The AI Agent Every Company is About to Build | Vercel CEO Guillermo Rauch

It's great to be here.

Yeah. When I think about, we can call it the agentic revolution, just like any new platform that has hit the internet or the software landscape, you think about the killer apps, right? When the personal computer came out, you know, what were the killer apps? The word processor, for some of us playing video games on our personal computers and things like that. Then mobile came along, right? And I think the killer app of mobile in many ways was not only shrinking interfaces from things that we used to use and putting them in a smaller screen, but enabling entire new use cases. And I think with agents we see a similar thing. So number one, clearly one of the killer apps of agents is building software. And building software, or what you could call coding agents, happens to be a core capability of solving a number of knowledge worker tasks because when you think about, okay, I'm preparing a presentation for somebody, you occasionally will say, well, we have to do some data science over here in order to then get a report or get some data back and put it into a slide, or you'll say I'll automate a bunch of different steps and summarize some documents and then I'll put some other information into a slide. And so I think clearly one of the foundational parts of this new period of time where we do a lot of our work increasingly with agents is coding as a capability. And I think this has transformed everyone's jobs, right? You can think of it as a number of sort of levels of expertise, I guess, when it comes to coding. So there are people like myself that can do agentic engineering, meaning I've been programming for 20 years and now if I sit down and face a really hard engineering task, I will use a coding agent to enhance my engineering. Then there's this new emergence of what you would call vibe coding, right? Which is everybody building a prototype of software or even a full-stack application depending on sort of where your ambitions are and maybe even how ambitious the application itself is. And so you have products like v0 and Lovable and things like this that are making it more, I guess they're democratizing building software or even building the creative act or enhancing the creative act of coming up with new software.

I also think agents are, one of the killer apps is what I would call the run-your-company-better agent, or the knowledge base plus data analysis plus project management agent. The sort of brain agent that sits alongside of you and disseminates knowledge, business intelligence, even day-to-day tasks like, you know, who should I talk to within the company that is an expert in a certain task, like navigating the org chart, navigating what is to many overwhelming amounts of information that reside in the internal systems of a, sort of think of this as like making the company's backend more efficient. And as I mentioned, I think coding is this omnipresent capability. So to give you a concrete example from within Vercel, what we noticed pretty quickly is that anybody that's helping a customer, anybody that's trying to close a sale, anybody that's even building new software needs to ask questions about, you know, what are our customers doing? When did they first reach out? How much time do we spend with them? How much do they use our platform? How many SKUs of Vercel does this customer use? And so this internal brain agent has sort of emerged as one of the killer apps of AI. And maybe for a lot of people this still seems foreign, like what are you talking about? There's an agent that can run my company. So excited to make that more of a thing.

Yeah, even if you have a team of 10 people or a team of hundreds of people like Vercel, I think the way that I think about tools like Codex or ChatGPT is that they give you a taste of what AI can do. But your job, the new job of someone that runs a company, is to actually enable their workforce with agents and to work on the agent. I think the future of what you would consider to be your intellectual property at the company, or your edge against competitors, is the ability to create, tune, optimize, and disseminate these agents internally. And while you can have this sort of aha moment when you use something like ChatGPT, maybe to give you an example, our internal agent is called V. So anyone within Vercel can go into our Slack workspace and say @V and sort of navigate their day-to-day. Whether it's, you give a great example. So if I need to create new content, for example, our marketing team needs to help promote a new product that we worked on or communicate a product change or write an engineering blog post in collaboration with an engineer that worked on a certain capability. All of this goes through this V agent, and this V agent has a number of skills that we continuously sort of update and improve.

It has sub-agents. It has sort of imagine the ability to create like a virtual employee team. So there is the content agent that is really good at writing marketing materials. There is the data analysis agent, we internally call this D0, but it's sort of think of it as like the nexus of intelligence within our company, like anytime we need to get information about how a customer is doing or how they could use more Vercel or things like this, we have this sort of D0 agent that is connected to our data warehouse. And so the experience of using an agent actually ends up being extremely user-friendly. Why? Because all you need to do is you join Vercel, you join our chat workspace, and now you sort of have this omnipresent intelligence that can help you. And now you might go to V and say, hey, can you change some information on the website? And so V can still sort of coordinate with other agents. It could delegate a task to Codex if it wanted to, it can create a prototype with v0, it can query Vercel to get information about our production systems. But I think what's key is enabling every company in the world to sort of deploy this brain and this intelligence and continue to sort of optimize it over time.

So maybe to back up, I wanted to share a little bit about our product development philosophy at Vercel. When we have a vision of the future that can be informed by, you know, pains that our customers have or things that we notice internally could be better, we try to solve that problem ourselves first. So this idea of let's have an agent that can help with every aspect of our job sort of emerged pretty obviously. Like you mentioned, anyone that uses ChatGPT notices, oh, it can reason, but ChatGPT doesn't have access to my internal knowledge base and customer records and the set of best practices of how we build software, etc. And so the inspiration was, anytime you talk to somebody, could there have been an agentic intelligence layer that could have gotten you that information sooner? So that was sort of like the inkling, the inspiration for it. Next thing is how do we build this? And so Vercel has built a number of agentic infrastructure services and tools. So we built the AI SDK that helps developers talk to any model in the world. We built AI Gateway which helps you get tokens from any model in the world. At the end of the day, what we realize is that, okay, if there's an agent like V, I don't want it to necessarily be Claude or Codex or open-weight. At the end of the day, the customer doesn't matter, and ideally we autonomously choose the best model for each task. So we almost thought of V as a superset of all agents in the world. And so we designated a few folks to sort of try it out and build this conversational experience.

First, it started out as a support assistant, and that alone was extremely useful. Why? Because we are hiring new people, and also in Slack we talk to a lot of our customers. And so anytime that you have a question about how Vercel works, we wanted to have an @Vercel functionality that could know anything about Vercel, and that itself was super, super, super helpful because it became sort of like this easy way of giving support to our customers. But the difference between an AI assistant and an agent is that an agent can do things for you. And so we started thinking in terms of skills and in terms of jobs to be done.

So we gave it a name. So V for our internal purposes. And so we wanted to have a clear distinction between the customer-facing agent, the agent we give users of Vercel, which is @Vercel, and the agent that runs our company. So V is sort of the shorthand for this. So we created the V team. The other thing we realized in this process, and maybe this goes at the heart of your question, is it's actually pretty hard to assemble all of the tools, all of the frameworks, and all of the infrastructure to make something like this happen and to improve it over time. And so that gave inspiration for us, we built V and then we shared the framework that we used to build it back to the world. We call this EVE. You might sound like we're super creative with our names. V, EVE, Vercel, but EVE is sort of, you know, what Next.js or React did to the web. They made it really easy to build websites and web applications. The thing that I think every knowledge worker, every individual, every entrepreneur will want in the future is to have an agent that they can call their own. And this is what we're helping people enable with EVE.

I had a lot of epiphanies from Open Claw that informed the development of EVE. I think you're absolutely spot on. One of those things is that Open Claw showed just how much a coding agent can do. Back to my initial point, what is Open Claw fundamentally? It's the raw intelligence of the model plus every tool at its disposal.

It can write code, it can run it, and it can have access to everything, and that's magic.

Another really important thing about Open Claw which is soul.md. So when you create an Open Claw or when you use Open Claw, you're not just taking the off-the-shelf agent that somebody else built. Clearly Claude, for example, it's a great agent, but Claude is Anthropic's agent. It has its own set of principles and sure they give you ways to customize it and whatnot, but it's not truly yours. It doesn't have a soul of its own, right? And so I think that was another really big unlock, which is what is the soul.md file? It's just literally markdown text that defines the genesis of that model. So when you create an agent with EVE, we basically learn from that, and basically an EVE agent at its most basic is a folder with an instructions.md file in it. So it's like the soul of your agent that's going to help you run your company, for example.

And then the other thing that we learned is it's awesome that it can run code, write code. It has a computer for it, right? Like the whole Mac Mini thing was actually quite meaningful, right? Like people realized, okay, this agent can do anything under the sun, but it's dangerous and it needs a space. It needs its own thing and give the agent some space, right? Like, and so people bought Mac Minis, and that basically giving an agent a computer massively improves its performance, its reasoning performance and its ability to deliver outcomes for you. And so what's really fascinating is it's not too unlike hiring a knowledge worker. What is the first thing a modern firm does when they hire a human? Here's your computer. They give us a MacBook. It has a bunch of programs installed. It's logged into all of your key systems. And so we wanted to give you that as well for your own agents that you build. But we wanted to build a secure and efficient environment for it to run. And so the security part is that you define the tools, the human-in-the-loop approvals, and the data access controls for anything that the agent can do. And the other aspect of it is it doesn't assume that the agent is always running in a computer, which is actually kind of counterintuitive. I just said an agent gets better if it has a computer, but not every agent is running 24/7.

And so in our lingo of the Vercel and cloud world, we call this serverless. The idea is that if the agent is not doing anything, it can go to sleep. Maybe another metaphor is imagine a Mac Mini that hibernates when the agent doesn't have anything to do so that it doesn't use electricity. And so because we at Vercel, we run billions of deployments, we needed a mechanism such that agents can be very, very, very efficiently operated and run. And so that's another sort of ingredient that we learned from the Open Claws of the world. Okay, if we're going to run these things at massive scale and we need to run them securely, how can we create infrastructure that enables that?

I agree. And my goal with the agents that we build in V is that whether you're an intern that just joined Vercel or you're a super-experienced engineer or you're somewhere in between, I don't think, whether, I think that's sort of the implementation detail that the agent builder needs to know about. What I want for the future is that someone that's building an agent can very carefully define governance, data access control, and the security model, right, because agents are interacting with customer data. So you can't just be like, I don't know, man, it runs a computer and it has access to all of the databases of everything. You have to be really, really, really thoughtful about it. That's literally our new job, right? And but whether it runs one or it runs a million computers is completely inconsequential to the end user. In fact, you can think of these agents as being orchestrators. In fact, when someone goes to our Slack and says @V, they're really talking to the orchestrating agent, the one that could delegate a task to a million computers, to one computer, maybe even no computer. You know, we have customers of Vercel that have built agents that have so much usage that they figured out ways to make the computer smaller and smaller and smaller just for the sake of cost efficiency. And so my hope for the future is that the very technical people can sort of know like, oh, this particular conversation with this agent resulted in all of this usage of computers and whatnot. But for the most part it's all about getting high-quality outcomes, high-quality analysis, high-quality accurate information. Performance is becoming more and more the talk of town, right? Like people really care for fast models and fast execution. So that's another aspect of how do you get your agent to be delightful.

Totally.

So first of all, I'm a user experience guy. You know, I started Vercel because I was frustrated with how slow creating software was and how slow the average website and web application experience was. So I always try to work backwards on the user experience. The ideal user experience with an agent is the Star Trek computer or the Iron Man Jarvis. It's ambient computing and I don't need to target a specific capability. That's why we're reasoning with agents to begin with. It's like there's probably hundreds if not thousands of internal tools that people at Vercel have built that I don't even know exist, frankly, there's just too much. And so when you have these intelligent agents, they can act as routers. V, our internal EVE agent, is a router. So if you ask it about Vercel knowledge, it goes to the capability that we have for looking up our documentation, our knowledge base, etc. If you need to help a customer with a support case, it has a support agent within it that has access to our support ticket infrastructure. So that answers sort of my perspective is that it's more on the god model.

And maybe to give you a metaphor, because I really think that what we're doing here is we're redefining how companies of the future will work. When you join a corporation, they might give you a corporate phone and that corporate phone is already preconfigured with your identity and with a set of applications. You have the application for, I don't know, internal chat. You have the application for this and that. So I think the internal agent that helps you run the company is not unlike that. It is the job of the new sort of IT department is to say what are the capabilities that we're bundling into this agent and also crucially how do we manage identity and who gets to access what information, which is also extremely business-specific. It depends on how regulated your business is. If you're a small startup, I can believe that your nine-person team, they all have pretty equal access to most of the information of the company. Maybe two have access to the financials, or maybe the distinction, I remember when I started Vercel was like some of us had, you know, read-write admin, and but I think most of the first 10-person team had read access to almost everything. And so the job of the person that works on this foundational agent is to determine the access control, the tools, the guardrails, the audit trails, and like I said, this is actually pretty hard work to do. And why we wanted to create a framework that made that the fundamental job, because wiring up the model, wiring up the infrastructure and all of that, customers can offload to us.

Totally.

The way that most of these agents are built is that you're talking to an AI that is helping you maintain your EVE project. You'll hear me use the word file system or folder a lot. I find that it makes the world really easy to understand if you think about it as a hierarchy of files and folders. So the way that an EVE agent works is that you start with that instructions file that says you are the agent that helps run Riley's business. You can even have some context about who you are, like our business, you know, we disseminate information about AI and our values are transparency, we're not opinionated, and we love shipping things, like something like that, right? But that agent still knows nothing. It's a tabula rasa. It just has the raw intelligence that comes from the model and it has a basic set of instructions. How can it do something useful for you? Well, you talked about, okay, let's help the marketing team create content, and let's say that one of the things that you really care about is posting on your blog. So in an EVE agent, the first thing you do is you can create a tools folder and you can now start exposing tools to the agent. And so you can say, let's say that your blog is running WordPress or some system like that. Now I can say to the agent, now you have a tool to read and write blog posts to WordPress. Okay, great. You created that file WordPress.ts on that folder and then you ship your agent. You use the word channel also, very important that this agent needs to communicate to your team in some channel. So EVE supports every channel under the sun. It can be WhatsApp, it can be Telegram, it can be Slack, it can be Microsoft,

It can be iMessage. Yes.

And so the next question is, okay, I created the agent, I gave it this sort of soul, I gave it access to WordPress.

And so this is the job of like you at some point, maybe Riley, you were working on your EVE agent, or someone in your team you designate as sort of the agent administrator. You're gonna say, okay, if the person lives within a certain part of the organization, we let them write directly to WordPress. Another approach that I've seen people take is that when they interact with the intern over Slack or over Telegram or whatever, you have to authenticate with WordPress. So you delegate to an existing permission system that you already have. So the EVE agent ends up being sort of the facilitator of the transaction, but it doesn't have direct access to WordPress itself. It will help you sort of draft up the content. So this is just an idea that we cooked up in this conversation, but imagine that every day you start realizing, hm, that's really powerful. I just unblocked my entire team to be able to draft up blog posts that go directly to WordPress. But next time tomorrow you hear an escalation and you hear, 'Hey Riley, I just saw your blog post. I read your most recent blog post. It reads like complete slop. What do you do?' And you go into your team and say, 'Guys, what did we just do? We became really productive and we started shipping a lot of slop. You know what you do next? You work on the content writing skill of your EVE agent.' And so this is the meta work that we will all be doing in the future. We're not working on the blog post itself. You did not go to the intern, scold at him like, 'Hey, what did you do? You shipped a bunch of slop.' You're putting that intelligence into the agent in the form of skills, in the form of tools. And of course over time you can get more sophisticated. And it's not just about blog, like how can we infuse the content writing capability with what people are saying on X about your business.

Totally.

So going back, you got that escalation that says Riley, you're shipping a lot of blog posts but they have too many em dashes. And so this is what's beautiful about that idea of it's just a folder. You go into your EVE agent and in the folder skills, you say contentwriting.md and you say this is how we write, this is what I like, this is what I don't like.

So EVE can have a schedule. For example, every day at night, it reads social media, it parses keywords, it gets replies from your posts. And from that, it can do something. It can draft up new content. It can even give you a report inside of Slack. And this we actually have found to be extremely helpful at Vercel. The idea that our agents proactively give us information. So every Monday I have my internal agent give me a download of what's happening across every product area. What are the key metrics that I care about? So you can have the agent be doing thinking in the background on your behalf. And I think it's not just about, I think most of the world still thinks about agents as something you prompt, but I think there's a lot of alpha in thinking about can we sort of automate even the prompting such that the agent can be doing useful work for me while I'm not at the computer.