The Shifting Value of Content in the AI Age with Cloudflare CEO Matthew Prince

0:05Matthew, thanks so much for being here. Thanks for having me. So I want to get like right into the juicy topics, but make sure our listeners understand like the scale and like her role of CloudFore first. So correct me if I'm wrong in any of this. $66 billion market cap company today, about$1.8 billion in trailing revenue, and then like the biggest CDN by far with a bunch of different products now in security in particular. Like what else should our audience understand about the role CloudFore plays? Not to nitpick on one thing, but we've never really thought of ourselves as a CDN. We started out very much as a security company.

0:43The whole thesis was, could you put a firewall in the cloud? We saw that servers were going to the cloud. We saw that software was going to the cloud. It seemed inevitable to us that the networking equipment would go to the cloud. And the big objection that everyone had was you were going to slow things down. And so we worked very hard to figure out how could we not slow anything down. And the goal was just to get back to parity. It turned out we were a little too good at our jobs and everything got a lot faster. And so, yes, we've ended up competing in the CDN space. But really what Cloudflare is is what the network should have been, what the internet should have been had we known in the 60s, 70s, 80s how important it was going to be.

1:18So how can we make it faster, more reliable, more secure, more efficient, more private? And that fundamentally is what we're working on every day at Cloudflare. How long has it been since you guys started the company? We launched in September of 2010. So we'll be coming up on our 15th year in September of this year. And I don't think there's a way to ask this question without somewhat trivializing the journey. But how did you become so dominant? I don't know. I mean, I think we just focused on how did we do the right thing for our customers? How do we solve the problems that were there? And at some level, the story of Cloudflare is that we have been customer zero along the entire journey.

2:01So every thing that started from could we take a firewall, put it in the cloud, how would we get the data to populate that firewall? We had to have a free service. Once we had a free service, all of a sudden we had to be able to figure out how to scale enormously across millions of customers in an efficient way. That meant that we had a whole bunch of weird stuff that was using us. We got attacked by every which direction. We had to build a public policy team in order to deal with those issues. We had to build our own security. We like someone almost hacked or stole our domain at some point as a way of hacking into us.

2:36So the next thing you know, we built our own registrar. And so to some extent, Cloudflare has been about, you know, start with a relatively simple idea, make it as broadly available as possible, and then solve all the problems that become sort of inherent once you've done that. Now you're in the position that I believe you've described as like the Internet's traffic cop. I think a lot of people feel with the sucking sound of attention toward AI assistance that the shape of the internet is changing. What is your – before we go to like point of view on what to do, what is your prediction for what's happening?

3:10So no matter what, the dominant kind of value creation model of the last 30 years of the web has been search. Search drove everything. It drove all of what you did online. Entire industries grew up around that. And the real three ways that you could derive value on the web in the past were you either sold a thing, whether that was a subscription or a product or something else. You sold ads against some content. And I didn't say the business model, but I said the value creation model because the third part is really important, which is a lot of people just created content for the ego of knowing that other people were doing it.

3:52The old adage is there are only two reasons why people create content, to get rich or to get famous. A lot of people are just doing it to get famous. And that's a lot of what drove – I mean, that's what drives Wikipedia. That's what drives a lot of content creation that is on the web. I think that the web is shifting now to a new interface. It's shifting away from search and it's shifting to AI. And we can see that through the trends in terms of Google usage. We can see that in terms of like our own usage where more and more people are turning to these AI systems where they used to turn to Google.

4:24Even Google itself is sort of morphing into an AI company kind of in their interface before our eyes. And as we do that, the natural thing that's going to happen is we're going to consume derivatives rather than consuming the original content itself. A study that just came out from Pew Research that says that if Google puts an AI overview on the top of search, it is much less likely that people click on the links. And that seems sort of like a duh. But the data that we have also substantiates that and shows that compared with 10 years ago, it's become 10 times harder for the same piece of content to get a click from Google than it was before.

5:09And that's because the answer box, that's because of AI overviews, that's because the search interfaces has gone there. And that's the good news for content creators. In the case of someone like OpenAI, it's 750 times harder than it was with the Google of old. With the case of Anthropic, it's 30 ,000 times harder than the content of old. And so what I worry about is that if the value creation model of the web has been all about how do I get traffic, the new interface of the web isn't going to send you traffic. And if that's the case, if content creators can't get value from selling a thing or a subscription, selling ads, or just the ego that they get knowing someone is reading their stuff, I worry that people aren't going to create content.

5:56And that's going to really not only starve the web, but it's actually going to starve even the AI companies that are using that content as effectively the fuel for their engines. How do you think that evolves? Because if you look forward, the other thing that people are talking about a lot right now is agents and the fact that you're not only getting information through an AI, it will actually go into actions on your behalf. So the time you actually spend on the web is going to go down effectively, or at least you're going to be dealing with one interface, which is this agent that goes off and does things in the background for you.

6:22So do you think that ultimately the AI companies will start paying for content? Do you think there'll be other ways to monetize it? Do you think it's a completely different model starts to emerge in terms of how the web works? There are going to be different solutions for different pieces of the equation. At some level, agent kind of commerce is going to be probably the easiest of these to solve, where there are going to be certain companies that say, listen, we'd love your agent to come and buy a widget from us. There are going to be others that right now are aggregators of information that the agents can actually disintermediate or disaggregate that content.

6:56And they'll be actually quite threatened by that. But ultimately, I think commerce agents and AI is probably ultimately pretty good. To separate commerce from content and content is what you're worried about. Content is a different piece where content, the problem right now is the default assumption has been that you get content for free. And it's actually interesting. A lot of the content creators are looking to the law as the solution to this. And generally, I'm a recovering law professor. So pardon me for going down this weird tangent. But it's actually, I think, really interesting, which is in copyright law, the more that you are a derivative as opposed to a direct copy, the actually – the safer you are, the more likely you are to fall under fair use.

7:41And we've actually seen a number of court cases, two that happened here in California that happened within a week of each other, one of which basically said AI uses of content is fair use. The other one which said it wasn't. There's going to be a whole bunch of things around that. But probably the more sensible one is the more that you're creating derivative content, the less likely it is to be a copyright violation. But kind of opposite of that, the more that you're creating derivative content, the more likely it is that someone isn't going to go back to that original source. And so I actually worry that a lot of the content creators are focused very much on what the law says today and on copyright law, which may not come out in their favor because it is actually protecting those derivative uses.

8:26I think what we have to figure out is probably a different business model where content creators get compensated. And I think the good news is as you talk to the big AI companies, and 80 % of the major AI companies are Cloudflare customers, so we have good relationship with them. We talk to them about it all the time. What they all say is you're absolutely right. We should be paying for content. The devil is in the details, though, because what they all are desperately worried about is how do you make sure that it's a level playing field? They all believe their technology is the best. They all believe that on a level playing field they're going to win.

8:56But they're really worried, well, if Google still gets content for free but we have to pay for it, that doesn't seem fair. Or if I'm paying for it, but somebody else gets it for free, that doesn't seem fair. So what we've been really working on is how can we create that really level playing field? And we think if that's the case, that AI companies will actually be quite willing to pay for that content. What are the approaches you've been taking to try and level the playing field here? So in order to have an economy, you have to have a market. In order to have a market, you have to have scarcity.

9:20Like no markets exist without some level of scarcity. And the problem right now with content is that content, there is no scarcity. They're giving it away for free. And so we spent the last year working not only across Cloppler's existing customers, but then going across the entire publisher ecosystem writ large, not just print publishers, but video, audio, music, film, across the entire spectrum. and saying, we think that there's a problem with AI, that it's starting to actually take value and not give you anything back. And across the board for every publisher from the Associated Press to Ziff Davis and everything in between, we've seen just incredible resonance with that message where they're all saying, you're absolutely right.

10:01Our business is getting astronomically harder over just the last six months, and we're seeing less and less of our existing business model working. So we need to do something about that. And so what we did on July first was we announced what we called the content independence day, where you could actually have independence from these AI companies. And we, for free, across all of our customers, whether they paid us or they didn't pay us, we started blocking by default any training that was being done by any AI companies that was there. And it was really important that we focused on that because that meant that we could treat Google the same as everyone else.

10:35Now what we're doing is we're working with the IETF and other standards organizations to say, let's define how you have to announce what your crawler is doing as it behaves online. And we're really encouraged by the early work that's there. As that happens, we think we'll be able to set in place really fine-grained permissions for content creators or anyone else to say, humans can get my content for free, but robots have to pay for it, and then figure that out. That first step of creating scarcity is what you have to do in order to figure out what the market is. And then after that, I think figuring out the market, that's going to be what takes some time.

11:13And I think we're still experimenting with different different things. That's super interesting because if you look in the sort of search precedent, we had a robots.txt file. And that's where you kind of specify whether a search engine could come and crawl the content. And it sounds like you're really extending some of those concepts on through to the AI layer. Yeah, that's right. And I think robots.txt was a relatively simplistic and blunt tool where today it basically says you can either allow something or disallow something. And you can basically do it either – you can do it on a directory on your site or to the entire site.

11:48But there's not that sort of fine-grained control. And so we think robots.txt is sort of like the street signs that are on the road. A lot of people don't necessarily follow the speed limit, though. And we actually see plenty of examples. In fact, some really prominent companies that do some very, very, very shady things where they basically say, absolutely, we follow the rules of the road. But when push comes to shove, if it turns out they're blocked, then all of a sudden they're doing a bunch of things that look not dissimilar to what we see Russian hackers or Iranian hackers do in order to try and get around those blocks.

12:22At Cloudflare, we're really good at identifying that and stopping it. And we're also really good at embarrassing those companies that do that. So watch our blog, and I have a feeling that some prominent AI companies that are misbehaving are going to get called out pretty soon. What do you think that should the idea of a marketplace for contributing to training work out? What do you think that does to the landscape of the types of content companies that win or lose? I can't imagine it's going to look like it does today because there's some notion of incrementality. I mean, this is going to take us down a little bit of a tangent, but I think a lot of the things that are wrong with the world today are ultimately Google's fault.

13:03They're not the worst actor. I'm glad we started with we're all friends here, and then it's all Google's fault. Yeah, it's all Google's fault. I think Google has been a net force for good in the world. I think that they actually believe in ecosystems. I think they're trying to do the right thing. But they taught everyone to worship, if they're content creators, sort of a deity which is traffic. And that was the proxy for value. It was how do you generate the most traffic? And that led to Facebook as the next iteration. It led to TikTok. It led to folks like the Huffington Post, which would literally write a piece of content and then A-B test headlines trying to figure out which one generated the largest cortisol response to get the most clicks.

13:43Or if you guys remember demand media. Demand media. Yeah, I mean, BuzzFeed, I mean, there's a whole bunch of folks that were just trying to figure out how do we actually stimulate rage and get people stirred up so they'll click on the thing so that I can either sell them a subscription or sell ads against a piece of content. And again, I think that that led to a lot of me-tooism. That led to a lot of people writing the same story with sort of a slightly different bend. I don't think it led to a lot of us actually figuring out how to advance human knowledge. And so what I think is interesting is if you think about the AI companies en masse, they're a relatively good approximation for the sum of human knowledge.

14:26Not perfect, but probably the best we've ever had, right, where they come together. And the reality is that they are in aggregate. They're like a giant block of Swiss cheese where, yeah, there's a whole bunch of cheese there, but there are holes in the cheese as well. And their very algorithms, as they come across a piece of content, they prune off that content, which is already kind of part of the meaty part of the cheese. Whereas the parts that are in holes are actually super valuable to them. And so I actually think that if we could create a market where you're rewarding content creators not for who stimulates the most cortisol, but who fills in the holes in the cheese, and you actually pay people for that, that that is a better outcome.

15:14And that's actually advancing human knowledge. And that's really amazing if we can - Isn't that kind of arguably companies like Mercor or Surge or Scale, as they do data labeling and they hire human experts to basically fill out content areas for AI companies. So do you basically view this as like a distributed model of that or sort of a web-based - I've spent the last year talking to a lot of people. One of the more interesting conversations that I had was with Daniel. I flipped to Stockholm and saw Daniel. And I think there's really nobody who has compensated content creators at scale like Daniel has.

15:48And it's amazing. The day before iTunes launched, the music industry was about an$8 to$9 billion industry. Spotify on its own today pays out over$10 billion a year to the music industry. And so done right, these can be very much pie expanding. There's plenty of cheese to go around if we do this correctly. And the thing I remember he was telling me a story, which I thought was sort of in the same vein, which was Spotify actually looks at queries that people have run that they don't have good answers for. Where there's, you know, somebody searches for, I don't know, I want a disco song about like how fun it is to dance with your dog, right?

16:31I don't know. And if somebody searches for that and it doesn't get it, they actually publish that list back to content creators and musicians. And there are several musicians that are making literally tens of millions of dollars a year just writing songs for what people care about listening to. Unmet demand. That are unmet demand. Yeah. And so I think that it's not exactly the same as data labeling. I think it's actually saying like for the first time in human history, we can actually very accurately identify where there are holes. It's the very nature of the pruning algorithms that these LLM models are trained on.

17:04And that we could then, if we sort of basically resurface that and say, hey, we don't have enough articles about the wing-toed ferret, that people will actually go out and do that. And that if we can then compensate people on that, that actually is much better than yet another article about what's happening in Washington, D.C., yet another article about how much San Francisco is on decline or on the rise. I mean, again, that's not actually adding to human knowledge. That's just rage bait effectively. How do you think that plays out as... So if you look at some of these labeling companies that also then hire experts in to provide some of the at least expert content that you mentioned, if you look at some of the models like MedPalm 2 from Google, which is a couple years old now, it outperformed human physicians, the average human physician in terms of output.

17:51So if you rated its output against people, at what point do you think we've run out of good content from people? In other words, there is some limit. I don't think that's true. I mean, I do think that there will be some – like there's always going to be people running new experiments and new tests and finding new things and new discoveries. And yeah, maybe we can imagine some distant future where it's all robots that are doing this in the labs. But that's a long way it's off. And so in the meantime, I think we can do that. My black mirror kind of version of the future though is actually one where we're not going to get rid of journalists.

18:26We're not going to get rid of scientists. We're not going to get rid of researchers. You're going to still need that work. What I worry about is if we don't figure out how to compensate broadly content creators who are independent, that we actually go back to almost a time in the Medici, where the web had historically been this incredible sort of distributor of value creation and knowledge creation. You could imagine a world in which all of a sudden you have five big AI companies. You have the conservative one and you have the liberal one. You have the European one and the Chinese one. And they all actually hire and run their own team of journalists, researchers, academics, the experts that fill in the holes in their cheese.

19:10And again, that's not too hard to imagine that in some not so distant future that becomes a thing. What I hope is that we figure out a way to compensate independent content creators and share that knowledge across all of them as opposed to creating these silos of knowledge behind each, you know, variation of an LLM. Do you feel like the large labs agree with you on how much can be paid out to creators to fill those holes? Because, you know, you look at the scale of ad revenue, you know, I mean, even ignoring things like commerce and whatever from the open web. But, you know, in aggregate, like what's been paid to labeling companies, like$10 billion less.

19:51We're like really far off if people are starting with a very large free today base. Well, again, I'm not sure labeling companies is the right – is labeling companies the right model or is it, you know, GPU spend or is it employee spend? You know, I actually think, you know, first of all, the amount that's paid to labeling companies will go up. the amount that's paid to employees and then GPUs is continuing to go up. And so the question is, how much value is content actually giving you? And the answer is somewhere between zero and 100%, right? And is it more or less than another unit of GPU time?

20:34I mean, there's a market that can figure that out. From that first principles view, I see it. Yeah. And so there is some value which is there. I think the mistake that a lot of content creators did was they actually did deals that don't scale as the business models of the AI companies scale with them. So if you do a deal that's like$20 million and you get all my content, that's an incredibly naive deal. It might seem like a great deal to the content providers day one, but it's exactly the opposite of what you want to do. What you really want to do is say, OK, if you imagine that there were a way for all of the content that is available, you say, here's how much that is creating value.

21:17That's going to be some percentage of whatever the subscription fee is for your AI model or if you're an ad-supported AI in the future, it's going to be some percentage of that. And then as the AI companies grow, which will inherently then mean the ad revenue shrinks, that you share in that upside as your downside gets diluted. And I think that there's still going to be advertising out there. There are still going to be subscriptions. There's still going to be tentpole content that people just have to consume even if they're AIs. But what you also want to do is allow that content to get into the AI systems and the content creators should get compensated for that.

21:56And again, if there's scarcity, a market's going to determine how valuable that actually is. One of the things that Cloudflare is known for, to your point, is really speeding up webpages and the internet. And as we shift from serving pages to sort of models being run, you're kind of shifting from a world of caching and serving pages to inference. How do you think about that in the context of CloudFare or some of the directions that you all are going? Well, I mean, I think we leaned in heavily. I mean, nobody remembers this, but back in 2020, we partnered with this, you know, graphics chip company in order to put GPUs at the edge of our network in order to allow people to do inference.

22:36And by the way, it was crickets. Like, you launch this product, no one responded. There wasn't a single, like, sales inquiry to use it. And so we apologized to the partner who happened to be NVIDIA and it kind of went on our way. Now, four years later, the market was ready for it. We basically just took out the same press release and issued it again. And then it's taken off like gangbusters. I think that we've leaned in heavily to – we believe that a lot of inference is going to happen on your end device. But there will always be some model which is too big or too resource intensive. And in that case, the next best place to run it is going to be on – at the inside the network at the edge.

23:13And that's what we're delivering. More importantly, I think that if you look at whether it's MCP or whatever the next protocol that connects agents to services and allows these things to connect, inherently because of how much of the internet we sit in front of, they have to pass through us. And so we're investing heavily behind those protocols, making sure that they have all of the security, the underlying rails and payments infrastructure and everything else that you need. And my hunch is that what we solve in the content space and the rails that we create for the payments there very naturally then become one of the models to do sort of agent to agent over MCP or whatever the final protocol becomes payment infrastructure to be able to handle that as well.

24:02So Cloudflare fundamentally is a network. And I remember when cryptocurrency and blockchains and everything, we're getting big people are like, aren't you worried about this? And I'm like, they still need a network. As AI gets big, they still need a network. And so I think we sit in the center of this. And as you especially have more agent-to-agent communication, I think the network actually becomes more and more important. Is there a bet you're making on what changes in terms of models or compound systems? that drive more model traffic to the architecture you described, where it's in-network versus in large data center today?

24:40I wish I could say we were that strategic. I mean, I think we go to wherever the market demands that we go. Including build a neocloud. I don't even know what a neocloud is, but sure. So I think we're fundamentally always just trying to say, how do we respond to whatever either our own team needs as customer zero or what our customers need. And the fact that, again, 80 % of the AI companies are using us, they are constantly pushing us to, can you do this? Can you do that? And I think our team has been uniquely good at being able to execute and innovate and stay at least up with whatever the trends are.

25:21And that's, again, I think I'm proud of the fact that we have ended up in a lot of these conversations and that so much of the internet does flow through us that one way or another, I think that we end up being in the center of a lot of these transactions. Does that imply any particular belief around open or closed models as people continue to develop capabilities? We have closed models that run on us. We have a lot more open models that run on us. We have historically been a company that believes very much in open source. And most of the things that we build internally, as long as we can, we try to open source all of that technology.