Can Cloudflare save the web from AI?

21:25Nilay Patel:But the only thing – the only comparison I'm making here – Is it better for you to take the annuity of payments over the course of the next 50 years or to take the lump sum up front? That's the tradeoff that they're making. But there's more money going into music creation at this point in time than there ever has been at human history. And so technology is not inherently a destroyer of value of information. In this case, it has been a massive enabler of value in this and allowed people to find audiences and, yes, sell more tickets to their concerts as well. 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 music and then give that back to musicians based on some sort of algorithm that hopefully rewards where there's actually a real value which is created.

22:15If you had the same thing where a portion of what is being paid for for the various AI companies, well, you had to pay for the researchers that built the AI systems and you had to pay for the chips, but also to pay for the 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.

22:34Nilay Patel:Yeah. 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. 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 gonna 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 so Spotify again This was fascinating Dan 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 are 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.

23:21And so they know that whatever they return is a pretty bad result. But the interesting thing is what happens next, which is they take them those searches for things that they don't have good results to do. And they publish that back to music creators. And I think that there's something that's pretty amazing about that, which is they're saying, here's an emotion that someone is searching for, which we don't have a good answer for, which we're then going to go and publish back to music creators. And there's a guy who, if I remember the story correctly, is in Denmark, who makes, and again, this is one of those moments where everyone's going to be like, I'm in the wrong profession, 40 million euros a year writing songs for unfulfilled Spotify queries.

24:02And he's not alone. He's the most successful. But there's a whole bunch of people that are making literally millions of dollars or millions of euros a year doing this thing where they're writing songs for what people are searching for that aren't there. Now extrapolate that to the next level, which is to say, for the first time in human history, we've built a mathematical model of human knowledge. That's what the LLMs are. And we know where they know things, but we also know where they're missing things. I picture like a giant block of Swiss cheese. And there's a lot of cheese, but there's a lot of holes in the cheese.

24:31And 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 example that this is actually working is, you know, my wife and I own a small local newspaper in Park City, Utah, which is our hometown. I think we will make more money off AI licensing deals this year than we do off digital advertising.

25:05And 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 artificial general intelligence, you need to know what the hot new restaurant is in Park City, Utah.

25:38And if you don't have access to the Park Record, our newspaper, you don't know that. And so what I think is interesting is we're not going to protect all media in the same way that the move to Spotify, there are a whole bunch of losers in the musician space, But there are going to be new winners like that person in Denmark who's creating things off of unfulfilled Spotify queries. And I tend to think that the winners in what this new space might be might actually be the kind of things that people really want to come back to media. More local news, more unique things, more Reddits of the world, right?

26:11More of what the internet used to be, you know, when I was first on it in the 90s. 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 we have today, which is a media ecosystem that is largely just rage baiting people into clicking on things so that they can serve them an ad.

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28:04Nilay Patel: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 is yet another lawsuit, right? The music companies are going to sue Anthropic. The White House came out 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.

28:36Nilay Patel:Yes. We're going to use the law to say this is illegal and we'll punish you if you do the bad thing. That's just up for grabs. Those are 50-50 and maybe existential. I mean maybe not. 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 the judge basically said that training is fair use against all the books. And by the way, you shouldn't have stolen the books. That was bad. But if you hadn't stolen the books, if you actually bought the books, then it would be OK.

29:07And that was a valuable enough result for Anthropic that they settled the rest of the case for$2 billion, which is a lot of money, even for Anthropic. And so I –

29:21Nilay Patel: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. Different regulations are going to be passed in different places around the world. So I – and again, as a also recovering intellectual property attorney, like I very quickly go to like, oh, let's just use intellectual property. But like that's such a kludge versus the much easier thing, which is let's just use technology. And, you know, identifying – I remember sitting with a bunch of media execs and they're like, oh, how are we going to stop these nerds in Palo Alto from scraping our stuff?

29:58And I was like, you know, I go to war every day with like North Korean and Iranian attackers and the Chinese. Like they're really good at it and they hide. Whereas like the nerds in Palo Alto have a Delaware-based C corporation. like it's pretty easy to identify them versus the others. And it's really difficult for them at scale to hide 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 being taken.

30:40I think that that was an interesting question like two years ago. But, you know, even the Googles of the world who've been at times challenging through this because Google, you know, they're sort of like a Marvel film, like the hero of yesterday becomes the villain of tomorrow. Like the challenge has been that they're like, we struck all these deals to get access to all the Internet and now we can use it for whatever we want. And we kind of were like, 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've been really actually impressed with the Google team is that they are much more willing to engage here.

31:18They understand the value of the ecosystem. There are people at Google who really do believe in making sure that there is a healthy, sustainable ecosystem going forward. And I think already some of the things that they've committed to around transparency of their crawler and some of the things that I expect that they will do over the next little bit, I think that that's actually a good sign. And it's going to make it so that, you know, if even Google is doing it and is willing to say, I'll announce what I'm doing. And in many cases, I'll even be willing to pay for content. I think that's actually just makes it even easier to convince all of the other AI companies to do the same.

31:52Nilay Patel:Do you think you need to turn the screws all the way and actually block the Google crawlers to get them to pay? As of September 15th, we're going to set the defaults across all of our free customers for it to be that Google is going to be blocked for AI training. But if they won't differentiate between AI training and search engine training, we're just going to block them across the board. Even if you're a site owner, you're like, I don't want that to be for me. We'll make it easy for you to turn it off. It's just about what we set the defaults to. But I'm really encouraged that Google is, that the sort of good forces at Google are realizing that this has to be a healthy ecosystem.

32:28And 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.

32:41Nilay Patel: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'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. All you publishers are complaining. You got super addicted to my firehose of traffic, and you have no leverage. You built no audience of your own. You didn't do anything. Look at all of these other platforms that I have to compete with. TikTok showed up and YouTube had to compete with them. ChadGBD showed up and the search team had to compete with them.

33:13Nilay Patel:And 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. Steve at Reddit has really become more aggressive. And Google doesn't work if it can't search these things. And it's actually more existential for them. The very nature of how Google search ranking works is it builds a tree, right? That's what page rank was. It sort of says, OK, here's a super reputable thing. And then let's see how it's connected to everything else that's online. The problem is with Cloudflare, again, 20 % plus of the internet, if that just disappears, that's in a giant hole in the middle of the tree.

33:52And so it doesn't just break it for this. It breaks it for everything. And I think that that's what we sort of realized that on behalf of and in conjunction with a lot of our customers, we can say, listen, this isn't fair anymore. You're creating costs. You are taking content. You are getting value from that content either in terms of the subscriptions that you're selling to your AI tools or to the ads that you're running against that. And that's just not a fair give to get anymore. And so the deal has to change. And so I'm really proud of the fact that we've played a role in helping the publishing industry go from what was two years ago when I had dinner with Neil from People.

34:35He's like, woe is me. What are we ever going to do? And I'm like, I think we can fix this. And now, like the last time I saw him, we gave each other a high five and said, I think we're making progress. And the deals that large publishers are doing are significantly better. And now I think the question is, how do we bring that to the rest of the internet? Because if we don't, we have this massive tragedy of the commons problem where it's just going to be take, take, take, impose costs, impose costs, impose costs, 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 the new local restaurant is, for creating local news and local media, for being an academic.

35:12If there's not some way that you can do those things and still eat, still make enough to eat, then people aren't going to do it. And that harms us all. And again, I've been very critical of Google over the years. I will say that their tune appears to be changing over the last few months. And I believe that at their core, they really do understand that this is an ecosystem, that they play an important role in that ecosystem, and that they need to give back to that ecosystem and play by rules that allow the ecosystem to flourish.

35:42Nilay Patel:You said Google's going to make some changes soon. What changes would those be? 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 the web. And I think that they, for a lot of technical reasons, pushed back and said, you know, that actually is incredibly inefficient. You don't want to – we now have to crawl twice. That's going to put twice as much load on everything that's out there.

36:14What 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 this is, and put that together. that they have signaled that largely in response to what was a ruling out of the United Kingdom, that they were going to put 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 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 great.

36:51Nilay Patel:I could argue with you about the music industry all day and all night. I think you know that. But it is true that changing access and copyright law and all that stuff around music industry changed the business, right? The incentives to put on shows and do residencies and all that changed because of the distribution changing. That I think we can 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.

37:19Nilay Patel:You run a local paper, maybe your people are publishing restaurant reviews that are best ingested by an LLM and spit out. Yeah, or instead of reviewing a hotel, review every hotel room. For every word that appears in a story in the New York Times, that reporter has written down probably 100 words somewhere else. That's all that other metadata, which traditionally has been constrained by how many column inches you had in the physical paper or how much attention a human would actually spend on that. Imagine if you could say to the LLMs, like, hey, listen, we're going to sell not just – and again, there's all kinds of things around protecting sources and there's stuff you have to get right.

38:01But if you get it right, there's an enormous rich source of a catalog of additional information. For every picture you see in a magazine or a newspaper, there are probably 50 or 60 that were taken of that same thing. And that's all valuable to these AI systems that are out there. So I think there's a lot of ways that we can imagine how as – there's just a bunch of content that's literally being thrown on the floor today that actually can be incredibly valuable.

38:27Nilay Patel:This is my universe. I feel confident about this one. 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 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 LLM, it will change the thing that we made, right?

38:59Nilay Patel:Because its distribution will necessarily change and its intended audience will change. Like maybe the biggest decoder trope of all is that your distribution inevitably changes the thing you make. And at the end of the day, maybe my future is just making YouTube face slinging AG1 and that is the future of all podcasting. There's just some force of distribution that changes the thing that you make. Is the outcome you're describing good? Where we're just making an infinite flood of information, GEO optimized for some human to consume digested by a chatbot in the middle? Well, so I think that, so first of all, is the current model good?

39:35You know, I mean, I've talked with lots of people at your parent corporation. And again, I think you guys do a good job. There's a lot of media that today was just how do we create content as inexpensively as possible?

39:49Nilay Patel:Sure. And then A-B test headlines in order to either stimulate a dopamine or cortisol response to that. If only the media was that scientific. But a lot of it is. I mean, I've sat with some of the folks from Huffington Post, some of the folks from BuzzFeed, where they were like, yeah, that's the game. And that's the game that we play. And again, I don't know that that's a game you play everywhere, but you can even see – you can track the New York Times. You can track the Wall Street Journal. You can track the FT and just watch how much more inflammatory and almost tabloid-ish the headlines have gotten over the last 20 years.

40:28And again, I think that those are still – every one of those is an amazing media organization. But in order to win in this space, it's been how do I provoke really a deep –

40:40Nilay Patel: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 it's shaping the content. So I'm asking you about the new distribution that you're describing. But let's just frame that 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 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.

41:17And 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 led to the rise of sort of very destructive populism around the world, you know, much less sort of real intellectual debate. So what could we move to? And again, I think there's a lot that can go wrong here. But what if you talk to Sam at OpenAI or Dario at Anthropic or you talk to the teams at Google that are building the AI systems at DeepMind and others? What do they really want?

41:54They 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 it either. And the best evidence of this is actually how some of these distribution deals have been done. So the New York Times, amazing media organization. and Reddit, also an amazing media organization, have about the same amount of tokens in that.

42:31The 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.

42:45Nilay Patel:Just to be clear for the audience, you're using tokens as a measure of amount of new content. Of content. Yeah. Content that's in there. And again, It's not just new content, but it's the legacy content as well. And so the question is why? And again, this is deeply unfair to the New York Times. But if you don't have the New York Times, then you can just license the Wall Street Journal and ask AI to rewrite it as if it's a New York liberal. And you get the New York Times. Deeply unfair. Except that all of these media publications, the major media publications, have made their business of telling the exact same story to their individual tribes.

43:18Whereas Reddit, like Reddit, if you don't have Reddit, there's no substitute for it. Reddit is this unique thing that's out there. And so I think a media of the future that looks more like truly unique kind of storytelling around, again, local communities, unique stories that no one else has told, real knowledge creation is what is valuable and is proven valuable by the market that exists today.

43:41Nilay Patel:But the other side of that market, just to be reductive here to so I understand the model, the market, the buyer in this market is a bunch of model companies. It's not people. 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 you don't have the latest information, then what's been amazing is it doesn't appear like any of these model companies on their own is going to run away. People are like, oh, well, what if OpenAI gets AGI? I'm like, two days later, Anthropoc 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.

44:22And then it won't be – AGI won't be enough. It will be AGI Plus or AGI Plus Plus or whatever. So what I think is going to be interesting is what is it that's going to turn these things from commodities into actually sticky products that people sell? And I think the answer is going to be who has access to the most true knowledge that gets you the right answers. And so that seems like all of the incentives from the end consumers are to say, I want to get as much back to the creators of real knowledge as I possibly can. I'll tell you, the financial piece, I think we can solve the financial piece.

44:57The piece that I'm actually much more worried about, and again, this comes out of this conversation. You should have Daniel Ek on the story because he's fascinating to talk about these things. But he, um, like he's 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 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. Um, it's by the way, it's a stupid strategy.

45:28Being rich and anonymous is the best story. Right. 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 Academy Awards, but some sort of recognition where we use math to measure who created, 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.

46:22I 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 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.

46:45Nilay Patel: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 essentially make it harder for sites like Stormfront, which is a neo-Nazi website, to exist. And you had a lot of – 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 are the consequences. But there should be some frameworks to regulate your power. Many things have changed.

47:15Nilay Patel: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? but it's a power of a layer of the internet that is pretty dominant 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? You know, I think 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, I think, a very human reaction.

47:51And it's often my co-founder, Michelle, who's like, Like, listen, I realize all the hard, thorny moral questions, but this is per se bad. We should do something about it. And I think we have largely come out to say, you know, it's tough. Like we don't want to be the ones that are deciding what's good and bad. 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 there's less incentive to create these various things? And what I found interesting about the question of what the future business model of the internet is going to be is it's sort of the first time I've thought, wow, maybe instead of trying to kind of deal with bad site here or there, which is basically like just cutting down dandelions.

48:42Like more are going to 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 buy nutritional supplements or whatever. All these things are very weird business models that are 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 maybe that's actually getting at what is the fundamental kind of roots that are there.

49:21And maybe I'm too much of an optimist, but I think the way that you stop a lot of, again, 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 today. And that we get away from what has been very much an attention-based economy to one that is much more of an information and knowledge-based economy. And so as we're thinking about, like, what does the future of the internet look like, that's what we're playing for.

49:53Nilay Patel:So it's the same power, right? Cloudflare has a lot of power on the internet, right? It's a platform layer. It has a lot of influence. You're able to stop things. In the case of the neo-Nazi websites, you declined to use your power, right? No, no. I mean, we kicked them off our systems. Yeah. 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. Yeah, I mean, they're all still around. So at some level, it shows that it's limited. But in this case, you're going to use your power. You're going to say, we will use Cloudflare to stop things from happening, and that will create a market.

50:28I guess the question is power. So it takes five minutes to sign up for Cloudflare. We have a free version of service. It takes 30 seconds to leave. So if we're ever doing something that's not in our customers' interest, we'll lose our customers. And so we are very much at the service of our customers. And I remember the first time that a media company called me and said, we have this new threat. You have to stop it. And I was like, what is the threat? And they're like, it's the AI companies. I mean, I rolled my eyes. I was like, that's the dumbest thing I've ever heard. Why are all media companies such Luddites?

50:59But 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 that was worth us spending our time and our resources on fighting it. So, you know, again, I think that 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 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?

51:37Nilay Patel: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? I think each of those things is sort of a moment in time. 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, when we made the decision around the daily storm, no one knew what Cloudflare was. And we were seeing a bunch of regulation that was happening online that really could have been a real threat to the underlying way the internet worked, regulating kind of key protocols like DNS and TLS.

52:19And 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 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 itself. But if you're going to use something as a means to an end, like to make a point, you know, Nazis are pretty fun to use for that point.

52:59And so I think we were able to make the point. We were able to sort of change the policy discussion. We were able to talk about what the challenges were and we could do it. So today, if the exact same set of facts came up, it just wouldn't be the exact same set of facts. Because today, obviously, CloudSolar is much more known. We've had those policy conversations. And that doesn't mean that, you know, it kind of feels like every five years, you know, another one of these things pops up. So we're probably due for one sometime soon. I think that the situation behind each of them is going to be very, very different.

53:42This is advertiser content from EY Global. Hey, everybody.

53:48Nilay Patel:This edition of Decoder Sessions features Andrew Melnazac, 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. Let's talk about EY AI. What is EY AI bringing to my enterprise? 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 reimagination engine, which has got our technology platforms, our deep industry expertise, our deep domain knowledge, and our training and our personnel that we bring to the clients to fundamentally reimagine that process that is out there.

54:31Nilay Patel: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. 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 are 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 reimagining that business and what it could be in future, and then looking at how AI can help you get there.

55:13That's the fundamental thing.

55:25Nilay Patel: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? Totally, yeah. So the big decision you recently made in May, you laid off 1 ,100 people, which you said was about 20 % of the company.

55:53Nilay Patel:How many employees is Cloudflare today? Somewhere between 4 ,500 and 5 ,000. So you're growing compared to two years ago. You very openly attributed the layoffs to AI usage inside the company. And I know that's true because you literally published an op-ed in the Wall Street Journal. The title was How I Choose Which Employees to Replace with AI. I didn't get to choose the title because, again, the way media works today is they rage-rate the titles, but yes, but I wrote the rest of it. The op-ed supports that title. 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 editor.

56:27That was the headline.

56:29Nilay Patel: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 broke people into builders, sellers, and measurers, and you're basically going to cut all the people who did measurement, all the audit functions. Not all, but a lot. Yeah, yeah. It certainly is. The majority of the people that we laid off came from that category of – and this is – Saul comes back to some old school basic business research, which is that there are three functions with any firm.

57:10There are people that build things. So the engineers, the product managers, the folks that actually create new products. The people that sell things, the people that are out there actually doing the deals and selling those things. And then the third category is what a lot of every organization is, which is the people that actually measure things. And again, I think each of those is going to be impacted by AI in very different ways.

57:30Nilay Patel: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, the builders. And all of those roles are totally scrambled. They're all kind of doing one of their jobs. That's true. I do think that there's a sort of increasingly jack-of-all-trades kind of aspect to this where because you can have these tools, someone who's a product manager can do a lot of what engineers do. Someone who's an engineer can do a lot of what product managers do. And the people that are winning in that space are the people that are sort of ambidextrous.

58:10They can do multiple different things out there. But where I get lost with some of the sort of AI maximalists who are like, we're all going to lose our jobs. If I can hire a builder and they are now 10 times as productive, which they are. I mean, it is wild to watch how much more productive the builders on our team are today. I'm going to hire as many of them as I can because I've got lots of stuff to do. And so that hasn't decreased the incentive for hiring engineers and product managers and everybody else. It's actually increased the incentive because the return that I get for the salary dollars that I spend on one of these people is now essentially 10 times as much.

58:53And so, of course, I'm going to hire as many as I possibly can, which is exactly what we're doing.

58:57Nilay Patel:So just walk me through this decision. You woke up one day and said, I've got a – it's Peter Drucker, I think, is he quoted. Yeah, it's sort of the builder-seller measure. framework comes out. For the decoder heads out there, this is like old school management philosophy. How did you make this decision? You were like, I got to do this. I'm going to sort these people into these categories and we're going to start making cuts. Do you see any evidence in the data? Walk me through it. We saw a number of different things. So one thing that we saw was that the world was sort of dividing into two camps.

59:30One camp, which tended to be sort of two different demographics within the organization. It was either people were very, very senior or people who were very, very junior. And those folks were like adopting AI like crazy. The junior folks, because they were just native to it. The senior folks, because they had the confidence to kind of bet their career that these paradigm shifts would be a way for them to kind of learn new things and take on new challenges. And they were confident enough in their jobs that they could do that. The other camp was sort of, you know, the folks who were kind of earlier in their career, they might not have been the most senior folks, but they weren't just the brand new folks who had come in.

1:00:10So they'd come through and been trained and sort of been taught that the way, the way you succeeded a business was by playing by a certain set of rules. And then all of a sudden they've, they watched around them as their colleagues were all of a sudden, you know, using these new tools that were, that were out there to be able to deliver these things. And the, 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 just the best people at using manual screwdrivers to screw screws into wood.

1:00:42And then all of a sudden we invented an electric screwdriver. Eric came along. We were able to buy it. And for most jobs, not every job, but for most jobs, using the electric screwdriver is just better. And you can get a lot more done with it. And, again, the people early in their career were the ones who adopted it or the people who were kind of late in their career were adopting it. And so the first thing that we sort of started to do back in the middle of 2025 was say, hey, guys, this is what's going on. And I understand all the incentives, if you're kind of in that second camp, are to fight against the electric screwdriver.

1:01:12But let's give you the resources to train you. Let's give you the confidence that you're going to have a job and you're going to do these things. But let's make sure that everybody across every role is learning how they can do that. And I think that that's just a really important step that you have to do in the first part. What we then learned, though, is that as we got everyone, not just the engineers, but people on finance and legal and everything else to start to use these tools, we found that one place where AI just shined was in measuring things. And I think one of the places where we don't talk about the advantage of AI enough are that AI is bias, but the biases are uncorrelated to the rest of the organization typically.

1:01:49Whereas humans have biases like crazy, but a group working together has biases that are massively correlated together. Even if you're working on internal audit and you're supposed to be kind of the bad guy who's looking over everyone's shoulder, you still go to lunch at the same cafeteria. You talk to the same people. You participate in the same all hands. You end up developing the same biases, whereas AI doesn't. It has a very different set of things. And so we found that we could use these tools in order to do things significantly more efficiently. So there's a woman on our team named Heather.

1:02:20Heather 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 they worked like crazy to generate all of the kind of information. They basically took the measurements and then generated documents that we would then distribute during earnings to all of our investors. And Heather was like, I think we can use tools to do this better. And so we took what used to take two weeks and we reduced it down to three minutes.

1:02:51And our investors are like, wow, these documents are much better. There are fewer errors. There's, there's, there are less mistakes we've, you know, and our, and our tools are auditing all of, all of those different things. And so for those 20 people, like we looked for other places for them, but a lot of them, what they liked doing was that sort of work. And, 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.

1:03:19And so, yeah, there was things like internal audit, which we were able to just get actually much more efficient at doing. There's also things like middle management, where traditionally the Harvard Business School number is that on average, you should have every manager have six direct reports. We found with tooling, we could actually be much more efficient with managers, and that the right number for us started to feel like when we enabled managers to have more tools to better participate in surface issues early and see how their team was doing, then we could get up to like 12 on average direct reports and everyone's actually happier in doing that.

1:03:54And why that matters is because as you increase the number of direct reports, what you actually do is decrease the amount of hierarchy in any organization. That's the way of measuring how flat versus how hierarchical an organization is. And so again, we could use these tools to say, hey, let's flatten the organization, which has made the organization much faster and more nimble. But in the process, there are a whole bunch of middle managers that just weren't the right folks. And so I think we sat there and we were like, gosh, we know we've got to get rid of these jobs. And so the question is, do we do it now or do we do it later?

1:04:26And the problem with doing it now is like, we feel very exposed. We feel very alone. Like, I mean, the number of death threats that I got, not even from our employees, but from just random people who are sort of anti-AI was really, I mean, pretty scary. But at the same time, we're like, is it kinder to say, we're going to make these changes now? and then do the work to not only give great severance and everything else, but actually go place these people because they're great people. Place them at other positions around. And we've been very successful at doing that across the board. Or is it better to kind of cover our own ass, wait until everybody else in the industry is sort of saying – is coming to the same conclusion?

1:05:06And by the way, that's coming. Uber just did a layoff, same rationale. you're going to see across the industry, not just in tech, but everyone start to get to this realization. I think we were early, but is it going to 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.

1:05:40And that I think is what real leadership is. And I think a lot of, when I talk to a lot of my peers, they're sort of sitting around saying, yeah, I know we need to do this, 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 yeah, there's a lot of things about the economy that are going to change. It doesn't mean jobs are over. We're going to hire as many builders and as many sellers as we possibly can.

1:06:07And there are still some measures on our team. Some people have to build the tools and do those things. But what it's going to look like going forward is going to be very different. And once you realize that as an organization, I think the sooner that you can do that is the kindest way that you can be to your own team.

1:06:23Nilay Patel: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? Well, the first thing is we've flattened the organization a lot. There's a lot of middle management that went away. And not just because we laid people off, but there's a whole bunch of managers that 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.

1:06:51I mean, 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 there's so much more leverage that you can have. And I think that what is a manager versus what's an individual contributor is going to 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 one thing because, you know, even individual contributors now are managing a fleet of agents that are working on their behalf.

1:07:21And so I think the biggest thing is that we've flattened the organization, you know, quite a bit. And then I think the other thing is that 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 XYZ company OS, whatever it is. But it's a set of tools that essentially takes a bunch of just the knowledge that's inherent to Cloudflow, 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 a wide range of the different tools that are out there.

1:07:59but then continuously is pulling and updating the information about what has to be true and having it so that when you want to figure out what information is pulling out of Salesforce or Workday or any of the systems of record that we have at Cloudflare, being able to pull that into one consistent interface has just allowed our teams to be significantly more productive and much better at cross-collaboration.

1:08:23Nilay Patel:There's something here which maybe is just the nature of a software company, and that's the way it is. And 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 could be measured by an AI and then the AI can tell you these people are the rising stars.

1:08:53Nilay Patel: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? Because that seems to be the challenge of how Silicon Valley might see the world and how every other business might see itself. Yeah, I mean I think we've all at various times worked in jobs where we're like, gosh, I'm just not being recognized for the hard work that I'm doing. or other times where you're like, I'm kind of like over-recognized and I'm not, and maybe I don't.

1:09:28I've never felt over-recognized. If I could get some more, that'd be great. You're doing a great job.

1:09:35Nilay Patel:Now, can you get your chat bot to tell me I'm doing a good job? Because that'd be really good. So I think that the, again, 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 for a million different reasons. Maybe they were part of the organization that we just didn't recognize enough. Maybe they didn't have a great manager. Maybe they didn't have things. One of the things that's great about these tools is you can find different ways to say, what do we as an organization value? And then look more broadly across who are the people who are really performing incredibly well.

1:10:15Nilay Patel:But that has to be legible to the system, right? So it's like the AI is going to watch every code commit and say that person is doing a lot or that person is the nicest to their agents in Slack. You have to watch them in some way to get that data back out. There's all kinds of signal that is inside of every organization. I'm 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. 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.

1:10:48I mean, obviously, you know, code commits and all kinds of things, but those are gameable in various ways. And so you really want to look at kind of this person did this thing and then trace it all the way through the organization. And what did that result in either higher revenue or lower cost or, you know, better kind of collaboration across the team? And again, you're right because we have, you know, Signal because we are a very digital company. We're able to pull that. But I think every company has, you know, Signal in various ways. I mean, like I think that you're going to just be able to see if you're a supermarket, you've got cameras that are seeing things.

1:11:30You'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 if the AI can say, hey, but that person just cleaned up a spill without having to be asked. Like, of course, we should be rewarding that stuff. Now, there's plenty of black mirror kind of horrible ways that this stuff can go wrong. And we're not like we're we try to we're very privacy respecting. We're not we're not we're not trying to like it's not a gotcha thing. But it was remarkable how much better I found it at being able to say, wow, there are some people across the team who might be very junior but are just way outperforming.

1:12:05And then what I can do as a leader is go to those people and say, hey, you're doing a great job. Keep doing it. By the way, here's my cell phone number. Call me if you ever need anything. And we're just watching a bunch of those folks turn into the next leaders at the company. And so I think that there's an – 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 independent outside lens that helps you then better run your organization in order to make smarter decisions.

1:12:39And whether that's around, you know, internal audit functions or that's around identifying, you know, great talent, these tools are various ways that you can do, you know, pretty amazing things. 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.

1:13:11And then you actually look down and you're like, no, they're not. But, but for a lot of times there were people who, who, who really were, you know, incredible, incredible stars. and it was great to be able to recognize them.

1:13:21Nilay Patel:Do you think being managed in an automated or quantified way will dehumanize or depersonalize your workforce? Because you can see a management by robot does get pretty black. Yeah, I mean, I think that's a decision. Like if every promotion decision is made by some totally unaccountable AI system, that seems wrong. But on the other hand, if an AI system is better able to say, hey, Matthew, CEO, 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. I think that's actually incredibly humanizing.

1:14:03That means that you can be seen for the contribution that you're doing. And again, there are lots of ways that bad organizations will use these technologies to do bad things. But that comes back to the leadership. Don't be a bad organization. Be organized around trying to do the right thing. Celebrate your employees. Make them rich. I mean that's exactly what you want. And again, I feel like we've become a better organization, better at recognizing where talent is, better at then being able to reward that talent and invest behind that because of these various tools.

1:14:37Nilay Patel:Let me connect that all the way at the beginning. I asked you, how do you make decisions? And you said you start with mission and values. and a thing that really struck me at our last conversation was that 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 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.

1:15:10I really don't. I think it is incorrect to say that we've automated the management function. I think that we have done. I mean, we're collecting a bunch of data

1:15:17Nilay Patel:on what everyone is doing. We're measuring it perfectly and then we're calling the customer. 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 making managers better at their jobs. And that scales management, right? Totally. It's funny you mentioned that you're up to like 12 direct reports.

1:15:49Nilay Patel:By the way, we're not there yet. You're not there yet. We're headed there. Two years ago, you said your number was about eight, which you called high. So you're going from eight to 12. Mark Zuckerberg is at like, we should have 50. And I keep saying Dakota has a long life ahead of it because it's a show about org charts. We're on the cusp of the weirdest org charts in history. Are you there? Are you at 50? No, no, no. No, I think, again, I really do think that humans are social creatures and we want to be able to know people. And the Dunbar number is real, which is the number of direct social relationships you can keep in your head, which is supposed to be something like 120.

1:16:23But people should have friends outside of work so you can't just occupy those all with work colleagues. So if I said eight before, that was wishful thinking. We were probably close to six. But we are making our way up and so we're probably closer to eight-ish now, but we're headed more towards 12. But I think you have to be very, very specific because you don't – you also don't want people playing games with that where they're like, well, I'm going to build out a big team of people where we don't need a big team. So I think you've got to be – I think that can be aspirational and directional. But I don't think you can be religious.

1:16:53Like I don't think you can just say, oh, everyone has to have at least 12. Like you've got to figure out where that makes sense and where it doesn't make sense. And again, as that evolves, I think that there's a big piece of it. But you have to also have some foundation that aligns people. And that's where mission, you know, comes in. And it's absolutely true. Like 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.

1:17:23And I think that it was only as we started to serve our customers and we saw just how important the internet was and how it really lacked defenders. There weren't a lot of people who were kind of fighting for it that we realized that our mission was really to help build a better internet. And if you talk to anyone at Cloudflare, anywhere through the organization, any country that we're in, any office that we're in, I think that what I find amazing is time and time and time again, they come back to saying the reason I work here is because I believe that the mission is one of the most important things we can do.

1:17:54And that's – I mean, like there's a lot of days that people are like, why do you still work at Cloudflare? Because I can't imagine anything more important right now than helping build a better internet. And I can't imagine anything that's more exciting to be working on.

1:18:08Nilay Patel: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 you even faster than I did last time. Thank you so much for being on Decoder. Thanks for having me. 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.

1:18:33Nilay Patel:Drop us a line at decoder at theverge.com. 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. The show's producers are Greg Ott, Kate 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. Support for the show comes from EY.

1:19:01Nilay Patel:In today's landscape, enterprises must navigate an increasingly complex ecosystem of AI technologies. EY.AI, the reimagination 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.