A talk by Malte Ubl, CTO of Vercel, arguing that AI engineering is emerging as the successor to web development and the defining engineering discipline of the coming decade. Drawing on Vercel's own experience, he explores building infrastructure and applications where AI agents act as both builders and users of software, and argues that as AI labs commoditize, value shifts to engineers building at the application layer. # Channel Identity Observations: "The New Application Layer - Malte Ubl, CTO Vercel" ## Video Type & Context - **Conference keynote** delivered at what the speaker calls "the first ever AI Engineer conference in Europe." - > "Welcome to the first ever AI Engineer conference in Europe." - The speaker is introduced by a host as **Malte Ubl, CTO of Vercel**, described as having "over 25 years of software engineering experience" with prior time at Google. - The speaker positions this as a keynote rather than his usual format: - > "usually I give technical talks, but I thought because I'm apparently going first that I need to give a proper keynote." ## Explicit Self-Description Claims - **Speaker affiliation:** > "my name is Malte and I'm the CTO of Vercel." - **Prior community role:** He describes having run a Berlin conference: - > "I used to run a little conference in Berlin called JSConfEU." - **Personal projects mentioned:** A "vibe coding stack" including **chat SDK** ("a way to hook your agents to whatever like Slack, Telegram, WhatsApp chat app you like") and **just bash** ("a bash interpreter written in TypeScript that gives you something like a sandbox with zip nanosecond startup time"). - **Employer-internal claims (about Vercel):** - Vercel runs at least two internal "compressed research" agents (contact-sales routing, abuse-report triage). - > "over 60% of page views on vercel.com were AI agents" (last 7 days, framed as previously unshared). - Vercel's in-house support agent has > "a 90% deflection rate." - Vercel's **AI SDK** has > "over 10 million dollars a week" (stated figure; likely a downloads/usage metric truncated in transcript) and is led by a Berlin-based engineer. ## Intended Audience - **AI engineers and software engineers**, framed as a professional community facing disruption: - > "it's more important than ever to come together as a community and reflect on both our professional as software engineers and AI engineers." - **European tech community specifically** — the talk repeatedly centers Europe: - > "it wasn't going to be like a web development conference that would really bring the tech community in Europe back together in 2026." - > "Europe is the leader in AI engineering innovation." - **Practitioners building agents in companies**, addressed with prescriptive advice: agent archetypes ("agent as a service," "compressed research," surfacing existing information, eliminating hated work). ## Claimed Scope of the Talk / Perspective Offered - **Thesis-driven keynote** about agents as a new application layer: - > "agents are a new kind of software." - > "as AI engineers, it's our job to build that next application layer." - Covers: economics of software demand ("speed running… how elastic the software market is"), practical agent archetypes, agents-as-users of software, security concerns ("marching head on into a security nightmare"), and model-layer commoditization. - Makes an **industry prediction**: model labs commoditize and value accrues to the application layer ("In that world, we the AI engineers are the powerful ones"). ## Observable Presentation Patterns (Demonstrated, Not Claimed) - **Forward-looking, thesis-oriented style** with named frameworks (Venn diagram, "SaaS copocalypse," "compressed research") rather than step-by-step tutorials. - **Self-critical/uncertain hedging** on predictions — distinguishes speculation from observation: - > "we don't know… there's going to be an S-curve… there's no signs of us reaching the S-curve." - > "I don't think that's very likely." - **Cites third-party ecosystem examples** to support claims: Anthropic's agent product, "Pi, the coding agent, made in Austria," OpenClaw/"Open Claw," Google's cost position. - **Reassurance-focused rhetoric** aimed at anxious engineers: - > "I couldn't be more convinced that the answer is yes" (to whether engineers have a future). - **Personal anecdote as evidence** (TikTok analogy for generational adaptation; JSConfEU timing story) rather than data, alongside a small number of internal Vercel metrics. ## Claims vs. Demonstration Distinction | Creator Claim | Evidence Type | |---|---| | 60%+ of vercel.com page views are AI agents | Internal company statistic, unverified by material | | 90% support deflection rate | Internal company statistic | | Europe leads AI engineering innovation | Speaker's opinion, supported by named examples (AI SDK, Pi, OpenClaw) | | Agent harnesses have "fundamentally the wrong architecture" | Stated opinion, with noted counterpoint (Anthropic) | | Agents = new application layer | Core thesis argued, not demonstrated | **Note:** The transcript contains apparent errors ("in Ed for sale" likely "at Vercel"; "Open Claw"/"OpenClaw" naming inconsistency; "10 million dollars a week" phrasing), suggesting imperfect transcription; quoted verbatim where cited. # Delivery Observation: Malte Ubl — "The New Application Layer" ## Overall Tone Conversational, enthusiastic keynote register. Frequent casual interjections ("Cool.", "All right.", "Um") and direct audience address ("Welcome to the first ever AI Engineer conference in Europe", "So you're definitely in the right place today"). - **Humor and lightness**: "Indulge me with a Venn diagram. Um maybe the circle should be better"; "I think we're all a little bit drunk on the coding agents"; "Everyone's now shipping sandboxes. I think it's almost a meme." - **Reassuring / thesis-driven framing**: repeatedly returns to a positive thesis — "I couldn't be more convinced that the answer is yes", "We'll all be fine and this is why", "I think we'll be all right." ## Vocabulary & Recurring Phrases - **"agents"** as the core term, used in nearly every section: "agents are a new kind of software", "build agents", "AI agents". - **"right?" as a constant tag question** — appears throughout: "that circle gets filled out, right?", "the more software we're going to make, right?", "The research goes faster", "That's all you ship, right?", "the process is still the same." - **"you know"** as a frequent filler: "you know, usually I give technical talks", "cuz, you know, people need to sleep", "you know, UI is now something that's so cheap." - Repetition for emphasis: "actually being built today, actually being effective, actually something you can do today"; "the the CRMs and Decagons of this world"; "be be be done." ## Teaching Habits & Structure - **Named categories / archetypes**: explicitly enumerates agent patterns — "agent as a service", "compressed research", "surface information that already exists", plus the question-driven one: "ask folks, what do you hate most about your job?" - **Concrete case studies from Vercel**: contact-sales routing ("I hear about 75% of the time that agent says, 'Well, actually, they just wanted support.'"), abuse reports, and the support agent "90% deflection rate." - **Quantified claims**: "over 60% of page views on vercel.com were AI agents"; "something that took maybe a person 15 minutes before"; "100,000 times a year". - **Vivid analogies**: TikTok video comparison for generational skill; "it almost feels like a little bit like 1999, where really everything can be hacked." - **Rhetorical questions to the audience**: "is there a job where it would be quite transformative…?", "Could it be up to date? Like it does the information exist?" - **Reveal framing**: "and we have not shared this before". ## Communication Patterns - **Hedging alongside strong claims**: "maybe not all of it. We'll find more in the future"; "I think that's what it's called, right?"; "We don't know like… there's going to be an S-curve." - **Self-positioning via personal history**: references running JSConfEU and "impeccable timing" leaving "the summer of 2019". - **Contrarian/opinionated asides**: "I think almost all currently popular agent harnesses have fundamentally the wrong architecture" — immediately updated: "as of actually yesterday… Anthropic disagrees with that thesis." - **Timed references to other speakers**: "You'll be hearing from Mario about it tomorrow", "Peter will be on stage here in an hour" — conference-aware delivery. ## Uncertainty Notes - Filler ("um", "you know") frequency and the "right?" tag are clearly stable patterns given many instances. - Whether pauses, gestures, or vocal emphasis occurred alongside these phrases cannot be verified from the transcript alone; some repeated words ("the the", "be be be") suggest live-speech disfluency, but pacing and delivery energy are not directly observable here. # Observation Document: "The New Application Layer" — Malte Ubl, CTO of Vercel ## Speaker - **Malte Ubl**, CTO of Vercel, keynote at the first AI Engineer conference in Europe. Introduced (by an unnamed emcee) as having over 25 years of software engineering experience, including time at Google. ## Personal Projects Mentioned - **Chat SDK**: a way to hook agents to chat apps (Slack, Telegram, WhatsApp). - **just bash**: a bash interpreter written in TypeScript providing a sandbox with "nanosecond startup time" for agents. --- ## Context & Framing Claims - Ubl formerly ran **JSConfEU** in Berlin, ending it in summer 2019; he attributes the conference's timing to COVID preventing a successor. - **Claim**: AI engineering is "the legitimate successor to web development" as a mainstream engineering discipline shaping the next decade. - **Claim**: The field faces a dual disruption — how we build (with AI) and what we build (AI and agents). - On anxiety about engineering jobs: he is "convinced" there is still a place for engineers, arguing the next generation will be better at the discipline because they grow up "molded in the AI world." --- ## Central Thesis: Agents as a New Kind of Software - **Venn diagram argument**: A circle represents "all software that should exist"; much was previously uneconomical to build with hardcoded traditional software, but agents make it economically viable, filling out the circle. - **Elasticity claim**: "We are speed running... an experiment in economics of how elastic the software market is" — cheaper software production means more software made, hence rising demand for engineers. - **Qualification preserved**: "maybe not all of it. We'll find more in the future" — and on the S-curve: "we don't know... there's going to be an S-curve... But there's no signs of us reaching the S-curve." - **SaaS "copocalypse"** (Silicon Valley term): companies increasingly choosing to *make* rather than *buy* software. Ubl counters: "I actually think the SaaS companies will be all right," and more companies making software means more work for engineers. --- ## Agent Archetypes Seen Working Today Ubl cautions against being "drunk on the coding agents" — success there doesn't automatically translate; he advocates low-hanging fruit over maximal process change. ### 1. Agent as a Service (24/7 automation) - Automating parts of support teams (citing CRMs and Decagons as startups in this space). - Guiding question: is there a job where going from 9-to-5 to 24/7 would be transformative? ### 2. Compressed Research - Pattern: **business event → research → human decision**; agents automate only the research phase, keeping the process and risk profile unchanged. - **Vercel examples**: - Contact sales agent: he reports ~75% of the time it routes to support; otherwise it researches the company (LinkedIn, size) and routes to the right person, with a human still deciding. - Abuse report agent: researches whether a site is abusive; the final decision "should be done by the actual professional." ### 3. Surfacing Existing Information - Information often exists but is not practically usable (e.g., out-of-date issue trackers that could be updated from Slack messages or Granola recordings). - Example: a manager asking for updates should already have an agent-generated list. ### 4. Eliminating Boring Work - Guiding question: "What do you hate most about your job?" - **Case study**: Vercel's in-house support agent has a claimed **90% deflection rate**; support team job satisfaction "exploded" because they now handle interesting cases instead of toil. Ubl frames eliminating boring work as "a very noble mission." --- ## Agents as Users of Software - **Metric disclosed**: "In the last 7 days... over 60% of page views on vercel.com were AI agents" — humans now a minority on their own web properties. - Usage shifting from dashboard clicking to **APIs and CLIs**; Ubl now asks feature proposers "what's the CLI?" — "UI is now something that's so cheap." - **Developer–infrastructure relationship change**: if an engineer didn't write the code (an agent did), they lack strong feelings about production behavior — software should run as prompted. - Sandboxes: "Everyone's now shipping sandboxes. I think it's almost a meme." ### Security Warning - "We're marching head on into a security nightmare... almost feels like 1999, where really everything can be hacked." Expects "a rude awakening" and calls for open-mindedness. ### Architecture Critique - **Claim**: "almost all currently popular agent harnesses have fundamentally the wrong architecture" — combining where the harness runs with where generated code runs. - **Contradiction/qualification he notes himself**: "as of actually yesterday, I did see that Anthropic disagrees with that thesis" — their new agent product does have that separation. --- ## Independence from Models & Europe's Role - **Claim**: The new application layer "can thrive independent of the models" — AI engineers build a stable layer atop changing model winners. - **Narrative-violation claim**: "Europe is the leader in AI engineering innovation," citing: - Vercel's AI SDK — stated as "over 10 million dollars a week" (likely a misspoken metric; recorded as expressed), led by Last Gammel in Berlin. - Pi, the coding agent "made in Austria" (Mario to speak). - Open Claw (Peter to appear on stage). - **Realism qualification**: "Europe isn't going to play a major role on the model side. But I don't think it needs to." ### Two Futures 1. **Big model labs win**: AI stays expensive, value accrues to one company (OpenAI, Anthropic, or Google); AI engineers become "forward deployed engineers." Ubl: "I don't think that's very likely." 2. **Models commoditize** (his expectation): Gemini is "amazing," Codex is "amazing," "Google will catch up"; Google credited with the cheapest infrastructure and an incentive to keep prices low. In this world, "we the AI engineers are the powerful ones" — business value and innovation (e.g., Open Claw) happen at the application layer. --- ## Unresolved Tensions (preserved as expressed) - The S-curve for engineer demand is asserted as not yet visible but acknowledged as unknown. - Ubl's harness-architecture thesis is stated strongly but was already contradicted by Anthropic's product, per his own admission. - The AI SDK metric ("10 million dollars a week") is unusual and stated without elaboration. # Observation: Speaker Roles & Provenance — "The New Application Layer - Malte Ubl, CTO Vercel" ## Speakers & Roles | Speaker | Role | Evidence | |---|---|---| | **Malte Ubl** | **Keynote speaker / presenter** (CTO of Vercel; self-identified "my name is Malte and I'm the CTO of Vercel") | Delivers the main talk | | **Unidentified emcee** | **Introducer / narrator** (off-stage voice) | "Our first speaker draws on over 25 years of software engineering experience… Please join me in welcoming to the stage the CTO of Vercel, Malte Ubl." | No guests; single-speaker keynote format. ## Referenced Sources & Third-Party Claims (as attributed by speaker) - **Vercel internal data** (speaker's own claims, unverified): - >60% of page views on vercel.com in the last 7 days were AI agents — "we have not shared this before" - Contact-sales and abuse-report agents; support agent with a stated "90% deflection rate" - AI SDK with "over 10 million dollars a week" (transcript wording; likely downloads/week), led by **Last Gammel** (Berlin) - **Named third parties / products** (mentions only, no endorsement implied): - **Anthropic** — speaker states Anthropic's new agent product separates harness from generated-code execution, "disagrees with that thesis" - **OpenAI / Google / Google Cloud / Codex** — model-lab commoditization claims; "Google has the cheapest infrastructure" - **CRM / Decagon** — cited as "agent as a service" startups - **Pi** (coding agent, "made in Austria"; speaker **Mario** to present tomorrow) - **Open Claw** (speaker **Peter** on stage "in an hour") - **JSConfEU** — speaker's prior conference in Berlin, ended summer 2019 - **Unattributed market framing**: "SaaS copocalypse" — attributed to Silicon Valley talk, not a named source. ## Personal Projects Mentioned (by speaker, not evaluated) - **chat SDK** — hooks agents to Slack/Telegram/WhatsApp - **just bash** — TypeScript bash interpreter with sandbox capabilities ## Promotional Segments - **None flagged as explicit promotion.** The talk references Vercel products (vercel.com, AI SDK, platform agents) as case studies; these are speaker-affiliated product mentions rather than flagged promotional segments. No sponsor or advertisement segments appear in the transcript. ## Availability & Uncertainty Notes - **Comment availability:** No metadata supplied; unknown. - **Transcription artifacts:** Speaker name spellings uncertain ("Last Gammel", "Open Claw", "Pi", "Mario", "Peter") — as rendered in transcript. - All statistics and claims are **speaker-asserted** with no independent citation in the source. \>\> 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. \>\> \[music\] \>\> Good morning, everyone. This is awesome. I'm so glad to be here. Welcome to the first ever AI Engineer conference in Europe. Um 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 uh stack. Uh 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 you like. And I've been working on just bash, which is a bash interpreter written in TypeScript that gives you something like a sandbox with zip nanosecond startup time um for your agents cuz they love bash. All right. One thing I want 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 JSConfEU. 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 would just wouldn't have been a conference one year later because of COVID. But also when we decided that we would, you know, 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, you know, software engineering itself faces an unprecedented disruption. So you're definitely in the right place today. And it's more important than ever to come together as a community and reflect on both our professional as software engineers and AI engineers. And that's because we're facing a disruption of both how we build, which is with AI, and what we build, 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 that the answer is 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 substantial under uh statement. And so I would not be good at the 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 all right. 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. Um 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 like all these things where like I have all these if statements, you have all this like knowledge about the the business, like you have to figure it all out, you have to hardcode into the application. So much of this software you just would never write because it would be obviously uh too expensive. But now with agents, that part of software becomes economically viable. I can build it now um with not that much 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 like 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 copocalypse. I think that's what it's called, right? People like make their own stuff and they don't buy the SaaS software anymore. I actually think the SaaS companies will be all right, you know. 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 the demand for software engineers is going up. Now, we don't know like, you know, like there's going to be an S-curve, you know. But there's no signs of of of us reaching the S-curve. In fact, because we're getting better at agents, etc., there's so much leeway in the future. Um I think we'll be all right. 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 want to spend some time talking to talking about archetypes of agents that I'm seeing actually being built today, actually being effective, actually something you can do today without, you know, 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 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 be be done where you can really really help companies save them millions or billions of dollars without actually, you know, making these massive changes to processes that in practice will always take a long time, fail often, etc. 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 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 in your head. Um startups are uh shipping, right? Like, you know, the the CRMs and Decagons of this world. Um but more generally, I think it's worth asking yourself, in your business, is there a job where it would be quite transformative if if that, you know, we went from a 9-to-5 thing cuz, you know, 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 there's many places for that. The next one is probably actually even more important. Um I call them 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 like 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, you know, maybe it goes from something that took a human 30 minutes, now they can do the same thing in 5 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 like 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 to the support team. But then in the other case, it will go, "Oh, that's interesting. Um let me check out their LinkedIn. Let me Google the company. Let me figure out the how large they are. Let me route it to the the 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 a abuse report, again, there's an agent taking a look. Is that website abusive? What What should we do, right? Still obviously the decision in the end should be done by by the actual professional, but they don't have to like do all this research themselves anymore. Next is what I think is probably the most magical thing 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 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? Like it 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? Like probably yes. And so you can, you know, build an agent that does this for your company, right? Whenever you have like a manager saying, well, give me a last list of updates, right? Why don't they already have that updates, right? Why doesn't an agent have already kind of done that research already? Um so again, this just makes takes advantage of existing information, which is so powerful. And finally, for the last big category, um 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 in Ed for sale. 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 each actually interesting cases, actually help people who really need help rather than doing all the toil, right? So, that's like 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 uh we have to consider another shift that the software itself is going to be used by agents now, right? And you know, I work in software development, developer tools, etc. And I think we're kind of ahead of the game here speech running that transformation. Um what I will share though is that, you know, on our own web properties, humans are actually now in the minority. So, in the last 7 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 the dashboard to uh usage shifting to our APIs and CLIs. So, whenever I know, you know, I have someone proposing a feature to me and they show me like a UI, I'm like, guys, what's the CLI? Like how do you do how do I automate this? How do how does an agent use this? You know, you know, 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 a strong feelings about how that stuff runs in production, right? And so for 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 you know, has to just run. And people are like expected 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, you know, they're agent now. And that requires us to have different infrastructure available, right? Everyone's now shipping sandboxes. I think it's almost a meme. Um 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. Um and I'm I'm sure this conference is going to have lots of stuff there as well. And then also more broadly, again, it was mentioned been here for for a while, like we're we're like 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. Um I think we'll have a rude awakening, but what that really means is that we have to be open-minded for for how to change things. Uh I will give one example. Um 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 uh that it generates runs, right? Um as of actually yesterday, I I did see that Anthropic disagrees with that thesis cuz they they uh 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 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 like paradigm shift happening in the future, right? We just had the paradigm shift of agents being kind of these like very general sandbox using things. In the future, we will see more of those paradigm shifts. Cool. Um last point I wanted to make is that this new application layer that we're building can thrive independent of the models, right? Cuz 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 an 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? Um our own AI SDK, which Vercel makes, it has now over 10 million dollars a week and is led by Last Gammel, who lives in Berlin, right? Um he's working on this. Then there's obviously Pi, the coding agent, uh 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 Open Claw, um 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? Like 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 deployed engineers who 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. Cloud 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 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 for what 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 one that actually create the business value, and it's the application layer where the real innovation happens, right? This is where Open Claw is invented, and that's where the next paradigm of AI engineering is discovered. And that's really all I wanted to leave you with today. Thank you very much. \>\> \[applause\]