it."
Maybe it went to the web, maybe it went to Crunchbase, or maybe it found it in a comment on YouTube where you said, "This is my email." This is actually the stuff that happens with agents. But the user experience is great because I didn't have to do all that. I just told my agent to do it.
The risk is exactly that: what are the guardrails for what's okay for this agent to do in the fulfillment of this mission? How can we prevent other people or external influences from altering what that mission was supposed to be in the first place?
I'll extend that example. I say, "Find Molly's email and send her a birthday note." It goes to YouTube. Sometimes you've probably done this: you've Googled an email, and then you find some shitty website or whatever. You find someone, copy and paste the email address, right?
Now imagine that in that YouTube comment, someone plants a prompt injection. A prompt injection is an instruction that's hidden, that's evil, and meant for my agent. My agent was just scrubbing YouTube, and now it got somewhat persuaded to do something evil. But it's acting on my behalf. It's acting with my tokens, my tools, and my resources.
That risk exists. So the long answer is that Vercel is also building the sandboxes and capabilities so that companies can operate agents, deploy agents, and really trust them. They can get the good experience from them, but really trust them to do the thing they were supposed to do.
Side note: Have you ever seen a sandbox that didn't have sand spill on the outside of it? Why are we calling it this?
Great question.
They're not enclosed environments.
Great question. The word sandbox is being used a lot, and sometimes it's kind of a technical misnomer in that it's not what people are calling a sandbox. This computer has access to the entire freaking world. It's not really a sandbox, right?
When OpenAI hacked Hugging Face, there were elements that were sandbox-like, and there were elements that truly weren't. But I'll tell you, the thing that concerned me about that incident is that the first escape of the agent came from a really good sandbox.
Going back in history, in the Linux community—in the Unix community, actually—one of the earliest words that was used was "jail." FreeBSD was a community that coined, I think, "jail," which, in my opinion, is arguably a better word, right? Because with a sandbox, you're right: you just escape. You just step out.
It spills everywhere.
So FreeBSD created a concept of jails—
Mm.
—to refer to sandboxes, which perhaps would be a term that people would hate, so let's not bring back "jail" necessarily. But to your point, the idea is that you are containing the agent within a controlled environment.
It's more like having the agent be a rat in a cage—it's fully contained, it can't break the glass, and you're watching it spin. In practice, I can tell you that, talking to prospects and talking to people we're helping figure out agents, people have not really figured out agent security yet.
A very, very important part of that is having very secure sandboxes, which is itself a really big challenge because coding agents are also extremely good at finding vulnerabilities in code.
We love coding agents. They're great at writing code. But overall, in order to be good at writing code, you're good at understanding the rules of code. And to understand the rules of code, you also understand how to break the rules of code. And so what's emerged is that these coding agents are really good at hacking, and that means that enterprises right now really need to be prioritizing protecting themselves from the potential AI hackers of the future.
So Vercel takes a stance here: we will not lock you in to any model provider. We will give you the tools so that you can use coding agents, secure your environments, and use every model under the sun, which is very attractive to enterprises because sometimes it emerges that a certain model may be better at cybersecurity than another. It's also economically better because you make all of the model providers compete for your business. It's also better from a quality standpoint. Whoever is the new hot model today might just keep the pole position for 2 weeks.
That is happening.
It's exactly happening. I was going to say, Vercel sponsors Formula One. We sponsor the Mercedes team. Mercedes is such a GOAT. I think they just win all the time. But other than that, the other teams are always flipping: 2, 3, 3, 2, 4, 3, 2. The AI landscape is a lot like that.
One day, you have Anthropic. The next day, an open model comes in. It's 20 times cheaper and is 98% as good or even better in some regards. And so Vercel has emerged as the place where not only people are coming to us to build and ship agents, they're also coming to us to get this optionality, or this best-of-all-worlds situation with AI.
Yeah. Wow. We didn't even talk about this, but the use of agents is exponentially increasing compute.
Yes.
How do you deal with that?
What's going to happen over the next few years is that agents are going to use far more of the internet and far more of the available resources than humans could, just from a fundamental physics standpoint. Think about it: it used to take me an entire afternoon to write a few files of code, and then I would deploy them. That would use a little bit of compute to build the software, and then it would go out onto the internet, and I would have to wait until humans visited and used the application.
Just picture that. You write code by hand, you ship it, we run some compute to build and test it, you put it out into the world, and then other humans come in through your door and use it. That triggers some compute and some networking. Now it's the agents writing code. That's why we added 1.5 billion deployments in 10 months. And now the agents are browsing the internet and using all of these resources, so the demands on infrastructure are going vertical.
You ask what is a good place in the stack to be, and I love being in the infrastructure space because, first, every week you wake up to an astonishing new record of usage. I was just looking at our data on our overall network utilization, and every day is a new record. But also, it's hard to even say when this ends. We have so many problems to solve with AI.
I think we've only scratched the surface of what's possible, from discovering cures to illnesses to the personal agent landscape, just adding more value to people's lives. Education, right? I was teaching math to my oldest kid last night, and I was like, “Ah, this app is kind of janky and not personalized enough.” This will be an agent. In fact, one of our most successful startup AI customers is building an incredible teacher assistant for older kids. I think it's more for teenagers in college, but it's happening, right? Education will also be disrupted with AI.
There are all these industries that have barely been touched by AI, so I can't even fathom the demands on compute, the energy grid, and the network. Obviously, I think there's a major cybersecurity concern that we need to get ahead of. We're investing a lot there. And so, yeah, it's a very exciting moment to build, and it's a very exciting moment to be in infrastructure. Also, I think for humanity itself, we've only scratched the surface of the wins that will come from this.
The cybersecurity concern is probably the next line item under the high-growth headline. Everybody is concerned about it. You don't know what to do with rogue agents. I was just speaking with Fred Wilson of USV. He's on the board of Coinbase, and I was like, “Fred, you've endured the crypto world. I'm sure you've probably clicked on a couple of links you didn't mean to.”
And he was like, “Yeah.” I said, “I've clicked on, like, 10.”
And that was with humans creating the attacking campaigns. It's like the classic scheme that promises you a bounty. Imagine once the agents have a perfect idea of you, your biases, and your context, so they can create a much more targeted attack.
Vercel hosts a lot of the largest crypto companies in the world and fintechs. We have Polymarket and Calcia as customers, and what's top of mind for a lot of these people is not just social-engineering-type attacks, but how do you protect your code?
Yeah.
Because the code that everyone is running on was written by humans. There was this funny moment in the past 3 years where a lot of my peers have been very skeptical of coding agents, and almost all of them have been proven wrong, right? There's very little—it's a very impactful amount, but it's very little that humans can add at this point to the coding agent capability.
There was a time when people were skeptical that agents could produce secure code. A lot of people would troll the agents because they would make obvious security mistakes. But the reality is that humans make obvious security mistakes, and in fact, a lot of the stuff that the world is suffering from today is that we're using coding agents that are now superintelligent. They're reading the human code and they're horrified. They're like, “What the hell were you guys doing over here?” And they're finding stuff that is just so bad.
To get ahead of this problem, we put $1 million toward a sandbox challenge. We told the world, “Vercel Sandbox, we believe, is one of the most secure sandboxes, if not the most secure sandbox, in the world. To strengthen it further, we want you to poke holes.” And we invited the entire world to attack us.
Only 1 person with an army of agents was able to make progress, and we're basically processing his contribution now and sharing it with industry peers. He and I are best buddies now, and we're DMing on X as we speak. For sure, we'll be collaborating with him for a long time to come because, as I mentioned, the contribution is small but impactful. Great example.
Yeah.
This gentleman has an amazing cybersecurity brain. This is not someone's child saying, “Hey, Claude, can you hack the sandbox?” and Claude did it, right? This is very sophisticated cybersecurity skill plus an army of agents.
What we're doing is—because we invited people with this bounty, we now have what is called the white-hat sort of hacker, right? They're like a good Samaritan. We're now sharing this finding with basically everybody in the world because this hacker found a critical vulnerability in Linux, and almost the entire world runs on Linux.
And so what Vercel is doing now is creating the sort of cybersecurity harnesses and incentive systems such that we can find out first and protect our infrastructure. Someone asked me on X, “What's going to happen in the future if all of the human code that we've written to date is insecure? What's going to happen?”
I said, “Look, I think in the short term, there's going to be almost like a war between four good tokens and four bad tokens.” The reality is that North Korea, China, enemies, adversaries, bad people, good people—we all have agents now.
I personally disagree with the whole “let's ban open models because of the cybersecurity risk.” I think that's nonsense because the thing that is making these models good at cybersecurity is just that they're intelligent.
Mm.
You would basically be prohibiting access to intelligence, and we can deploy this intelligence in a defensive way, like we just did, and then help the entire industry. But I think there's going to be a rocky next couple of years because we're going to have to strengthen a lot of these foundations.
Now, a really positive silver lining: I mentioned this week that I worked on a proof system, and a lot of my colleagues are researching this now. We can make agents, who are inexhaustible in their energy and capability, basically create a kind of code that we can prove, almost mathematically, is correct, and humans couldn't do this.
A very small percentage of humans in the audience could do it. I don't know if you saw that OpenAI proved Navier–Stokes, and none of the mathematicians can understand this proof. I opened the GitHub repo, and OpenAI could also not understand it. It's just so much code in this mathematical proof.
I'm not saying that our machine code will necessarily look this way in the short term, but it's gonna move more toward mathematical certainty. By the way, Vercel has been going down this path of strengthening our infrastructure with more verifiable code for the past few years, but the surface is enormous. Most companies have not done this yet. Most of the code is still human-written, and it's not correctly verified, which creates risk for the world.
But again, I think I just want to deliver a message of optimism. I think it's all gonna be good.
Everything's gonna be okay.
I swear, everything's gonna be okay.
We haven't talked about one of the most talked-about subjects yet, and that is the open-versus-closed war.
We're talking about a lot of wars.
We didn't know this was a war podcast, but here we are.
It is.
Well, I do a lot of interviews with defense companies. Now here we are. But okay, of the many tweets that you tweet that go viral, one of them was about how you and Vercel see everything that's going on in the world on the infrastructure side: the difference between open-weight and closed-source usage. So what are you seeing there now?
For context, Vercel operates one of the largest token distribution networks in the world. In the internet that I described earlier—the internet of pages—we had content distribution networks, or CDNs, and we would transmit pages. Now, the really interesting new thing is tokens. It's a unit of intelligence, and you need networks to distribute them, to get your tokens, to power your agents, to send inputs, and to get outputs back.
Developers come to Vercel to get tokens to power their agents, and we're basically one of the largest token suppliers in the world. We aggregate all of the model providers and all of the open models in the world, or most of them, so we get a lot of really good data. We then give it back to the world under Creative Commons, so anyone can use this anonymized volumetric data to understand where the future is headed.
The thing that's astonishing is that, since the beginning of the year, when we started the Vercel AI Gateway, as we call this network, it was mostly OpenAI, Anthropic, and Google. That's where developers and enterprises were getting their AI. In fact, Google Gemini had an amazing run, where most enterprises had found the perfect balance between price and performance with Gemini models. I think they did a great job with that, and they continue to be very strong there.
Then we had the rise of coding models. I think maybe people don't know this, but a lot of the tokens in the world today are being consumed by developers and by what you can think of as software factories—the agents that these developers are commanding. This is one of the biggest sources of token demand in the world.
At the beginning of the year, most of the traffic was going to proprietary models—OpenAI, Gemini, xAI, and so on. Now the situation is almost entirely flipped. Eighty percent of the tokens in our network—and this is a tweet that went viral—are from open models.
There are a few reasons behind this. Open models used to be terrible at coding. I had personally never used them. Even though I'm the biggest open-source person in the world, and I created some of the most popular open-source software in the world, I will continue to fight for open. Our mission in this AI era is what I call: I will enable you, and I will enable the largest companies in the world, to own your open intelligence stack. I want you not to be tied and anchored to a model, and to have control over your data.
But I couldn't live up to that myself because I was like, “Well, the best coding model isn't open. I can't even use this open thing.” Then some of these Chinese labs started putting out stuff that was extremely competitive with the frontier. The Kimi models—I actually used Kimi again yesterday, and I thought, “This model is so good.”
Of course, it's not at the top on every single benchmark or level of execution. There are a lot of things that it cannot do, but enterprises realized that a lot of what they do—maybe 80% of their traffic, and maybe that's what the data is showing—requires a certain level of intelligence. I don't need to hire Albert Einstein to solve every problem, answer every support ticket, spell-check my stuff, and classify my data.
The world is literally opening up to choice and saying, “I'm gonna use the best model for each task.” For example, something that's really common with developers today is that you do need Einstein sometimes—or Einstein-level intelligence—to create a plan. I'm gonna write a document about how I'm gonna approach this problem, and I need as much intelligence as possible. But then I need execution. I need to translate that plan into action, into code, into instructions, into operations, and basically every open model is amazing at that task.
What I think the data is clearly telling us is that the future's gonna be a portfolio of options. Enterprises also love having the negotiation power to say, “Look, I'm not anchoring or verticalizing myself to a specific lab. I'm implementing tools and protocols that make the model more of a module, like an engine that you can swap out.”
If, by tomorrow, Anthropic is not doing so well in a particular dimension, I just change it out and go to the Vercel AI Gateway with 1 line of code. The other thing that's kind of nuts is that you would think replacing models would be this massive engineering effort, but in reality it's 1 line of code.
A lot of what the world is researching right now is whether we can make the model choice automatic. There are a lot of promising directions and examples of places where you don't even have to ask. Much of my career, and much of my success, has been about thinking backward from the user experience first. This world where you have to first choose a model in order to do a task is not very user-friendly.
I would much rather have my colleagues say, “Okay, this is my query. This is my prompt,” and then we can decide where to route it based on context and intelligence needs. Sometimes, for very high-end engineers, they need to choose a specific model because they know it very well and have to choose it. So it's a combination of broadening access to every model under the sun and also letting some people pick.
A clear commonality that I've seen in the conversations I've had—and one in particular with Bending Spoons—is that Luca mentioned that 99% of the time, they're using open models. They're not using frontier models.
So what role do frontier models play, and how does that impose a risk on them, given all this crazy momentum and these hyper-billion-dollar valuations? What is the risk to all that and to everything they've built?
The biggest risk is that it's hard for them to understand what their retention is. The best products in the world—I always give this advice to young founders—focus on the non-cheatable metrics of your business. You know what's cheatable? Top of funnel. Run ads.
There are a lot of startups that are kind of frowned upon. They just do these baity marketing campaigns, record videos, make silly jokes, or whatever. Cool. That's top of funnel. But are you getting a customer for life? Are you doing a great job for them day in and day out so that, by year 10, they're still with you?
I think that's the biggest risk with a lot of the model companies: actually, there's zero loyalty. In fact, we have amazing loyalty to our AI Gateway product because we have the best interests of the customer in mind. If they want the absolute top intelligence from a model, they can get it, and they stay. There's no reason to leave.
What I would worry about if I were them is: how fleeting am I? Am I—
By the way, you were talking about crypto. There are a lot of elements—and I want to be super clear about this to everyone who's listening—of AI that resemble some of the crypto highs—
Yeah.
—of easy come, easy go. There were people who had zero loyalty to a coin. They were just saying, “I love this coin because it's the hot coin for the next 2 months,” and then selling it. Or they were even lying or manufacturing usage. There are all kinds of crazy things going on with AI, including people inventing token volumes.
There are a lot of free promotions. There's a lot of fake ZDR—zero data retention. One of the things that we guarantee in our AI Gateway for enterprises is zero data retention. You come to me because I can guarantee contractually, with all my providers and with US-based inference providers, that no one copies your data or trains on your data.
There are a lot of things going on in the market that I think are very frothy. You hear about token volumes, and you hear about promises of training versus no training.
There’s a lot of weird stuff going on. That reminds me of crypto a little bit—the speculation element, et cetera. Another thing with crypto is that there were people who were hardcore believers, and they’re still doing really well because they’ve been in it for so long, they understand the technology, and they love it. And there are tourists.
What I would ask myself if I were one of these companies is: What percentage of my users are here just because I gave them free subsidies on a plan, or because I happened to have a good day where my model was good, but by next week it’s not good? There’s a lot of volatility there.
Now, I do think that if your model is really intelligent and you can sustain it economically—which is a big if—why wouldn’t you have customers? There’s always going to be a demand for frontier intelligence. But I do think that you can run a business that is primarily open with models, and you’re going to get better prices and more ownership over your intelligence stack, which creates more defensiveness for your own business against the model businesses.
The other thing is, if the model labs were so convinced that the frontier intelligence advantage is enduring, why are they going into random software businesses? So I think some of the—
Like all of them building different applications for all the different verticals.
Yeah, like tomorrow they launch, “Oh, here’s our Slack clone,” or, “Here’s our other thing,” and whatever. There’s some behavior that seems to indicate that they’re starting to diversify from just being a token supplier because they’re finding that they’re—
My wine is from the Champagne region of France, and only that one can be called whatever.
Champagne.
Yeah, exactly. And so they’re seeing, “My token is not that much better than that other token.” And so my goal is: Hey, let’s drive the token price to 0, let’s drive developer happiness to 100, and enterprise value of our customers and ourselves to 100. So we’re in that situation.
But I also would not say, “Okay, these companies are going to disappear tomorrow.” I think they’re going to do well for long periods of time.
Yeah, I have so many different directions I can go with this.
It’s a fun topic.
It’s a very fun topic. What’s going to happen? Are they going to IPO, or is it a money pit?
What I’ll say is, it’s hard to predict. The whole point of IPOs and public companies is that they can forecast accurately. What you deliver to the market is a solid engine of a business. I’m Costco. I went public. I can say my business works this way: I sell this many Costco subscriptions, I’m growing at this rate, and people’s demand for high-quality Kirkland bread and lox and whatever—I can understand it.
With some of these AI companies, it’s much harder to understand. I could understand that on both sides there’s nervousness, where the public-market investors are like, “I was super, super excited about this thing because they had this model, and then I woke up the next day and there’s a free model that’s the same.”
Local models are coming, too. There are models that are going to run on your computer and are going to do amazing things. It’s already happening. I have one running on this laptop. This is a MacBook Air, and it can run a small Qwen model that can do very interesting things.
And so this is, to me, the fun of this game. I got into technology because you have to have an extremely open mind, be super agile, and stay on your feet. What I always tell our customers is that the primary value Vercel gives your business is iteration velocity, not speed. Speed is—you could be just spinning in circles. I’m giving you the engine so that you can innovate really fast.
The worst thing you could do today is stay put, where you say, “I’m not going to implement AI in my business. I’m not going to build agents. I’m not going to try open models because I heard this thing on TV and I’m scared,” or whatever. You have to be super open-minded and agile as a business and, by the way, as an engineer. Our greatest engineers are the ones who did not stick to what they knew. They learned new ways to use agents and AI to make themselves better.
It’s true for everybody. It’s true for the workforce. If you want your job to stay great, relevant, fun, and engaging, you have to actualize. You have to incorporate these new tools, and so I think that’s the name of the game today. It’s a very rapidly moving game.
Another one of my bangers was this: I look around at my peers in Silicon Valley, and they’re— You would think, “Okay, AI has arrived, and we’re all working 2 hours a week.” The opposite is happening. I get text messages at midnight from the CEOs and CTOs of these companies, where they’re saying, “Oh, we’re going to launch this thing. We’re preparing this. Help me out with that.”
And everyone’s working. It’s not even 9 to 5. It’s more like 7 to 7, 7 days a week, from 7:00 a.m. to 7:00 p.m. And, by the way, the reason I tweeted this is that a lot of this is super fun. It’s not that we’re suffering out here. There’s so much good stuff happening, so many new things, and it’s exciting to build and exciting to ship. Maybe sometimes it’s too exciting and people get carried away, but it’s a fascinating time for technology.
I was listening to DHH. He has this presentation at Ruby on Rails. I don’t know if you saw that, and he was like, “I’m in this state of delirium.”
Yes.
I don’t watch videos, so I—
You listen to it?
I do the craziest things because I host a fireside chat every Friday with our company.
Mm-hmm.
And I show them how I watch videos.
How do you watch videos?
I get the transcript on my terminal. I skim it really fast.
And then you ask your agent questions and process it?
Watching a video takes too long. I did several peeks at the video just to get some of the body language, but mostly HSR. I read the videos because otherwise it’s too slow.
So weird.
Yeah, totally. No, it is.
Well, he was saying he’s in a state of—he’s not in AI psychosis. He’s in delirium and—
AI delirium, for sure.
Euphoria because it’s just so exciting. It’s like—
Yeah.
The Internet is being invented as we speak.
Hundred percent. The rules are being rewritten. That’s why I was telling you I was shipping software on Sunday, and part of that is very much in the same wavelength as what DHH is talking about, because DHH, much like me, loved the idea of creating great developer experiences for humans.
I realized several years ago that what got us here was not going to get us there. If there was one big move that I made, it’s that I got the AI psychosis, delirium, whatever you want to call it, mosquito bite many years ago. Not to give myself too much credit, but it takes courage to do that, because you have to sit in front of your company and tell them with a straight face and conviction that the thing they fell in love with is no longer there.
The thing that DHH and I fell in love with was beautiful code, easy to write for humans with our little monkey extremities, right? Primate, evolved extremities. And that’s just not the game anymore.
Mm-hmm.
But what’s awesome is there’s a new game—and, well, the game that has always been here is that you have to make the agents work on the right things. Capital allocation.
I don’t know if you’ve heard of Marc Andreessen, but at some point, he went viral in a self-serving way that was hilarious. He said, “The last job is venture capitalist.” Sadly, I think he’s kind of right. I wouldn’t say venture capitalist; I would say capital allocator.
What you do as an engineer is allocate tokens, and we all have the same wall-clock time. None of us, to my knowledge, can distort time. We all have the same clock running, and we have to invent, create, and do good for the world. Now we have this superpower of tokens. What are we going to put them toward? What are they going to investigate? What languages and tools are they going to use?
That’s what DHH’s presentation was about. He’s like, “Ruby on Rails got me here. I think other things will get me there.” I think right now it might be this programming language called Rust, which was also super controversial when we introduced it a few years ago inside Vercel because it’s a language that is—
They named it beautifully. I picture it in my head as this rusty, not-pliable tool, and the things that are made for a good developer experience were these soft, nice fabrics. Now you have to grab this rusty, hard engine that is always telling you that you’re wrong.
One of the things Rust does is tell you all the time that you’re wrong in a really cryptic way. It’s cryptic because it’s almost like it’s approaching mathematical notation. It tells you, “You violated these 5 lemmas, and you’re wrong and you’re an idiot.” That’s what the compiler tells you. And that’s what DHH’s point was.
In the past, you as a human needed to swallow that pill. It took a specific type of character to swallow that pill. Almost like when you watch Magnus Carlsen lock in for a chess game, so locked into the rules of the game—as a human, you need to lock into the rules of this language. And now it's coding agents that do it, and we basically live in the promised land.
We ascended to: Oh my God, all of the code in the world is going to be secure. This was where my optimism was coming from. All the code is going to be fast. It's going to be secure.
Incidentally, Vercel built a platform where this kind of code is amazing to deploy. We built almost the perfect platform for this moment, which I'm really happy about. But the world has changed, and as a developer, you have to—it's almost like an ego death. You have to forget what got you here. Going back to the Marc Andreessen thing, choosing what to work on is still something that you weigh in on, and choosing with your creativity is very, very important.
How good is AI at real professional work? Mercour's AI Productivity Index, or APEX, tracks it with every major frontier model release. Built with partners like Harvey and Cognition, see where the frontier actually stands at mercour.com/apex. Today's episode is sponsored by VC-X by Fundrise, the public ticker for private tech, allowing investors of all sizes to invest in venture capital. Learn more at getvcx.com. Public is a multi-asset investing platform where you can automate your investing with AI agents. Create your own custom agent with a simple prompt. Agents can monitor markets, execute trading strategies, and manage your cash across stocks, bonds, options, crypto, and more. Wanna buy at market close and sell the next day's open? Just tell your agent. Automate your investing at public.com. Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit deel.com/sorcery. That's D-E-E-L.com/sorcery.
I have to ask you, because there are some really quick money grabs in this universe, whether it's neoclouds—
Yeah.
—all these kinds of new providers; the coding agents are spewing off money. How do you stay focused in that when all of that stuff is going on? Or even these—
Quality.
—data companies are making $2 billion.
It's so easy. I'll tell you an example. The sandbox product—to give people a really simple explanation: as a human, I join a company, and I'm given a laptop and do my work. I install Excel and whatever. It's my personal computer to do work. Agents also need computers. They're the sandboxes. We don't see them; they live in the cloud.
What's nice about this world is you can see the computer: Oh, it's Apple; it's beautiful and very valuable. In this new world, you buy the Vercel Sandbox and give it to the agent. Regarding the relative quality of the sandbox product—not to pat ourselves on the back, but I want to give the world this kind of quality—the products and services we're creating for this agentic era, this agentic infrastructure, are the highest quality in the game.
I hear every day from customers who migrate off of, “Oh, yeah, I went to that neocloud, and they gave me a deal on this and whatever.” It's not reliable, it's not secure, and it's not easy to use for agents. There's still a massive quality gap between all of these providers, and I commend everyone in our industry who's not just yapping and launching into every other business for whatever reason, because they're committed to this line of business.
We've been launching sandboxes in the cloud for 11 years, because every single time a Vercel deployment is made, we had almost the same challenges even before agents existed. We had to create a secure cloud computer for the code to be built in, so we came into this market with a very unique perspective. We came with a lot of experience, and we're delivering a great product. I think you're going to find that quality is still the name of the game.
Yes, everyone can show you they can create something really quickly with AI, but they still need to maintain it. They need to put those tokens to work for a lifetime of commitment. They have to make it reliable and secure and stuff. This is why I always remind the team: a lot of the world has changed, and some of the things that make companies win and what makes people win are the same.
Well, Vercel seems to be winning. You guys are at a $9.3 billion valuation. The Information reported you guys at 600 million in annualized revenue. That's growing. You have 60% of AI coding agents using the platform, and I think it was 485,000 customers. You named a few already, and it's a crazy list.
The customer growth of Vercel has been exceptional for the market that we're in. Maybe no other infrastructure company in the public market today has seen this kind of customer acquisition that we've seen. And that was based on this idea of making infrastructure more accessible to the world, and it turns out agents are now making the choices, and they're choosing right.
So I've heard that you're also involved in the hiring process. You have around 800 employees?
Yes.
And you're hiring, so let's talk about what you're looking for in those hires so we can help when people watch this video.
AI leverage is extremely key to the hiring process. First of all, it used to be that if you had a static resume, it was already kind of hard to hire you. You needed to show—borrowing from the crypto world—proof of work. What have you shipped? But now the barrier to shipping has also gotten lower. So I'm not even interested in, “Oh, yeah, I have this little demo,” or, “I vibe-coded this thing.” I'm actually looking for your ability to commandeer swaths of agents and really get leverage back from this new ecosystem.
Maybe you can call this agentic engineering. You can call it building software factories. I'm looking for people who are at that level of execution.
I still really value the communication quality of people—their communication competence. I believe that the future is going to have 2 extremes. There are going to be human-centric interactions that have to be the most humane and highest-quality interactions that you can possibly find. If you go to vercel.com, you're going to find this beautiful human-centric experience. It's for your eyes, and it communicates our values, our craftsmanship, and our design.
The same goes for how you speak to people. I don't want to read your AI-generated tweet slop. I want to hear what you actually think. I really care about people being able to be great human communicators, because that's going to matter a lot.
Especially—we employ fantastic AEs who are selling our agent platform to the Fortune 500s, and they're establishing trust-based human relationships. I really care about how they show up and how they communicate, and their technical understanding, by the way. I expect a much higher level of technical competence. Why? Because with curiosity and the ability to prompt, every problem, every subject becomes tractable to you.
It doesn't mean that you're going to become as competent as a Rust engineer with 20 years of experience—they didn't even exist—or like a C++ engineer with 20 years of experience in C++. But now an AE can be forward-deployed and speak way more eloquently about our technology, its impact, its APIs, and its data flow—all the things that were more in the realm of engineering.
I borrowed a quote from a friend of mine who was CEO of Splunk: the 2 most valuable people at the company are the ones who are close to the code or close to the customer. Code is the engine of everything; it's the thing that powers the products that we sell. The customer is who we live for; it's who we serve.
But now it's almost code at both extremes, because more and more we're forward-deploying our sales force, our sales engineers, and our forward-deployed engineers—meaning I'm helping people migrate over and sell in record time. We did this example with Mercedes. When we started partnering with them, they asked us, “How can you make our F1 team better?”
Being a performance maniac, I said, “Well, we can make your website much faster, because when people go to buy your merch or want to get the latest results from the race or whatever, I want to make you faster and I want to make you agentic.”
That process would have taken quite a bit of time. But the first iteration of the migration of their old stack to the new one actually took 5 minutes. We used an agent to rewrite the code from the old platform to the new one. Five minutes. When I saw the agent's result, I was like, “This used to take months.”
In fact, a lot of what could have been a slowdown to our business in the past was that enterprises were fully bought into the vision of the cloud and acceleration, et cetera, but everyone dreaded migrations.
Yeah. They would hire consultants for this.
That's right.
And it would take a year.
Cloud consultants—
A year.
And Scrum masters.
Yeah.
Have you ever heard of Scrum masters?
Yeah.
And agile coaches.
Mm-hmm.
Anyone would talk about the migration. I can now forward-deploy an engineer and do the migration.
Mm-hmm.
And so that's why it's no longer even just close to the code or close to the customer; it's close to the customer's code and close to the code—or close to the agent and close to the agent, right? And so I expect a much higher level of technical proficiency and curiosity from everybody at the company.
We're still hiring humans very happily, so that's not going away.
Fantastic. Um, so as we close out, one of my partners is Brex, and they're all about performance, spending smarter, moving faster. But I take this, because we're on the topic of performance—
Big Vercel customer, by the way.
Really?
Yes.
Wow. Well, I have to ask this question in a personal way. You run a very large company. You've been doing this for 11 years. You have some of the best customers you could possibly have. You also have 6 kids. Congratulations on 6.
Yeah, we just had our new baby girl last week.
Aw, what's her name?
Lisa.
Aw. How do you think about performance in your personal life? I usually ask this because I think of it in terms of who you surround yourself with or who you're inspired by. Who are those key mentors who keep you aligned and on track?
It could also be some of your closest friends who are CEOs of companies, while you're gathering information and trying to figure out what's actually going on in the world. Who are those people for you?
A lot of them are unknown, in the sense that I remember my first boxing coach, who taught me the basics of fitness, nutrition, and performance that were so simple. I've always loved boxing and martial arts because, as humans, we get in our own way all the time.
This might be controversial to some of your guests or audience, but so much of performance optimization focuses on the last mile, 1% optimizations: buy this supplement, do this thing, follow this longevity protocol. No one has gotten the 90% right—the basics of getting your diet right, eating clean, whole foods, and even walking. Walk and do pull-ups. I do the most basic things in the world, and I try not to deviate from that.
I try to tune out all of the nonsense about supplements and, God forbid, peptides. There are people who have gotten all that right and should totally optimize beyond that, and it's also their preference. To each their own. But my message has always been—and I hope to instill this in my kids—just work on your foundations.
This is also advice for our team and for every software company out there. It's so easy to get distracted by nonsense and take your eye off the foundations. There's a customer, there's a pain, and there's a product that serves them. It has to work great, and most of the work that we have to do is based on what customers and their agents are telling us.
Most of the work is actually pretty simple. I think what's really hard for us as humans is staying focused and keeping it simple. For example, this morning I did light cardio for an hour. I try to do basic things.
For my family, I always try to set the example. The reason I try to eat well, exercise, not drink alcohol, and do all these things is that your kids are always watching, and they become a blueprint of you. We do Brazilian jiu-jitsu together, and I hope to pass on these lessons.
Even with the broader Vercel team, I'll give you an example. We celebrated Oktoberfest, but I told the team, "Oktoberfest is fine, but I haven't had a beer in years at this point." I would love to portray a message of, "Can we make both things fun?" I also don't want to be the preachy guy who's just like, "Never drink," or whatever.
We combined it with activities and fun things, including fitness activities. I don't know if you've ever played that game where you have to hold really heavy jugs. We did a competition to see who could hold the jugs the longest. We have bodyweight fitness equipment at the office, so I try to be consistent in my life.
I blur the lines between life and work. How can you possibly have 6 kids and do this?
Yeah.
It's because I blur the lines. I'm teaching my kids what I know. I'm teaching them engineering. I bring them to the office. If they go through the interview process and the 6 stages of grief that we put people through—yes, we have a high bar—if they meet it, by all means.
I bring them to the office, and I'm living and working all at once.
Well, G, this was such a fun conversation, and I could probably ask you 10 more questions. There was one I didn't ask, which Darren from Tembo sent me, and he wanted to know: Is serverless dead?
No, the opposite. What's happening with compute is that we need so much of it, and what's happening with software is that there is so much of it being deployed. The reason enterprises love Vercel is that there is no way on earth they could deploy as much software as their employees are producing if all of it were running all the time.
The beauty of serverless was that when the software isn't being used, we spin it down. There are so many people building personal software. They use it every once in a while, or they deploy it whenever they need it. So you need servers to come online and go offline intelligently.
We call the next evolution of serverless fluid compute. It's a better generation of technology, but it's also a better name for what's happening. You need compute that flows like liquid. If you get lots of traffic, it expands. If you get no traffic, it compresses.
It's heterogeneous in the sense that it can work for sandboxes, it can work for functions, it can run your website, and it can run your agent. I've never been more excited about the next chapter of serverless, which is fluid compute, and I think it's going to define the next decade. I'm excited to see how that pans out, Tembo.
Awesome. Well, again, I'm not going to try to ask another question.
You can. I can go on and on.
Thank you so much.
Thank you, Molly.
And I'm definitely going to clip out every single time you said "code." You probably hit 1,000.
Awesome.
Hey, it's Molly. If you enjoy our interviews, check out our newsletter, Sorcery.vc, where we deliver a once a week top deals and tech headlines email, and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.