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Speaker 2Hello and welcome to Decoder. I'm Nilay Patel, Editor-in-Chief of The Verge, and Decoder is my show about big ideas and other problems. This episode is part of a two-part series on the future of business. Today, I'm talking with Matt. I'm talking with Matthew Prince, the CEO of Cloudflare. Cloudflare is one of the most important infrastructure companies in the world. It protects all kinds of apps and services from bad actors on the internet, basically making it possible to operate a business online. Matthew last joined us on the show about two and a half years ago, at what we thought then was a wild pivot point for the internet. But now, because of AI, it turns out things are even wilder, and Matthew and Cloudflare are right at the center of it. Cloudflare found in June that bots now make up more than half of internet traffic, a number that just keeps going up. It's more and more common. More and more AI companies scrape more and more of the web, and now, as more and more people send AI agents out to do things for them on the web. Cloudflare sits between websites and all those AI tools, and allows website owners some level of control. They can block all those tools, allow them, or as you'll hear Matthew describe, potentially only allow those that pay money for access. So Matthew and I talked about how to control all those bots, what kind of mess they're making of the web, and what kinds of information might be more valuable in the future as some of these payment schemes come into focus. You'll hear me ask pretty directly if some of the outcomes he's describing are actually good. Matthew is a thoughtful guy, and his answer is something I'm still thinking about well after we had this conversation. Matthew is also at the center of another important AI debate. Earlier this year, Cloudflare laid off more than 1,000 people, 20% of the company. And Matthew wrote an op-ed about that decision, which ran in the Wall Street Journal under the headline, "How I Choose Which Cloudflare Employees to Replace with AI." That is pure decoder bait. AI, big controversial decision. And org charts, all in one. So obviously, we talked about that decision in detail, and what it might mean for how companies are structured in the future. One last thing before we get started. You can subscribe to Decoder on YouTube, where we put out new episodes every Monday and Thursday. Okay, Matthew Prince, CEO of Cloudflare. Here we go. Matthew Prince, you're the co-founder and CEO of Cloudflare. Welcome back to Decoder. Thanks for having me. All right. I'm really excited to talk to you again. It's been about two years since you were on the show. I was just looking back over that episode, and I said something to you like, "It's a momentous time for the internet." And I was not even close. It's now an even more momentous time for the internet. You are at the forefront of rebooting how companies work with AI. That is the most decoder bait of all time. I want to talk about bots, and the internet, and publishers, and Google, and all the things that you are in the middle of. But let's start at the very beginning. Cloudflare is a complicated. Important company. The last time we were in the show, you summed it up. You said, "Cloudflare is a service that makes the internet faster and protects it from bad guys." Is that still how you would describe what Cloudflare does?
Speaker 3That's usually when I'm trying to answer a question at a cocktail party and I don't want to talk to the person anymore. I say that. What I would say if I actually was sort of interested in talking to the person more is probably that Cloudflare is trying to rebuild the internet the way it should have been built from the beginning if we knew how important it was going to be. And so we run a giant network. We're in over 350 cities worldwide. Literally thousands of data centers. In all those places we have equipment running. And then we do a handful of things. We stop if you're trying to put an application or content online. We make sure that it's safe. If you're a person who is an employee who's online, we make sure that wherever you go online is safe. We help give people the ability to write applications that can scale to an entire internet audience and run on the infrastructure that we have. That's the fastest growing part of our business. And I think the thing that we've recently started to think about is. The business model of the internet is changing dramatically. And we're sort of trying to help work on shaping what that future business model of the internet looks like and how can we make it as healthy as possible.
Speaker 2Can I connect the dots between the business model of the internet, how the internet should have worked, and Cloudflare trying to build the internet as it should have been? That is different than Cloudflare protects from bad guys. I will note that's what you said to me last time, which now makes me feel like you don't want to talk to me at the cocktail party, but that's fine. That's a shift. That's just a notable shift, right? The business model of the internet has changed. It has dramatically changed because of AI, because of bot traffic, because of AI scrapers, the whole thing. Describe what you think the business model of the internet is right now and what it should be.
Speaker 3So for the last at least 30 years, the business model of the internet has been advertising. It's not the entire business model of the internet, but it's really the thing that has driven all of the growth of the web, all of the growth of what has built what we all enjoy today. And it really is a miracle. And the company that is responsible for that. More than any other is Google, who for the last 28 years has really defined that. And we all think of it for the search business that they have. But they really built out all of the ecosystem around advertising online. You know, they bought DoubleClick. They built things like Google Analytics that lets you actually see who is coming to your property. And they really are the hero of sort of what I call like the first generation of the internet and the first generation of the web. What's changing, though, very quickly is who is actually using the web or what is using the web. Last November, I was at the Web Summit, the big European tech event, and I was asked, you know, when do you think that non-human traffic agents and all of those things are going to pass human traffic online? And we have a lot of data because we see a huge percentage of the internet. So we pulled all of that data and looked at it and said that, you know, it would be the second half of 2027, automated traffic will become larger than human traffic, which was kind of felt like a big deal that we could see that first time in the internet. It's history. I was asked again at South by Southwest in March of this year, 2026, and we pulled the data again and it had moved up where it was going to then be the first half of 2027. We're like, wow, this is growing. You know, I mean, this AI thing is is a big deal and people are using it like crazy. It's driving a huge amount of traffic. And so I was stunned when just a few months later in May, a team came to me and said, you won't believe it, but automated traffic is now past human traffic online. And that's just expanding like crazy. And if you if you extrapolate that out with the giant caveat, that I've run wrong so far in every prediction that I've made on this. But five years from now, we think that automated traffic will be a thousand times human traffic online, not because human traffic is going to decline. We think it'll stay kind of around the same, but because we're just seeing such an explosion in all of this, the rest of the traffic. And the challenge of that is if you have, first of all, a thousand times more traffic, someone's got to pay for the infrastructure to to to power that like that. That's going to require bandwidth that's going to require servers that's going to require a lot of things in order to make that in order to make that happen. And the traditional model of how to pay for that, which was advertising, doesn't work for bots. Bots don't click on ads. They don't respond to pretty swirls of paint and what we traditionally think of as a brand. And so we've got to come up with something else that that's going to power that that just incredible, insatiable demand that's going to be put on the Internet going forward. And and that's what I'm spending a lot of my time trying to think about what that what that's going
Speaker 2to look like when you describe that as a business. Yeah, I mean, I think there's I mean, there's there's certainly a lot of revenue. Well, there's maybe for the Cloud Flares and the Googles of the world, but for the sort of the anthropics of the world, $10 billion of revenue in a single month.
Speaker 3So like there is enormous demand for these AI services.
Speaker 2And if you're an AI company, what you really need are three things.
Speaker 3You need great technology, you need great software, you need great technology, you need great technology to be able to do all of the things that you need to be able to do all of the things that you need to be able to do all of the things that you need to be able to do all of the talent and researchers. And right now that's scarce. And so right now we have just a scarcity of people who really understand how to build these systems. But that's going to change. Every single university in the world is standing back up their AI department. We're training people like crazy. You know, labor markets are pretty efficient. So we're going to have more and more people coming into the space. The second thing that you need is you need chips. You need the ability to actually the silicon to run these things. And today, you know, NVIDIA is the best in the world at that. But you've got a whole bunch of others, whether that's, you know, AMD or Qualcomm or all the hyperscalers that are building their own chips in order to power these things. And so while we have a massive shortage in the availability of silicon and the ability to actually power it up and turn it on, but that's going to shift and change as well. And so the third thing that you've always needed, you actually need the data to feed into all of these different models. And that's been the one thing that's, I think, going to go the other direction, which is that historically we've just made the Internet completely open and given bots access to all of the stuff that's being created, your episodes, everything else that's out there. I think that's starting to change. And what we're seeing is a shift where more and more of the people who are creating content, really creating information, are saying, you know, maybe we'll give that away for free to humans. But if a bot is coming for it, then bots have to pay for it because they don't have that traditional give to get. We can't put an ad in front of them and have that be something that allows me to help pay for the content creation that's there. And so what we're seeing is actually going back to some of the original protocols of the Internet, the 403 protocol, which was written in, you know, the very first version of Netscape. It was actually payment required and you actually have to, like, you know, pay for the content that you're creating. you're receiving. And that's something, excuse me, I've said 403, it's actually 402. That's something that, again, we're working with other leading companies like Coinbase and Stripe in order to say, how do we make sure that we can allow people who are creating content, people who are doing things online, anyone who's putting a website up to say that in exchange for that thousands and thousands and thousands of times more traffic that's going to come to you, you're not going to maybe get kind of the advertising revenue that comes from it, but maybe you can get a fraction of a penny every time somebody actually accesses that information. And where does that fraction of a penny come from? It comes from the fee that people are going to be paying for their AI agents and other systems that are out there. Really similar to how like a Spotify or an Apple Music works today.
Speaker 2I like that we're less than 10 minutes in, and we're already at the 1996 dream of micropayments on the web. We're going to stick with that for one more turn here. When I said business model, what I was really pushing at was the idea of incentives, right? So maybe there is some business model for information. You're going to publish. Some new information and bots will come and find it. And yep, the 402 protocol will come back to life and we're going to do, I don't know, crypto micropayments using Stripe Power by Cloudflare. That's a version of the future that many people have talked about for a long time. The incentives to stand all that up on the web is the thing that I'm worried about when I say there's a business model and customers and revenue. If I stand up a website and I think most of my customers are going to be bots and not people, I might not do that. I might just start a TikTok channel. Instead, and then monetize my TikTok audience in whatever way I might want to monetize a TikTok audience. That seems like a really big inflection point right now at this second. You mentioned Google and, you know, I've asked you about this many times. The incentives to put new information on the web just seem to be in permanent decline. It just doesn't seem like a good idea anymore. Where, where on the flip side, the web is an application program. Is it, it's like, absolute apex. Like every new app that comes out is a web app, or if it's a desktop app, it's just Electron, right? Like there's something happening with the web as an application platform that is incredible. And something happening to the web is an information platform that is devastating. And you're trying to connect those dots, right? You're trying to say we can change the incentives over here. What's a version of the future, maybe it's microtransactions, maybe it's not, where the incentives to make the web an information platform are as good as YouTube?
Speaker 3Yeah. You've sort of illustrated what is, what is kind of a tough to reconcile dichotomy that's happening right now. So if you look at things like the publicly accessible data on Wikipedia contributions, it's down significantly because people are like, what's the incentive to like put information on Wikipedia? Something that again, you know, people are doing for, for, for a lot of different reasons. And I think the problem there is like back, back in the day, if you were contributing things to Wikipedia, you knew people were at least reading Wikipedia. Now the, the interface through which people consume that information, isn't going to Wikipedia itself. It's just reading the answer through whatever answer engine you're using, whether that's open AI chat, GPT, or anthropic clod, or, you know, grok on X or whatever it is. And that means that the people who are, you know, the editors of Wikipedia are saying, maybe it doesn't make as much sense for me to do that. The flip side of that is, you know, the web as a whole actually was, had been declining since about 2012. So the, the web grew like crazy in the, in the late nineties and through the, through the two thousands. And then starting around 2012, you really saw it plateauing and actually decreasing up until about 2025, where something flipped and starting in about October of 2025, driven a lot because of the various vibe coding platforms, the ability that we made it easy for anyone to create a website that more and more people were creating those applications. And as you said, even your desktop application, your mobile application, increasingly, it's just a, it's just a wrapper around what is fundamentally a web application and the growth of the web itself. with really high quality stuff and a lot more people contributing to it, is faster today than it has been at any time since the early 2000s. And so that's the tension between those various things. I think what's unique about Cloudflare is that because we sit in front of so much of the web, more than 20% of the web, we have the ability to overcome some of the incentives problems that you have. And so we can very quickly turn something on and say, okay, for a fraction of a penny, you have to pay a fraction of a penny in order to get access to this information. And that can kickstart what I think is the beginning of what we need. And again, the problem is if you don't have something like that, we face a massive tragedy of commons problems. So let's say today I ask, I don't know, whatever my favorite AI agent is, where should I go to lunch? I mean, if I was doing research, I might go look at a couple of different menus as an individual. My AI agent today goes and scans every single menu in the local area. In order to figure out what's going on. And again, only one of those places is going to actually get my lunch dollars. And so if that just expands infinitely, if there's no cost to doing that, like at some point, my agent is just going to look at literally every piece of resource, every resource that's available everywhere on the internet, and then come back and say, you know, you should go to Wendy's. That's an enormous waste. And so we've got to have something which is actually saying that, you know, there's a cost every time you load a webpage, there's a, there's, there's, there's, there's bandwidth, there's servers, there's things that are behind the scenes. And so we've got to have something that's going to be able to do that. And someone has to pay for that. And if it's not going to be advertising and it's not going to be directly commerce, then, then there has to be something that actually puts some constraints there. And I think where we're in a good place to say is like, yeah, it can be a tiny amount of money, a thousandth of a penny or something like that. And, but that's enough that we can actually start to say, okay, that, that will help pay for the infrastructure. And then if you have incredibly valuable content, you know, if you're a, if you're a news publisher or you're, you're an academic, then maybe, maybe there's a premium on top of that, that you charge and say, Hey, I'm not going to get paid for that. I'm not going to get paid for that. I'm not going to get paid I'm not going to give you this content unless you pay even more for it. But I believe that it's valuable and we can create a market for it in order for that to happen. I think, again, you've got to have a player like us that's in the market that can kickstart that. But I think once you kickstart it, we've seen in, from the, from the side of the buyers, the big AI companies that they're all willing to do this. We've seen that from the side of the sellers, the big content creators that they're all really excited about this. And so what's really been lacking is actually the technology that, that, that links those things together. And again, that's what we're spending a
Speaker 2It feels like the, the theoretical underpinning of this conversation is the very notion of scarcity itself. I'm an old copyright lawyer in copyright law for years and years and years had just a built-in mechanism to be important, which was that a one copy of a CD was one copy of a CD. And if you wanted another one, it was pretty hard to make another copy of a CD. Even when it got easy, you still needed another physical CDR and that imposed some costs on how many copies you could make. And then it was hard to distribute them. And all of that went away with the internet, right? Everything, digital files, and the, the, the burden of making another copy fell to zero. And I think a bunch of consumers expected everything would be free. There's that famous quote, information wants to be free. There's a second half of that quote, everyone forgets, which is that information also wants to be expensive because it's hard to generate. And the internet just turned that upside down, right? The, the gating mechanism of physical media, which provided some scarcity and thus some economic value that you could measure, went away and we decided information should be zero and maybe supported by advertising. It was actually attention that became valuable because that was scarce in its way. You're talking about imposing scarcity, right? With your technology.
Speaker 3You know, we always talk about markets needing supply and demand. That's not exactly right. What you need is you need, um, demand for sure. And you want infinite demand ideally, or as much demand as you can get. Infinite would probably be bad because you then it would be hard to discover price, but you want, you want demand. Um, and then you want actually some constrained supply. There's no, there's no market for air where either of us are sitting right now because there's plenty of air. But if we go scuba diving, then all of a sudden there's a market for air because air is constrained underwater. And so you have to buy it in order to, in order to be able to do it. Music, I think is the example that, that I look to, um, when I think about what, what could this look like in the future? Um, you know, I flew up to Stockholm to meet with Daniel Lack who started Spotify and, and it was just a fascinating conversation because if you think about the history of music, you know, sure. Once upon a time, like the majority of music sales was from, or, or, or albums or whatever, whatever it was. Um, and then along came the internet and along with it, Napster and Rockstar and Kazaa and all of the things that, that essentially, you know, commodified music and made it available for free for everyone. And even if you're an incredibly law-abiding human, um, the majority of people were actually just downloading music because they wanted access to music. And if you go back 23 years ago, um, the music industry as in total was about nine valued about nine billion, eight billion dollars, um, which is a lot of money, but it's not a lot of money for the entire music industry. Like that's the Beatles and the Rolling Stones and everything else. But people were like, we can't make any money off of this. And then almost exactly 23 years ago, uh, to right now, Steve Jobs steps on stage and announces iTunes and that it's going to be 99 cents a song, but they're include cover art and they're going to make sure it's high quality and all, all these mostly appeal to this emotion of you should be paying for, for music. Now that's not the business model that, but it was a, it was a flag in the ground that said that this information is actually worth paying for. And it's, and it's really valuable. And, you know, it was the iTunes that then eventually begat, you know, the, the, the Spotify's of the world. And the, and the incredible thing is, you know, just last year, um, Spotify sent something like $12 billion back into the music creator ecosystem. And we can debate whether the right people are getting it and whether, you know, it's, it's, it's fairly allocated.
Speaker 2This is my favorite thing to argue about. Cause I, whatever happens in the music industry happens to everybody else five years later. So I spent a lot of time thinking about it and the, the turn there, which I think is fascinating and is either good or bad, is that the amount paid for music, for the music files themselves, became very small, right? You can get a million streams on Spotify and you're not making any money, but the amount generated by touring and commercial sponsorships and sync licensing to advertising all skyrocketed.
Speaker 3That's just simply not true. Why is private equity buying all of the music catalogs for hundreds of millions of dollars? The answer is because actually making money off the streaming of the music is extremely lucrative. And again, Spotify alone is sending $12 billion back to the music industry, back to the actual rights holders behind these various things. And so you can, there is more, there's way more money coming from Spotify into this than there is from touring or any of the other things that are there. Those are other ways to make money, but actually it's the streaming that is really driving all of the real growth.
Speaker 2Sure. But I just want to draw a distinction here and we can argue, you're not here to argue with me about music. Which is my favorite thing to do. So I apologize for just doing it, but private equity is going to make that money, not the musicians, right? They're paying some of the catalog holders for some of the things, but that money flooding in.
Speaker 3If the musicians, if the Beatles, you know, if the Rolling Stones or whoever used the latest ones to sell their music catalogs had held onto the music catalogs, then the musicians would have made that. They are making the determination that, and by the way, when they sold the rights, they got to get the check. So it's- Did you get the check?
Speaker 2The only thing, the only comparison I'm making here-
Speaker 3You're in a lottery. Is it better for you to take the annuity of payments over the course of the next 50 years or to take the lump sum up front? That's the trade-off that they're making, but there's more money going into music creation at this point in time than there ever has been at human history. And so technology is not inherently a destroyer of value of information. In this case, it has been an massive enabler of value in this and allowed people to find audiences and yeah, sell more tickets to their concerts as well. But I think that that's- That's actually the model that we need to think about, which is how do we take what Spotify has done, which is to say we pool together the resources of a bunch of people that are paying for access to the entire catalog of music and then give that back to musicians based on, you know, some sort of algorithm that hopefully rewards where there's actually a real value, which is created. If you had the same thing where a portion of what is being paid for, for the various AI companies, well, you had to pay for the researchers that built the AI systems and you had to pay for the chips, but also to pay for the costs. If you had the same thing where a portion of what is being paid for, for the researchers that built the AI systems and you had to pay for the costs. Not a lot of songs like that that are out there. And so they know that whatever they return is a pretty bad result. But the interesting thing is what happens next, which is they take them those searches for things that they don't have good results to do. And they publish that back to music creators. And I think that there's something that's pretty amazing about that, which is they're saying, here's an emotion that someone is searching for, which we don't have a good answer for, which we're then going to go and publish back to music creators. And there's a guy who, if I remember the story correctly, is in Denmark who makes, and again, this is one of those moments where everyone's going to be like, I'm in the wrong profession, 40 million euros a year writing songs for unfulfilled Spotify queries. And he's not alone. He's the most successful. But there's a whole bunch of people that are making literally millions of dollars or millions of euros a year doing this thing where they're writing songs for what people are searching for that aren't out there. Now, extrapolate that to the next level, which is to. To say, for the first time in human history, we've built a mathematical model of human knowledge. That's what the LLMs are. And we know where they know things, but we also know where they're missing things. I picture it like a giant block of Swiss cheese. And there's a lot of cheese, but there's a lot of holes in the cheese. And the really interesting thing is when you talk to the leaders of the big AI companies and you say, what do you want to pay for? They don't want yet another story about what's happening at 1500 Pennsylvania Avenue, which is what the current media environment is feeding us like crazy. What they want. What they want is to fill in the holes in the cheese. They want new knowledge that no one ever knew about before. And so the example that this is actually is actually working is, you know, my wife and I own a small local newspaper in Park City, Utah, which is our hometown. I think we will make more money off AI licensing deals this year than we do off digital advertising. And the reason why is because local media is exactly the sort of thing that is much more valuable in kind of the media world that we're going into. But. It was completely decimated in the media world that we are coming out of where what mattered was volume and scale and dividing things. Whereas local media is all about, let's tell you about the cool new restaurant that just opened down the street. If you're an AI company and you want to be able to be the best travel planner that's out there, you want to have, you know, artificial general intelligence. Like you need to know what the hot new restaurant is in Park City, Utah. And if you don't have access to the park record, our newspaper, you don't know that. And so what I think is interesting is. We're not going to protect all media in the same way that, you know, the move to Spotify. There are a whole bunch of losers in the in the musician space, but there are going to be new winners like that person in Denmark who's creating things off of unfulfilled Spotify queries. And I tend to think that the winners in what this new space might be might actually be the kind of things that people really want to come back to media. More local news, more unique things, more Reddits of the world. Right. More of what the Internet used to be. You know, when I when I was first on. In the 90s, I think that that's actually what most Internet users are craving. And I think that if we get the incentives right, we actually have a way of maybe incentivizing more of that unique original content as opposed to what we have today, which is a media ecosystem that is largely just rage baiting people into clicking on things so that they can serve them an ad.
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Speaker 2One of the things you would need to build in order to make that work is a way to stop the AI crawlers, to stop the model companies from showing up. Just today, there was yet another launch. There was a big lawsuit, right? The music companies are going to sue Anthropic. The White House came out in support of OpenAI and its case against the New York Times today, saying that training should be fair use. I think I need to disclose that in some series of corporate mergers, the Verge's parent company is now suing Google in some way. I have literally nothing to do with it. It's just all that. It's all the swirl, right? And that is a legal swirl. Yes. We're going to use the law to say this is illegal and we'll punish you if you do the bad thing. That's just up for grabs. Those are 50-50. Maybe existential. I
Speaker 3mean, maybe not. I mean, I think that the law right now, at least in the U.S., and the U.S. is different than everywhere else, and so you've got this patchwork around it. But, like, the best case on this is probably the Anthropic case where the judge basically said that training is fair use against all the books. And, by the way, you shouldn't have stolen the books. That was bad. But if you hadn't stolen the books, if you actually bought the books, then it would be okay. And that was a valuable enough result for Anthropic that they settled the rest of the case for $2. billion, which is, you know, a lot of money, even for Anthropic. And so I—
Speaker 2Right. So when you're building technology, you're keeping that in the back of your mind, right? The market is coming to some sort of understanding of what's valuable and what's not, and you need to stop them from showing up.
Speaker 3Different regulations are going to be passed in different places around the world. So, like, I—and, again, as an also recovering intellectual property attorney, like, I very quickly go to, like, oh, let's just use intellectual property. But, like, that's such a kludge. Versus the much easier thing, which is let's just use technology. And, you know, identifying—I remember sitting with a bunch of media execs, and they're like, oh, how are we going to stop these nerds in Palo Alto from scraping our stuff? And I was like, you know, I go to war every day. with like north korean and iranian hackers and the chinese like they're really good at it um and they hide whereas like the nerds in palo alto have a delaware based c corporation like it's pretty easy to identify them versus versus the others and it's really difficult for them at scale to hide from from us and in fact what we're seeing is actually much more of them being willing to say listen we will specifically identify when we are coming to a site that it is us that you can rely on us and we'll tell you exactly what we're doing so that you can have the right to control how that information is is being being taken i think that that's a that was an interesting question like two years ago but you know even the googles of the world um who who've who've been at times challenging uh through this because google you know they they're sort of like a marvel film like the hero of yesterday becomes the villain of tomorrow like the challenge has been that they're like we struck all these deals to get access to all the internet and now we can use it for whatever we want and we kind of were like in the past you were sending people traffic now you're training on things and sending them no traffic that's a different give to get and what i'm you know been really actually impressed with the google team is that they are much more willing to engage here they understand the value of the ecosystem there are people at google who really do believe in making sure that there is a healthy sustainable ecosystem going forward and i think already some of the things that they've committed to around transparency of their crawler and some of the things that i expect that they will do over the next little bit i think that that that that's actually that's a good sign and it's going to make it so that you know if if if even google is doing it and is willing to say i'll announce what i'm doing and in many cases i'll even be willing to pay for content like i think that's actually just makes it even easier to convince all of the other ai companies to do the same do you think
Speaker 2you need to turn the screws all the way and actually block the google crawlers to get them to pay for content i think that's
Speaker 3okay as of september 15th we're going to set the defaults across all of our free customers for it to be that google is going to be blocked uh it for ai training but if they won't differentiate between ai training and search engine training we're just going to block them across the board even if you're a site owner you're like i don't want that to be for me we'll make it easy for you to turn it off it's just about what we set the defaults to um but but i i'm i'm really encouraged that google is that the sort of good forces at google are are realizing that this has to be a healthy ecosystem and that they have to play by somewhat the same rules for this new market which is ai that everyone else is playing for and that they can't leverage the monopoly that they had in search yesterday to create a monopoly in ai tomorrow i've
Speaker 2talked to asunder about this many times i don't think he loves the fact that i am the person who keeps calling it google zero but so be it sooner is very thoughtful he is he's very kind every time i talk to him i get the sense that what he wants to say is well you didn't do anything about it right all of a sudden all you publishers are complaining you got super addicted to my fire hose of traffic and you have no leverage you you built no audience of your own you didn't do anything look at all of these other platforms that have to compete with tiktok showed up and i youtube had to compete with them chad gbd showed up and the search team had to compete with them and you're you did nothing this feels like this something right we're gonna block the google search traffic we're gonna block the crawler i think the ceo of people is talking about literally blocking google steve at reddit is
Speaker 3really becoming you know more aggressive and google doesn't work if it can't search these things and it's actually more existential for them the very nature of how google search ranking works is it builds a tree right that's what page rank was it sort of says okay here's here's a super reputable thing and then let's see how it's connected to everything else that's online the problem is if you know with cloudflare again 20 plus of the internet if that just disappears that's in a giant hole in the middle of the tree and so it doesn't just break it for this it breaks it for everything and i think that that's the that's that's what you know we sort of realized that on behalf of and in conjunction with a lot of our customers we could say listen this isn't fair anymore you're not you're creating costs you are taking content you are getting value from that content either in terms of the subscriptions that you're selling to your ai tools or to the ads that you're running against that and you're and that's just not a fair give to get anymore and so the deal has to change and so i'm really proud of the fact that you know we've played a role in the development of the cloud and we've played a role in in helping you know the publishing industry go from what was you know two years ago when i had you know dinner with with neil from from people he's like you know he's like woe is me what are we ever going to do and i'm like i think we can fix this and and now like the last time i saw him we gave each other a high five and said i think we're making progress and the deals that large publishers are doing are significantly better and and now i think the question is how do we bring that to the rest of the internet because if we don't we have this massive tragedy of the commons problem where it's just going to be take take take imposed costs and post costs and post costs and and the incentives for actually creating things for contributing to the wikipedia's of the world for putting up a new website for writing about what you know the new local restaurant is for creating local news and local media for being an academic like if if we if there's not some way that you can do those things and still eat like still make enough to eat then people aren't going to do it and that harms us all and again i i i've been very critical of google over the years i will say that they're tuned appears to be changing over the last uh over the last few months and i believe that at their core they really do understand that this is an ecosystem that they play an important role in that ecosystem and that they need to give back to that ecosystem and and and play by rules that allow the ecosystem
Speaker 2to flourish you said google's gonna make some changes soon what changes would those be you know
Speaker 3i think the thing that they've already committed to is just a lot more transparency on what their crawler is doing uh so what we had pushed them to do is split their crawler apart and say you know we we're going to crawl their crawler apart and say you know we're going to crawl their crawler apart we're going to crawl for you know ai separate from crawling for for the web um and i think that they they for a lot of technical reasons pushed back and said you know that actually is incredibly inefficient um you don't want to we did not have to crawl twice that's going to put twice as much load uh on on everything that's out there um what if instead we just said when our crawler comes to a page we'll announce what it's doing and then give you the ability that if you don't like it doing something to say no no that's not allowed but but this is and and and put that that together that they have they have signaled uh that largely in response to um what was a ruling out of the united kingdom that they were going to put those those uh procedures in place to allow publishers to make that choice and that they wouldn't just do it in the united kingdom but they'd actually do it on a on a broader basis and i think we come out of this on the other side with a stronger web and frankly with even a better google which would be which
Speaker 2i could argue with you about the music industry all day and all night i think you know that but it is true that changing access and copyright law and all that stuff around music industry changed the business right the incentives to put on shows and do residencies and all that changed because of the distribution changing that i think we can we can generally grant you're describing an information market where the incentives will shift again right where it might be more economically lucrative to make information for the bots than for people and that might shape the very nature of the information you run a local paper maybe your people are publishing restaurant reviews that are best ingested by an lm and spit out
Speaker 3yeah or or instead of reviewing a hotel review every hotel room you know for every word that appears in a story in the new york times that reporter has written down probably 100 words somewhere else that's all that other metadata which traditionally has been constrained by you know how many column inches you had in in the in the physical paper or how much attention a human would actually spend on that imagine if you could say to the lms like hey listen we're going to sell and again there's there's all kinds of things around protecting sources and you have to there's there's stuff you have to get right but if you get it right there's an enormous rich like source of of a catalog of additional information for every picture you see in a magazine or a newspaper there are probably 50 or 60 that were taken of that same thing and like that's all valuable to these to these ai systems that are that are out there so i think there's a lot of ways that we can imagine how as as there's there's just a bunch of content that's literally being thrown on the
Speaker 2actually incredibly valuable this is this is my universe i feel confident about this one um you know i went i was in a packaging meeting today for one of our big stories and we had a pretty fulsome debate about the lead image and a story we're going to run in a few weeks then we disagreed and eventually we picked one or we picked a direction and that was an editorial choice that was designed to elicit some reaction in humans we could publish all the rest of the photos they're all really really good and we decided one would be the winner and the rest wouldn't but if i publish all the photos and i give them to an lm it will change the thing that we made right because its distribution will necessarily change and its intended audience will change like maybe the biggest decoder trope of all is that your distribution inevitably changes the thing you make and at the end of the day maybe my future is just making youtube face slinging ag1 and that is the future of all podcasting it's there's just some force of distribution that changes the thing that you make is the outcome you're describing good where we're just making an infinite flood of information geo optimized for some human to consume digested by a chat bot in the middle
Speaker 3well so so i think that um so first of all is the is the current model good um you know i mean i've talked with lots of lots of people at your parent parent corporation and again i think you guys do a good job but there's i mean there's a lot of um you know media that with today was just how do we create content as inexpensively as possible sure and then a b test headlines in order to either stimulate a dopamine or cortisol a response to that. -
Speaker 2If only the media was that scientific. But a lot of it is.
Speaker 3I mean, I've sat with some of the folks from Huffington Post, some of the folks from BuzzFeed, where they were like, yeah, that's the game. And that's the game that we play. And again, I don't know that that's the game we play everywhere, but you can even see, you can track the New York Times, you can track the Wall Street Journal, you can track the FT, and just watch how much more inflammatory and almost tabloid-ish the headlines have gotten over the last 20 years. And again, I think that those are still, every one of those is an amazing media organization. But in order to win in this space, it's been how do I provoke really a deep.
Speaker 2Well, what you're describing is they're playing to their distribution, which is largely social media, right? It's algorithmic social media algorithms, and that is the distribution, and it's shaping the content. So I'm asking you about the new distribution that you're describing.
Speaker 3But let's just frame that the sentence that I say that gets everyone. Yeah. And I think it's what's divided the world. I think it's what's led to the rise of sort of very destructive populism around the world, much less sort of real intellectual debate. So what could we move to? And again, I think there's a lot that can go wrong here. But what if you talk to Sam at OpenAI or Dario at Anthropic, or you talk to the teams at Google that are building the AI systems at DeepMind and others, what do they really want? They want new, true knowledge. They want the thing that nobody knows about yet. They want the story about the interesting thing that no one else is covering. They want that thing which is actually advancing human knowledge forward. That's what I want to read too, right? I don't actually want to read yet another take of what happened in the Trump White House today. There's plenty of that. And they don't want it either. And the best evidence of this is actually how some of these distribution deals have been done. So the New York Times, amazing media organization, and Reddit. Also an amazing media organization, have about the same amount of tokens in that the New York Times has been publishing for a lot longer. Reddit is a lot higher volume. And so they do deals. Who gets more money for their tokens? The answer is Reddit by at least seven, by some measures, 14, by some other.
Speaker 2Just to be clear for the audience, you're using tokens as a measure of amount of new content.
Speaker 3Of content, yeah. Content that's in there. And again, it's not just new content, but it's the legacy content as well. And so the question is why? And again, this is deeply unfair to the New York Times. But if you don't have the New York Times, then you can just license the Wall Street Journal and ask AI to rewrite it as if it's a New York liberal. And you get the New York Times. Deeply unfair. Except that all of these media publications, the major media publications, have made their business of telling the exact same story to their individual tribes. Whereas Reddit, like Reddit, if you don't have Reddit, there's no substitute for it. Reddit is this unique thing that's out there. And so I think a media of the future. That looks more like truly unique kind of storytelling around, again, local communities, unique stories that no one else has told, real knowledge creation, is what is valuable and is proven valuable by the market that exists today.
Speaker 2But the other side of that market, just to be reductive here just so I understand the model, the market, the buyer in this market is a bunch of model companies.
Speaker 3It's not people. But then ultimately, the customers of those model companies, which is all of us. And if. If you, as a model company, are giving me stuff where I'm not, where it's, where you don't have the latest information, then I, then what's been amazing is it doesn't appear like any of these model companies on their own is going to, like, run away. I mean, people are like, oh, well, what if, you know, OpenAI gets AGI? I'm like, two days later, Anthropic will have AGI. And then, you know, Grok will have it a couple days after that. And Google will have it a couple days after that. And then it won't be, AGI won't be enough. It'll be AGI Plus or AGI Plus Plus or whatever. I mean, it'll be. So what I think is going to be interesting is what is it that's going to turn these things from commodities into actually sticky products that people sell? And I think the answer is going to be who has access to the most true knowledge that gets you the right answers. And so, like, that seems like all of the incentives from the end consumers are to say, I want to get as much back to the creators of real knowledge as I possibly can. I'll tell you, the financial piece, I think we can solve the financial. The piece that I'm actually much more worried about, and again, this comes out of this conference. You should have Daniel Ek on the story because he's fascinating to talk about these things. But he, like, he's like, listen, you've been thinking a lot about how to get content creators paid. He said, if you think about musicians, there are two reasons that people become musicians, to get rich and to get famous. And if you, at the end of the day, like, had to cause musicians to rank which one is more important, fame probably beats rich. And so, I think that's a problem. That's the next problem. I think we'll solve the financial problem. But the next problem is, how do we actually recognize the creators? And so, what I've been pitching to the Big AI Lab is, how do we actually recognize the creators? And so, what I've been pitching to the Big AI Lab is, we should create, I don't know if it's the Nobel Prize or the Academy Awards, but some sort of recognition where we use math to measure who contributed the most to, you know, I don't know, mammalian biological research in some specific field and measure it in the last year and then have a big ceremony and give them an award and celebrate them and talk about how wonderful they were at advancing this. And so, I think figuring out how we still take the people who are actually out there creating the knowledge and say that even though the medium through which they're going to be, that knowledge is going to get disseminated, might be removed from the original research, it might be the AI bot or the chatbot that's out there, we still have to say, but you're doing really important work, and we're going to recognize you for that important work.
Speaker 2And so, I think figuring out how we still take the people who are actually out there creating the knowledge and say that even though the medium through which they're going to be, that knowledge is going to get disseminated, might be the AI bot or the chatbot that's out there, we still have to say, but you're doing really important work, and we're going to recognize you for that important work. And so, I think figuring out how we still take the people who are out there creating the knowledge and say that even though the medium through which they're going to be, that knowledge is going to get disseminated, might be the AI bot or the chatbot that's out there, we still have to say, but you're doing really important work, and we're going to recognize you for that important work. You're able to stop things. In the case of the neo-Nazi websites, you declined to use your power, right?
Speaker 3No, no. I mean we kicked them off our systems.
Speaker 2Yeah, you said you can't have Cloudflare protect you from DDoS attacks and then maybe they're just going to DDoS to new oblivion or whatever.
Speaker 3Yeah, I mean they're all still around. So at some level it shows that it's limited.
Speaker 2But in this case, you're going to use your power. You're going to say we're actually – we will use Cloudflare to stop things from happening and that will create a market.
Speaker 3I guess the question is power. So it takes five minutes to sign up for Cloudflare. We have a free version of the service. It takes 30 seconds to leave. So if we're ever doing something that's not in our customers' interest, we'll lose our customers. And so we are very much at the service of our customers. And I remember the first time that a media company called me and said, we have this new threat. You have to stop it. And I was like, what is the threat? And they're like, it's the AI companies. I mean I rolled my eyes. I was like, that's the dumbest thing I've ever heard. Why are all media companies such Luddites? But then we pulled the data and we saw that really, again, that there was an existential threat to how the internet was working. And I think we became convinced. I certainly became convinced that this was something that was worth us spending our time and our resources on fighting it. And so, again, I think that we have a really privileged position because we have provided so much value to so many companies that are out there that they trust us. But if we ever screw that up, they'll leave us in a second. So is that power or is that just being a good steward to the internet?
Speaker 2It's 2026. The valence of speech on the internet has changed. If you had to make the Kiwi Farms Daily Stormer decisions again today, would you make them the same way?
Speaker 3I think each of those things is sort of a moment in time. And there were – I think there are puts and takes under all those things. I think that the – at some level – at the time, when we made the decision around the Daily Stormer, no one knew what Cloudflare was. And we were seeing a bunch of regulation that was happening online that really could have been a real threat to the underlying way the internet worked, regulating kind of key protocols like DNS and TLS. And we were nervous about that. And so the question was, how did you make that point? And so one of the real rationales of kicking Daily Stormer off was – and then writing about it, talking about it, going on the news about it, writing another Wall Street Journal editorial about it, was because it helped us then frame what was the right kind of policy decision that was out there. And again, we talked about Rawls last time. I'll talk about Kant this time. We very much offended Kant in that. We were using this site as a means to an end that was not into itself. But if you're going to use something as a means to an end, like to make a point, you know, Nazis are pretty fun to use. And so I think we were able to make the point. We were able to sort of change the policy decision. We were able to talk about what the challenges were, and we could do it. So today, if the exact same set of facts came up, it just wouldn't be the exact same set of facts because today, obviously, cloud storage is much more known. We've had those policy conversations. And that doesn't mean that, you know, it kind of feels like every five years, you know, another one of these things pops up. So we're probably due for one sometime soon. I think that the situation behind each of them, is going to be very, very different.
Speaker 1This is advertiser content from EY Global.
Speaker 2Hey, everybody. This edition of Decoder Sessions features Andrew Melnizak, the Verge's general manager, in conversation with Raj Sharma, global managing partner for growth and innovation at EY Global. I hope you enjoy this conversation.
Speaker 1Let's talk about EY AI. What is EY AI bringing to my enterprise?
Speaker 4So EY.AI at a high level, Andrew, is a culmination of many years of work where we have built our infrastructure, our intelligence layer, our compliant ecosystems, all bundled into a reimagination engine, which has got our technology platforms, our deep industry expertise, our deep domain knowledge, and our training and our personnel that we bring to the clients to function. Fundamentally, reimagine that process that is out there.
Speaker 1What are some of the mistakes that you see when you sit down with CEOs, CTOs, heads of innovation? You're like, okay, we can get in here. We see this all the time. We can help you.
Speaker 4The one thing that we always ask our clients to watch out for is to get too narrow in the discussion of the AI that is out there. AI is only as good as the hands that shape it. If you're going to invest into that type of a technology, you need to start with a business, a business mindset of the value that you want to create from an enterprise perspective, rather than taking a technology-first approach. Looking at that business, looking at reimagining that business and what it could be in future, and then looking at how AI can help you get there, that's the fundamental thing.
Speaker 2I usually do the decoder questions first. We just got into it. So, I want to ask the first one first really quickly, and then I want to spend a lot of time on structure. The last time you were on the show, I asked you how you made decisions, and we had a long conversation about values and mission, and how you kind of came to figure out what your values and mission were, and you came back to that. It's been two years. Are you still there? Is that how you make all your decisions? Totally, yeah. The other, so the big decision you recently made, in May, you laid off 1,100 people, which you said was about 20% of the company. How many employees is Cloudflare today?
Speaker 3Somewhere between 4,500 and 5,000.
Speaker 2So you're growing compared to two years ago. You very openly attributed the layoffs to AI usage inside the company, and I know that's true because you literally published an op-ed in the Wall Street Journal. The title was How I Choose Which Employees to Replace with AI.
Speaker 3I didn't get to choose the title because, again, the way media works today is they rage-bait the titles, but that's, but yes, but I wrote the rest of it.
Speaker 2The op-ed supports that title.
Speaker 3I don't know that that's how you tell that something is true, that somebody wrote a Wall Street Journal editorial, but that's the editorial editor. That was the headline.
Speaker 2And the opening is two weeks ago, you laid off more than 20% of your workforce. You wrote that, and then you said you didn't do it because Cloudflare is struggling. You did it because to win the future, Cloudflare needs to change, and I'm just going to run through your rubric, and I just want to ask you about that rubric specifically. You said you broke people into builders, sellers, and measures, and you're basically going to cut all the people who did measurement, all the audit functions.
Speaker 3Not all, but a lot. Yeah, yeah. That certainly is. The majority of the people that we laid off came from that. That category of, and this all comes back to some old school basic business research, which is that there are three functions within any firm. There are people that build things, so the engineers, the product managers, the folks that actually create new products, the people that sell things, the people that are out there actually doing the deals and selling those things. And then the third category is what a lot of every organization is, which is the people that actually measure things. And again, I think each of those is going to be impacted by AI in very different ways.
Speaker 2I've had a lot of software CEOs on the show recently, and we've talked about how AI is scrambling every software company. And I usually ask about product managers, designers, and engineers, right, the builders. And all of those roles are totally scrambled, right? They're all kind of doing one of their jobs.
Speaker 3Yeah, that's true. I do think that there's a sort of increasingly jack-of-all-trades kind of aspect to this, where because you can have these tools, you know, someone who's a product manager can do a lot of what engineers do, someone who's an engineer can do a lot of what product managers do. And the people that are winning in that space are the people that can, that are sort of ambidextrous. They can do multiple different things out there. But where I get lost with some of the sort of AI maximalists who are like, we're all going to lose our jobs. Like, if I can hire a builder and they are now 10 times as productive, which is, they are. I mean, it is wild. It's wild to watch, you know, how much more productive, you know, the builders on our team are today. I'm going to hire as many of them as I can because I got lots of stuff to do. And so, that hasn't decreased the incentive for hiring engineers and product managers and everybody else. It's actually increased the incentive because the return that I get for the salary dollars that I spend on one of these people is now essentially 10 times as much. And so, of course, I'm going to hire as many as I possibly can, which is exactly what we're doing.
Speaker 2So, just walk me through this decision. You woke up one day and said, I've got to, I am, it's Peter Drucker, I think, is he quoted.
Speaker 3Yeah, it's sort of the builder-seller-measure framework comes out of Drucker.
Speaker 2For the decoder heads out there, this is like old school management philosophy. You just, how'd you make this decision? You were like, I got to do this. I'm going to sort these people into these categories and we're going to start making cuts. Did you see any evidence in the data? Walk me through it.
Speaker 3We saw a number of different things. So, one thing that we saw was that the world was sort of dividing into two camps. One camp, which tended to be sort of two different demographics within the organization. It was either people who were very, very senior or people who were very, very junior. And those folks were like adopting AI like crazy. The junior folks, because they were just native to it. The senior folks, because they had the confidence to kind of bet their career that these paradigm shifts would be a way for them to kind of learn new things and take on new challenges. And they were confident enough in their job. that they could they could do that. The other camp was sort of, you know, the folks who were kind of earlier in their career, they might not have been the most senior folks, but they weren't just the brand new folks who had come in. So they'd come through and been trained and sort of been taught that way, the way you succeeded a business was by playing by a certain set of rules. And then all of a sudden they've, they watched around them as their colleagues were all of a sudden, you know, using these new tools that were, that were out there to be able to deliver these things. And the analogy, which is wildly imperfect analogy that I use is it's, it's like we had hired the best kind of screw. If you imagine our job was to screw screws into wood, we hired the, just the best people at using manual screwdrivers to screw screws into wood. And then all of a sudden we invented an electric screwdriver or it came along, we were able to buy it. And for most jobs, not every job, but for most jobs using the electric screwdriver is just better. And you can get a lot more, I'm done with it. And again, the people early in their career were the ones who, who, who adopted or the people who are kind of late in their career were adopting it. And so the first thing that we sort of started to do back in kind of the middle of 2025 was say, Hey guys, this is what's going on. And I understand all the incentives. If you're, if you're kind of in that second camp or to fight against the electric screwdriver, but like, let's give you the resources to train you. Let's give you the confidence that you're going to have a job and you're going to do these things, but let's make sure that everybody across every role is learning how they can, how they can do that. And I think that that's just a really important step that you have to do. And the, and the first part, what we then learned though, is that as we got everyone, not just the engineers, but people on finance and legal and everything else to start to use these tools. We found that one place where AI just shined was in measuring things. And I think one of the places where we don't talk about the advantage of AI enough are that AI is bias, but the biases are uncorrelated to the rest of the organization typically, whereas humans have biases like crazy, but a group working together has biases that are massively correlated together. We, even if you're working on internal audit, right. And you're supposed to be kind of the bad guy who's, you know, looking over everyone's shoulder, like you still go to lunch, the same cafeteria, you talk to the same people, you participate in the same all hands. You have, you end up developing the same biases, whereas AI doesn't, it has a very different set of things. And so we found that we could use these tools in order to do things significantly more efficiently. So there's a woman on our team named Heather. Heather was on our investor relations team. And what she would do was lead a team that every, every time we would kind of close the books before we'd have earnings, because we're a public company, they would spend about two weeks, team, about 20 people. And, and they worked like crazy to generate all of the kind of information. They basically took the measurements and then generated documents that we would then distribute during earnings to all of our investors. And Heather was like, I think we can use tools to do this better. And so we took what used to take two weeks and we reduced it down to three minutes. And our investors are like, wow, these documents are much better. There are fewer errors. There's, there are less mistakes. We've, you know, and our, and our tools are auditing all of, all of those different things. And so for those 20 people, like we looked for other places for them, but a lot of them, what they liked doing was that sort of work. And they would be great at doing that sort of work as the Heather at some startup or somewhere else that was there, but we just didn't need some of the functions that were there. And what it tended to be were all of those functions that were, that were largely measurement. And so, yeah, there was things like internal audit, which we were able to, you know, just get actually much more efficient at doing. There's also things like middle management, where, you know, traditionally kind of the Harvard business school number is that on average, you should have, you know, every manager have like six direct reports. We found with tooling, we could actually be much more efficient with managers and that the right number for us started to feel like when we enabled managers to have more tools to better participate in surface issues early and see how their team was doing that we could get up to like 12 on average direct reports. And everyone's actually happier in doing that. And why that matters is because, as you'd increase the number of direct reports, what you actually do is decrease the amount of hierarchy in any, in any organization. That's the way of measuring how flat versus how hierarchical organization is. And so again, we could use these tools to say, Hey, let's flatten the organization, which has made the organization much faster and more nimble. But in the process, there are a whole bunch of middle managers that just weren't the right folks. And so I think we sat there and we were like, gosh, we know we've got to get rid of these jobs. And so the question is, do we do it now or do we do it later? And the problem with doing it now is like, we feel very exposed. We feel very alone. Like, I mean, the number of death threats that I got, not even from our employees, but from just random people who are sort of anti AI was, was, was really, I mean, pretty scary. But, but, but at the same time, we're like, is it kinder to say, we're going to make these changes now and then do the work to not only give great severance and everything else, but actually go place these people because they're great people, place them at other positions around. And we've been very successful at doing that. And so I think that's a big part of the reason why we're doing this. And I think that's a big part of the reason why we're doing this. have a great manager maybe things one of the things that's great about these tools is you can find different ways to say what do we as an organization value and then look more broadly across who are the people who are really performing incredibly well and that has to be legible to the
Speaker 2system right so it's like the ai is going to watch every code commit and say that person's doing a lot or that person is the nicest to their agents in slack or you have to watch them in some way And there's all
Speaker 3kinds of signal that is inside of every organization.
Speaker 2I'm just stuck on this, and I'm running out of time, so I'm sorry to interrupt. But give me an example of signal that helped you through AI identify rising stars.
Speaker 3So we knew people who were high performers. We trained models based on what their high performers were. We ingested a ton of things across that. I mean, obviously, code commits and all kinds of things. But those are gameable in various ways. And so you really want to look at kind of this person did this thing and then trace it all the way through the organization, and what did that result in in either higher revenue or lower cost or better kind of collaboration across the team. And again, you're right, because we have signal, because we are a very digital company, we're able to pull that. But I think every company has signal in various ways. I think that you're going to just be able to see, if you're a supermarket, you've got cameras that are seeing things. You're going to see the person who sees the spill on the floor and cleans it up. A manager may never see that, but the camera did. And if the AI can say, hey, that person just cleaned up a spill without having to be asked, of course we should be rewarding that stuff. Now, there's plenty of black mirror kind of horrible ways that this stuff can go wrong. And we're very privacy-respecting. It's not a gotcha thing. But it was remarkable how much better I found it at being able to say, wow, there are some people across the team who might be very junior, but are just way outperforming. And then what I can do as a leader is go to those people and say, hey, you're doing a great job. Keep doing it. By the way, here's my cell phone number. Call me if you ever need anything. And we're just watching a bunch of those folks turn into the next leaders at the company. And so I think that, again, it goes back to one of the real values, which is AI has bias, but it's uncorrelated to all the rest of the bias in the organization. And so that provides an independent outside lens that helps you then better run your organization in order to make smarter decisions. And whether that's around internal audit functions or that's around identifying great talent, these tools are various ways that you can do pretty amazing things. And in our case, we didn't go out and buy. You know, some, some widget, we, we just said, okay, let's take all of the, all the things we've learned about who's, who's performing well or what products do well, or, or whatever it is, train models on that and then run it across the system and see what it, what it shows up. And yeah, there were some, there were some mistakes. There's some people that said like, this person's a huge star. And then you actually look down and you're like, no, they're not. But, but for a lot of times there were people who, who, who really were, you know, incredible, incredible stars. And it was great to be able to recognize them.
Speaker 2Do you think being managed in, in, in automated or quantified way will dehumanize or depersonalize your, your workforce? Cause you can, you can see a management by robot does get pretty.
Speaker 3Yeah. I mean, I mean, I think that's, that's a decision. Like if, if you, if every promotion decision is made by, you know, some, some, you know, totally unaccountable, like AI system, that seems wrong. But on the other hand, if a AI system is better able to say, Hey, Matthew, CEO, you know, here's this, you're a junior customer support person. Who's just been giving amazing answers to customers. You may not have ever seen them before, but you should give them a call. Like, I think that's actually incredibly humanizing. That means that you can be seen for the contribution that you're doing. And again, there are lots of ways that bad organizations will use these technologies to do bad things, but that comes back to the leadership. Like, don't be a bad organization, be organized around, trying to do the right thing, like celebrate your employees, make them, make them rich. Like, I mean, that's, that's exactly what you want. And I, and again, I feel like we've become a better organization, better at recognizing where talent is better than being able to reward that talent. Uh, and, and, and invest behind that because of these, these various tools.
Speaker 2Let me connect that all the way at the beginning. I asked you, you know, how do you make decisions? And you said you'd start with mission and values. And a thing that really struck me at our last conversation was that you came to that realization that that was emergent as you began. I think you said you had a joke that was like, your, your mission was to just like impress your mom, right? And then that became this much bigger mission about security and all these other things that you're doing. How has your relationship to leadership changed as you've automated the management function? Cause there's something big in there.
Speaker 3I really don't, I think it is incorrect to say that we've automated the management function. I think we're collecting a bunch of data on
Speaker 2what everyone is doing. We're measuring it perfectly. And then we're calling the customer.
Speaker 3I don't think we're measuring it perfectly. I think we're measuring it. We're giving then managers more tools to help both recognize the people who are overperforming, to help the people who are struggling get the resources that they do. And so I think we're surfacing data that allows managers to be better managers. I don't think we're replacing managers, right? I think we're making managers better at their jobs.
Speaker 2And that scales management, right? Totally. It's funny you mentioned that you're up to like 12 direct reports. By the way, we're not there yet.
Speaker 3We're not there yet. We're headed there.
Speaker 2So, yeah. Two years ago, you said your number was about eight, which you called high. So you're going from eight to 12. Mark Zuckerberg is at like, we should have 50. And I keep saying Dakota has a long life ahead of it because there's a show about org charts. We're on the cusp of the weirdest org charts in history. Are you there? Are you at 50? Oh, no, no, no.
Speaker 3I think, again, I really do think that humans are social creatures and we want to be able to know people. And the Dunbar number is real, which is the number of direct social relationships you can keep in your head. Which is supposed to be something like 120. But people should have friends outside of work. So you can't just occupy those all with work colleagues. So if I said eight before, that was wishful thinking. We were probably close to six. But we are making our way up. And so we're probably closer to eight-ish now. But we're headed more towards 12. But I think you have to be very, very specific because you also don't want people playing games with that. Where they're like, well, I'm going to build out a big team of people. We don't need a big team. So I think you've got to be – I think that can be aspirational and directional. But I don't think that's going to happen. I don't think that's going to happen. I don't think you can be religious. I don't think you can just say, oh, everyone has to have at least 12. You've got to figure out where that makes sense and where it doesn't make sense. And again, as that evolves, I think that there's a big piece of it. But you have to also have some foundation that aligns people. And that's where mission comes in. And it's absolutely true. Our mission in the beginning was take advantage of this interesting kind of market opportunity, hopefully make some money and impress our parents so that they'd get off our back about why we didn't go work at a bank or whatever. And I think that it was only as we started to serve our customers and we saw just how important the Internet was and how it really lacked defenders. There weren't a lot of people who were kind of fighting for it that we realized that our mission was really to help build a better Internet. And if you talk to anyone at CloudFlare, anywhere through the organization, any country that we're in, any office that we're in, I think that what I find amazing is time and time and time again they come back to saying the reason I work here is, you know, because I believe that the mission is one of the most important things we can do. And that's, I mean, I don't, like, there's a lot of days that people are like, why do you still work at CloudFlare? I'm like, because I can't imagine anything more important right now than helping build a better Internet. And that, I can't imagine anything that's more exciting to be working on.
Speaker 2Well, Matthew, that's a great place to leave it. We're going to have to have you back very soon because I feel like the Internet's going to change even faster than it did last time. Thank you so much for being on The Coder. I'd like to thank Matthew for joining me and thank you for listening to The Coder. To get new episodes every Monday and Thursday, subscribe to our YouTube channel at DecoderPod and find us on TikTok and Instagram under DecoderPod as well for more fun stuff we put out every day. If you'd like to let us know what you thought about this episode or really anything else at all, let us know. Drop us a line at decoder at theverge.com. We really do read all the emails or hit me up directly on threads or BlueSky. If you enjoyed this episode, please send a link to it to someone you think might like it too. It really helps us grow the show, which you can subscribe to wherever you get podcasts. The Coder is a production of The Verge and part of the Vox Media Podcast Network. The show's producers are Greg Ott, Kate Cox, and Nick Statt. This episode was edited by Kabir Chopra. Our editorial director is Kevin McShane. The Decoder music is by Breakmaster Cylinder. We'll see you next time.
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