← The MAD Podcast with Matt Turck
The MAD Podcast with Matt Turck
Cloudflare CEO: Bot Takeover, Edge AI & The Hard Decision Every CEO Will Face
01:28:07
Loading summary
Transcript68 lines
- [00:00]
A
We actually had bot traffic pass human traffic online in the first half of 2026. In five years, you might have a thousand times as much traffic on the Internet as you do today. In the next six 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 their team. The underlying business model of the Internet for the last 28 years has remained basically the same, which is it's largely advertising. The problem is bots don't click on ads. Over the next five years, the business model of the Internet is going to change radically.
- [00:34]
B
Hi, I'm Matt Turk. Welcome to the Matt Podcast. Today I'm excited to welcome Matthew Prince, co founder and CEO of Cloudflare, one of the Internet's most important companies that sits in front of a very large portion of global Internet traffic. We started the conversation by unpacking a huge milestone. For the first time, the number of bots and AI agents has outnumbered humans on the Internet. We also cover how Cloudflare has become an AI infrastructure company and dig into Cloudflare workers, AI G and agent security. We also don't shy away from some of the more controversial topics, including Cloudflare's recent decision to right size its team to adapt to the new AI era. I should add that Matthew is a wonderful storyteller and he shares some truly wild and hilarious episodes from Cloudflare's journey from scrappy startup to the massive public company it is today. Please enjoy this fantastic conversation with Matthew. I want to start with something that feels like a very crucial, important moment in the future history of the Internet. What you tweeted a couple of weeks ago and you said effectively that the number of bots and machines on the Internet now outnumbers humans. So can you unpack that and explain what that was?
- [01:48]
A
Yeah. So, I mean, 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 Kleffler, it was about 20% of traffic on the Internet was bots. And that held fairly consistent over a period of time until, until about two years ago when we started to see a real rise in bots driven mainly by AI and, 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 will automated traffic pass human traffic? And we pulled the data and we sort of extrapolated out the trends and, and we thought that it was going of 2027. Fast forward to south by Southwest this year, March of 2026. And I was asked the same question again. And we looked at the data again and we're like, oh, wow, it's growing a lot faster than we expected. It's moved now to the first half of 2027. And then, you know, 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.
- [03:14]
B
And what was the denominator? Was it like a HTTP request?
- [03:17]
A
Yeah, so, so Cloudflare sits in front of, you know, a huge percentage of the Internet. And so we, and it's, and a, and a super representative sample. And, and so as a result, we can always look at what are the general trends across the Internet. And we have radar. If you go to radar.cloudflare.com, that's 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, in the last couple of months, it, it, the, the bot traffic exceeded the human traffic. And I, and I, I think that if you extrapolate this out, you know, in five years, I think you'll see a thousand 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 that it's just going to, it's, it's growing at such an exponential rate that, that you're just going to see an enormous amount of the Internet that's driven by, by, by these, by these various bots and agents and other systems.
- [04:05]
B
And when we say bots, do we mean agents? Do we mean crawling bots? What do we mean?
- [04:12]
A
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 kind of the ickiest way, you call it a crawler or a scraper, but it's the same thing behind the scenes. It's, it' 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 Clock, or I go to, you know, any of these systems and I'm shopping for a digital camera, you're going to see, you know, 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, you know, 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.
- [05:28]
B
Yeah, and what, what does that change from, I guess, an infrastructure perspective like what you just described? 5,000 sites versus 5. In some ways that sounds inefficient. I mean, it's efficient for me as a user ultimately, because I get the best answer. What does that change in terms of requirements for the infrastructure?
- [05:45]
A
Yeah, I think, I mean, first of all, there, there, if, if this trend continues, there's just going to be an enormous amount of additional demand on, on the Internet. And I go back to, you know, during COVID where over the course of two weeks, we saw Internet traffic double. You know, if, if, if our projections are right, that's going to seem quaint very soon. You know, in five years, you might have a thousand times as much traffic on the Internet as you do today. And that's going to mean more, you know, 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 have to figure out some new business model in order to fund that, someone has to pay for it. And, and, you know, the business model of the Internet historically has been ads. And bots don't click on ads. So it's, it's going to be something different going forward. And, you know, I think the most interesting question that 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.
- [06:53]
B
Yeah, that's a whole new vocabulary, because it used to be clicks and views. And what is it going to be now like actions or we've got to
- [07:01]
A
figure out exactly what that is. And it's going to change a number of things. Like, you know, what is a brand in an agentic world? You know, a brand historically has been, you know, a way, as a, as a shortcut to tell humans kind of this is something that has a certain set of expectations, will have a certain set of experience associated with it. If I, 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. You know, the, the thing about, the thing about bots, they have infinite amount of patience in order to discover, you know, everything that that might be, might be. Right. So the, what, 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, and again, I, I'm not sure that I have ideas of what that might look like and I think that Clefler 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.
- [08:11]
B
All right, fascinating. I'd love to spend a little bit of time on Cloudflare 101. If I put Cloudflare in front of my website, what happens?
- [08:21]
A
Yeah, so you know what, 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, you know, a realization that, you know, software was moving the cloud, servers were moving the cloud, therefore all the security and networking infrastructure had to move to the cloud as well. And, 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 is, is essentially putting a bouncer in front of the website that could check anyone who is trying to come to it and then stop the bad ones. And then because we were, we needed to make sure we didn't slow things down, we would also then take a lot of the load off of your website and be able to, you know, for, 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, you know, major banks and governments and health, all the things that we are now count as customers. But in the early days those, those, those things didn't, they were never going to trust us because we were a dopey little startup and had, you know, we had no infrastructure, we had no data to actually provide the security services. And so the thing that we did was we, we created a free sort of stripped down version of the service with the idea of making it available to, to everyone. What was, what was interesting, we expected it was going to be a bunch of like, you know, SMBs and startups and, and, and individuals that would sign up. But it turns out that, you know, if you think of it as sort of X, y axis and you know, the X axis is is budget and the is, is like security issues. There's almost a perfectly diagonal line that 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 the, we even SMBs startups wouldn't sign up even though it was free. But two organizations kind of defy that or two, two groups defy that. One was, was hacker kids because they're all always attacking each other. And so overnight every hacker kid in the world signed up for, for cloud and, and then they were attacking each other, trying to take us down. And then the other were, you know, sort of human rights organizations, humanitarian organizations, nonprofits. Because if you're doing any of that work, turns out nine times out of ten you're pissing somebody off. And oftentimes it's you know, 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, you know, and we all of a sudden came under just massive attacks. And so we were constantly trying to out how do we stay in front of it? How do we actually continue to, to exist and thrive in this world? And that, that forced us to build, you know, a number of different things. So we, you know, we, we built a registrar product so you 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, you know, a DNS infrastructure because we couldn't get anyone else to support us. We 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 you could, where our team could turn around and actually take the ideas that they had and deploy them in a way that was, that was able to be, you know, incredibly limited, sandboxed and other things because, you know, at some point we got big enough that if we had an issue it was, it was incredibly, you know, disruptive to the world in terms of what we were doing. And so, you know, the real story of Cloudflare has been, you know, we started with this idea that was pretty simple, which was how do you put a firewall in the cloud? And then that, 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, you know, I mean, I have a hard time articulating exactly what it is that we do. At some level we, you know, we're sort of the next generation generation sort of AWS or Google Cloud where we've rethought how that works. We still provide, you know, security and performance across that, but we have, you know, additional products that take advantage of the network that we have in order to provide things like a cloud based VPN and other things. And, and, and you know, we're increasingly, because of the massive percentage of the Internet that we sit in front of, we're increasingly sort of playing a role in figuring out what's that business model of, of the Internet of the future. And so our is to help build a better Internet. And I think anything that sort of is in fulfillment of that mission is the sort of problem that we're always thinking about.
- [13:38]
B
Yeah, the concept of network is fascinating and seems very central to the story. And it's a network of users, but it's also physical network.
- [13:46]
A
Right.
- [13:46]
B
Like what you guys did initially was to create this edge network. How does one even go about building that as a young startup?
- [13:53]
A
I mean, in the very beginning when we launched, we had servers in five cities around the world. The Chicago, Ashburn, Virginia, San Jose, California, Amsterdam and Tokyo. Except Tokyo sort of, 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 US ended up hitting, hitting Tokyo. And so we would literally turn the Tokyo servers on and off throughout the day, depending on, you know, who is awake around the world today. Fast forward and you know, we're in over 350 cities worldwide. We're in over a thousand data centers worldwide. And, and we will go from, you know, 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. What's needed there. But I think that that was the, that was, you know, a huge focus behind the scenes was how do you figure out how to get into all of these places around, around the world? And it was, I mean, it's a series of, of kind of stories of how did we create enough value to, you know, the ISPs around the world, the Internet providers for consumers that they would invite us to be into their, into their buildings. And, you know, it was a number of different things. I remember we, Telecom Pakistan, it 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, the latency of backhauling the traffic to Frankfurt. So set of servers and we'll install them in our network. And so the secret to Cloudflare 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, which is really important. We do other things as well. So if you type in www.Amazon.com, it turns out that, you know, Amazon gets to choose where www points verisign, which runs.com gets to choose where Amazon.com points. The question is, who gets to decide where.com points. And the answer is there are these 13 root servers that are out there that, that underlie the Internet. And when I, when I say a server, people picture a single box. But in these cases, there are often, you know, thousands of machines that are, that are sitting behind this and they're run by organ 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, in a standard packet. So there will Never be a 14th root server. And, 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, and, and, and so as a result, the University of Maryland will probably continue to run it. Even though, you know, 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, 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, is a request to one of these root servers. And so we provide those services, we provide them for free. And, and we do it for two of the 13. We've been asked to do it for more, but we think, think two is sufficient. And, 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 will improve everything. And then in the process of getting that in, that then helps us, you know, all of the other services that we provide run on that same 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, when we can get into these place means that we then have a really privileged access to kind of the fundamental core of how the Internet works.
- [19:02]
B
It's amazing, right? Like we all take the Internet for granted. It's so unbelievably interesting to hear this, right? Like how it all works. So that's physical network. Do you think of Cloudflare as a network effects kind of business currently around, you know, whether that's a data network effect or otherwise, or is that more of a VC way of looking at the world?
- [19:23]
A
No, I mean, I think networks inherently have network effects. And you know, as we see as we have gotten bigger. Our rate of growth of, of who uses us has continued to accelerate. And so I think there are multiple different network effects that, that are stacking on top of each other. But, but, but one of them is, you know, we provide a VPN service and a, and a, and one of the most popular DNS services in the world, 1.1.101. Everyone who uses one of those things, then they're inherently going to get access to everything else on cloudflare a little bit faster. And so as more people use kind of 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, you know, as we think about, you know, what is, what is, what is the future business model of the Internet 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, you know, it's interesting. It takes about five minutes to sign up for Clefler's basic services. It takes about, you know, 10 seconds to leave. And so while I think that there are things that are always driving what it is, that's the value behind cloudflare, we have to constantly live up to providing that value. Otherwise, you know, our customers aren't locked in in any way. And if we, if we're not providing service, if we're not creating value, you know, the whole thing could go away, you know, very quickly.
- [21:10]
B
But at least from a security standpoint, why would you. I guess you could always go to a competitor. But like you, you benefit from the collective wisdom of knowing all the DDoS attacks in the world at any point in time.
- [21:22]
A
And that's, and again, I think that another one of the, the, the network effects that we have is that, you know, we, we act almost like an immune system. And so an attack against any one of our customers benefits all of the customers that, that are out there. That the, the story that Michelle, my, my co founder wouldn't want me to tell because it's a little, it's a little, 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 just being like. I mean, 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 a, like, employee handbook or something to sort of say, you know, there might be some kind of colorful things that sign up for Cloudflare.
- [22:29]
B
But.
- [22:29]
A
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, like, over a thousand Turkish prostitution sites had signed up for Cloudflare. And it was really strange because we were like. And, I mean, we didn't have. We didn't have a sales team, we had a market. We nothing. We hadn't translated the website into Turkish. There was. I mean, it was. It was just like. And. And it wasn't like there were a bunch of, like, I don't know, Bulgarian, you know, escort sites that were signing up for whatever reason was Turkish. And so we, you know, 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. He was. First of all, we got on the phone and he was just effusively thankful for Cloudflare. And he said, you know, you might not know this about Turkey, but as you know, 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 very much more conservative, much more Muslim country. And they think what we're doing is just the epitome of evil. And. And so. And so he said, listen, one of. When someone reads TechCrunch, they heard about you. We signed up. We are always getting these attacks, we assume from kind of, sort of more sort of Muslim fundamentalist, kind of Eastern Turkish people. You protected us from this tax, 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. 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, 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, right? 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, you know, sign up for the surface. He's like, no, no, we need help. And I'm like, no, just whatever, sign up, you'll be fine. What had happened was the finals in Eurovision, one of the six contestants was transgender and Baku, you know, Azerbaijan is a, again, a very relatively conservative Muslim country. And some people thought that this was incredibly offensive, that this was happening there. And so they launch 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's is, it's 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 JP Morgan and he's like, we're under attack. You know, they, they, they're, they're taking offline a bunch of our kind of 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 her and our one network guy didn't own a suit. So we, like, over the weekend we bought him a suit and we all fly out Sunday night and we're in the J.P. morgan offices first thing like 6am on Monday morning. And like, I remember they have this whole room, it's a war room, where they're, they're dealing with this and they slide this stack of logs across the table. And this guy on our team, his name's Cherie, he looks at it and goes oh, we know these guys. It's the Turkish escort attackers. It turns out is it actually wasn't anyone in Turkey. It turns out it was originally a student in Iran who, who again saw what was happening in Turkey and thought it was, it was repugnant. So, you know, launched attacks against them, then saw the Eurovision contest attacks against them that got him recognized and he actually got brought into the, the Iranian military apparatus, the sort of forward cyber, the offensive cyber capabilities. At which point they attacked a bunch of US banks, which is how they came after this. And the same guy to this day is running all of Iranian cyber attacks. And so when you see like all of the things where they are creating like the sort of Lego style movies, it's this one guy who' who started out as the, as, as attacking, you know, Turkish escorts and, and, and again that's, I think shows kind of the power of Cloudflare. Serving everyone helps us learn from even these sort of weird corners of the Internet. And as a result, today, you know, almost every major financial institution in the world, almost every government, you know, relies on us in order to, in order to stay, stay safe online.
- [28:14]
B
It's fascinating and, and hilarious.
- [28:16]
A
And Michelle will be mortified when she's, she's like, you need to stop. I went, it was funny. I, Allen and 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. There you go.
- [28:40]
B
Okay, well, thanks for sharing the fact that you found your initial customer sort of segments in like hacker kids and human rights organizations. When you think about like VC slides and raising money, that's not exactly the first obvious, you know, Silicon Valley kind of playbook.
- [29:01]
A
No, no. And it was, it was, it's interesting. I remember a VC early on said, okay, you guys have gotten really popular, but how are you going to expand outside of you know, the Bay Area? And I remember sort of saying. And the person was just completely incredulous. I was like, we're really big in like, you know, Tunisia, but we don't have anyone in the Bay Area. And so it turned out that wherever the Internet was slow, wherever sort of 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 sort of the tech natives, the YC crowd, the folks that would be sort of what you would think would be our natural audience. Whereas, you know, I mean, we were like in, if you went to Congo, you know, 50% of the top hundred local websites in Congo, you know, were using Cloudflare because it was a, because the further you were actually away from sort of the tech epicenters, the, the more valuable what we provided was.
- [30:06]
B
Yeah. Goes to show that's not one way of doing things. And no one playbook.
- [30:11]
A
No. And, and, and, and, and again, I, I think, you know, it's, and this, 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 kind of 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, that, that builds what it is that really drives the business going forward.
- [30:54]
B
Yeah, and speaking of VCs, there was some like, fun back and forth on X maybe a couple of weeks ago now, I guess without necessarily re litigating the specifics precisely because you had a little bit of a different kind of business. What was your path and what were some of the, I guess, lessons learned in terms of like, yeah, fundraising.
- [31:16]
A
You know, I think first of all, I mean, we ended up getting to work with just some incredible investors over time. You know, Carl Ledbetter, Scott Sandel, Brad Burnham at usv. You know, they, they really matched kind of our style. And what, what our style tended to be was we thought of venture capitalists primarily as, you know, sources of money and, and you know, mostly sort of we wanted, when we needed money, we wanted to be able to access capital.
- [31:49]
B
No thought leadership.
- [31:50]
A
But we didn't. Yeah, we really just weren't like, we didn't need help hiring. We didn't really want a buddy. We sort of wanted like, we wanted people who, you know, would push us from time to time, would sort of say, hey, have you thought about what's over the horizon? But we're weren't, you know, in our business being like, well, I think you should price it at, you know, 22.99, not, you know, 21.99. I mean like we did, it was like we, we were sort of like we, 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, we saw lots of other varieties of that, you know, people who, you know, really wanted to be kind of operators and, and, and I, 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. A bunch of people at Mergence Capital, like Santi and Gordon, who I love, but there was one guy who was just like, like, you're an idiot and we're never going to invest in you. And, and again, I get it. We kind of were, but, but, but that's okay because we found people who, who did believe in us and, and, and have, and have, you know, done incredibly well coming along the journey with us. And it made sense. But. But we were an odd, you know, company. You know, I think that if you look at the three of us that founded it, most companies get founded by, by people who are friends with each other. Michelle Lee and I, we were not friends. It wasn't. We were enemies. I think we had a ton of respect for each other, but we were just radically different people to this day. Like, you know, Michelle, like, 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 along. That sounds like the lowest circle of hell to me. And, and, but, but again, like, that's, but we, we're. We've obviously, you know, we've become friends over time because we, you know, built this together, but we were radically different as, 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 to. You want it to be like a Venn diagram where, 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 in, you know, we each have our own lanes, and we can, we can, we can succeed in those. Those lanes. And even though, you know, even though I, I am. 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. Of. Of what I think has. Has caused us to be. Be successful over time. And you know, we, 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 you know, I, 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, like, what you want is, is to cover as much surface area as possible and for each person to have a very distinct lane. And so in our case, I, you know, Lee was the technical genius that was, that just was heads down, writing code, didn't want to be on the board, didn't want to meet with investors, was sort, you know, but he, but, but an absolute technical genius. Michelle was sort of the operations person who, you know, like, would take a thing that worked once and figure out how to scale it to, you know, a million times. And so, you know, ended up running a lot of like our go to market organization, those things that you need to have real process and scale. And then I, I'm, I'm a good storyteller. And so, and so like in this, you know, in the case of the VC thing, like, you know, Vinod Khosli, Tesla, we is thinking of investing in us. I am doing most of the talking because I'm the good storyteller. Michelle's, you know, thinking about, I mean, she was a, she literally was a Six Sigma black belt. Like, she's, she's a process person and, and she's incredibly good at, I'm terrible at that. But like, she was doing that. And Lee's like, why am I at this dinner? Like, seriously, I could be, have so many more productive things going on if I was just back writing code. And so again, I don't, I don't blame people for saying, like, you know, if you're pattern matching off, you know, everyone's got to be a good storyteller. That wasn't, that was, 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, different skills. And I think that's, you know, part of why we were such a strong founding team.
- [37:06]
B
Okay, awesome. Let's talk about the AI stuff at Cloudflare from a product standpoint because you guys have built so much and I think the world is starting to realize. But I was struck. I'm like, I knew some of the things you built, but as I was prepping for this, it's just such a list. So walk us through the general strategy and maybe timeline of when you started building for AI and what you built.
- [37:37]
A
Yeah. So I think that the real kind of beginning of it starts back in. Well, I mean, at some level, Cloudflare has always been an AI companion. I remember pitching Benchmark, actually. And, and I said, you know, Cloudflare is an AI company. And like, Matt Kohler rolled his eyes. So like that I was like, I'm never going to say that ever again. And that was back in like 2010 or something. And. But at some level that's always been true again, the Turkish Escorts, like, that's a machine learning system that's recognizing patterns. And then, and that whole thesis was if you get enough traffic going through our system and know you can run machine learning systems against it, you can do interesting things. So, so like that's always been kind of in our DNA. And if you, if you actually kind of look at where the real start of Cloudflare was, it, it came from Paul Graham, before Y Combinator used to throw a, used to throw a conference at MIT called the MIT Anti Spam Conference. And, and it was, it was really a machine learning conference because Spam was this perfect machine learning place. And you know, like John Graham Cumming, who's now on our board, but was our CTO for a really long time, like, he was a machine learning guy. And so like, it was always kind of in our core, but we would not have really described ourselves. I think that the modern era of kind 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. Software, you know, and, and, but, but our network kept growing and then the, the size and importance of the customers that we had kept growing and it, it was terrifying because if you pushed, when you push code out, it, you know, there was always a risk you'd make a mistake and take things down. And we had, we had done that and I remember getting a call from the CEO of FedEx at the time and we, we were in the midst of an outage and he was like, when are you going to be back online? And, and I, and I was like, any second. Al, we're so sorry, but, 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 off, 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, you know, some systems that were on us and, 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, you know, automatically to whatever, whatever size you need. It can be, you know, rolled out to a single customer or a group of customers or to all of our customers in, you know, really fine grain controlled way. You can pull it back very quickly. And it needs to be cost effective because we're, we're, you know, we're still running and trying to, you know, build this as a, 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 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, and you can look this up, we actually issued the exact same press release, just changed the date and our stock doubled, like, and so, 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, you know, Inference, we're really, really good at and you know, almost all of the models you now use Cloudflare to directly access. And you get better performance, you get better responsiveness. We can deliver at a much lower, lower cost than most anyone else.
- [42:12]
B
And those are open source models that,
- [42:15]
A
but even the, even the big, like, you know, OpenAI is, you know, big customer of ours, you know, all their mobile app is built, you know, on us. We have, you know, 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. All of cloud AI sits on top of us.
- [42:38]
B
But if I'm a developer and I'm looking to run Kimi, Mistral, whatever, I can do this totally run on us.
- [42:47]
A
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.
- [42:56]
B
That's what in France, the edge network doesn't land itself to training.
- [43:02]
A
Not, not today. You know, 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, you know, network fabric that's connecting all of those machines. And so where, you know, an AWS or, or you know, even in, you know, SpaceX, they're, they're building giant data centers with lots of machines very close together, hyper networked. We're, we're, we have just as many machines, but they're spread out all around the world. And as a result most training tasks were not the right place to do that. We're always testing and experimenting and you know, I don't know that that will necessarily be, be the case forever. But, but, but what we are really good at that is anything that you need kind of a beast, beefy machine where like your phone or your laptop isn't enough and you want it to be either fast or, or lower cost or, or you have some sort of regulatory, jurisdictional reason why, why you want it to run, you know, in a particular region and not necessarily get set back to, you know, Ashburn, Virginia. And, and I think that's driven, you know, a huge amount of the adoption of, of this, these AI workloads loads across, across our network and that's by far the fastest growing part of our business.
- [44:31]
B
So that's workers. Another product that seems incredibly timely given the current conversation is the gateway. Do you want to talk about that? What that does?
- [44:41]
A
Yeah. So I mean again, this, it's all driven by, by us. And so we needed to be able to use AI models. But we're a security company. We're, you know, we have, you know, various regulatory requirements based on the customers that we have. And so we needed some way to be able to understand like how our team was using these, these models. And so we built something that we, you know, called the AI gateway. And, and it, it allows you to do a couple of things. One is it allows you to audit as if you're the CIO or CTO audit all of the sort 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's that allows you to very quickly surface. Surface things based on, you know, what you might think of as problematic. If you've got a customer support agent and it starts acting like a Nazi, like you want to be able to see that, you know, incredibly quickly. And so we give you that auditing. We also allow you to do basically, you know, prompt injection. The way that, if, if you're, you know, the way that Claude or the way that anthropic sort of put guardrails around, around Fable in order to take what was Mythos and, and turn it into something thought they could release broadly is they put a whole bunch of prompts and say do not do. You know, the following things you, as a business, like if you're, if you're Cloudflare, you know, there are certain things that we don't want AI systems to do and the AI gateway allows you to, to inject that into it. And then the, and then the third thing, which again we built for ourselves was you need to control costs. The, the cost of all these tokens just, you know, it can, can be just overwhelming. And it's really easy, easy for that to lose, for you to lose control of that. Gateway allows you to route things intelligently where you don't necessarily have, I don't know, somebody who wants, you know, 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, 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 we, and, and people are always asking us like, what are you guys doing around AI? And we showed it off and, and people are like, I need that. And so now again, that's turned into, into a, into a product.
- [47:05]
B
So continuing out Tor drawable objects, agents, SDK workflows, browser runs, sandboxes, it's all
- [47:14]
A
just, it's stuff we needed.
- [47:16]
B
Yeah.
- [47:16]
A
And then it turns out other developers needed it as well. And so, you know, if you think about like, how did AWS do develop? It was Amazon's way of building essentially systems where their own team could build things very, very quickly. 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 any AI today. There we are the best place to build any kind of agentic workload. An example of this, if you, you take every knowledge worker on earth and you imagine that they're, 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, it's just too expensive to do that. And, and I think the idea of every knowledge worker having just one agent is insane. You, you're going to have hundreds of different agents that are working on your behalf, in which case we don't, 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, of doing that. And so again what workers did is if, if once upon a time we had, you know, 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, and we built all of workers around a concept which is, which everyone's familiar with because it's the, the tabs in your browser which are isolates and that, that is a, you know, safe environment that is sandboxed from the other tabs that are running. But it doesn't need to happen have you know, a whole new copy of, 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 right, whatever you're asking it to do, it's effectively going to be writing code for you all the time. It, that is turning out to be kind of the perfect environment to be able to, to, to be able to build these things. And, and again, I, I, I wish it was because we were so clever and saw the future, but I think a lot of it is, 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.
- [50:01]
B
That looming CPU shortage crisis. By the way, it seems to be an under, somewhat under discussed topic.
- [50:09]
A
I mean these agents, you need a lot of GPUs, we all know how, but CPU utilization is going through the roof and that's going to be, be in a bunch of different directions. And so we're constantly trying to think about how can we improve the underlying kind of efficiency of the network. So a while back, three or four months now, we rewrote WordPress in Rust in order to, to deliver it. We called it M Dash because we used 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 a thousand times, like people aren't going to be putting WordPress sites up because it's going to cost three or four thousand dollars 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 want it, we need to own it, we open source, we give it, we give it away. But because we believe that our mission is to help build a better Internet. And what 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 waves that they're just significantly more cost effective and efficient to run.
- [52:13]
B
In terms of braking, what does an agentic Internet mean in terms of security?
- [52:20]
A
Yeah, I mean it's, it's that security is going to be, I think for the next two years we're going to see just a series of really scary things happen, happen on line. You know, the, the. 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, any server running anywhere. You know, I think for, for the next, you know, 104 day, 104 weeks, so two years you're going to see a log 4J like vulnerability every single week. Because, and 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. And I think security is going to be, be. It's 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, you know, 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, what's going to happen is software is going to get just massively better as a result. So internally it clouds Cloudflare. You know, we like last year we had an, 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 the, all of those files, every code release. And it's trained on 10 years of incidents. We have big public incidents that, you know, make the news, but there's, there's sort of a background noise of small incidents over time. And like one of those sort of just audible gasp moments that we had was a guy who runs our infrastructure engineering team 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 clip if, and then it goes like this. 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 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 gonna see is that it's gonna seem like software is incredibly scary for the next two years and then it'll kind of just fade away and we're gonna all be releasing software which is so much better than it ever has been before. And so like our uptime and our reliability and our performance has gone up, up, you know, 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, you know, build, build our systems. And I think everyone is, is going to be doing that going forward.
- [56:04]
B
Since we are on the, on that topic, let, let's go into how you guys use AI internally. You have some interesting stats that you published just a few weeks ago in April where you said the company as 93% of R&D employees using AI coding tools, 3,683 internal users, whatever, 241 billion tokens. How did you get there? How did you create that culture for a company that was started in 2009 and two, how do you measure success?
- [56:36]
A
We were selling picks and shovels and sort of the AI gold rush. But we were actually pretty cautious users ourselves. We'd run experiments but we were sort of not, not kind of 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 is an incredible engineer. We're not supposed to talk about 10x engineers, but Ken is clearly a 10x engineer. He's just a genius. And he last in the spring of 2025. 5. He's like this AI stuff is, is BS. I'm going to go play with all of these tools and show you just how much of a mess they, they are and why, why, why we shouldn't be relying on them. And, and he did, he went away super senior guy on our team, went away for a month, played with him, came back and he was like oh my God, I am now a hundred times more productive than I was before. Which is, which if that's right and he's a 10x engineer means, means that he alone was more productive than our entire team was back in like 2019. Right. And so, and, and, and, and like I kind of believe that's true. Like it's, it was, 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 the release of Claude Opus and, and, and a bunch of things but it felt like it, it tipped where we all of a sudden, on our engineering side, we're getting, you know, 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, you know, for us, you know, we've, there, there, there have been. The people that I continue to worry about are the ones that have been very hesitant to embrace these tools schools. 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 unfair. Unfair. And, and yet again, you kind of have to adjust to what's out there. But I, I really do worry that we're going to have this sort of lost generation of, of sort of either, you know, young millennials or, or older Gen Z folks that just, they, they're, they were sort of, they're going to have incentives to, to say we shouldn't use these tools because again, and if they do, they don't feel like they have any advantage of 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 piece. Part of, of Cloudflare we've got, you know, legal, finance, you know, marketing, sales, all of these other organizations that are part of the team that, that we're like, how can we make them significantly more productive as well? And, and, and so we came up with this idea that, you know, could we create sort of a, a 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, it's 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 like 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. So for us it was Auto Cloudflare and, 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 kind of the, the, 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 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 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, in, in things that we had put up before. Nothing, nothing significant but, you know, little, 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 you know, our shareholders doing all the things that are actually the really productive parts of 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'm on the organizing part of the group that's organizing the 2034 Olympics in Utah. And I was talking to the Academy Lario, who's the CT of the ioc, and he's like, hey, listen, we, we need this. We need a system to do this. And I was like, well, let me show you what we're doing at Cleflare. And so I showed it to him. We never thought this was gonna be a product. And he's like, I need you in Lucen, you know, next week to and to. And bring your team because we need to implement this. So we all flew up and now they're actually using this to, you know, to help break better organized Olympic Games. And I think that if you get. And 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 sort of in the sort of the. I guess 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 we're like, 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, you know, 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 not as many salespeople as I, 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 it 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 sort of these deep dive audits to make sure that we're, you know, not screwing up procurement or we're doing revenue recognition correctly or you know, and they're, 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, any issues that are there. And I think that that's like, 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, and it's, and it's just incredible to see, to see how much more productive the teams are.
- [66:31]
B
And do you think that there is a painful transition period from the current world to the next world? So do you think everybody's going to have to go through organizations, recalibrate.
- [66:43]
A
We laid off more than 20% of our, of our team. And not because the business was struggling, but, 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 talk to peers at other companies, they're all seeing the same thing 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 six to 12 months, months almost every company is going to go through some exercise like this where they're going to cut a bunch of their, their team. And I think a lot of people are wait, a lot of, 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, 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 six 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 invest, which nobody does, but we did. And we're working incredibly hard to place these people because they're incredible people. And somebody who is a, a middle manager at cloudflare can be a senior manager at a startup and do an extraordinary job. But, but once you're, as an organization, you've realized you're going to do it like the, the kindest thing that you can do for your team is to do it as soon as possible. Because what 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, and the market gets flooded with a bunch of people who are all of a sudden looking, looking for jobs. And so that was the cattle that was sort of the, the rat us. And, and again, I, there were, there are people who are really close friends of mine who, who we let go because the roles that they had just didn't make sense anymore. And, and, and, and we, we wanted to do it in a significant enough way that we would never have to do it again. And so we're, I feel comfortable saying that for the foreseeable future we're not gonna have to do anything like that again because we've reorganized the organization. And, and I think that, you know, one of the metrics that, that we look at is, is span of control. And so how many direct reports. What's the average number of direct reports in an, in an organization? And you. The, the historic number that like the Harvard Business School did a study and they, they came up that the, the right number for that is about six. So for every manager they have six direct reports. And that was exactly what we, we were at. It's so clear that with these new tools, a manager can manage a lot more people. You know, Meta is trying to get to 50 to 1. I think that's, that seems like too many to me. But, But I think 12 to 1 is right. And, and the benefit of expanding the number of the average number of direct reports is it inherently flattens the organization. The, the fewer number of direct reports on average a manager has inherently, the organization is going to be much more hierarchical. The more more direct reports they have, it's going to be flatter. And I think one of the things that, you know, we're seeing is that the flatter the organization is, the more, 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, is a, is a bad person or a bad individual. In fact they're, they're great. But there are roles that you're just not going to need anymore. And, and, and some people you're going to be able to sort of rehome and reskill inside your organization. But like if you, if you're going to go from, you know, 6 to 1 to 12 to 1, that, that means a whole bunch of middle managers are going to, are going to go away.
- [71:09]
B
So what do you do if you're one of those people? If you're a middle manager and I think earlier you mentioned all Gen Z or young Millennial and you find yourself in that situation like mid career, do you just go down a complete rabbit hole of like just making yourself as AI peeled as possible?
- [71:27]
A
I think, I think yes. And, and, and recognize that it's natural for that to feel scary and that the, and that your instinct is going to be to fight against it, but that the more that you can embrace these tools, the better. I've, I've never seen, 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, you know, 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. So we, we, we hired 1,111. That number is meaningful to us. But interns this summer, you know, and, and I mean it's like they are the most extraordinary humans because everybody stopped hiring interns, which I think is just total mistake sake. And so we got sort of the pick of the litter. And, and, and they're, and they're all totally AI native. And what we're trying to do is get both of those groups to get the, the folks that have been more hesitant because the fact is 92% of organization engineering organizations using AI tools like that, that should be 100% for sure. And, and it's, but you've got to get people who especially are sort of mid career career to be brave enough to learn these new, these new tricks. And, and I think that that's, that's, that's really important. And, and that, and again, you can't have one person who is ten or a hundred times as productive in the same role as somebody else making the same amount of money as somebody else who's, who's sort of doing it the old way. Like one of those two is going to lead leave. And the worst case is if the person who's 100 times as productive leaves. And so we're just, we are continuously trying to get every lift everyone up. And, and again, part of why we did the layoff was in order to be able to, you know, really, really free up the resources and, and catalyze the entire organization to be able to do this. But, and it's not just your developers has to be finance, legal, marketing, everything has got to be embracing these new tools.
- [73:57]
B
So almost a year ago now you declared, I think that was content Independence Day, July 1st. July 1st.
- [74:04]
A
Coming up on the second, second anniversary or I guess first anniversary.
- [74:07]
B
Yes. What happened in the last year? Or how is that whole debate evolving?
- [74:11]
A
Yeah, so, and what was it in the first place? Yeah, so, so, so again I think that it is, you've just seen an enormous rise in the amount of sort of automated traffic that's running across the Internet. I think in five years that bots and agents will outnumber humans online a thousand to one. At the same time, the interface through which we access the Internet is changing and we've gone through other sort of platform changes before. We went from browsing the Internet on a browser, on your desktop or laptop, to social media, social 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 a thousand times as much traffic, which means, 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 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? 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, is, is going to look like. And you know, we, we have great relations with all the different AI labs and, and, and they get it and they actually, you know, they, they, they 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. 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 you know that, that's that. So step one was we said we, we need to create controls that allow the people who have content online to be able to say who can access it and who, who can't. And, and again it's, everyone's going to make different decisions. In our case, we want all the bots to be consuming our, our information. We want that to be out there. And that's probably half of our customers are in that camp where they, as easy as possible. And so we provide the tools to as cost effectively as efficiently as possible get information and take, take HTML which has all this croft around it converted into markdown, which is a much more streamlined system. And then as a result like you can get more information in these AI systems without blowing up their context windows and, and all kinds of things. It makes sense in that case. On the other hand, if you're an ad supported business, like 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 you're, the ad systems don't work. So we said like 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, Conde Nast, Meredith, you know they, they are, they 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 that's sort of the first step. But we've got to go beyond that. If you're a small blog or you know, influencer, a content creator like you don't have the ability to go strike the same deal that a Conde 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 our network, we estimate that somewhere between 1 and 10% of those would be sort of monetizable through some micro payment transaction. And, 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 thousand transactions per second. So we need to be, you know, two orders of magnitude bigger than Visa, but, but at much, much smaller volumes. And so we're working on that. And, and we think that, you know, in partnership with, with folks like Coinbase and Stripe, you know, and, and, and protocols like X402 which is, you know, it's, it's interesting with the original Internet had something, a response code, the 402. We all know 4, 404, which is not found in 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, you know, 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, you know, what is that business model that's going to power the next 28 years of the Internet. But something has to pay, pay content creators because they deserve to eat. Something has to pay for the infrastructure that all of these bots are, are, are, are, are taxing effectively. And, and, and I, and, and I think we're working a lot around figuring out exactly what that looks like.
- [80:20]
B
Correct. It's been an absolutely fascinating conversation. The, the overarching thought as I was listening to you, is to which ext layer is becoming even more relevant today than it's been for the last 17 years, which you Build the network. And now the Internet is changing and you are absolutely at this sort of central point for it.
- [80:44]
A
Yeah.
- [80:45]
B
Is that how you guys think about it? Like you have another 17 years.
- [80:50]
A
People are like, why, you know, why do you keep doing this? Because there are days that aren't fun. I mean laying off a bunch of people, I mean that was, that wasn't fun. And it's, and you know, I've made plenty of money, so it's not about any of that. What it is about is really our mission. And we, 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 Internet. And like I, I can't imagine anything that I could possibly be doing that is more rewarding than, than figuring out how do we create some sort of sustainable business for the future. And I think there's, there's a lot that's to, to be incredibly optimistic about. The, the business model of the Internet for the last 28 years wasn't the most healthy. Traffic has always been a terrible proxy for Val. 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, you know, if we think about what can replace it going forward, it can be something which is, which is, which is much healthier and much, much better. I was, I, I flipped a Stockholm to, to meet with Daniel Ack who started Spotify. And, and because I mean like nobody has compensated creators at scale like Spotify. It's just, it's just, it's remarkable and we can quibble about are the right people getting the money or not. But, but there' 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 22 years ago the music industry was dying because on Napster and everything, it was just normalizing. Everyone's 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, there's something that's there. And then, I mean Spotify last year sent something like $12 billion out to music creators. That's more than the. That's more than the entire music industry's market cap was 22 years ago, which is. Which is extraordinary. And. And so Daniel was telling the story. He said, one of the things that they. That they do is if you search on Spotify for, like, Taylor Swift Shake it Off, like, 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 a disco beat about how much fun it is to dance with my a 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 euros 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 the cheese. 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. They're 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 that 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. 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, you know, I don't know, cancer research and, you know, foreign policy news. I mean, you can create a bunch of these things and they can actually measure and say, you know, this particular year, the best podcast was, you know, the first Mark podcast that was, that was out there or whatever it is. And we should be rewarding and celebrating, celebrating both, 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, you know, interesting information. My wife and I bought the local newspaper in our. 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, you know, 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 be amazing if they were covering, like, in the Marriott Market Marquee Hotel in, in times square, room 1313 is better than room 1314. Or if, you know, if you're, if you want to sleep in late, room, you know, 1314 faces north, and so it's less likely to get sun in the morning. Like, those are the sorts of, here's the best bodega in New York, the very interesting quirky local stories. I think that that is both a medium, a 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.
- [87:40]
B
Fascinating. Well, Matthew, thank you so much. This was an absolutely wonderful conversation. Really appreciate it.
- [87:46]
A
Thank you for having me.
- [87:48]
B
Hi, it's Matt Turk again. Thanks for listening to this episode of the MAD podcast. If you enjoyed it, we'd be very grateful. If you would consider subscribing if you haven't already, or leaving a positive review or comment on whichever platform you're watching this or listening to this episode from. This really helps us build a podcast and get great guests. Thanks and see you at the next episode.