Cloudflare CEO: The Internet's Business Model Is Dead

Yeah. There have always been bots that ran around online. The way Google works is they scrape the internet, and they then build their index based on that. And historically, throughout most of the history of Cloudflare, about 20% of traffic on the internet was bots. And that held fairly consistent over a period of time until about two years ago, when we started to see a real rise in bots driven mainly by AI and the LLMs and everything that was going on behind those.

And last fall, in the fall of 2025, I was asked at what point automated traffic will pass human traffic. We pulled the data, sort of extrapolated out the trends, and thought that it was going to be the end of 2027. Fast forward to South by Southwest this year, March of 2026, and I was asked the same question again. We looked at the data again and were like, oh wow, it's growing a lot faster than we expected. It's moved now to the first half of 2027.

And I was pretty shocked when my team came to me just a few weeks ago and they said, "You won't believe it, but we actually had bot traffic pass human traffic online in the first half of 2026." So I think what that shows is just how fast these different systems, again, almost all driven by AI, are growing, and they're really driving so much more traffic across the internet.

Yeah. So Cloudflare sits in front of a huge percentage of the internet, and it's a super representative sample. As a result, we can always look at what are the general trends across the internet, because we're tracking a number of different things. And one of those is how much human traffic is there, how much bot traffic is there. And in the last couple of months, the bot traffic exceeded the human traffic.

And I think that if you extrapolate this out, in five years, I think you'll see 1,000 times more bot traffic than human traffic. And if I had to take kind of an over-under bet on that, I'd take the over bet. It's growing at such an exponential rate that you're just going to see an enormous amount of the internet that's driven by these various bots and agents and other systems.

I mean, I think that agent, bot, crawler are all synonyms. It all means the same thing. It depends on whether you want to describe it in a sort of normatively positive way, in which case you call it an agent. If you want to describe it in kind of the ickiest way, you call it a crawler or a scraper, but it's the same thing behind the scenes. It's a machine that's accessing resources as opposed to kind of a human eyeball driving a browser accessing those resources.

And again, in this particular case, you still have a whole bunch of this sort of scraper, crawler, hacker traffic that hasn't changed that much. You still have some of the sort of bots like Googlebot that are building search indexes. That hasn't changed that much. If anything, it's gone a little bit down. But the thing that's really driving this is what I think we would all call agents, which is, if I go to ChatGPT or I go to Claude, or I go to any of these systems and I'm shopping for a digital camera, you're going to see thousands of times more site visits for that same activity, that same job to be done of shopping for a digital camera, than if I did it myself.

I might visit five sites if I'm personally trying to figure out what digital camera to buy, whereas my agent might visit 5,000. And that's what's really driving this increased demand.

Yeah, I think, I mean, first of all, if this trend continues, there's just going to be an enormous amount of additional demand on the internet. And I go back to during COVID, where over the course of two weeks, we saw internet traffic double. If our projections are right, that's going to seem quaint very soon. In five years, you might have 1,000 times as much traffic on the internet as you do today. And that's going to mean more servers, more network infrastructure, more CPUs, more GPUs, more memory. All of the things that have to serve these bots are going to be very important.

And it's also going to mean we're going to have to figure out some new business model in order to fund that. Someone has to pay for it. And the business model of the internet historically has been ads, and bots don't click on ads. So it's going to be something different going forward. And I think the most interesting question in the world today is, over the next five years, the business model of the internet is going to change radically.

And what it changes to is totally undefined at this point.

We've got to figure out exactly what that is. And it's going to change a number of things, like what is a brand in an agentic world? A brand historically has been a way, as a shortcut, to tell humans this is something that has a certain set of expectations, will have a certain set of experience associated with it. If I see a Walmart logo on the side of a building, I know what it's going to be like when I walk in.

If I see a Marriott logo, if I see a McDonald's logo, I know what that's going to be like. The thing about bots, they have an infinite amount of patience in order to discover everything that might be right. So the basic idea of what a brand is going forward is going to be very different than what it has been in what had been the very much human-driven kind of commerce and internet experience. And again, I'm not sure.

I'm not sure that I have ideas of what that might look like. And I think that Cloudflare will play some role in helping figure that out. But I think it's all going to get discovered over the next five years. And that's incredibly exciting.

Yeah. What Cloudflare started out as was: how can you take a firewall, like a security product, and put it in the cloud? And the original idea came from a realization that software was moving to the cloud, servers were moving to the cloud. Therefore, all the security and networking infrastructure had to move to the cloud as well. And so that was the basic premise that we started with. And so if you signed up for Cloudflare 15 years ago and you put us in front of your website, what you were effectively doing was essentially putting a bouncer in front of the website that could check anyone who was trying to come to it and then stop the bad ones.

And then, because we needed to make sure we didn't slow things down, we would also take a lot of the load off of your website and be able to, for good visitors, deliver the content significantly faster. So the original idea of Cloudflare was sort of performance and security in a very easy-to-adopt package. We knew as a business that in order to succeed, we eventually had to sell our services to major banks and governments and healthcare, all the things that we now count as customers.

But in the early days, those things were never going to trust us because we were a dopey little startup. And we had no infrastructure, we had no data to actually provide the security services. And so the thing that we did was we created a free sort of stripped-down version of the service with the idea of making it available to everyone. What was interesting, we expected it was going to be a bunch of SMBs and startups and individuals that would sign up.

But it turns out that if you think of it as sort of an X-Y axis, and the X-axis is budget and the Y-axis is security issues, there's almost a perfectly diagonal line: the smaller your budget is, the fewer security issues you have. The bigger your budget is, the more security issues you have. And so it turned out that even SMBs and startups wouldn't sign up, even though it was free. But two organizations kind of defied that, or two groups defied that.

One was hacker kids, because they're always attacking each other. And so overnight, every hacker kid in the world signed up for Cloudflare. And then they were attacking each other, trying to take us down. And then the other were sort of human rights organizations, humanitarian organizations, nonprofits. Because if you're doing any of that work, it turns out nine times out of ten, you're pissing somebody off. And oftentimes it's a government or something that will then attack you.

So overnight we had, like, every humanitarian organization in the world, every hacker kid in the world using Cloudflare. They were all—and we all of a sudden came under just massive attacks. And so we were constantly trying to figure out, how do we stay in front of it? How do we actually continue to exist and thrive in this world? And that forced us to build a number of different things. So we built a registrar product so we could register domains, because we had used a registrar and we came this close to our domain getting stolen, which would have been a disaster for us.

We had to build DDoS mitigation, which initially we didn't think we wanted to build at all. We had to build a DNS infrastructure because we couldn't get anyone else to support us. We needed to build our own sort of VPN because everybody else was too slow or not secure enough. And eventually we had to build our own developer platform where our team could turn around and actually take the ideas that they had and deploy them in a way that was able to be incredibly limited, sandboxed, and other things.

Because at some point we got big enough that if we had an issue, it was incredibly disruptive to the world in terms of what we were doing. And so the real story of Cloudflare has been: we started with this idea that was pretty simple, which was, how do you put a firewall in the cloud? And then we sort of created so many problems over time for ourselves that we had to solve.

And then in the process of solving those problems, we've built a whole series of products. And so Cloudflare today, unlike when we started, I mean, I have a hard time articulating exactly what it is that we do. At some level, we're sort of the next-generation AWS or Google Cloud, where we've rethought how that works. We still provide security and performance across that. But we have additional products that take advantage of the network that we have in order to provide things like a cloud-based VPN and other things.

We're increasingly, because of the massive percentage of the internet that we sit in front of, playing a role in figuring out what's the business model of the internet of the future. And so our mission is to help build a better internet. And I think anything that is in fulfillment of that mission is the sort of problem that we're always thinking about.

I mean, in the very beginning, when we launched, we had servers in five cities around the world: Chicago, Ashburn, Virginia, San Jose, California, Amsterdam, and Tokyo. Except Tokyo, if we had been totally honest, deserved an asterisk because we couldn't totally figure out the routing. And if we got it wrong, a whole bunch of traffic from the U.S. ended up hitting Tokyo. And so we would literally turn the Tokyo servers on and off throughout the day, depending on who was awake around the world that day.

Fast forward, and we're in over 350 cities worldwide. We're in over 1,000 data centers worldwide. And the minimum deployment is sort of like a rack of servers. In some places we'll have hundreds of racks of servers, just depending on what's needed there. But I think that was a huge focus behind the scenes: how do you figure out how to get into all of these places around the world?

And it was a series of stories of how did we create enough value to the ISPs around the world, the internet providers for consumers, that they would invite us into their buildings. And it was a number of different things. I remember Telecom Pakistan was this incredibly difficult organization to work with. And there's a lot of people in Pakistan, so there was a lot of traffic that was coming from it.

It was all hitting our Frankfurt data center. And I kept saying, we should put servers in Pakistan. And our team kept saying, you don't understand, they're incredibly difficult. They've kicked Facebook out, they've kicked YouTube out, they've kicked Akamai out. They're never going to let us in. And then out of the blue one day, we get an email from the guy who's the head of networks at Telecom Pakistan. And he says, "Hey, is there any way that we can get Cloudflare gear into our network and into our system?"

And I went to the team and I was like, I thought you said these guys were difficult. And so we got the guy who ran networks on the phone, and we were like, "Oh, we'd heard you were kind of difficult. Why do you want us there?" And he said, "I'm a huge cricket fan. And the Pakistani national cricket team is a Cloudflare customer. They were a free customer."

And I'm sick of the latency of backhauling the traffic to Frankfurt. So set up servers, and we'll install them in our network. And so the secret to Cloudflare's success has always been: how do we provide a huge number of services for free to a bunch of people? And then it ends up being that there's somebody in that group who is really important. We do other things as well. It turns out that Amazon gets to choose where www.com points.

com points? And the answer is there are these 13 root servers that are out there that underlie the internet. And when I say a server, people picture a single box. But in these cases, there are often thousands of machines that are sitting behind this, and they're run by organizations that you'd be sort of surprised by. Like USC has one, the University of Maryland has one, NASA has one. And the reason there are 13 is because that's the amount that you can stick in a standard packet.

So there will never be a 14th root server. And the organizations that run them will probably never change as well, because this has become this incredibly political topic. Like China wants one, Russia wants one. And so as a result, the University of Maryland will probably continue to run it, even though, why the University of Maryland? We provide the infrastructure for two of the 13 root servers. We don't run the root servers themselves, but they are on our network.

And that's incredibly important because anytime you send an email, anytime you click on a link, anytime you use an app on your phone, the very first thing that happens is a request to one of these root servers. And so we provide those services, we provide them for free, and we do it for two of the 13. We've been asked to do it for more, but we think two is sufficient. And that's, again, one of the things that when we go to an ISP anywhere in the world, we say, "Hey, would you like one of the root servers to be running inside your network?"

And they're like, absolutely, that'll improve everything. And then in the process of getting that in, that then helps us. All of the other services that we provide run on that same infrastructure. And so because we've done the hard work to make it so that every service at Cloudflare can run on any one of our servers, when we can get into these places, it means that we then have really privileged access to kind of the fundamental core of how the internet works.

No, I mean, I think networks inherently have network effects, and as we have gotten bigger, our rate of growth of who uses us has continued to accelerate. And so I think there are multiple different network effects that are stacking on top of each other. One, everyone who uses one of those things, they're inherently going to get access to everything else on Cloudflare a little bit faster. And so as more people use one side of our network, it just makes the other side of our network much more valuable.

And as more people use the other side of our network, it makes the other side of the network more valuable. And so I think those things are very much compounding. And then going forward, as we think about what the future business model of the internet is going to look like, I think that's going to be another place where it's going to make it incredibly compelling for as many people as possible to be on our network.

But it's interesting. It takes about five minutes to sign up for Cloudflare's basic services. It takes about 10 seconds to leave. And so, while I think that there are things that are always driving the value behind Cloudflare, we have to constantly live up to providing that value. Otherwise, our customers aren't locked in in any way. And if we're not providing service, if we're not creating value, the whole thing could go away very quickly.

And again, I think that's another one of the network effects that we have, is that we act almost like an immune system. And so an attack against any one of our customers benefits all of the customers that are out there. The story that Michelle, my co-founder, wouldn't want me to tell because it's a little blue, I guess, was that early on, I remember we used to have a bell that would go off anytime anyone signed up.

For Cloudflare, and the bell went off, and we all would run back to our laptops to see who had signed up. And this was back in 2010 or maybe early 2011. And I remember my eyes got wide and I blushed because it was a Turkish prostitution website that had signed up. And it was like, oh, okay, I guess we need an employee handbook or something to sort of say there might be some kind of colorful things that sign up for Cloudflare.

But then what happened next is the bell went off again, and it was another Turkish prostitution site, and then another one, and then another one. And by the end of the first week, over 1,000 Turkish prostitution sites had signed up for Cloudflare. And it was really strange because we were like—

Yeah. And I mean, we didn't have a sales team. We hadn't marketed. We hadn't translated the website into Turkish. It wasn't like there were a bunch of Bulgarian escort sites that were signing up. For whatever reason, it was Turkish. And so curiosity got the better of us. And so we contacted one of the webmasters behind this.

We set up a Skype call with them. And it was interesting. First of all, we got on the phone, and he was just effusively thankful for Cloudflare. And he said, you might not know this about Turkey, but as you go further west in Turkey, it's very European. They don't love what we do, but they kind of tolerate it. But as you go further east, it becomes a much more conservative, much more Muslim country.

And they think what we're doing is just the epitome of evil. And so he said, listen, someone reads TechCrunch. They heard about you. We signed up. We are always getting these attacks, we assume from more Muslim fundamentalist, Eastern Turkish people. You protected us from this attack. By the way, there's not a lot of money in Turkish escorts, so we're using the free version of your service.

And thank you very much. And so we have machine learning systems that will categorize attacks. And so we labeled this style of attacks the TE, which stood for Turkish Escort Attacks. And so anytime we'd see this, the system would identify the TE attacks are coming. Fast-forward a year later, and I was in our office late on, I think, Thursday or Friday afternoon. And the phone rings, and it's a Dutch gentleman. He's calling from Baku, Azerbaijan.

And he says, the contest is tomorrow. We're completely offline. Everyone has told us you're the only ones who can help. And I was like, what contest? And I grew up in Park City, Utah. I hadn't traveled out of the country until college and wasn't very familiar with things that happen around the rest of the world. So when he said Eurovision, I said, what's that? And he's like, no, it's a really big deal. And I was like, a song contest?

Like, it's like American Idol with nationalism, whatever. Just sign up for the service. He's like, no, no, we need help. And I'm like, no, just sign up, you'll be fine. What had happened was the finals in Eurovision, one of the 26 contestants was transgender. And Baku, Azerbaijan, is again a relatively conservative Muslim country. And some people thought that this was incredibly offensive, that this was happening there. And so they launched pretty significant attacks against them and knocked them offline.

I came in the next morning, and we had a bunch of French engineers, and their eyes were like saucers. And they're like, do you know who signed up last night? And I'm like, oh yeah, that song contest. And they're like, no, no, you don't understand what a big deal it is. And for those of you who are also ignorant Americans in the audience, Eurovision gets more viewers than the Super Bowl. It is American Idol with nationalism.

It's crazy. And so we protected them, and we looked at the attacks, and the system is identifying them, and it goes, TE, TE, TE, TE. Exact same pattern, exact same attacker. Fast-forward a year after that, I get a frantic call from the CTO of JPMorgan, and he's like, we're under attack. They're taking offline a bunch of our consumer-facing services. We've heard you guys are really good at this. You need to bring your best solutions engineers and best salespeople and be in New York first thing Monday morning.

We didn't have salespeople, and our one network guy didn't own a suit. On Monday morning, I remember they have this whole room—it's a war room where they're dealing with this—and they slide this stack of logs across the table. And this guy on our team, his name's Sheree, he looks at it and he goes, oh, we know these guys. It's the Turkish escort attackers. What it turns out is, it actually wasn't anyone in Turkey.

It turns out it was originally a student in Iran who again saw what was happening in Turkey and thought it was repugnant, so launched attacks against them, then saw the Eurovision contest, launched attacks against them, then saw U.S. banks, which is how they came after us. And the same guy, to this day, is running all of Iran's cyberattacks.

And so when you see all of the things where they are creating sort of LEGO-style movies, it's this one guy who started out attacking Turkish escorts. And again, that, I think, shows the power of Cloudflare serving everyone. It helps us learn from even these weird corners of the internet. And as a result today, almost every major financial institution in the world, almost every government, relies on us in order to stay safe online.

And Michelle will be mortified when she hears this. She's like, you need to stop. It was funny, Allen & Company, the big investment bank, invited me to one of their conferences they do in Arizona. And I told this story, and I haven't been invited back since. So anyway, there you go. Okay.

No, no. And it was interesting. I remember a VC early on said, "Okay, you guys have gotten really popular, but how are you going to expand outside of the Bay Area?" And I remember saying—and the person was just completely incredulous—"We're really big in Tunisia, but we don't have anyone in the Bay Area." And so it turned out that wherever the internet was slow, wherever it was more lawless, those were the places that we initially got most of our traffic.

And it actually took a really long time for us to win the tech natives, the YC crowd, the folks that would be what you would think would be our natural audience. Whereas, I mean, if you went to Congo, 50% of the top 100 local websites in Congo were using Cloudflare because the further you were away from the tech epicenters, the more valuable what we provided was.

No, no, no, no one playbook. No. And again, I think—and this, I say this to people and it sometimes kind of frustrates them—but it wasn't like we wrote grand strategy memos on why we built a developer platform. We built it because we needed it. But that's then turned out to be incredibly valuable to defining what Cloudflare is going forward. And so, at some level, the story of Cloudflare has always been: create these really thorny, hard technical problems, solve them for ourselves, and then, in the process, that builds on what it is that really drives the business going forward.

I think first of all, we ended up getting to work with just some incredible investors over time. Carl Ledbetter, Scott Sandell, Brad Burnham at USV. They really matched kind of our style. And what our style tended to be was we thought of venture capitalists primarily as sources of money. And mostly, when we needed money, we wanted to be able to access capital.

Yeah, we really just weren't—we didn't need help hiring. We didn't really want a buddy. We sort of wanted people who would push us from time to time, would sort of say, "Hey, have you thought about what's over the horizon?" I mean, like, we did—it was like, we were sort of like, we know our business better than anyone else. And so, like, if you believe in us, do that and get out of the way. We saw lots of other varieties of that, people who really wanted to be kind of operators.

And again, I think there's not one way of doing this. For some founders, that's incredibly valuable to them and they want that. And so, we talked to almost everyone that was out there. And there were lots of people that just thought we were complete idiots. Like a bunch of people at Emergence Capital, like Santi and Gordon, who I love. But there was one guy who was just like, "You're an idiot and we're never going to invest in you."

And again, I get it. We kind of were. But that's okay because we found people who did believe in us and have done incredibly well coming along the journey with us. And it made sense. But we were an odd company. I think that if you look at the three of us that founded it, most companies get founded by people who are friends with each other. Michelle, Lee, and I, we were not friends.

It wasn't that we were enemies. I think we had a ton of respect for each other, but we were just radically different people. To this day, Michelle, she has a giant pink piano in her living room, and her idea of a good time is at night to sit down with her kids and she plays piano, her husband plays guitar, and the kids sing.

That sounds like the lowest circle of hell to me. But again, we've obviously become friends over time because we built this together. But we were radically different as people. And I think that some investors, when they looked at us, they were like, "How does this motley crew fit together?" But what was powerful was because we were so different. And the way Michelle describes it is, she's like, when you're starting a company, you want it to be like a Venn diagram where you've got big circles and they have just enough overlap that you can still communicate with the other people, but that your lanes are incredibly clearly defined.

And so, in the 16, now almost 17 years that we've been at this, Michelle and I have never really had a fight because fundamentally what I do and what she does are just—we each have our own lanes, and we can succeed in those lanes. And even though I am good at some things, she is good at a completely different set of things. And then that just really drives a lot of what I think has caused us to be successful over time.

And we now get founders that are coming to us for advice all the time. And one of the most common questions we get is, like, how did you guys split up responsibilities? And it depends on how snarky a mood I'm in. But if you're asking that question, it probably means you have the wrong co-founders because fundamentally, what you want is to cover as much surface area as possible and for each person to have a very distinct lane.

And so in our case, Lee was the technical genius that just was heads down writing code. He didn't want to be on the board, didn't want to meet with investors, but an absolute technical genius. Michelle was sort of the operations person who would take a thing that worked once and figure out how to scale it to a million times. And so ended up running a lot of our go-to-market organization, those things that you need to have real process and scale.

And then I'm a good storyteller. And so, like, in the case of the VC thing, Vinod Khosla is thinking of investing in us. I am doing most of the talking because I'm the good storyteller. Michelle's thinking about—I mean, she literally was a Six Sigma black belt. She's a process person and she's incredibly good at it. I'm terrible at that. But she was doing that, and Lee's like, "Why am I at this dinner?"

Like, seriously, I could have so many more productive things going on if I was just back writing code. And so again, I don't blame people for saying, like, if you're pattern matching off everyone's got to be a good storyteller, that just wasn't what we were. But I actually think there's real strength in that because you want different people with different perspectives and different skills. And I think that's part of why we were such a strong founding team.

Yeah, so I think that the real beginning of it starts back in—well, I mean, at some level, Cloudflare has always been an AI company. And I remember pitching Benchmark, actually, and I said, Cloudflare is an AI company. And Matt Cohler rolled his eyes. I was like, I'm never going to say that ever again. And that was back in 2010 or something. But at some level, that's always been true.

Again, the threat scores, like, that's a machine learning system that's recognizing patterns. And that whole thesis was if you get enough traffic going through our system and you can run machine learning systems against it, you can do interesting things. So that's always been kind of in our DNA. And if you actually kind of look at where the real start of Cloudflare was, it came from Paul Graham. Before Y Combinator, he used to throw a conference at MIT called the MIT Anti-Spam Conference.

And it was really a machine learning conference because spam was this perfect machine learning place. And John Graham-Cumming, who's now on our board but was our CTO for a really long time, he was a machine learning guy. And so it was always kind of in our core, but we would not have really described ourselves that way. I think that the modern era of Cloudflare and AI started really in 2017.

And what had happened was we were deploying software in the same way that everyone was deploying software, but our network kept growing, and the size and importance of the customers that we had kept growing. And it was terrifying because when you push code out, there was always a risk you'd make a mistake and take things down. And we had done that. And I remember getting a call from the CEO of FedEx at the time, and we were in the midst of an outage, and he was like, "When are you going to be back online?"

And I was like, "Any second now. We're so sorry, but you're not even a customer." And he's like, "No, no, but we rely on a bunch of your customers, and some of our planes can't land if you're offline." And they could technically land, but they had a sort of checklist of procedures, and one of these things was to check against some systems that were on us. And that was just terrifying to us. And so we thought, we've got to build a new way of developing and deploying software which can be extremely lightweight.

It can scale automatically to whatever size you need. It can be rolled out to a single customer or a group of customers or to all of our customers in a really fine-grained, controlled way. You can pull it back very quickly. And it needs to be cost-effective because we're still running and trying to build this as efficiently as possible. And that gave rise to the Cloudflare developer platform, which we call Cloudflare Workers.

I wish I could say that we saw what was coming in AI. And we did, in some cases, back in 2020, either late '21 or early '22, I can't remember. We did a partnership with this graphics processor company to put GPUs at the edge of our network in order, we said, to be able to do a bunch of interesting things, including inference. Issued a press release, did a whole thing. It was crickets. No one cared. And we're like, huh, that's surprising.

And that graphics chip company was NVIDIA. And hilariously, like two or three years later in 2024, we—and you can look this up—we actually issued the exact same press release, just changed the date, and our stock doubled. And so I think we've always kind of been in this space thinking about it. And I think because we are so close to users around the world and we are so connected to everything else, it makes us just a very natural place to take some of these AI tasks.

So inference, we're really, really good at. And almost all of the models, you can now use Cloudflare to directly access, and you get better performance, you get better responsiveness. We can deliver at a much lower cost than most anyone else.

But even the big, like, OpenAI is a big customer of ours. All their mobile app is built on us. We have direct access to them, and we can get you better performance than you can if you oftentimes just go directly to them. Anthropic, again, another big customer. Claude.ai sits on top of us. And so—

Totally run on us. And in that case, those will be processed on the GPUs that are sitting in our network, distributed around the world in hundreds of cities.

Not today. I think that if you think about what you need for training, you need lots and lots and lots of machines with very powerful GPUs. We have both of those things. But what we don't have is a way of, like, we don't have an InfiniBand network fabric that's connecting all of those machines. And so where an AWS or even an xAI, they're building giant data centers with lots of machines very close together, hyper-networked.

We have just as many machines, but they're spread out all around the world. And as a result, most training tasks, we're not the right place to do that. We're always testing and experimenting. And I don't know that that will necessarily be the case forever. But what we are really good at is anything that you need kind of a beefy machine where your phone or your laptop isn't enough, and you want it to be either fast or lower cost, or you have some sort of regulatory or jurisdictional reason why you want it to run in a particular region and not necessarily get sent back to Ashburn, Virginia.

And I think that's driven a huge amount of the adoption of these AI workloads across our network. And that's by far the fastest-growing part of our business.

Yeah. So, I mean, again, it's all driven by AI. And so we needed to be able to use AI models, but we're a security company. We have various regulatory requirements based on the customers that we have. And so we needed some way to be able to understand how our team was using these models. And so we built something that we call the AI Gateway. And it allows you to do a couple of things. One is it allows you to audit, as if you're the CIO or CTO, all of the prompts that have gone off to the various AI systems and then all the responses that you get back.

And we actually have an AI system that allows you to very quickly surface things based on what you might think of as problematic. If you've got a customer support agent and it starts acting like a Nazi, you want to be able to see that incredibly quickly. And so we give you that auditing. We also allow you to do basically prompt injection. The way that Claude, or the way that Anthropic, sort of put guardrails around Claude in order to take what was Claude and turn it into something that they thought they could release broadly, is they put a whole bunch of prompts that say, "Do not do the following things."

You as a business, like if you're Cloudflare, there are certain things that we don't want AI systems to do. And the AI Gateway allows you to inject that into it. And then the third thing, which again, we built for ourselves, was we need to control costs. The cost of all these tokens can be just overwhelming, and it's really easy for you to lose control of that.

Gateway allows you to route things intelligently where you don't necessarily have somebody who wants an AI agent to summarize their email. Like, you don't need the latest frontier model in order to do that. You can run it on something which is a lot simpler. And so for our team, oftentimes they have no idea which model they're hitting. Gateway is just deciding that for them. And again, we built that for ourselves. And people are always asking us, like, what are you guys doing around AI?

And we showed it off, and people were like, "I need that." And so now, again, that's turned into a product.

It's all just stuff we needed. Yeah. And then it turns out other developers needed it as well. And so, if you think about how AWS developed, it was Amazon's way of building essentially systems where their own team could build things very, very quickly. And I think the story of Cloudflare has very much been the same thing, where we needed all of these things to build what we were doing.

And then that's turning out to be incredibly valuable to our customers and to anyone who's trying to do anything in AI today. We are the best place to build any kind of agentic workload. An example of this: if you take every knowledge worker on Earth and you imagine that they're each going to have one agent that is working on their behalf, it turns out that the CPU utilization of that is more—it's 40 times the current annual CPU production that's out there.

If you're doing it in a traditional sort of AWS containers-based way, it's just too expensive to do that. And I think the idea of every knowledge worker having just one agent is insane. You're going to have hundreds of different agents that are working on your behalf, in which case we just don't have the capacity to be able to provide that. And so what we've done is said there's got to be a better way of doing that. And so again, what Workers did is it said, if once upon a time we had physical servers, and then we had VMs, then we had containers, Workers said, what's the next step beyond that that's even more efficient?

And we built all of Workers around a concept which everyone's familiar with because it's the tabs in your browser, which are isolates. And that is a safe environment that is sandboxed from the other tabs that are running. But it doesn't need to have a whole new copy of the operating system. It doesn't need to have a whole bunch of tools. And as a result, you can stand it up much more quickly. You can tear it down much more quickly.

And for agentic workloads, where your agent is effectively going to be writing whatever you're asking it to do, it's effectively going to be writing code for you all the time. That is turning out to be kind of the perfect environment to be able to build these things. And again, I wish it was because we were so clever and saw the future. But I think a lot of it was what we needed to build for ourselves, and it's turning out to be just a very powerful platform for anyone who's doing anything kind of on the modern internet.

I mean, these agents, like, you need a lot of GPUs, we all know that, but CPU utilization is going through the roof. And that's going in a bunch of different directions. And so we're constantly trying to think about how can we improve the underlying efficiency of the network? So, like, a while back, about three or four months now, we rewrote WordPress in Rust in order to deliver it.

And we called it M-Dash because it was a play on the fact that we used AI to do it. And people are like, why'd you do that? And we did it because there's a huge community that supports WordPress. WordPress should be successful going forward, but there's no way that WordPress is going to be able to scale for what's coming going forward. It's a PHP piece of software. Again, amazing for what it was, but it costs like three or four dollars at current traffic levels in order to run.

If traffic explodes 1,000 times, people aren't going to be putting WordPress sites up because it's going to cost $3,000 or $4,000 in order to be able to run these things. So we've got to reinvent a bunch of these fundamental technologies that are out there. Not because we're like, oh, we need to open source, we give it away, but because we believe that our mission is to help build a better internet.

And with the tidal wave that is coming, if we don't get in front of it, if we don't upgrade some of these fundamental systems, it's going to make a lot of the internet just break because we have to have an infrastructure that can actually scale. And that's going to be, how do we take the user interfaces and the things that people know and are familiar with and have an ecosystem around them, but then port them into ways that they're just significantly more cost-effective and efficient to run.

I think for the next two years, we're going to see just a series of really scary things happen online. Probably the worst kind of bug that was out there for a long time was this thing called Log4j, where you could send a very simple command and compromise almost any server running anywhere. I think for the next 104 weeks, so two years, you're going to see a Log4j-like vulnerability every single week. Again, we were part of Glasswing and got to use Mythos to look at software.

We get early releases of the various OpenAI models. We've built our own security models. These models are incredible at finding vulnerabilities, and they're going to find them like crazy. I think security is going to seem really scary for the next little bit. There's going to be a bunch of VCs that invest a bunch of money because you're going to see just an explosion in cybersecurity companies that are stopping this. But what's interesting is I think it's going to be a little bit of a head fake because I think that two years from now, software is going to get just massively better as a result.

So internally at Cloudflare, last year we had an outage that was incredibly embarrassing and awful. And we said, "We have to get better." And so we actually built an agent that not only reviews every code release that we send out, but every configuration change. So if you go to the Cloudflare dashboard, you push a button that generates a file that then gets pushed out to the rest of our network. And we now have an agent that's checking all of those files, every code release.

And it's trained on 10 years of incidents. We have big public incidents that make the news, but there's sort of a background noise of small incidents over time. And one of those sort of just audible-gasp moments that we had was a guy who runs our infrastructure engineering team who was presenting at our all-hands meeting. And he said, "Okay, here's sort of our background noise of incidents." And then there's a click, and then it goes like this.

And he's like, "What do you think happened there?" And that was the moment that we released this agent that's checking it. And I think one of the things that people don't appreciate and don't talk about enough with AI is, yeah, AI is good at replacing a bunch of tasks that humans do, and it doesn't tire, and it doesn't need breaks, and it doesn't have to sleep. But the really interesting thing is it's also uncorrelated to all the other biases that are within an organization. A team of people working together will tend to develop a set of biases.

And that doesn't mean that AI doesn't have biases, but they're uncorrelated with the rest of the team. And so it's actually incredibly good at measuring things. And what I think you're going to see is that software is going to seem incredibly scary for the next two years, and then it'll kind of just fade away, and we're going to all be releasing software which is so much better than it ever has been before. And so our uptime and our reliability and our performance has gone up an order of magnitude over the course of the last year.

And it's all because we're using agents in order to more securely build our systems. And I think everyone is going to be doing that going forward.

We were selling picks and shovels in sort of the AI gold rush, but we were actually pretty cautious users ourselves. We'd run experiments, but we were not all in on it. And we had a bunch of people internally that were skeptical. A guy named Kenton Varda, who built the Workers platform—this incredible engineer. We're not supposed to talk about 10x engineers, but Kenton is clearly a 10x engineer. He's just a genius. And last spring, in 2025, he's like, "This AI stuff is BS."

"I'm going to go play with all of these tools and show you just how much of a mess they are and why we shouldn't be relying on them." And he did. He went away—a super senior guy on our team—went away for a month, played with them, came back, and he was like, "Oh my God, I am now 100 times more productive than I was before." Which, if that's right, and he's a 10x engineer, means that he alone was more productive than our entire team was back in, like, 2019.

Right. And I kind of believe that's true. It was remarkable. And so internally, on the engineering side, I think it spread pretty quickly. And I think the real turning point for us was probably November of 2025, where it felt like—and it was with the release of Claude Opus and a bunch of things—but it felt like it tipped, where all of a sudden, on our engineering side, we were getting much, much, much more productive.

I think that's the story everyone—that's sort of where everyone is today, and everyone is seeing some version of that. I will say that for us, the people that I continue to worry about are the ones that have been very hesitant to embrace these tools. And it tends to be not the super senior folks, not the super junior folks. It tends to be the people kind of in the middle of their career. And it makes some sense, where they've been doing well in the world that existed.

They've been told this is the game to play, and if you play this game, you're going to succeed. And so they've played the game, and now someone comes along and says, "We're changing the rules of the game on you." And that feels deeply, deeply, deeply uncomfortable, unfair. And yet again, you kind of have to adjust to what's out there. But I really do worry that we're going to have this sort of lost generation of either young millennials or older Gen Z folks that just—they're going to have incentives to say we shouldn't use these tools because, again, if they do, they don't feel like they have any advantage to the people who are coming from behind them.

And so a lot of what I've been trying to do is, how do you bring those groups along? The other piece was, I think engineering teams are very natural users of these products, and coding has been a place where you've gotten really clear value from them. But that's just a small part of Cloudflare. We've got legal, finance, marketing, sales, all of these other organizations that are part of the team that we're like, how can we make them significantly more productive as well?

And so we came up with this idea that, could we create a sort of user-friendly system that allowed someone on the finance team to be able to do their job incredibly efficiently? And we called it Cloudflare OS. And it's basically a harness where we've taken a bunch of things that have to be true and gotten them into it. We've taken a bunch of things that are sort of just informative based on our experience, and then we've taught it skills where it can do various things.

There's nothing that's that magical about what we did, except that we had a pretty significant advantage because we had all this security tooling where we could hook into all the different systems of record we have, the ERP system we have, the sales systems we have, the workplace management systems that we have, and do it in a way that was secure and where an agent working on behalf of a user could inherit the specific kind of access that that user had. And I think that's where a lot of these things fall down, is where people don't have that security model in place.

We did. And so we were able to build it pretty quickly. The other thing that was where I think people fall down is, if you ask someone to describe what they do in their job, they'll describe it, but they'll leave like half of their job out. And so the question is, how do you capture really what are the jobs to be done within an organization? And so the clever thing—there's a guy named Sam Ray on our team—and he was like, "Listen, we're going to set up an email address and we're going to tell everyone that it's a magic AI agent."

Com. And we told everyone, "It's a magic AI agent. We've set it up. You can ask it anything." Now, in reality, behind the scenes, it was a team of about 20 people that staffed this 24/7. And yes, they were using AI tools, but what they were really doing was gathering the information about what are the real problems that people have in their jobs. And then they were building that in and turning it into a set of skill files.

Emails and information to be done. And so an example of this is, there's a woman named Heather who's on our investor relations team. And so we're a public company. And so every time we have earnings, it's about two weeks of prep ahead of time to generate all the IR documents and everything that needs to be done. And it's kind of arduous, kind of drudgerous work to put this all together. And Heather's like, "I think I can automate it all." And so we went from what used to be a two-week process down to what is now a three-minute process.

It is more accurate. We actually found errors in things that we had put up before. Nothing significant, but little things here and there. And now we're able to take that, and that means that then our IR team can spend more time meeting with investors, talking with our shareholders, doing all the things that are actually the really productive parts of their job, and much less time actually generating those documents. And so I think that every company is going to be going through this.

And it's interesting, again, we get questions like, hey, how are you guys doing this? And we keep showing off this Cloudflare OS thing. I was on the group that's organizing the 2034 Olympics in Utah. And I was talking to a guy named Ilario, who's the CTO of the IOC, and he's like, listen, we need this. We need a system to do this. And I was like, well, let me show you what we're doing at Cloudflare.

And so I showed it to him. We never thought this was going to be a product. And he's like, I need you in Lausanne next week, and bring your team because we need to implement this. And so we all flew up, and now they're actually using this to help better organize the Olympic Games. And I think every organization is going to have to build something like this, and if you do it in a way which is secure, that gives users access, again, I think it's going to just massively empower teams in order to be successful.

I'm not in the Dario camp of AI is going to replace all jobs. I think it is going to replace a certain set of jobs. Like, I think if I have a developer and I can now give them AI tools and they're 10 times as productive, I'm going to hire as many developers as I can. If I have a salesperson and I can give them tools that eliminate the parts of their job that they don't like, which is coming up with account plans and doing all of those things, what they want is to be in front of customers and out there selling.

I'm going to hire as many salespeople as I can. Where I think there's going to be a big change is the parts of the organization that aren't building and they aren't selling; they're basically measuring. And it turns out that AI systems are much better measurers than any humans, again, in part because they're uncorrelated. And so I think a lot of those things are going to be the case. Another example internally: internal audit, which is again one of these things that you do when you're a public company.

You probably don't do it when you're a small startup, but you do eventually. We have 105 or something risk areas. And every quarter historically, the internal audit team has picked six to 10 of them, and then they do these deep-dive audits to make sure that we're not screwing up procurement or we're doing revenue recognition correctly, and they're measuring, effectively, the organization. We're now getting to a place with these tools where we can take all 105 of those risk areas and continuously audit them and find any issues that are there.

And I think that that's making us a better organization. It's freeing up people to be able to work on either building or selling, which are really where value is created within organizations. And it's just incredible to see how much more productive the teams are.

We laid off more than 20% of our team, not because the business was struggling and not because they weren't great team members, but we just need fewer middle managers. We need fewer measurers. And those roles were going away. And as I talked to peers at other companies, they're all seeing the same thing. And they're all saying, "Yeah, we're going to have to do the same thing at some point." And you're seeing these sort of trickle out, but there's a real fear in leaders out there that they don't want to be the first ones to do that.

And pardon the vernacular, but I think that's chicken shit, because the cruelest thing that you can do is wait. I do think in the next 6 to 12 months, almost every company is going to go through some exercise like this where they're going to cut a bunch of their team. And I think a lot of CEOs are waiting around to do it because they're afraid that they're going to look bad in the process. What really struck me was the realization that once you know that that change is going to happen, the kindest thing that you can do for your team is to do it as soon as possible, because it's way easier to get a job today than it's going to be in 6 to 12 months, because the market's going to get flooded.

And so we put together an incredibly—I mean, the most generous severance package in tech that we've seen. We let stock continue to vest, which nobody does, but we did. And we're working incredibly hard to place these people because they're incredible people. And somebody who's a middle manager at Cloudflare can be a senior manager at a startup and do an extraordinary job. But once, as an organization, you've realized you're going to do it, the kindest thing that you can do for your team is to do it as soon as possible.

Because the worst thing that can happen is that there's just a bloodbath 6 to 12 months from now where everyone does it at the same time and the market gets flooded with a bunch of people who are all of a sudden looking for jobs. And so that was the catalyst. That was sort of the rationale that went through our minds. And again, there are people who are really close friends of mine who we let go because the roles that they had just didn't make sense anymore.

And we wanted to do it in a significant enough way that we would never have to do it again. And so I feel comfortable saying that for the foreseeable future, we're not going to have to do anything like that again because we've reorganized the organization. And I think one of the metrics that we look at is span of control. And so, how many direct reports? What's the average number of direct reports in an organization? And the historic number that Harvard Business School did a study on, and they came up with, was about six.

So for every manager, they have six direct reports. And that was exactly what we were at. It's so clear that with these new tools, a manager can manage a lot more people. Meta is trying to get to 50 to 1. I think that seems like too many to me, but I think 12 to 1 is right. And the benefit of expanding the average number of direct reports is it inherently flattens the organization. The fewer number of direct reports, on average, a manager has, inherently the organization is going to be much more hierarchical.

The more direct reports they have, it's going to be flatter. And I think one of the things that we're seeing is that the flatter the organization is, the easier it is for us to move quickly, to be able to deliver things. And again, I think that's what's driven a lot of us. But yeah, I think this is coming across the industry. And again, it's not a statement that any person is a bad person or a bad individual.

In fact, they're great. But there are roles that you're just not going to need anymore. And some people you're going to be able to sort of rehome and reskill inside your organization. But if you're going to go from six-to-one to 12-to-one, that means a whole bunch of middle managers are going to go away.

I think yes. And recognize that it's natural for that to feel scary and that your instinct is going to be to fight against it. But the more that you can embrace these tools, the better. I have never seen, and again, running this now for 17 years, I've never seen more senior managers on our team raise their hand and say, "Hey, I want to go back to being an individual contributor." And so we're rethinking even how compensation works and everything else, because I think that the power of an individual contributor and the amount of work that they can do is extraordinary.

And so I think that for us, our most senior members of our team are embracing this because it's a way for them to reinvent themselves, and they're senior enough that they're not scared about it. Our most junior folks—we hired 1,111, that number is meaningful to us, interns this summer. And I mean, they're the most extraordinary humans because everybody stopped hiring interns, which I think is just a total mistake. And so we got sort of the pick of the litter.

And they're all totally AI-native. And what we're trying to do is get both of those groups, to get the folks that have been more hesitant, because the fact is 92% of our engineering organization is using AI tools. That should be 100%, for sure. But you've got to get people who especially are sort of mid-career to be brave enough to learn these new tricks. And I think that that's really important. And again, you can't have one person who is 10 or 100 times as productive in the same role as somebody else making the same amount of money as somebody else who's sort of doing it the old way.

One of those two is going to leave. And the worst case is if the person who's 100 times as productive leaves. And so we are continuously trying to find every way to lift everyone up. And again, part of why we did the layoff was in order to really free up the resources and catalyze the entire organization to be able to do this. But it's not just your developers. It has to be finance, legal, marketing.

Everything has got to be embracing these new tools.

Independence Day, July 1st.

Coming up on the first anniversary, I guess.

Yeah. So, what was it in the first place? I think that you've just seen an enormous rise in the amount of automated traffic that's running across the internet. I think in five years, bots and agents will outnumber humans online 1,000 to one. At the same time, the interface through which we access the internet is changing. And we've gone through other platform changes before. We went from browsing the internet on a browser on your desktop or laptop to social media.

To mobile. But throughout all of those things, the underlying business model of the internet for the last 28 years has remained basically the same, which is it's largely advertising and then, to a lesser extent, subscription-driven. The problem is that, first, there's just going to be a lot more cost to run on the internet because you're going to have 1,000 times as much traffic, which means you're going to have to have servers and CPUs and network and all that stuff. And someone needs to pay for it.

And the business model of the last 28 years, which is largely advertising-based, doesn't work because bots don't click on ads. And so something has to change. And so a part of that is, how do we make the internet more efficient? Like, how do we take legacy software and port it to things that can continue to scale in a cost-effective way? But another big part of that is, how do we figure out what the future business model of the internet is going to look like?

And we have great relations with all of the different AI labs and companies, and they get it. And they actually say, listen, as long as it's fair, as long as everybody has to do the same thing, we get that we've got to pay for the content that we're using in order to build our systems and our models. But we've got to build a system to do that. And so we're experimenting in a bunch of different ways.

The first thing that we did was we said, in order for a market to exist, you always think you have to have supply and demand. It's not exactly right. What you actually need to have is scarcity of supply and demand. If everything is free, then no one pays for it. Like, we're sitting in this room, we're breathing the air. Air doesn't cost us anything. On the other hand, if we go scuba diving, air is scarce, and so we have to pay for it.

And so that's that. So step one was we said we need to create controls that allow the people who have content online to be able to say who can access it and who can't. And again, everyone's going to make different decisions. In our case, we want all the bots to be consuming our information. We want that to be out there. And that's probably half of our customers are in that camp, where they actually want to make it as easy as possible.

And so we provide the tools to, as cost-effectively, as efficiently as possible, get information and take HTML, which has all this cruft around it, convert it into Markdown, which is a much more streamlined system. And then, as a result, you can get more information in these AI systems without blowing up their context windows and all kinds of things. It makes sense in that case. On the other hand, if you're an ad-supported business, agents aren't good for you because they're taking your content and then people are consuming it through their AI system and you're not getting eyeballs.

So the ad system doesn't work. So we said, let's give everyone the tools to be able to stop it. Let's create some scarcity in the supply that's out there. And what we've seen is, if you go across the biggest publishers in the world, Condé Nast, Meredith, because we've now given them these tools, they're actually signing much better deals with the AI companies. And so that's, I think, sort of the first step. But we've got to go beyond that because if you're a small blog or an influencer or content creator, you don't have the ability to go strike the same deal that Condé Nast does.

There should be some, basically, a micropayment. Every time we access a site and get information, we're happy to pay a fraction of a penny in order to do that. That's harder than it sounds. So we process, in any given second, about half a billion requests on our network. We estimate that somewhere between 1% and 10% of those would be sort of monetizable through some micropayment transaction. And so that means that you have to be able to support, day one, call it 10 million financial transactions per second, with a clear ramp to be able to get to 100 million transactions per second.

Visa, which is the largest payments network in the world, does fewer than 100,000 transactions per second. So we need to be two orders of magnitude bigger than Visa, but at much, much smaller volumes. And so we're working on that. 402, which is interesting, the original internet had something, a response code, the 402. We all know 404, which is not found, and 500, which is an error. I mean, there are different things, but 402 was payment required, and we just never have really built anything around that.

I think that's going to happen going forward. And so Google really is responsible for having built the business model that's powered the last 28 years of the internet. And I think we are trying to figure out what is that business model that's going to power the next 28 years of the internet. But something has to pay content creators because they deserve to eat. Something has to pay for the infrastructure that all of these bots are taxing, effectively.

And I think we're working a lot around figuring out exactly what that looks like.

People are like, why do you keep doing this? Because there are days that aren't fun. I mean, laying off a bunch of people, that wasn't fun. And I've made plenty of money, so it's not about any of that. What it is about is really our mission. And we believe in that mission fundamentally. And we do things that cost us money or that certainly don't make us any money because we believe in helping build a better internet.

And, like, I can't imagine anything that I could possibly be doing that is more rewarding than figuring out how do we create some sort of sustainable business for the future. And I think there's a lot to be incredibly optimistic about. The business model of the internet for the last 28 years wasn't the most healthy. Traffic has always been a terrible proxy for value. And so much of the media landscape was, how do you sort of define your narrow audience and then, with a headline, piss them off enough that they'll click on a link in order to drive eyeballs to your site?

And so much of what is dividing the world today is actually the underlying business model of the internet, which has been traffic-based. How do you drive as much traffic as possible? That's going away. And I think that if we think about what can replace it going forward, it can be something which is much healthier and much, much better. I flew up to Stockholm to meet with Daniel Ek, who started Spotify.

And because, I mean, like, nobody has compensated creators at scale like Spotify. It's remarkable. And we can quibble about, are the right people getting the money or not, but there's more money going into music creation today, per capita, per GDP, than any time in human history by far. And Spotify gets a lot of credit for that. And you forget that, like, 22 years ago, the music industry was dying—Kazaa and Napster and everything.

It was just normalizing everyone stealing content. And then Steve Jobs steps on stage, announces iTunes, 99 cents a song. That's not the business model that won, but it at least planted a flag that said that there's something that's there. And Spotify last year sent something like $12 billion out to music creators. That's more than the entire music industry's market cap was 22 years ago, which is extraordinary. And so Daniel was telling me a story.

He said, one of the things that they do is if you search on Spotify for, like, Taylor Swift, "Shake It Off," they know, they return results, and they know that those results are what you were actually looking for. On the other hand, if you search for, like, "I want a song to, ooh, a disco beat about how much fun it is to dance with my cat," they also return results, but they know that they probably don't have that. And what they do is they actually publish those queries that are sort of bad results back to music creators.

And there are hundreds of music creators that are making a living off just doing this. One in particular is based in Denmark. Daniel shared is making something like €40 million a year just writing songs for unfulfilled Spotify queries. And I think there's something that's actually quite beautiful about that, because if you search for something on Spotify, what you're searching for is, how do I kind of bring an emotion out? And so, going forward, we, for the first time in human history, have essentially a mathematical model of all of human knowledge.

That's what the LLMs are, right? It's not perfect, but it gives you that. It also shows you where the gaps are, where there are the holes. I picture, like, a giant block of Swiss cheese. There's lots of cheese, but there's a lot of holes. And when you talk to the AI companies, what they want is highly reputable sources that are filling in the holes in the cheese, that are contributing net new knowledge. They don't want yet another story about what happened at 1500 Pennsylvania Avenue, right?

They want something where people are actually telling and creating new information that moves the world forward. And I think that's what I want. I think that's what you want.

I think that's what all of us are craving, is how do we get back to sort of a media environment which isn't just trying to provoke outrage in order to drive traffic, but is actually trying to find the truth and fill that in? And if we can create a system where the people who, again, are highly reputable and are creating sort of net new knowledge, those are the people that get rewarded, then I think that's incredibly, incredibly beautiful. What I keep pushing the AI labs to do is, I'm like, we should create a system where—create the equivalent of, I don't know if it's the Academy Awards, the Nobel Prize—where we measure across a whole bunch of different segments who has contributed the most to human knowledge in the last year in, I don't know, cancer research and foreign policy news.

I mean, you can create a bunch of these things and they can actually measure and say, this particular year the best podcast was The MAD Podcast that was out there, or whatever it is. And we should be rewarding and celebrating, both in terms of honoring these people, but then also paying them for doing that. And I think if we do that, you're going to get a lot more interesting information. My wife and I bought the local newspaper in our hometown, Park City, Utah.

I think we will make more this year off AI licensing deals than we do off display ads. Why? Because if you're planning a vacation to go skiing in Park City, Utah, you want to know what's the best hotel to stay at, what's the best restaurant, who's going to be performing, what are the snow conditions like? And the only place that has that is the local newspaper. And so while the last 28 years of the internet kind of killed local, quirky, unique, interesting information, what I'm hopeful is that as we figure out what the business model is for the next 28 years, it actually brings a lot of those things back and it actually gets back to, let's talk about facts, let's talk about reality.

And, like, the New York Times, it'd be amazing if they were covering, like, in the Marriott Marquis Hotel in Times Square, room 1313 is better than room 1314. Or if you want to sleep in late, room 1314 faces north, and so it's less likely to get sun in the morning. Those are the sorts of—here's the best bodega in New York—the very interesting, quirky local stories. I think that is both a media future and an internet future that we all crave and want.

And I think it's one that we actually have an opportunity to build because we get to reinvent what the business model is going to be.

Thank you for having me.