Can Cloudflare save the web from AI?

Cloudflare discovered in June that bots already make up more than half of internet traffic — and CEO Matthew Prince says that bots could outnumber humans a thousand to one within five years. That's a huge change to the internet, and if the web is going to keep existing, it needs a huge change to its business model. Can Cloudflare use its place in the ecosystem to direct the money back to the people who make content? Read the full interview transcript on The Verge. Links: How I choose which Cloudflare employees to replace with AI | Wall Street Journal Why Cloudflare CEO Matthew Prince is the internet’s unlikely defender | Decoder (2024) Cloudflare will now block AI crawlers by default | The Verge Patreon partners with Cloudflare to block AI crawlers | 404 Media Sony and Warner sue Anthropic in latest AI music lawsuit | Billboard Trump administration supports OpenAI in NYT copyright lawsuit | The Verge Google Zero is here — now what? | The Verge (2024) Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder’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. Learn more about your ad choices. Visit podcastchoices.com/adchoices

• 0:00Speaker 00

  Support for the show comes from EY. AI is reshaping how enterprises operate, compete and create value. But organizations are struggling to move beyond fragmented tools and siloed AI investments to create real impact. EY.ai, the re-imagination engine, is an open, dynamic, AI-led technology system at the heart of EY. By combining AI, technology and people with trusted experience, EY helps organizations turn AI ambition into enterprise value. Because AI is only as valuable as the handsets shape it. Go to ey.ai to explore more.

• 0:44Speaker 00

  Hello and welcome to Decoder. I'm Neelai 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 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 the internet traffic, a number that just keeps going up as more and more AI companies scrape more and more of the web.

• 1:26Speaker 00

  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.

• 2:11Speaker 00

  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 decisions, 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.

• 2:52Speaker 00

  Matthew Prince, you're the co-founder and CEO of Cloudflare. Welcome back to Decoder.

• 2:56Speaker 01

  Thanks for having me.

• 2:57Speaker 00

  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 at 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're in the middle of. But let's start at the very beginning. Cloudflare is a complicated, important company. The last time I ran 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?

• 3:33Speaker 01

  It'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'd 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

• 4:17Speaker 01

  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.

• 4:35Speaker 00

  Can 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 didn'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 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.

• 5:05Speaker 01

  So, 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 is 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 about for the search business that they have, but they really built out all of the ecosystem around advertising online. 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 the, sort of what I'd call like the first generation of the internet and the first generation of the web.

• 5:48Speaker 01

  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, 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 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'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

• 6:33Speaker 01

  2027. We're like, wow, this is growing. I mean, this AI thing 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 has now passed human traffic online." And that's just expanding like crazy. And 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 1,000 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 to that is, if you have, first of all, 1,000 times more traffic, someone's got to pay for the infrastructure to power that.

• 7:18Speaker 01

  Like, 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's going to power that just incredible, insatiable demand that's going to be put on the internet going forward. And that's what I'm spending a lot of my time trying to think about, what that's going to look like.

• 7:52Speaker 00

  When you describe that as a business model, that sort of implies that there's going to be customers and revenue and profits, and I don't know if any of that's true.

• 8:04Speaker 01

  I think, I mean, there's certainly a lot of revenue.

• 8:07Speaker 00

  Well, there's maybe for the Cloudflare and the Googles of the world, but for the truth...

• 8:11Speaker 01

  Or the anthropics of the world. $10 billion of revenue in a single month. So, like, there is enormous demand for these AI services. And if you're an AI company, what you really need are three things. You need great 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. 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, Nvidia is the best in the world at that, but you've got a whole bunch of others, whether that's AMD or Qualcomm or all the hyperscalers that are building their

• 8:55Speaker 01

  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 that 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, we 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.

• 9:38Speaker 01

  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 the very first version of Netscape, was actually payment required. And you actually have to pay for the content that you're receiving. And that's something, excuse me, I 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

• 10:22Speaker 01

  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? Comes from the fee that people are going to be paying for their AI agents and other systems that are, they're out there, really similar to how like a Spotify or an Apple Music works today.

• 10:41Speaker 00

  I 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. 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.

• 11:10Speaker 01

  Yep.

• 11:11Speaker 00

  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.

• 11:38Speaker 01

  Yeah.

• 11:38Speaker 00

  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 it just doesn't seem like a good idea anymore. Where we're on the flip side, the web is an application program is 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 you're trying to say we can change the incentives over here. What's a version of the future?

• 12:19Speaker 00

  Maybe it's microtransactions, maybe it's not, where the incentives to make the web an information platform are as good as YouTube?

• 12:26Speaker 01

  You've sort of illustrated what is what is um 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, that's why what's the incentive to like put information on Wikipedia? Uh, something that again, you know, people are doing uh 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 OpenAI's ChatGPT or Anthropic Claude or you know, Grok on X or whatever it is. And and that means that the people who are, you know, the editors of Wikipedia are saying,

• 13:11Speaker 01

  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. Uh, 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 um starting in about October of 2025, driven a lot because of the various five 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.

• 13:52Speaker 01

  And the growth of the web itself um with with really high quality stuff and and a lot more people contributing to it uh is faster today than it has been at any time since the early two thousands. And so that's that's that's that's the 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, um we have the ability to overcome some of the incentives problems that you 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 this information. And and that can kickstart what I think is the beginning of of what we need. And and again, the the problem is if you don't have something like that, we face a massive tragedy to comments problem.

• 14:36Speaker 01

  So let's say today I ask, I don't know, whatever my favorite AI agent is, you know, where should I go to lunch? I mean, if I was doing research, I might go look at a couple of different menus, you know, as an individual. My agent today goes and scans every single menu in the local area in order to figure out what's going on. And 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's 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. Um, 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 you load a webpage.

• 15:18Speaker 01

  There's a there's there's there's there's bandwidth, there's servers, there's things that are behind 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 uh 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. Um, 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 give you this content unless you pay even more for it, but I believe that it's valuable and we can create a market um 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.

• 16:03Speaker 01

  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 lot of time actually building.

• 16:21Speaker 00

  Here, it feels like the the theoretical underpinning of this conversation is the very notion of scarcity itself. I'm an old copyright lawyer and copyright law for years and years and years had a 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 cost 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? We moved 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.

• 17:06Speaker 00

  And the internet just turned that upside down, right? That 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. And it was actually a tension that became valuable because that was scarce in its way. You're talking about imposing scarcity, right, with your technology?

• 17:29Speaker 01

  You 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 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 like, what could this look like in the future? Um, you know, I flew up to Stockholm to meet with Daniel Akh, who started Spotify.

• 18:10Speaker 01

  And and I mean, 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 was from, you know, CDs or or or albums or whatever it was, whatever it was. Um, and then along came the internet and along with it Napster and Grokster 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 uh to music. And if you go back 23 years ago, um the music industry as in total was about nine valued at about nine billion

• 18:51Speaker 01

  or eight 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 including cover art and they're going to make sure it's high quality and and all all these things. And but mostly it appealed to this emotion of you should be paying for for music. Now, that's not the business model that won, but it was 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 Spotify's of the world.

• 19:33Speaker 01

  And the and the incredible thing is, you know, just last year, um Spotify sent something like 12 billion dollars 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.

• 19:49Speaker 00

  This is my favorite thing to argue about because I I well, I think 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 liter the music files themselves became very small, right? You can get a million streams on Spotify, you're not making any money. But the amount generated by touring and commercial sponsorships and sync licensing to advertising all skyrocketed.

• 20:17Speaker 01

  That's that's just simply not true. Why is private equity buying all of the music catalogs for hundreds of 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 dollars back to the music industry, back to the actual rights holders behind uh 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 or any any of the other things that are there. You those are other ways to make money. But actually, it's the it's the streaming that is is really driving all of the real growth.

• 20:50Speaker 00

  Sure, but I I just want to draw a distinction here. And we don't 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.

• 21:06Speaker 01

  If the musicians, if the Beatles, you know, if the Rolling Stones or whoever used the latest ones to sell their, their music catalogs had held on to the music catalogs, then the musicians would have made that. They're, they are making the determination that, and by the way, when they sold the, sold the rights, they got to get the check. So it's.

• 21:24Speaker 00

  Did you get the check? But the only thing, the only comparison I'm making here.

• 21:27Speaker 01

  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 upfront? 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 fact, in this case, it has been a massive enabler of value in this and, and allowed people to find audiences and yes, sell more tickets to their, their concerts as well. But, but I think that 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, of music and then give that back to musicians based on, you know, some sort of algorithm that,

• 22:11Speaker 01

  that, that hopefully rewards where there's actually a real value, which is, which is created. If you had the same thing where a portion of what is being paid for, for the various AI companies, well, yeah, to pay for the researchers that built the AI systems and you had to pay for the chips, but also to pay for the content, which is actually the real knowledge that is training these things. I think that's exactly the type of model that you need in order to actually unlock what could be a real golden age of information creation.

• 22:34Speaker 00

  Yeah. The, the comparison I'm making is not whether a bunch of aging rock stars are going to sell their catalogs and cash out because they're old, right? That's fine. They can do that. It's more that the shift you're describing into gating access into, you know, wide open access on Spotify to every song ever made. And then we're going to move some pennies around and some people get rich and we'll create some winners and losers fundamentally changed the entire business model of music.

• 22:55Speaker 01

  So Spotify, again, this is fascinating, the conversation with Dan was fascinating. He said, okay, listen, if you go on Spotify and you search for Taylor Swift, Shake It Off, like they return a result and they're pretty sure that they have given you what you were looking for. On the other hand, if you go to Spotify and you search for, I want a song to a disco beat about how much fun it is to dance with my cat. 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 didn't take then those searches for things that they don't have good results to do and they publish that back to music creators. And, and I think that there's something that's pretty amazing about that, which is they're saying, here's, here's, here's an emotion

• 23:38Speaker 01

  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, is in, 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, they're writing songs for what people are searching for that are on there. Now extrapolate that to the next level, which is to say, for the first time in human history, we've built a mathematical

• 24:19Speaker 01

  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 is to fill in the holes in the cheese. They want new knowledge that no one ever knew about before. And so the, 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

• 25:02Speaker 01

  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 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

• 25:43Speaker 01

  is interesting is we're not going to protect all media in the same way that, you know, the move to Spotify, there are, 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, off unfulfilled Spotify queries. And, 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, you know, first on it in the, in the nineties. Like, 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

• 26:28Speaker 01

  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 app.

• 26:47Speaker 00

  Support for the show comes from EY. AI is reshaping how organizations operate, compete and create value. But as AI accelerates, the challenge is no longer how to access the technology. It's how to leap beyond the legacy constraints and apply AI with the right judgment, trusted experience and credibility to transform your organization. That is where ey.ai, the re-imagination engine comes in. ey.ai, the re-imagination engine is an open, dynamic, AI-led technology system at the heart of EY. It brings together EY technology and investments, a powerful ecosystem of alliances and seamless integration into each

• 27:30Speaker 00

  client's unique environment. Through globally connected and orchestrated solutions, ey.ai, the re-imagination engine helps organizations scale AI from isolated investments into a connected enterprise-wide intelligence capability, giving leaders the confidence to reimagine the enterprise and realize value at scale. Go to ey.ai to explore more.

• 28:04Speaker 00

  One 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's yet another lawsuit, right? The, the music companies are going to sue Anthropic. The White House came out in, in support of OpenAI in 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.

• 28:36Speaker 01

  Yes.

• 28:36Speaker 00

  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 and maybe existential.

• 28:45Speaker 01

  I mean, maybe not. I mean, it's, I mean, I think that the law right now, at least in the US, and the US 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, where the, where the judge basically said that training is fair use against all, all the books. And by the way, you shouldn't have stolen the books. That was bad. But, 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, um, uh, result for Anthropic that they settled the rest of the case for $2 billion, which is, you know, a lot of money, um, even, even for Anthropic. And so, so I, I.

• 29:21Speaker 00

  Right. 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.

• 29:31Speaker 01

  Different regulations are going to be passed in different places around the world. So like I, and again, as a also recovering intellectual property attorney, like I, I very quickly go to like, oh, let's just use intellectual property. But, 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. And they hide, whereas like the nerds

• 30:11Speaker 01

  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, who've, who've been. At times challenging through this because Google, you know, they they they're sort of like a Marvel film like the hero of yesterday becomes the villain of tomorrow.

• 30:56Speaker 01

  Like the the challenge has been that they 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, eh, 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.

• 31:35Speaker 01

  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 in many cases, I'll even be willing to pay for content. I think that's actually just makes it even easier to convince all of the other AI companies to do the same.

• 31:52Speaker 00

  Do you think you need to turn the screws all the way and actually block the Google crawlers to get them to pay?

• 31:57Speaker 01

  As of September fifteenth, we're going to set the defaults across all of our free customers for it to be that Google is going to be blocked. It 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 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 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.

• 32:41Speaker 00

  I've talked to Sundar 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. Sundar is very thoughtful. He 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 you publishers are complaining. You got super addicted to my fire hose of traffic and that 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. Chat G P D 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 going to block the Google search traffic. We're going to block the crawler. I think the CEO of People is talking about literally blocking Google.

• 33:24Speaker 01

  Steve at Reddit is has really become, you know, more aggressive and Google doesn't work if it can't search these things. And and it's and it's actually more existential for them. The very nature of how Google's search ranking works is it builds a tree, right? That's what PageRank was. It sort of says, OK, 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 that, you know, with CloudFlare, again, twenty percent 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.

• 34:10Speaker 01

  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 and then that's just not a fair give to get anymore. And so the deal has to change. And so I I'm really proud of the fact that, you know, 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, they all high fives and said, I think we're 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?

• 34:51Speaker 01

  Because if we don't, we have this massive tragedy of the commons problem where it's just going to be take, take, take, impose costs, impose costs, impose costs. And and the incentives for actually creating things, for contributing to the Wikipedias 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 their tune appears to be changing over the last, uh, over the last few months.

• 35:30Speaker 01

  And I believe that at their core, they really do understand that this is an ecosystem and 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 to flourish.

• 35:43Speaker 00

  You said Google is going to make some changes soon. What changes would those be?

• 35:46Speaker 01

  You know, I think the thing that they've already committed to is just a lot more transparency on what their crawler is doing. So what we had pushed them to do is split their crawler apart and say, you know, we are going to crawl for, you know, AI separate from crawling for for the web. Um, and and I think that they they, for a lot of technical reasons, pushed back and said, you know, that actually is incredibly inefficient. 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. 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.

• 36:28Speaker 01

  That they have they have signaled that largely in response to what was a a ruling out of the United Kingdom, that they were going to put those those 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 would be great.

• 36:51Speaker 00

  I could argue with you about the music industry all day and all night. I think you know that. But it 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 L M and spit out.

• 37:26Speaker 01

  Yeah, or or instead of reviewing a 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 a hundred 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 L M's like, hey, listen, we're going to sell not just, 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.

• 38:06Speaker 01

  For every picture you see in a magazine or a newspaper, there are probably fifty or sixty 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 that there's there's just a bunch of content that's literally being thrown on the floor today, it actually can be incredibly valuable.

• 38:27Speaker 00

  This is this is my universe. Uh, I feel confident about this one. Um, yeah, 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 in a story we're going to run in a few weeks. Then we disagreed and we 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 L M, 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.

• 39:09Speaker 00

  And at the end of the day, maybe my future is just making YouTube face slinging A G one 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, G E O optimized for some human to consume, digested by a chatbot in the middle?

• 39:31Speaker 01

  Well, 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 your parent parent corporation. And again, I think you guys do 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?

• 39:50Speaker 00

  Sure.

• 39:50Speaker 01

  And then A B test headlines in order to either stimulate a dopamine or cortisol response to that.

• 39:58Speaker 00

  If only the media was that scientific, we we would probably do that.

• 40:01Speaker 01

  But a lot of it is. I mean, I I've sat with some of the, you know, 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 I don't know that that's a game we play everywhere, but you can even see, you you can even track the New York Times, you can track the Wall Street Journal, you can track the F T. And just watch how much more inflammatory and almost tabloid-ish the headlines have gotten over the last twenty years. And and again, I think that that's that that those are still, um, 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?

• 40:40Speaker 00

  Well, 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 shaping the content. So I'm asking you about the new distribution that you're describing.

• 40:51Speaker 01

  But let's just frame that, you know, the sentence that I say that gets everyone at Google to yell at me is everything wrong with the world today is Google's fault. That is not fair to Google. Google has been, by and large, been a great company, but Google begets Facebook, which begets TikTok, which has us in this attention economy hole where it's just like, what we're trying to do is get as much attention as possible. And the best way to do that is to actually stimulate, again, a deep sort of mammalian response. That's the media landscape that we live in today. And I think it's deeply broken. And I think it's what's divided the world. I think it's what's led to the rise of sort

• 41:32Speaker 01

  of very destructive populism around the world, you know, much less sort of 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, you know, 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, you know, 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

• 42:16Speaker 01

  it either. And the best, 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.

• 42:44Speaker 00

  Just to be clear for the audience, you're using tokens as a measure of amount of new content.

• 42:49Speaker 01

  Of content, yeah. Content that's, that's, that's, that's, 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, 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

• 43:33Speaker 01

  that no one else has told, real knowledge creation, is what is valuable and is proven valuable by the market that exists today.

• 43:41Speaker 00

  But the other side of that market, just to be reductive here to try and understand the model, the market, the buyer in this market is a bunch of model companies. It's not people.

• 43:51Speaker 01

  Well, but, but then ultimately, the customers of those model companies, which is all of us. And 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 what, I mean, 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

• 44:36Speaker 01

  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, the, the, the creators of real knowledge as I possibly can. Now, I'll tell you, the financial piece, I think we can solve the financial piece. The piece that I'm actually much more worried about, and again, this comes out of this, this comment, you should have Daniel Ek on the, on the story, because he's fascinating to talk about these things. But he, like, talking to him, 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

• 45:16Speaker 01

  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. By the way, it's a stupid strategy, being rich and anonymous is the best story. But the, but, but, but that's true. I think that a lot of people really do want recognition. This is part of why Wikipedia is seeing a drop in the number of contributors and information. It's because people don't get recognized as much, because you're not going to the original sources. 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 labs is we should create, I don't know if it's the Nobel Prize, or the

• 45:59Speaker 01

  Academy Awards, but some sort of recognition where we use math to measure who create, you know, 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. 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.

• 46:44Speaker 00

  The last time you were on, we spent a lot of time talking about content moderation and CloudFlare using its power on the internet to, you know, essentially make it harder for sites like Stormfront, which is a neo-Nazi website, to exist. And you had a lot of, you were, you were in torment about it. You had a lot of power, you were going to use it, you published some op-eds about it. We talked about it for a while. And eventually, you came to decide, you didn't want to be in business with these folks and the consequences of the consequences, but there should be some frameworks to regulate your power. Many things have changed. But we've kind of had a long conversation about CloudFlare using its power to block AI scrapers and create economic opportunity. It's the same power in many ways, right? It's a power of a layer of the internet that is pretty dominant

• 47:29Speaker 00

  to, to stop things from happening. Have you changed your mind? Is it just the economic rationale that's made that more comfortable for you? Or is there something else happening?

• 47:37Speaker 01

  You know, I think, what, one of the things is, and I think it's been interesting inside of CloudFlare, has always been, like, when we see these bad things that are using us, you know, there's, there's, I think, a very human reaction. And it's, it's often my co-founder, Michelle, who's like, listen, I realize all the hard, thorny, moral questions, but this is per se bad. We should do something about it. And, and I think we have largely come out to say, you know, that's, it's tough. Like, we don't want to be the ones that are deciding what's good and bad. And even, and there, and there actually aren't that many things that are just sort of per se bad that are out there. But wouldn't it be great if we could change the incentives so that, you know, there's less incentive to create

• 48:22Speaker 01

  these, these various, various things? And, and what I found interesting about, you know, the, the, the question of what the future business model of the internet's going to be, is it's sort of the first time I've, I've thought, wow, maybe, instead of trying to kind of deal with, you know, bad site here, there, which is basically like, just, you know, cutting down dandelions, like, more are going to, you know, spot up, you're not solving the root problem. I think if we can get the incentives for the next business model of the internet to be less around, how do we just create rage and emotion? And which, by the way, being a neo-Nazi is one of the most effective ways to just really piss people off, and they tend to click on your things. And then, and then buy nutritional supplements or whatever. All these things are very weird business models that are

• 49:05Speaker 01

  behind them. But I think if we can get back to something where we're actually rewarding not rage creation, but information creation and knowledge creation, that, that, that maybe that's actually getting at what is, you know, the fundamental kind of roots that are there. And maybe I'm too much of an optimist, but I think the way that you stop a lot of, again, the, the just horrible things we see online, is by solving the business model that is really broken, that has led to the online communities that we have, that we have today, and, and that we get away from what has been a very much, excuse me, an attention-based economy, to one that is much more of an information, knowledge-based economy. And so as we're thinking about, like, what does the future of the internet

• 49:50Speaker 01

  look like? That's what we're playing for.

• 49:52Speaker 00

  So it's the same power, right? You have, Cloudflare has a lot of power on the internet, right? It's a platform layer of, there's a lot of influence. You're able to stop things. In the case of the neo-nazi websites, you declined to use your power.

• 50:05Speaker 01

  No, no, I mean, we did, we kicked them off our systems.

• 50:09Speaker 00

  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.

• 50:14Speaker 01

  Yeah, I mean, they're all still around. So that, so at some level, it, you know, it shows that it's limited.

• 50:21Speaker 00

  But 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.

• 50:27Speaker 01

  I guess the question is, you know, power. So, you know, 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, you know, we are very much at the service of our customers. And I remember the first time that, you know, a media company called me and said, you know, we have this new threat, you have to stop it. You know, 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, you know, 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

• 51:11Speaker 01

  that was, that was worth us spending our time and our resources on, on fighting it. And so, you know, again, I think that we, we have, you know, 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, if we ever, if we ever screw that up, you know, they'll leave us in a second. So, you know, is that power or is that just being a good steward to the internet?

• 51:36Speaker 00

  It'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?

• 51:46Speaker 01

  I think each of those things is sort of a moment in time and, and there were, you know, I think there are puts and takes under all those things. I think that the, you know, at some level, you know, we, at the time, like no one, 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, that was happening online that was, that was really, could have been, you know, 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, you know, one of the real rationales of kicking Daily Stormer off was, and then

• 52:29Speaker 01

  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, you know, we talked about Rawls last time, I'll talk about Kant this time. You know, we very much offended Kant in that. We were using this site as a means to an end that was not into a, you know, itself. But if you're going to use something as a means to an end, like to make a point, neo-nazis are pretty fun to use for that point. And so I think we, 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, 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.

• 53:12Speaker 01

  Because today, obviously, Cloudflare is much more known, we've, we've had those, 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.

• 53:42Speaker 02

  This is advertiser content from EY Global.

• 53:47Speaker 00

  Hey, everybody. This edition of Decoder Sessions features Andrew Melinzak, 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.

• 53:58Speaker 02

  Let's talk about EY AI. What is EY AI bringing to my enterprise?

• 54:04Speaker 03

  So 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 re-imagination 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 fundamentally reimagine that process that is out there.

• 54:31Speaker 02

  What 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.

• 54:42Speaker 03

  The 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 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 re-imagining 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.

• 55:25Speaker 00

  I 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?

• 55:43Speaker 01

  Totally, yeah.

• 55:45Speaker 00

  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?

• 55:54Speaker 01

  Somewhere between 4,500 and 5,000.

• 55:56Speaker 00

  So you're growing compared to two years ago. You very openly attributed 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."

• 56:10Speaker 01

  I didn't get to choose the title, because again, the way media works today is they rage, rage, rage at the titles, but that's, but yes, but I wrote, but I wrote the rest of it.

• 56:19Speaker 00

  The op-ed supports that title.

• 56:20Speaker 01

  I 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, the editorial editor.

• 56:27Speaker 00

  That was the headline. And 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, you broke people into builders, sellers, and measurers, and you're basically going to cut all the people who did measurement, all the audit functions.

• 56:51Speaker 01

  Not all, but a lot. Yeah, yeah. It certainly is. The majority of the people that we laid off came from that, that, that, that category of, and this is, it's all, you know, comes back to some, you know, old school, basic, you know, business research, which is that there are three functions within any, within any firm. There's, 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, you know, a lot of, a lot of every organization is, which is the people that actually measure things. And, and again, I, I think each of those is going to be impacted by AI in very different ways.

• 57:30Speaker 00

  I'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, they're all kind of doing one of their jobs. And I don't think it's sorted out.

• 57:47Speaker 01

  That's, that's true. I do think that there's, there's, there's a, there's a sort of increasingly jack-of-all-trades kind of aspect to this, where, you know, that, where because you can have these tools, you know, someone who's a product manager can do a lot of what engineers do, someone with 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, but like, 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, which is, they are, I mean, just, it is wild to watch, you know, how much more productive,

• 58:31Speaker 01

  you know, are the builders on our team are today. I'm gonna hire as many of them as I can because I got lots of stuff to do. And so I like that hasn't decreased the incentive for hiring engineers and product managers and everyone else. It's actually increased the incentive because the return that I get for the salary dollars that I spend on one of these, these people is now essentially 10 times as much. And so of course I'm gonna hire as many as I possibly can, which is, which is exactly what we're doing.

• 58:57Speaker 00

  So just walk me through this decision. You, you woke up one day and said, I've got a, I am, it's Peter Drucker, I think is he quoted.

• 59:04Speaker 01

  Yeah, yeah, it's sort of the builder seller measure framework comes out of.

• 59:08Speaker 00

  For, for the decoder heads out there, this is like old school management philosophy. You just, how'd you make this decision? You were like, I gotta do this. I'm gonna sort these people into these categories and we're gonna start making cuts. Do you see any evidence in the data? Walk me through it.

• 59:21Speaker 01

  We saw, we saw a number of different things. So, so one thing that we saw was that the world was, was sort of dividing into, 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, they had the confidence to, to, to, to, to kind of bet their, their career, that, 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 jobs that they, they could, they could do that.

• 1:00:01Speaker 01

  The, the other camp was sort of, you know, the, the folks who were kind of earlier in their, your 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 at 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, and the analogy, which is wildly imperfect analogy that I use is it's, it's like we had hired the best kind of screwdriver, if you imagine our job was to screw, screws into wood. We hired the, just the best people at using manual screwdrivers to screw, uh, 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.

• 1:00:46Speaker 01

  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 done with it. And again, the people early in their career were the ones who, who, who adopted or the people who were kind of late in their career were, were adopting it. And so the first thing that we sort of started to do back in, in 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 are 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, you're gonna have a job and you're gonna, you're gonna 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 in the, in the first part.

• 1:01:27Speaker 01

  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 has 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 at 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.

• 1:02:12Speaker 01

  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 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 then distributed during earnings to all of our, 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 were like, wow, these documents are much better. There are fewer errors, there's, there's, there are less mistakes.

• 1:02:56Speaker 01

  We've, you know, and, 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, 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.

• 1:03:37Speaker 01

  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, you know, better participate in surface issues early and, 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 our 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.

• 1:04:22Speaker 01

  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, and 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 gonna 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, and we've been very successful at doing that across the board. Or is it better to kind of cover our own ass? Wait until everybody else in the industry is, is, is, is sort of saying, is coming to the same conclusion.

• 1:05:06Speaker 01

  And, and by the way, that's coming, Uber just did a layoff, the same rationale. You're gonna see across the industry, not just in tech, but everyone start to get to this realization. I think we were early, but is it gonna be easier to get a job back in April when we did this? Or next April, when everyone is doing it? And once we kind of realized that, we were like, if we're real leaders, we should be the ones taking the arrows. We should be protecting our team. We should be working to make sure that even the people that we said, listen, we don't have a role for you anymore. We can help them find great roles at other places because they're great people. And that, that's, that I think is what real leadership is. And I think a lot of, when I talked to a lot of my peers, they're sort of sitting around saying, yeah, I know we need to do this.

• 1:05:47Speaker 01

  But gosh, I saw like your stock went way down and you got all these really scary, you know, death threats and other things. And I don't want to have to go through that. I think that's chicken shit. Like if you're a real leader, get out there and actually do the work. And, and yeah, there's a lot of things about the economy that are gonna change. Doesn't mean jobs are over. We're gonna hire as many builders and as many sellers as we possibly can. And there are still some measures on our team. So people have to, you know, build, build the tools and, and do those things. But, but what it's going to look like going forward is, is going to be very different. And once you realize that as an organization, I think that sooner that you can do that is the kindest way that you can be to your own team.

• 1:06:23Speaker 00

  What a, another decoder trope is that structure is a rough proxy for culture. I'm always saying, if you tell me the structure of your company, I can tell you about 80% of your problems. The 20% is usually where the actual magic is. How has your structure changed and how has that changed your culture?

• 1:06:37Speaker 01

  Well, the first thing is we've just, we've flattened the organization a lot. There's a lot of middle management that went away. And, and, and not just because we laid people off, but there's a whole bunch of managers that are, are raising their hand and saying, I don't want to be a manager anymore. I want to go back to being an individual contributor. I mean, it's, it's wild to see all these really senior managers that are leaving big jobs to go to Anthropic to be an individual contributor. And that's because like you could just, there's so much more leverage that you can, you can have. And I think that what is a manager versus what's an individual contributor is gonna get really fuzzy. And that's one of the things that we're spending a lot of time thinking about is, it doesn't even make sense to have those as two separate tracks. Maybe that all merges together into, into one thing, because, you know, even individual contributors now are managing a fleet of agents that are working on, on their behalf.

• 1:07:21Speaker 01

  And so I think the, the biggest thing is that we've, we've flattened the organization, you know, quite a bit. And then I think the other thing is that we've, we've centralized through something we call CloudFlare OS, which we've now open sourced because enough of our customers were like, that's really cool. We want to use that too. And so we've got a whole bunch of customers that are taking it and turning it into, you know, XYZ company OS, whatever it is. But it's, it's a set of tools that essentially takes a bunch of just the knowledge that's inherent to CloudFlare, the things that have to be true, the things that sort of inform our decisions, and then allows anyone on our team to have access to, you know, a wide range of the different tools that are out there. But, but then continuously is pulling and updating the information about what has to be true.

• 1:08:04Speaker 01

  And, and having it so that when you want to figure out like what information is, is, is pulling out of Salesforce or Workday or, you know, and any of the systems or record that we have at, at CloudFlare, being able to pull that into one consistent interface has just allowed, allowed our teams to be significantly more productive and, and are much better at cross collaboration.

• 1:08:23Speaker 00

  There, there's something here, which maybe is just the nature of a software company. And, and that's the way it is. And it's, it's a worldview that I understand because of how software companies and tech company works, where everything that is happening in your company happens in a digital system. And then that thing can be measured. You've got a line in your piece, "As CEO, I've never had better tools to measure exactly how the business is performing, including identifying our rising stars." This implies your rising stars are producing data that can be measured by an AI. And then the AI can tell you, these people are the rising stars. There's something about that that is fascinating to me. Not every company works that way, where everyone's job is to tell Slack everything that's going on or tell CloudFlare OS everything that's going on. Like they're out in the world doing stuff. How do you connect those dots?

• 1:09:05Speaker 00

  Because that seems to be the challenge of how Silicon Valley might see the world and how every other business might see itself.

• 1:09:12Speaker 01

  Yeah, I mean, I think that, like, I think we've all at various times worked in jobs where we're like, gosh, I'm just not being recognized for, for the hard work that I'm doing. Or, or other times where, you know, you're like, I'm kind of like over recognized and, and I'm not, and maybe I don't, I don't.

• 1:09:29Speaker 00

  I've never felt over recognized. If I could get some more, that'd be great.

• 1:09:33Speaker 01

  You're, you're doing a great job.

• 1:09:35Speaker 00

  Now, can you get your chatbot to tell me I'm doing a good job? Because that'd be really good.

• 1:09:39Speaker 01

  Um, so the, uh, I, I think that the, um, again, I think, I think it is absolutely the case that there have been great people who've worked at CloudFlare that we just missed in the past. And, and, and for, you know, a million different reasons. Um, you know, maybe they're a part of the organization that we just, you know, didn't, didn't recognize enough. Maybe they didn't have a great manager, maybe didn't think. 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.

• 1:10:15Speaker 00

  But that has to be legible to the system, right? So it's like, 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 like, you have to watch them in some way, right?

• 1:10:27Speaker 01

  Yeah.

• 1:10:27Speaker 00

  To get that data back.

• 1:10:28Speaker 01

  But there's, there's all kinds of signal that, that, you know, is inside of every organization.

• 1:10:33Speaker 00

  Can you just, I, I, I've just stuck on this and I'm running out of time, so I'm sorry to interrupt. But give you an example of Signal that helped you through AI identify rising stars.

• 1:10:41Speaker 01

  So 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, you know, code commits and all, all kinds of things, but those are gamable in, in various ways. And, and, and so you, you really want to look at kind of here, 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, or, you know, better, um, kind of collaboration across the team. And, and, and again, you're right, because we, we have, you know, Signal, because we're a very digital, digital company, we're able to pull that. But, but I think every company has, you know, Signal in various ways.

• 1:11:23Speaker 01

  I mean, I, like, I think that you're going to just be able to see, if you're a supermarket, you've got cameras that are, that are seeing things. You're going to see the person who like sees the spill on the floor and cleans it up. Like a manager may never see that, but the camera did. And, and if the AI can say, hey, but that, that person just cleaned up a spill without having to be asked, like, of course, we should be rewarding that stuff. Now, now there's plenty of Black Mirror, kind of horrible ways that this stuff can go wrong. And, and we're not, like, we're, we're, we try to, we're very privacy, you know, respecting. We're not, we're not, we're not trying to, like, it's not a gotcha thing. Um, but, but it was remarkable how much better, you know, 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, and then what I can do as a leader is go to those people and say, hey, you're

• 1:12:08Speaker 01

  doing a great job. Keep doing it. By the way, I, you know, if you, 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, you know, next leaders at, at the company. And so I, I think that there's an, that, again, it goes back to one of the real values that these systems have, which is AI has bias, but it's uncorrelated to all the rest of the bias in the organization. And so that provides a, a, an independent outside lens that helps you then better run your organization in order to make smarter decisions. And whether that's around, you know, internal audit functions, or that's around identifying, um, you know, great talent, um, the, these tools are, are various ways that you can, that you can do, um, you know, pretty amazing things.

• 1:12:50Speaker 01

  And in our case, like, 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 were some people that said, like, this person's a huge star. And then you actually look down, 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, you know, great to be able to recognize them.

• 1:13:21Speaker 00

  Do you think being managed in, in, in automated or a quantified way will dehumanize or depersonalize your, your workforce? Because you can, you can see how management by robot does get pretty black.

• 1:13:32Speaker 01

  Yeah. I mean, and, and 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 AI system is better able to say, hey, Matthew, CEO, you know, here's this 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, but that comes back to the, the leadership. Like, don't be a bad organization.

• 1:14:17Speaker 01

  Be organized around trying to do the right thing. Like, celebrate your employees, make them, make them rich. Like, I mean, it'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.

• 1:14:37Speaker 00

  Let 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, and values. And a thing that really struck me at our last conversation was that you, you came to that realization that was emergent as you began leading CloudFlare. 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? Because there's something big in there.

• 1:15:10Speaker 01

  I, I really don't, I, I think it is incorrect to say that we've automated the management function. I think that what we have done.

• 1:15:16Speaker 00

  We're collecting a bunch of data on whatever everyone's doing. We're measuring it perfectly and then we're calling the customers.

• 1:15:20Speaker 01

  I don't, I 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, we're making managers better at their, at their, at their jobs.

• 1:15:44Speaker 00

  And that scales management, right? Actually, it's, it's funny, you, you mentioned that you're up to like 12 direct reports. The last time you said.

• 1:15:50Speaker 01

  We're not, we're not, we're not there yet.

• 1:15:51Speaker 00

  We're not there yet.

• 1:15:52Speaker 01

  We're headed there, so, yeah.

• 1:15:54Speaker 00

  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 Decoder 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, are you there? Are you at 50?

• 1:16:09Speaker 01

  Well, no, no, no. I, I think, again, I, I, I, I really do think that humans are social creatures and we want, 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, in your head, which is supposedly something like 120. But people should have, you know, friends outside of work, so you can't just occupy those all with, with work colleagues. So if I said eight before, that was wishful thinking. We were probably close to six. And we, 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 don't, you also don't want people playing games with that, where they're like, we're going to build out a big team of people, where we don't need a big team. So, so I think you've got to be, like, I think that can be aspirational and directional. But, but I don't think, I don't think you can be religious.

• 1:16:53Speaker 01

  Like, I don't think you can just say, oh, everyone has to have at least 12. Like, you've got to, you've got to figure out, you know, where that makes sense and where it doesn't make sense. And, um, and again, as that, as that, as that evolves, I think that there, there's a, there's a big piece of it. But you have to also have some foundation that aligns people. And that's where mission, you know, comes in. And it's absolutely true. Like, our, our mission in the beginning was, you know, take advantage of this, you know, interesting kind of market opportunity, hopefully make some money and impress our parents so that they'd get off our back about, you know, why we didn't go work at a bank or whatever. And, um, and, and I, and I, 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, um, that we realized that our mission was really to help build a better internet.

• 1:17:38Speaker 01

  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's, what's 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, I like, there's, there's a lot of days that, that, 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, that I can't imagine anything that's more exciting to be working on.

• 1:18:08Speaker 00

  Well, 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 Decoder.

• 1:18:14Speaker 01

  Thanks for having me.

• 1:18:18Speaker 00

  I'd like to thank Matthew for joining me and thank you for listening to Decoder. 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 [email protected]. We really do read all the emails, or hit me up directly on Threads or Blue Sky. 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. Decoder is a production of The Verge and part of the Vox Media Podcast Network. Shows producers are Greg Ott, Kay Cox, and Nick Stat. 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.

• 1:18:59Speaker 02

  Support for the show comes from EY. In today's landscape, enterprises must navigate an increasingly complex ecosystem of AI technologies. EY.ai, the re-imagination engine, gives organizations the confidence to reimagine their enterprises and realize value at scale. The difference isn't just the technology, but the intelligence surrounding it. By combining AI, technology, and people with trusted experience, EY helps organizations turn AI ambition into enterprise value. Because AI is only as valuable as the hands that shape it. Go to ey.ai to explore more.