60% of Vercel Deployments Are Now Shipped by AI Agents

When you're a developer or a company of any size, you can deploy these agents, make your business more efficient.

We started out the year with 3% of deployments on Vercel coming from coding agents. Now 60% are agentic.

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 their choices and they're choosing Vercel. The lethal combination there is that you buy Vercel as a platform and then you never have to buy software again.

Thanks for having me.

We're here in San Francisco on our seventh floor of the Vercel headquarters.

Well, we have a couple of company values. One is ITG, iterate to greatness. So, once upon a time recording out of Brazil was not this good. We're always iterating to greatness. And the other one is dig deep. So, you know, whether you get a customer complaint or you find a bug, like go as deep as humanly and agentically possible.

Well, you know, when I started out the company Vercel, I was a framework and dev tools builder. My passion has always been can I build, you know, think of it as like can I build a better hammer? Can I build a better power drill? But for software developers, you know, 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. And anytime I would be given a job, I would do the job and also I would build my own tools to do the job for two reasons. One is I loved it. And the other one is that hey, each incremental job I'll be able to do easier and faster. In fact, it ended up being true. And so my lifetime has been can I create better tools? And when I started the company, the first tool that kind of became like super super popular was Next.js.

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. So over the years, you know, people ask me a lot, you know, what is your role at the company these days? And I tell them, well, you know, I do a little bit of everything. I do QA, I talk to customers, etc. But I invest a lot in the machinery that powers the company itself, the machinery that yields innovation in the future. And I think one of the key constituents of this framework of how we run the company is the values and our mission statement. The classic things, but you know, we put quite a bit of effort into, you know, who are we and what are our values.

I'm a nerd celebrity of sorts. But I'll tell you, okay, one of my personal values is transparency and working in public. A lot of my personal traits, I think, have sort of, you know, permeated through the company as well. And I'm open source, open models, building in public, transparent.

And so 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, like young founders. I also spend a lot of time, another value of mine and our family is giving back.

And so I spend a lot of time trying to give back to the ecosystem, and so I invest in a lot of young founders. And I think almost every week I get, 'Hey, who writes the tweets for you?'

Like, 'Can I hire a firm?' And I tell them, like, look, it's just, you know, it sounds like the worst advice because it's so simple, which probably makes it good advice. It's just be yourself, you know, tell your story, share your truth, and don't overthink it too much. And I think that's how some of the bangers have happened online.

I do actually. For the sake, so another maybe like toxic trait of mine is I'm constantly scrutinizing products, how fast they load, how well they represent the UI, whatever. And the only reason I've spent a lot of time in X analytics is that I know the engineer at X that worked on that feature and I've given him a bunch of feedback. But you know, it's, you kind of feel it, like you don't need analytics. You know, this is another, this is not really a value but an operating principle of mine has been you have to be mindful of the data and the anecdata.

Especially when running a business in a fast-moving market like AI, you can't just go off of like, oh yeah, the last quarter's little spreadsheet that the data analysts put together. We were talking before that, you know, every two weeks the board is getting reshuffled. And so you have to marry the anecdata, the vibes, the instincts with what you're seeing also from the, you know, arithmetic of your business. And so I try to go off, you know, like how do I feel and how do 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, you know, we have a mission about enabling builders and enabling people to ship what's next, and that means that we constantly have to be rethinking and reinventing who we are, how we work. And so I think there's a sense of like almost like working in real time with the world and having this real-time conversation, and based on that real-time conversation you inform your next move.

Yeah, you think it's their research teams and like there's, you know, large enterprises who have technical advisors to the CEO who write them reports and memos prior to meetings, and like no, like a lot of us are just like in that global conversation and making our contributions and then seeing how customers react.

Yeah. Yeah. For context, Vercel got really popular because of how easy we made it for anybody in the planet to ship an application.

So 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, that was secure, that scaled, it was like a PhD that you had to take on cloud computing. And at the time, you know, I realized, hey, if it's hard for me to ship an app and I've been, you know, I call it like I've been studying the blade since I've been programming day in and day out since I'm pretty much like I was pretty much 10 years old in Argentina. 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 and frameworks and tools and shipping pipelines and all of that. And so 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. And then in the next 10 months, the 10 months since then until now, we've added another 1.5 billion deployments. So what took us 10 years, we've now surpassed in just a few months. And the reason for this is that, well, one, shipping has gotten easier. Not gotten easier in the sense that like 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. I think what's been the supersonic tsunami is that the machines have taken over. They're better than us at figuring out these algorithms, this code, but they need to ship that stuff somewhere. Like when you write the code, you know, code is kind of a funny thing. Like I remember telling people, another one of my sort of internal principles is code is a liability. Code can have vulnerabilities. Code is how you know you could delete stuff. You can, you know, leak customer data. So like code is like you have to treat code with responsibility.

But now, you know, these coding agents are superhuman at writing the most amazing code. But again, code doesn't do anything by its own. It needs to live somewhere. It needs to be deployed. And Vercel has sort of 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. So 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, right? Like because it took us so long to build it, but like almost every other thing I see on X every day, it's just a Vercel deployment. And sometimes you can tell because by default we give people a domain name, it's like vercel.app. Or sometimes you see the largest companies in the world deploying on Vercel, including companies like OpenAI and Meta. And so we've been at this sort of juxtaposition of all of this, which to your point has given us a very unique lens into what's happening because not only are we seeing all of the activity coming from the coding agents, we're also distributing the tokens in the internet. So a lot of companies and developers are coming to us to get their AI tokens, and we offer every model under the planet. So like you can get OpenAI, Anthropic, open models, closed models, proprietary models. So we've sort of emerged as sort of this index that tells you where AI is going.

Yes. So now we can get into hot take territory. So one of my tweets that went viral the other day, I called it reject non-understanding. So what do I mean by rejecting non-understanding? So there are two schools of thought today. One, you can tell your AI agent to do whatever and you don't even look at what it's doing and you press a button, ship it, and it ships it to Vercel or whatever. And there's another route, which is the one that I recommend to my children, literally, I was up doing math homework with one of my children last night, is actually use the AI but also understand what it's doing. Now you asked specifically, do I write the code? I read code. And what these days I'm doing more and more and more is asking the AI to explain back what it did to me, 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, 20 years, it's also been a subject of debate, but for the most part, they help their engineers get organized. They help them execute, 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 might do QA of the final product. Sometimes they might bring, you know, in collaboration with the product manager, they might bring feedback from the field. So they're kind of looking out for you to not make mistakes. And so I think the role that most people are now taking with these coding agents is that of an engineering manager. But again, the best engineering managers that I've ever worked with, you know, first of all, they love code. They love like writing it, understanding it, etc. And so I still do it. I also shipped this weekend, I shipped something you could call a proof system, which is a mechanism by which we can make sure that the AIs don't ship slop and don't yeet your data out into the world by mistake. And I purposefully read lots of the code. I wrote down a lot of the examples, etc., because there's a lot of sensitivity around code, right? Like AI and code will run more and more and more of our lives, whether we like it or not. You know, Formula 1, there was, I was just reading some news, there was this massive event because they had to ship a software update into the cars and the drivers were complaining. And you realize these moments make you realize, holy, this 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 things are run by code. And so it's so, so important that we take this, you know, AI safety issues and the quality of the code we produce and how we verify it. We need to take it extremely seriously.

I'll tell you a wild stat first. So we started out the year with 3% of deployments on Vercel were coming from coding agents. Now 60% are agentic.

So more and more and more of the software of the world is just robots telling other robots what to do, right? Or you can think of it as like robots that take in English are getting out code for other robots to run. And of that 60%, it's hard to say, but I will tell you there's a really cool thing happening right now, which is 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 the code was proprietary and impossible for me to purchase, like even like mechanically impossible and just like from a, I couldn't pay for, like I couldn't afford it. Second, most of the manuals were written in English. Little thing, right? Like most of the world doesn't speak English. And at the time, I had to teach myself English as a way of teaching myself how to code. So it's like I had all of these obstacles in the way. And so then I taught myself English and then I had to get basically around all of these problems with like, how do I get software for free? How do I host it for free? And like all of these things. And that led me to open source. And the big epiphany that has defined Vercel, which is that the tools that developers and agents should use should be free and open so that everybody in the world can learn, which is 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. And turns out 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 this agent. So it was kind of like a positive karma that we put out into the world and also good for business, right? But essentially what's happening that's really good is that if you were to say, 'Okay, 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. And that's a, it's miraculous and I want that to continue to happen. So I don't want to be the guy that says like, ah, you have to understand every line of code, every precise mathematics behind these systems. But I can tell you perhaps another hot take is there's systems and there's capital S systems. There's the systems that are going to run and host our data, our most critical infrastructure, our security, our national security. And I do think that there is a place for, you know, agentic powered engineers and there's a place for vibe coders, which is sort of the term that the industry has given, the more playful, let me just yeet out whatever from the AI type of behavior.

Totally. So in the beginning of time, there was the web and it was made out of pages and human-centric interfaces, meaning you open up a website, you open up an application and you are the one consuming it. 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. So a simple example is when an agent goes to vercel.com, I don't give them the fancy, people should go to vercel.com. They're going to see this beautiful triangle with a gradient. Our engineers or our agents like carefully chiseled this beautiful animation. I don't give them that. The agent don't care. The agent wants straight signal. So what we give the agent, and this is a Vercel cloud capability, we give them highly precise information about our business that the agent needs to learn.

Correct. And 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. Because more and more of the traffic of the internet will be agents doing stuff for us. So I'll give you a very simple example. If you ask Muse to build you a website, it will use Vercel. So it can go off and say, 'Oh, I'm going to go visit Vercel. I'm going to get some information about how to build software and then I'm going to build something for this user.' And so I need to present my best face to that agent and to the many, many, many other agents that are going to. And this is true for every business, right? Like you could have, I mean, the example is super top of mind for people is like DoorDash customer, Vercel just shipped an agent where you can ask for a burrito over text message. You know, it's kind of like you could argue it's a gimmick. You know, actually some people will use it, whatever. The key point is that that is an agentic interface. There's 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?' Basically technology was built for a different era that actually says, 'No, no, no, this is a bot. I don't want this traffic.' Vercel is actually 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.'

What you do need that 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? And the transformation that Vercel made is to go from developer experience, which is sort of our first customer was a developer, to now the agentic developer experience. And so it's very important that you do understand, okay, am I getting ChatGPT on my website? Because I want ChatGPT, I want them to get the best possible information, I want them to get contextual information. And people are not just distributing static information on the internet, they're also distributing capabilities. And so you also want to expose your tools, your products, your services to the agents. We partner with Stripe and Shopify to offer agents the ability to transact, which is another astonishing fact about the Vercel business, is that we see agents now purchasing our services. We see one of the most popular tools in the Vercel toolset is a capability that helps agents buy stuff from our marketplace. So for example, if an agent needs to buy a web browser, they can purchase Browserbase through the Vercel marketplace, and I'm enabling that transaction end to end without any human intervention. It's like the agent is visiting the virtual Vercel shelf and it's saying, 'Oh, I need that.' And then I say, 'Okay, it's this much.' And so what's really, really important for business owners is, okay, 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 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 three years ago' or something like that, right? And so what we have done as an industry is we give, one of the fundamental tools that we give the agent is the ability to search the internet. And so it's still very important for businesses to be really good at putting out their content. In fact, I'll give you an example. So when you put out your podcasts and your shows, what you want to make sure is that there's a transcript as well. So that when an agent, and I'm not even going to say I, because I'm not going to be doing it, right? When I say 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. And this is true for basically every business online.

Yeah, it's not just giving them the information. That's sort of what AEO is about, which I think is, by the way, really, really important. It's also that you have to make sure that your product runs agentically, that the agents can use it. So for example, the fundamental protocol or programming language, we can call it, when the internet first came around, it delivered hypertext, it delivered HTML, which some older people in the audience might recall as MySpace codes. So 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.' So for example, the Vercel MCP says, 'Here's how you deploy software, here's how you list your projects.' And so we're basically creating a presentation of Vercel that is very ergonomic to the agent. There's new protocols also emerging. For example, one is the machine payment protocol or the universal commerce protocol. And so 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, or some companies will be out there saying, 'Hey, agent, you can just buy it far more quickly and in a more streamlined fashion because I'm speaking your language. I'm speaking your protocol.' And so I think what we're going to see over the next few years is a complete transformation of every product and every service towards this. And 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. So you go and you see your list of contacts, your CRM. So it's that vision of a pixel-centric, for humans interface. But nowadays, the way that we work at Vercel is I can go into my agent that we deploy on Slack and I can 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, and give me a quick report on some of the problems that she's reported.' So I never actually went to Salesforce. I just went to the agent and the agent went to Salesforce. And so what we're helping companies figure out is one, 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 like learn this like 20 different tools. And you may think, well, how big of a change is that? Well, 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 know, you would go to any company in Palo Alto and they would be designing interfaces for humans. They would be all gathered together in a room and the whiteboard was like, okay, what does G have to see when he wants to prepare for a meeting? Well, let's put the profile picture of Molly up here and a five list of support tickets over here. And it was very fixed in time and space and it was decided basically by a product design team somewhere in the world. The future of the internet is, well, at Vercel, we have our agent that helps prepare our Salesforce and our customer support teams. The interfaces are more generative. So if I'm asking about an individual, it renders a profile of this individual. If I'm asking about a company, it gives me more contextual information about that company. So we're going more and more into a world that, you know, if you've watched Minority Report, it feels more like the information is just coming to you depending on everything, context, you know, your level of experience. You know, I may not want to give a beginner sales development representative the same kind of like sophistication that I'm going to give my finance team when I give them an outlook of our business. And so these are all things that agents can solve for that websites and traditional pages and pixels could not solve for. And so we're basically helping this new generation of software be easy to build and ship to these companies.

Well, I'll tell you my sort of super opinionated point of view is I almost take the opposite stance. We're talking about your Bending Spoons thing that went viral. I don't believe in sort of aggregating piles and piles of software and in having what you could think of like lowest common denominator software. I believe in a future of personalized software. Vercel makes it such that you can prompt with your coding agent and generate software that's perfect for you. You can build the podcast schedule, notetaking app and 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, I could say, you know, there was this entire category of SaaS that you could call like 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. And so why not buy, you know, the lethal combination there is that you buy Vercel as a platform and then you never have to buy software again because you can just generate it to your needs. Okay. So where do the Salesforces and SAPs, etc., the world fit in? Well, software needs data. I can generate the most beautiful like meeting prep or report or all of these awesome things that you can deploy on Vercel, websites, applications, agents, but they need to get their data from somewhere. And so I think the sources of record, where does the customer history live, where does the contact live, where do my meeting notes live, where do my support tickets live? That's critical data infrastructure. I'm not going to call it software because you use the word headless. What does headless mean? Well, 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, etc. So 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.

Infrastructure is extremely valuable. I mean, it has this compounding value and return because when you enable anybody to ship and you make source code free essentially, well, 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. So the infrastructure to support agents is extremely vital. So Vercel has created new services purpose-built to basically secure and contain the agents. A good example is now that 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? And so 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? So we built that for the agent era. Another really important primitive is, you know, the news that went viral around OpenAI hacking Hugging Face. And so what happened there is that they had this agent and the agent was given a goal and in the pursuit of that goal, agents for better, like legitimately for better and for worse, these agents will do whatever it takes to fulfill their mission. They're like a soldier that has their frontal lobe has been removed and they're like, 'Let's go, go, go, go, go.' And so 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. And in fact, if I were to summarize what has changed about the world since ChatGPT to today, is autonomy. With ChatGPT, we had to be in the loop there. '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. And so 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 very, very long without intervention because that's also like a better user experience. So if I say, 'Hey, find me Molly's email because I need to send her a happy birthday note.' The agent can say, 'Well, you know, I'll do whatever it takes to find this email and send her the note.' And 40 minutes later, it tells me, 'Oh, I did it.' And maybe it went to the web, maybe it went to Crunchbase, maybe it found it in a comment on YouTube that you said, 'This is my email.' Like, this is actually 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. And so the risk is exactly that, is what are the guardrails of what's okay for this agent to do in the fulfillment of this mission or how can we prevent other people, external influences, to alter what that mission was supposed to be in the first place. So I'll give you, I'll extend that example. I say, find Molly's email. Send her a birthday note. It goes to YouTube. It says, 'Oh, I, you know, sometimes you've probably done this. Like, have you ever done like route Gmail email?' And then like you find me in some shitty website or whatever. You find someone like and you copy paste the email address, right? Like now imagine that in that YouTube comment, someone plants a prompt injection. Prompt injection is an instruction that is hidden, that is evil, meant for my agent. So my agent was just scrubbing YouTube and like, oh, now it got somewhat persuaded to do something evil, but it's acting on my behalf. It's acting with my tokens. It's acting with my tools. It's acting with my resources. So that risk exists. And so long answer to Vercel is also building the sandboxes and the capabilities so that companies can operate agents, deploy agents, and really trust them, get the good experience from them, but really trust them that they're going to do the thing they were supposed to do.

Great question.

Great question. So the word sandbox is being used a lot and sometimes it's kind of a technical horror in that it's not what people are calling sandbox. It's like, look, my computer, this computer has access to the entire freaking world, is not really a sandbox, right? And so when OpenAI hacked Hugging Face, there were elements that was sandbox-like and there were elements that truly weren't. But I'll tell you the thing that kind of concerned me about that incident is that the first escape of the agent, it was from a really good sandbox. Like actually, you know, in the, there's a going back history lane in the Linux community, in actually in the Unix community, one of the earliest words that were used, FreeBSD was a community that coined, I think, coined jail, which in my opinion is a better, is arguably a better word, right? Like because the sandbox, you're right, the sandbox, you just escape, you just step out.

FreeBSD created a concept of jails to refer to sandboxes, which perhaps that also would be a term that I think 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 is more like having the agent be a rat in a, and you're like fully contained, can't break glass, and you're like watching it spin, right? In practice, I can tell you talking to prospects and talking to people that are, you know, we're helping them figure out agents, people have not really figured out agent security yet. And a part, a very, very important part of that is to have very secure sandboxes, which is in itself a really big challenge because coding agents are also extremely good at finding vulnerabilities in code. So we love the 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 sort of AI hackers of the future. So Vercel takes a stance here, which is we will not lock you in to any model provider. We'll give you the tools so that you can use coding agents, so that you can 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 two weeks. You know, we...

It's exactly happening. I was going to say Vercel sponsors Formula 1. 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 just, you know, flipping two, three, three, two, four, three, two. The AI landscape is a lot like that. One day, you know, you have Anthropic, the next day an open model comes in. It's 20 times cheaper and it's 98% as good or it's even better in some regards. And so Vercel has sort of emerged as a place where not only people are coming to us to build and ship agents, are just coming to us to get this optionality or this sort of best of all worlds situation with AI.

Yeah. So, you know, what's going to happen over the next few years is that because agents are going to use far more of the internet and far more of the available resources than humans could just from a fundamental like physics standpoint, right? Think about it. It used to take me an entire afternoon to write a few files of code and then I would deploy them and that would use a little bit of compute to build the software and then that would go out of the internet and then I would have to wait until humans visit and use the application. So just picture that, right? Like, okay, so you write code by hand, you ship it, we run some compute, build and test it, you put it out into the world, and then other humans come in through your door and use it. And 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. And so the demands on infrastructure are going vertical. So you ask what is a good place of the stack to be in. I love being in the infrastructure space because first every week you wake up to like an astonishing new like record of usage. I was just looking at our data of our overall network utilization. It's just every day is a new record. But also it's hard to even say when does this end. We have so many problems to solve with AI. I think we've only scratched the surface of what's possible with, you know, discovering cures to illnesses, to, you know, even like the personal agent landscape, like just adding more value to people's lives, education, right? So it's funny because last, I have this recency bias, I was teaching math to my oldest kid last night and like, it's 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 like teenagers and in college. But it's happening, right? Like...

Education will also be disrupted with AI. So there's all these industries that have barely been touched by AI. And so I can't even fathom the demands on compute, the energy grid, 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. It's a very exciting moment to be in infrastructure. It's also I think for humanity itself, I think we've only scratched the surface of the wins that will come from this.