The New Application Layer - Malte Ubl, CTO Vercel

Our first speaker draws on over 25 years of software engineering experience. From his time at Google and now Vercel, he will explore what it means to build infrastructure and applications in a world where agents are both the builders and users of software.

Please join me in welcoming to the stage the CTO of Vercel, Malte Ubl.

Good morning, everyone. This is awesome. I'm so glad to be here. Welcome to the first-ever AI engineer conference in Europe. My name is Malte, and I'm the CTO of Vercel. Now, this is not you know, usually I give technical talks, but I thought, because I'm apparently going first, that I need to give a proper keynote.

But I did want to feature what I call my vibe coding stack. I've been hacking on a thing called Chat SDK, which is a way to hook your agents to whatever, like Slack, Telegram, WhatsApp, chat app you like.

And I've been working on JustBash, which is a bash interpreter written in TypeScript that gives you something like a sandbox with nanoseconds startup time for your agents, because they love bash. Allright. One thing I wanted to mention is that the reason why I'm so excited to be here is that I used to run a little conference in Berlin called JSConfU.

And I feel like once in my life I had completely impeccable timing, because it was the summer of 2019, and we decided after 10 years it was enough, and we went out with a bang. And the reason why this was such great timing was that there just wouldn't have been a conference one year later because of COVID.

But also, when we decided that we would step away, we were hoping that someone else would take the reins. And again, that did not happen because of COVID. So it's now been more than half a decade, and I'm very excited that things are finally starting up again.

But it was also clear that it wasn't going to be like a web development conference that would really bring the tech community in Europe back together in 2026,right? In many ways, I think AI engineering is the legitimate successor to web development as a really mainstream discipline of engineering that will shape the next decade of software development, as software engineering itself faces an unprecedented disruption.

So you're definitely in theright place today. And it's more important than ever to come together as a community and reflect on both our profession as software engineers and AI engineers. And that's because we're facing a disruption of both how we built, which is with AI, and what we built, which is AI and agents.

And of course, disruption can sometimes lead to anxiety. In fact, I really actually very often get asked, "Hey, Malte, is there still a place for engineers in the future? And what about that next generation of engineers?" And I couldn't be more convinced of the answer as yes.

I often give this example of, like, envision me doing a TikTok video. They mentioned in the intro that I have 25 years of experience, which is actually a substantial understatement. And so I would not be good at a TikTok video.

I should not be recording TikTok videos because I didn't grow up with this,right? And in a very similar way, the next generation of junior engineers are just going to be so much better at this discipline because they get molded in the AI world, just like all of you are.

But it's not only the kids that are going to be allright. We'll all be fine. And this is why. One of our main thesis is that agents are a new kind of software. Because there was always all this stuff we wanted to automate, but not all of it was economically viable to do with traditional software.

But it is with agents. And what that means is there will be just so much more software in the future. Indulge me with a Venn diagram. Maybe the circle should be better, because the circle represents all software that should exist.

Imagine all software that should exist.

The problem was that we couldn't write all of it because it was too expensive using traditional methods. Like, you can envision all these things where you have all these if statements, you have all this knowledge about the business, you have to figure it all out, you have to hard code into the application.

So much of this software you just would never write because it would be obviously too expensive. But now with agents, that part of software becomes economically viable. I can build it now with not that much effort,right? And that means that with AI agents, essentially all the software maybe not all of it.

We'll find more in the future. But that circle gets filled out,right? All of this stuff that should be automatable is automatable. There's going to be so much more software out there.

And in a similar line, more and more companies, when they ask that question, whether they should buy some software, like a SaaS product, or make some software themselves, they're answering that with the make side,right? Over in Silicon Valley, where I live today, we are talking a lot about the SaaS apocalypse, I think is what it's called,right?

People make their own stuff, and they don't buy the SaaS software anymore. I actually think the SaaS companies will be allright. Don't worry about them. But as engineers ourselves, more companies making more software, again, leads to us having more work, even if it's faster.

And in fact, the way I've been kind of framing this for a while is that we are speed running what's really an experiment in economics of how elastic the software market is. The thesis being that the cheaper it is to make software, the more software we're going to make,right?

And as a consequence, what's actually happening is that demand for software engineers is going up. Now, we don't know.

There's going to be an S-curve, you know? But there's no signs of us reaching the S-curve. In fact, because we're getting better at agents, et cetera, there's so much leeway in the future, I think we'll be allright.

So as AI engineers, it's our job to build that next application layer. And of course, what that actually means is building agents,right? I wanted to spend some time talking about archetypes of agents that I'm seeing actually being built today, actually being effective, actually something you can do today without having to make major changes.

I think we're all a little bit drunk on the coding agents because they're so great,right? They work so well, and it seems so obvious that you can translate that to all other domains. And sometimes these things don't go so well,right?

But the thing is that we don't really have to be doing the most advanced agents you could possibly imagine. There's just so much low-hanging fruit to be done where you can really, really help companies save them millions or billions of dollars without actually making these massive changes to processes that, in practice, will always take a long time, fail often, et cetera.

So this is what I'm actually seeing in the wild. The first part, when you think about what agents you can think build, is people think, well, agents, that rings a bell. I have a team of support agents. Maybe I can automate part of that,right?

And that's also where kind of the first generation of what we call agent as a service. You can make that acronym in your head. Startups are shipping,right? Like the CRS and Decagon of this world. But more generally, I think it's worth asking yourself, in your business, is there a job where it would be quite transformative if we went from a 9:00 to 5:00 thing, because people need to sleep, and I can actually do it 24/7, because agents don't need to sleep,right?

And I think there's many places for that. The next one is probably actually even more important. I call it compressed research, because every business has a certain type of business process that, in a very abstract fashion, has the following shape.

There's some business event, and you have to do some research, and then you make a human decision,right? And you can just build an agent that does the research phase automatically. And that's all you do. That's all you ship,right?

And the important part why this is such an easy thing to ship is because the process is still the same. There's still that business event. There's now the research, and there's a human decision. The research goes faster. And maybe it goes from something that took a human 30 minutes, now they can do the same thing in five minutes.

And if you run that process 100,000 times a year, you just save the company a whole lot of money, but you didn't increase the risk profile, and you didn't have to change the process. At Vercel, we actually have at least two agents of this shape.

When you go to vercel.com and you hit the Contact Sales button, that message actually goes to an agent,right? And I hear about 75% of the time that agent says, well, actually, they just wanted support and hand it over to the support team.

But then in the other case, it will go, oh, that's interesting. Let me check out their LinkedIn. Let me Google the company. Let me figure out how large they are. Let me route it to theright person,right? And then there's a human eventually taking a look at it.

Makes sense. But that obviously was something that took maybe a person 15 minutes before, and now they don't have to do it anymore. And another example is exactly the same process. If you sent us an abuse report, again, there's an agent taking a look.

Is that website abusive? What should we do,right? Still, obviously, the decision in the end should be done by the actual professional, but they don't have to do all this research themselves anymore.

Next is what I think is probably the most magical thing that you can do in any company today, which is to surface information that already exists. It's extremely common that there's information somewhere in the company,right? But for all intents and purposes, you cannot practically use it.

Take, for example, everyone you all engineers, you have issue trackers,right? So is it up to date? Probably not all the time,right? Could it be up to date? Does the information exist? Did you Slack it? Did you have a granola recording that technically contains the information that could update your issue tracker?

Yes,right? Probably yes. And so you can build an agent that does this for your company,right? Whenever you have a manager saying, well, give me a list of updates,right? Why don't they already have the updates,right? Why doesn't an agent have already kind of done their research already?

So again, this just takes advantage of existing information, which is so powerful. And finally, for the last big category,

there's a magical question that you can do to figure out agents you should build in your company, which is to ask folks, what do you hate most about your job? And I actually have a case study about this at Vercel.

So we actually did build our own in-house support agent, and it has what's called a 90% deflection rate. So 90% of the time, it just helps the person in real time, rather than going down somewhere else. And what happened?

The job satisfaction rate on our support team exploded. Why? Because they no longer have to do the boring stuff,right? Oh, my credit card got rejected. Blah, blah, blah,right? Now they get to actually go and figure out actually interesting cases, actually help people who really need help, rather than doing all the toil,right?

So I think eliminating boring work is a very noble mission that we should all kind of strive to do for the companies that we work for. Cool. So clearly, that new application layer are agents. But we also have to shift.

We have to consider another shift, that the software itself is going to be used by agents now,right? And I work in software development, developer tools, et cetera. And I think we're kind of ahead of the game here, speed running that transformation.

What I will share, though, is that on our own web properties, humans are actually now on the minority. So in the last seven days, and we have not shared this before, over 60% of page views on vercel.com were AI agents.

In a similar way, we're seeing the way you use our platform going from people clicking around in a dashboard to usage shifting to our API and CLI. So whenever I now have someone proposing a feature to me, and they show me a UI, I'm like, guys, what's the CLI?

How do I automate this? How does an agent use this? And UI is now something that's so cheap.

The other thing that we're observing is that kind of the relationship changes between software development, software developers, and infrastructure,right? If I didn't write the code myself, I also don't have maybe as strong feelings about how that stuff runs in production,right?

And so for a company like us, it's really important that we shift how we deploy infrastructure to a model where most of the software was written by agent and has to just run. And people expect it to run just like they prompted the agent to do the work.

And finally, and nobody here obviously is surprised about this, the applications themselves are their agent now. And that requires us to have different infrastructure available,right? Everyone's now shipping sandboxes. I think it's almost a meme. I was mentioning earlier that I created this thing called Just Bash.

And I'm really interested in kind of this innovation of how you can give an agent a computer, maybe without giving them a computer. There's lots of interesting stuff there in the market. And I'm sure this conference is going to have lots of stuff there as well.

And then also more broadly, again, it was mentioned I've been here for a while. We're marching head on into a security nightmare. It almost feels like a little bit like 1999, where really everything can be hacked,right? And we just didn't know how to make something secure.

I think we'll have a rude awakening. But what that really means is that we have to be open-minded for how to change things. I will give one example. I think almost all currently popular agent harnesses have fundamentally the wrong architecture.

And that is that they combine where the harness runs with where the code that it runs, that it generates runs,right? As of actually yesterday, I did see that Anthropic agrees with that thesis because on their new agent product, they do have that separation.

And it's really, really key. And that's really just also a point that these are all solvable problems. But my main message today is that we are still in the very early innings, and we have to be prepared to be open-minded about paradigm shift happening in the future,right?

We just have the paradigm shift of agents being kind of these very general sandbox-using things. In the future, we will see more of those paradigm shifts.

Cool. Last point I wanted to make is that this new application layer that we're building can thrive independent of the models,right? Because sometimes model X is better. Sometimes model Y is better. But we are, as AI engineers, building a stable layer on top.

And one of the very interesting consequences is that we don't have to work at a model lab to drive AI innovation. In fact, and I think this is almost like a narrative violation, Europe is the leader in AI engineering innovation,right?

Our own AI SDK, which Vercel makes, it takes now over $10 million a week, and it's led by Lars Gamel, who lives in Berlin,right? He's working on this. Then there's obviously Pi, the coding agent, made in Austria. You'll be hearing from Mario about it tomorrow.

And of course, probably some of you have heard of it. There's a little thing called OpenClaw. And Peter will be on stage here in an hour. And so it appears to me that Europe, against all odds, is taking actually a leadership role in AI engineering.

But we also have to be realistic,right? Europe isn't going to play a major role on the model side. But I don't think it needs to. In fact, I do see kind of two big futures ahead of us. One is where the big model labs win.

In that world, AI will stay very expensive. All the value of all that cool agent tech will accrue to that company. And we won't really be AI engineers anymore,right? We'll be like forward-deploy engineers, whoever the winner is, if it's OpenAI, Anthropic, or Google.

But I don't think that's very likely. And I think what's actually going on is that the opposite is happening. The model companies are commoditizing. Claude is amazing. Codex is amazing. Google will catch up. And importantly,

I'll give them props now, because I think Google's playing an amazing role here, because they have the cheapest infrastructure on the cost side. And so in that commoditized world, they will always decide to make it cheaper,right? And that will keep the price floor where it should be, which is very low.

And that's the outcome that we want,right? Because in that world, we, the AI engineers, are the powerful ones. Our agents are the ones that actually create the business value. And it's the application layer where the real innovation happens,right?

This is where OpenClaw gets invented, and that's where the next paradigm of AI engineering gets discovered. And that's really all I wanted to leave you with today. Thank you very much.