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Go to UI.AI to explore more. Hello and welcome to the Coder, I'm the lab editor and chief of the Verge, and Coder 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 West joined us in the show about two and a half years ago, but 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.
CloudFlare found a june that bots now make up more than half of their traffic, a number that just keeps going up is more and more AI companies straight, more and more of the web. And now is more and more people send AI agents out to do things for them in 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 the spots, what kind of mess they're making for 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 is an answer to something I'm still thinking about well after we had this conversation. Matthew is also at the center of another important AI debate.
Earlier this year, CloudFlare laid off more than 1,000 people, 20% of the company. And Matthew wrote an op-ed about that decision, which ran in the Wall Street Journal under the headline, how I choose which CloudFlare employees to replace with AI. That is pure decoder debate. AI, big controversial decisions, and worksharts, 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, or you put out new episodes every Monday and Thursday. Okay, Matthew Prince, CEO of CloudFlare. Here we go.
Matthew Prince, CEO of CloudFlare. Welcome back to Decoder. Thanks for having me. I'm really excited to talk to you again.
It's been about two years since we're on the show. I was just looking back for that episode, and I said something 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. Let's start at the very beginning. CloudFlare is a complicated, important company.
The last time I 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? That's usually when I'm trying to answer a question at a cocktail party and I don't want to talk to a person anymore. I say if I actually sort of interesting to talk to the person more, 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, you know, where we're 350 cities, we're wide, you know, 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, you know, write applications that can scale to an entire internet audience and run on the infrastructure that we have as the fastest one part of our business. 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.
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 don't want to talk to me in the cloud so far. 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. 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 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.
We all think about it for the search business that they have, but they really built out all of the ecosystem around advertising online, they got double click, they built things like Google Analytics that lets you actually see who is coming to your property. And they really are the hero of sort of what I call the first generation of the internet and first generation of the web. What's changing though, very quickly, is who is actually using the web or what is using the web. Last November, I was at the web summit, the big European Tech event.
I was asked, when do you think that non-human traffic agents and all those things are going to pass human traffic online? We had a lot of data because we see a huge percentage of the internet, so we pulled all that data and looked at it and said that it would be the second half of 2027, automated traffic would become larger than human traffic, which was kind of a big deal. We can see that first time in history. I was asked again in South by Southwest in March of this year of 2026, and we pulled the data again and it had moved up, where I was going to then be the first half of 2027.
We were like, wow, this is growing. I mean, this AI thing is a big deal, and people are using like crazy and striving a huge amount of traffic. And so I was stunned when just a few months later in May, 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.
If you extrapolate that out with the giant caveat that I've run wrong so far in every prediction that I've made on this, but five years from now, we think that automated traffic will be a thousand times human traffic online, not because human traffic is going to decline. We think it'll stay kind of around the same. But because we're just seeing such an explosion in all of this, the rest of the traffic. And the challenge of that is if you have first of all, a thousand times more traffic, someone's got to pay for the infrastructure to power that.
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 happen. And the traditional model of how to pay for that, which was advertising, doesn't work for 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.
When you describe it 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. I think there's certainly a lot of revenue. Well, maybe for the Cloudflares in the Google's world. But for the end-froppics of the world, $10 billion of revenue in a single month.
So 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 with 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 you need is chips. You need the ability to actually 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 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 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 don't maybe get that away for free humans, but if a bot is coming for it, then bots have to pay for it because they don't have that traditional give to get. We can't put an ad in front of them and have that be something that allows me to help pay for the content creations there. And so what we're seeing is actually going back to some of the original protocols of the internet, 403 protocol, which was written in the very first version of Netscape, was actually payment required. And you actually have to pay for that content that you're receiving.
And that's something, actually, we have to say 4, 364, too. 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 are doing things online, anyone who's putting a website up to say that in exchange for that, thousands and thousands of times more traffic that's going to come to you, you're not going to maybe get the advertising revenue that comes from it, but maybe you can get a fraction of a penny every time somebody actually accesses that information. And where does that fraction of a penny come from? It comes from the feed that people are going to be paying for their AI agents and other systems that are really similar to how a Spotify or Apple Music works today.
I like that we're less than 10 minutes in and we're already at the 1996 dream of micro payments. We're going to stick with that for one more turn here. What I said is this 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 the bots will come and find it. And yep, the 4.2 protocol will come back to life and we're going to do crypto micro payments using Stripe Power by Cloudclare. That's a version of the future that many people have talked about for a long time. The incentives to stand all that up on the web is the thing that I'm worried about when I say there's a business model and customers in 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 my way and monetize a TikTok audience. That seems like a really big inflection point right now at the second. You mentioned Google and I've asked you know about this many times.
The incentives to put new information on the web just seem to be in permanent decline. It just doesn't seem like a good idea anymore. Where on the flip side, the web is an application program. It's like absolute apex.
Every new app that comes out is a web app or if it's a desktop app, it's just a electron. There's something happening with the web is an application platform that is incredible and something happening to the web is an information platform that is devastating. You're trying to connect those dots. You're trying to say we can change the incentives over here.
What's a version of the future? Maybe it's a transaction that is not where the incentives to make the web an information platform are as good as you do. You've illustrated what is tough to reconcile with the economy that's happening right now. You look at things like publicly accessible data on Wikipedia contributions.
It's down significantly because people are like, what's the incentive to put information on Wikipedia? Something that again, people are doing for a lot of different reasons. I think the problem there is back in the day, if you were contributing to Wikipedia, you knew people are at least reading Wikipedia. Now the interface through which people consume that information isn't going to Wikipedia itself.
It's just reading the answer through whatever answer you're using, whether that's open AI, chat, GPT, or anthropic cloth or Grock on X or whatever it is. That means that the editors of Wikipedia are saying, maybe it doesn't make as much sense for me to do that. The flip side of that is the web as a whole, actually they've been declining since about 2012. The web grew like crazy in the late 90s and through the 2000s.
And then starting around 2012, you really saw it plateauing and actually decreasing up until about 2025, where something flipped and starting in October of 2025, driven a lot because of the various web 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 wrapper around what is fundamentally a web application. And the growth of the web itself with really high quality stuff and a lot more people contributing to it is faster today than it's been at any time since the early 2000s. And so that's the tension between those various things.
I think what's unique about Cloudflare is that because we sit in front of so much of the web, more than 20% of the web, we have the ability to overcome some of the incentives problems that you have. And so we can very quickly turn something on and say, okay, for a fractional, you have to pay a fractional penny in order to get access to this information. And that can kickstart what I think is the beginning of what we need. And again, the problem is if you don't have something like that, we face a massive tragedy to comment from.
So let's say today I ask, I don't know, whatever my favorite AI agent is, where should I go to lunch? I mean, if I was doing research, I might go look at a couple of different menus as an individual. My agent today goes and scans every single menu in the local area in order to figure out what's going on. And again, only one of those places is going to actually get my lunch dollars.
And so if that just expands infinitely, there's no cost of doing that, like at some point my agent is going to look at literally every piece of resource, every resource that's available everywhere on the internet, and then come back and say, you know, you should go to Wendy's. That's an enormous waste. And so we've got to have something which is actually saying that there's a cost every time you load a webpage. There's bandwidth, there's servers, there's things that are behind that.
And someone has to pay for that. If it's not going to be advertising and it's not going to be directly commerce, then there has to be something that actually puts some constraints there. And I think where we're in a good place to say is like, yeah, it can be a tiny amount of money, a thousandth of a penny or something like that. But that's enough that we can actually start to say, okay, that will help pay for the infrastructure.
And then if you have incredibly valuable content, you know, if you're a news publisher or you're an academic, then 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 for it. In order for that to happen, I think again, you've got to have a player like us that's in a market that can kickstart that. But I think once you kickstart it, we've seen it from the side of the buyers, the big AI companies that they're all willing to do this.
We've seen it 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 links those things together. And again, that's what we're spending a lot of time actually building. Here it feels like the theoretical underpreting of this conversation is the very notion of scarcity itself.
An old copyright lawyer in copyright law for years and years and years had just a built-in mechanism to be important, which was that one copy of a CD was one copy of a CD. And if you wanted another one, it's 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 it was hard to distribute them. And all of that went away with the internet.
We moved everything into digital files and the burden of making another copy fell to zero. And I think a bunch of consumers expect everything to be free. There's a famous quote, information wants to be free. There's a second half of that quote everyone forgets, which is information also wants to be expensive because it's hard to generate.
And the internet just turned that upside down. The gating mechanism of physical media, which provided some scarcity and thus some economic value that you could measure one away. And we decided information should be zero and maybe supported by advertising. It was actually a tension that became valuable because that was scarce in its way.
You're talking about imposing scarcity with your technology. We always talk about markets needing supply and demand. That's not exactly right. You need demand for sure.
You want infinite demand ideally or as much demand as you can get. Infinite would probably be bad because you'd be hard to discover price. But you want demand. And then you want actually some constrained supply.
There's no market for error where either of us are sitting right now because there's plenty of error. But if we go scuba diving, then all of a sudden there's a market for error because error is constrained under water and so you have to buy it in order to do it. The music I think is the example that I look to when I think about what could this look like in the future. I flip to Stockholm to meet with Daniel Akk who started Spotify.
And it was just a fascinating conversation because if you think about the history of music, once upon a time the majority of music sales was from CDs or albums or whatever it was. And then along came the internet and along with it, Napster and Crockster and Kazah and all of the things that essentially commodified music and made it available for free for everyone. And even if you're an incredibly law-abiding human, the majority of people were actually just downloading music because they wanted access. If you go back 23 years ago, the music industry as in total was about $8 billion, which is a lot of money, but it's not a lot of money for the entire music industry.
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 to right now, Steve Jobs steps on stage and announces iTunes and then it's going to be 99 cents a song. They're including cover art and they're going to make sure it's high quality and all these things.
But mostly to appeal to this emotion of you should be paying for music. Now, that's not the business model that won. But it was a flag in the ground that said that this information is actually worth paying for and it's really valuable. And it was the iTunes that then eventually began to get the Spotify to the world.
And the incredible thing is, just last year, Spotify sent something like $12 billion back into the music creator ecosystem. And we can debate whether the right people are getting it, whether it's fairly allocated. This is my favorite thing that I get back. 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 turn there, which I think is fascinating and is either good or bad, is that the amount paid for music, the music files themselves became very small. You can get a million streams on Spotify or not making any money, but the amount generated by touring and commercial sponsorships. And that's the thing licensing to advertising, all skyrocketed.
That's just simply not true. Why is private equity buying all of the music catalogs for hundreds of millions of dollars? The answer is because actually making money off the streaming of the music is extremely lucrative. And again, Spotify alone is sending $12 billion back to the music industry, back to the actual rights holders behind these various things.
And so there's way more money coming from Spotify into this than there is from touring or any of the other things. Those are other ways to make money, but actually it's the streaming that is really driving all of the real growth. Sure, but I just want to draw a distinction here. You're not going 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. They're paying some of the catalog holders for some of the things that money flooding in. If the Rolling Stones or whoever used the lights once they sell their music catalogs had held onto the music catalogs, then the musicians would have made that. They're making the determination.
And by the way, when they sold the rights, they got the check. The only comparison I make in the gallery is it better for you to take the annuity of payments over the course of the next 50 years or take the lump sum up front. That's the trade-off that they're making. But there's more money going into music creation at this point in time than there ever has been in human history.
And so technology is not inherently a destroyer of value of information. In this case, it has been an massive enabler of value in this and allowed people to find audiences and sell more tickets to their concerts as well. But I think 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 real value, which is created.
If you had the same thing where a portion of what is being paid for for the various AI companies, well, you had to pay for the researchers that built the AI systems and you had to pay for the chips, but also to pay for the content, which is actually the real knowledge of this 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. Yeah, the comparison I'm making is not whether a bunch of aging rock stores are going to sell their catalogs and cashwaxs or that's fine. They can do that.
It's more that the shift you're describing into gating access, and so wide open access on Spotify every sign I made, and we're going to move some pennies around and some people get rich and will create some winners and losers. Fundamentally change the entire business model with music. Spotify, again, this is fastening, it's a conversation with Dan, it's fastening. 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, is they take them those searches for things that they don't have good results to, and they publish that back to music creators.
And I think 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 in the wrong profession, 40 million euros a year writing songs for unfulfilled Spotify queries. And he's not alone. 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 they're writing songs for what they're making.
And so we're going to talk about the next level, which is the first time in human history, we've built a mathematical model of human knowledge. That's what the all-arms are. And we know why are they no things, but we also know where they're missing things. I make sure that the 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, 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 my wife and I own a small local newspaper in Park City, Utah, which is our hometown. I think we will make more money off AI licensing deals this year than we do off digital advertising. And the reason why is because local media is exactly the sort of thing that is much more valuable in kind of the media world that we're going into, but was completely decimated in the media world that we're 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 partner restaurant is in Park City, Utah. And if you don't have access to the park record or 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 they 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 Reddit's of the world. More of what the internet used to be when I was first on it in the 90s. I think that that's actually what most internet users are craving.
And I think that as 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 that is largely just rage-baiting people into clicking on things so that they can serve them now. Support for the show comes from UI. 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 reimagination engine, comes in. EY.AI, the reimagination 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 client's unique environment.
Through globally connected and orchestrated solutions, EY.AI, the reimagination engine, helps organizations scale AI from isolated investments into a connected enterprise-wide intelligence capability, given leaders the confidence to reimagine the enterprise and realize value at scale. Go to EY.AI to explore more. 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 music companies are going to see went through, 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 it in some series of corporate mergers. The Virgis parent company is not 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. 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 upper grabs. Those are 50, 50, and maybe existential. Maybe not. I think that the law right now, at least in the US, in the US is different than everywhere else.
You guys have a patchwork around it. The best case on this is probably in the drop-out case, where the judge basically said that training is fair use against all the books. By the way, you should have stolen the books. That was bad.
But if you hadn't stolen the books, you actually bought the books and it would be okay. That was a valuable enough result for entropic that they settled the rest of the case for $2 billion, which is a lot of money, even for entropic. When you're building technology, you're keeping that in the back of your mind. The market is coming to some sort of understanding what's valuable, what's not.
You need to stop them from showing up. Different regulations are going to be passed in a different place around the world. Again, as a recovering intellectual property attorney, I very quickly go to it. Let's just use intellectual property.
That's such a cluge versus the much easier thing, which is technology. Identifying, I remember sitting with a bunch of media execs, and they're like, oh, how are we going to stop these nerds and Palo Alto from scraping our stuff? I was like, I go to war every day with North Korean and Iranian attackers and Chinese. They're really good at it.
They hide, whereas the nerds in Palo Alto have a Delaware-based C corporation. It's pretty easy to identify them versus the others. It's really difficult for them at scale to hide from us. 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 tell you exactly what we're doing, so that you can have the right to control how that information is being taken.
I think that that was an interesting question like two years ago. Even the Google's the world, who've been at times challenging through this, because Google, they're sort of like a Marvel film. The hero of yesterday becomes the villain of tomorrow. The challenge has been that we struck all these deals to get access to all the internet.
Now we can use it for whatever we want. We're kind of like, in the past, you were sending people traffic. Now you're training on things and sending them no traffic. That's a different give to get.
What I've been really impressed with 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. 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's a good sign, and it's going to make it so that even Google is doing it and is willing to say, all announced what I'm doing.
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 the other AI companies to do the same. Do you think you need to turn this series 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, whether 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, which is going to block across the board, even if you're a site owner and you're like, I don't want that to be for me.
It makes it easy for you to turn it off. It's just about what we set the defaults to. I'm really encouraged that Google is that good forces at Google are realizing that this has to be a healthy ecosystem, and that they have to play by some of the same rules for this new market, which is AI that everyone else is playing for, and that they can't leverage the monopoly that they had in search yesterday to create a monopoly in AI tomorrow. I was talking to a student about this many times.
I don't think he loves the fact that the person keeps calling it Google zero, but so be it. As soon as 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 your publishers are complaining.
You got super addicted to my virus of traffic, and you have no leverage. You built no audience of your own. You didn't do anything. Look at all these other platforms that I was competing with.
Tech Doc showed up, and I YouTube had to compete with them. Chat to be showed up, and the search team had to compete with them, and you did nothing. This feels like this something. 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. I believe it read it has really become more aggressive. Google doesn't work if it can't search these things.
In addition, the very nature of how Google's search ranking works is to build a tree. That's what page rank was. It says, here's a super reputable thing, and let's see how it's connected to everything else that's online. It probably is a cloud flare again, 20% plus of the internet.
If that just appears, that's in a giant hole in the middle of the tree. It doesn't just break it for this. It breaks it for everything. I think that's what we 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 the ads that you're running against that. That's just unfair give to get anymore.
The deal has to change. I'm really proud of the fact that we played a role in helping the publishing industry go from what was two years ago when I had dinner with Neil from People. He's like, whoa, is me? What are we ever going to do?
You can fix this. Last time I saw him, we gave each other a high five. I think we're making progress. The deals that large publishers are doing are significantly better.
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, the comments problem, where it's just going to be take, take, take, impose costs and post costs and post costs. The incentives for actually creating things, for contributing to the Wikipedia 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. If there's not some way that you can do those things and still make enough to eat, then people aren't going to do it.
That harms us all. 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. 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 play by rules that allow the ecosystem to flourish.
You said Google doesn't make some changes soon. What changes will this be? I think the thing that they've already committed to is just a lot more transparency on what their crawler is doing. What we had pushed them to do is split their crawler apart and say we're going to crawl for AI separate from crawling for the web.
I think that for a lot of technical reasons, push back and said that actually is incredibly inefficient. You don't want to, now I have to crawl twice. It's going to put twice as much load on everything that's out there. What if instead, when our crawler comes to a page, we'll announce what it's doing and then give you the ability to do something to say no, no, that's not allowed, but this is and put that together.
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. They wouldn't just do it in the United Kingdom, but they'd actually do it on a broader basis. 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. I could argue with you about the music industry all day and all that.
I think you know that. But it is true that changing access and copyright law and all that stuff from music industry changes the business. The incentives to put on shows and do residencies and all that change because of the distribution changing. That I think we can generally grant.
You're describing an information market where the incentives will shift again. 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 now.
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 LMs, like, hey, listen, we're going to sell not just any kind of things, there's all kinds of things around protecting sources and stuff to get right. If you get it right, there's an enormous rich source of catalog of additional information.
Every picture you see in a magazine or a newspaper, they're probably 50 or 60 that were taken of that same thing. That's all valuable to these AI systems that are out there. I think there's a lot of ways that we can imagine how there's just a bunch of content that's literally thrown on the floor today. It actually would be incredibly valuable.
This is my universe. I feel confident about this one. I was in a packaging meeting today for whatever of our big stories. We had a pretty fulsome debate about the lead image in a story we were on in a few weeks.
We disagreed. We picked one or a picture 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 it's distribution, won't necessarily change.
And it's 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 slim age one, 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 is the current model good. I've talked with lots of people at your parent corporation.
Hey, you guys, do a good job. There's a lot of media that was today. It was just how do we create content as inexpensively as possible? Sure.
And then AB test headlines in order to either stimulate a dopamine or cortisol response to that. Only the media was that scientific. A lot of it is. I've sat with some of the folks from Huffington Post and the folks from BuzzFeed where they were like, yeah, that's the game.
And that's the game that we play. You can even see you can track the New York Times, you can track the Wall Street Journal, you can track the FT, and just watch how much more inflammatory and almost tabloid-ish the headlines have gotten over the last 20 years. And again, I think that those are still, every one of those is an amazing media organization. But in order to win in this space, it's been how do I provoke really a deep?
What you're describing is they're playing to their distribution, which is largely social media. 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. As Ben Leuver said, it's great. But Google gets Facebook, which gets TikTok, which has us in this attention economy whole, 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 led to the rise of sort of very destructive populism around the world, much less sort of real intellectual debate. So what could we move to? And again, I think there's a lot of them go wrong here.
But what if you talk to Sam at OpenAI, or Dario and Fratvik, or you talk to the teams at Google, and they're building AI systems at DeepMind and others, what do they really want? They want new, true knowledge. They want the thing that nobody knows about yet. They want the story about the interesting thing that no one else is covering.
They want that thing which is actually advancing human knowledge forward. That's what I want to read too, right? I don't actually want to read yet another take of what happened in the Trump White House today. There's plenty of that.
And they don't want it either. 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 it. The New York Times has been publishing for a lot longer, 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. Just be clear for your image. You're using tokens as a measure of amount of new content.
Content, yeah. Content content that's in there. And again, it's 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 Aye 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, 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. But the other side of that market, just to be reductive here to sign up for the market, the buyer in this market is a bunch of model companies. It's not pure. But then ultimately the customers are 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, you know, opening an eye gets AGI? I'm like, two days later, and it's radical at AGI, and then, you know, Grog will have a couple days after that, and Google have a couple days after that, and then it will be AGI, it won't 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 is going to be, who has access to the most true knowledge that gets you the right answers? And so, like, that seems like all of the incentives from the end consumers are to say, I want to get as much back to the creators of real knowledge as I possibly can. I'll tell you, the financial piece, I think we installed the financial piece. The piece that I'm actually much more worried about, and again, this comes out of this comment, you should have Daniel on the sort of fascinating talk of this.
Like, you've been thinking a lot about how to get content creators paid. You say, 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, had to cause musicians to rank, which one is more important, fame probably beats rich. It's by the way, it's a stupid strategy being rich and anonymous, it's the best.
Sorry. 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 is because people don't get recognized as much, because you're not going to the original sources.
And so I think 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, you know, contribute 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 can get disseminated, might be removed from the original research. It might be the AI, 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. The last thing we're on, we spent a lot of time talking about content migration, and Cloudflare using its power on the internet to, you know, essentially make it harder for sites like Stormfro which means you're not supposed 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 them off as about it. We talked about it for a while and eventually you came to decide, you don't want to be a business with these folks and 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 the layer of the internet that is pre-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 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. And it's often my co-founder Michelle who's like, listen, I realize all the hard work or any 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 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 various things?
And what I found interesting about, you know, the question of what the future business model of the internet is going to be is sort of the first time I thought, wow, maybe instead of trying to kind of deal with, you know, bad site here or there, which is basically like just, you know, cutting down dandelions, like more 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 in the not-seas is one of the most effective ways to just really, this people off, and they tend to click on your things. And then buy nutritional supplements or whatever.
I think they're 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, 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, 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 extension-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?
It's the same power, right? You have quite far as a lot of power on the internet, right? It's a platform layer of influence you're able to stop things. In the case of the neo-nauts websites, you decline to user power, right?
We kick them off our systems. You can't have cloud-flared protective from DDoS attacks, and then maybe they're just going to do DDoS to do whatever. They're all still around, so it's somewhat like it shows that it's limited. But in this case, you're going to use your power.
You're going to say we're actually, we will use cloud-flared to stop things from happening, and that will create a market. I guess the question is, you know, power. So, you know, it takes five minutes to sign up for cloud-flared. 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. 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 company. And I rolled my eyes.
I was like, it's the dumbest thing I've ever heard. Why are all media companies such as Luddites? But then we pulled the data. And we saw that really, again, 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 a really privileged position because we have provided so much value to start. 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? It's 26th. The valence of speech on the internet has changed. If you had to make the Kiwi Farms daily storm or decisions again today, would you make them the same way?
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 on the daily storm, no one knew what cloud was. And we were thinking a bunch of regulation that was happening online that was really could have been, you know, a real threat to the underlying way the internet worked on 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 storm off was, and then writing about it, talking about it, going on the news about writing another Wall Street Journal editorial about it, was because it helped us then frame what was the right kind of policy decision was out there. And then we talked about Rawls last time.
I'll talk about this time. You know, we very much offended caught 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, not super fun to use that point.
And so I think we were able to make the point we were able to sort of change the policy of the session. We were able to talk about what the challenges were. And we do it. So today, if the exact same set of facts came up, it just wouldn't be the exact same set of facts because today obviously, cloud search was 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 sometimes soon. I think that the situation behind each of them is going to be very, very different.
This is advertiser content from EY Global. Hey, this edition of Decoder Sessions features Andrew Melmazak, the Virgis General Manager in conversation with Rod Sharma, global managing partner for growth in invasion at EY Global. I've been joined as 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 combination of many years of work where we have built our infrastructure, our intelligence layer, our compliant ecosystems, all bundled into a remandination engine, which has got, our technology platforms, our deep industry expert, our deep domain knowledge and our training and our personnel that we bring to the plans to fundamentally reimagine that process that is out there. What are some of the mistakes that you see when you sit down with CEOs, CEOs, heads of innovation, and you're like, okay, we can get in here. We see this all 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. It's only as good as the handset shape. 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 reimagining that business and what it could be in future, and then looking at how AI can help you get there. That's the fundamental thing. I usually do the code of 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're on the show, I asked you how you made decisions, and we don't have a section of 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. You're growing compared to two years ago. You very openly and truly lay out the AI usage inside the company.
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 that they created the titles, but that's about yes. But I wrote the rest of it.
The op-ed supports, that title. I don't know if that's how you tell that something is true that somebody wrote a Wall Street Journal in the tutorial, but that's the editorial editor. That was that line. The opening, you laid out for the 20 percent workforce.
You wrote that. You did because CloudFlare is struggling. You did because it's with future CloudFlare needs to change. needs to change.
And I'm just going to run through your rubric. And I just want to ask you about that rubric specifically. You said you broke people into builders, sellers, and measures, and you're basically going to cut all the people who did measurement, all the audit functions. Not all, but a lot.
Yeah. That's certainly the majority of the people we laid off came from that category of, and this is all, you know, comes back to some old school basic, you know, business research, which is that there are three functions with any firm. There's people who build things, so the engineers, the product managers, folks 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 our 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. 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 all kind of doing one of their jobs. Yeah, I don't think that's true. I do think that there's, there's a sort of increasingly jack-of-all trades kind of aspect of this where, you know, where because you can have these tools, you know, someone who's a product manager can do a lot of what engineers do, someone who can do a lot of product managers do, and the people that are winning in that space are the people that can, they're sort of ambidextrous. They can do multiple different things out there.
But, like, when I get lost with some of the AI maximalists, they're 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, it is wild to watch, you know, how much more productive, you know, our, the builders on our team are today. I'm not here 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 everything 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 not hiring as many as I possibly can, which is exactly what we're doing. So just walking through this decision, you woke up one day and said, I've got a, I am Peter Drucker, I think you see your quoted.
Yeah, it's sort of the builder seller measure framework comes out from the decoder heads out there. This is like old school management philosophy. You just, how'd you make this decision? You were like, I got to do this.
I'm going to sort these people in these categories and we're going to start making cuts and you see any evidence in the data walking 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. 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 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 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 the folks who were kind of earlier in their career. They might not be the most senior folks, but they weren't just the brand new folks who had come in. So they come through and been trained and sort of been taught the way you succeeded in business was by playing by a certain set of rules. And then all of a sudden they watched around them as their colleagues were all of a sudden using these new tools that were out there to be able to deliver these things.
And the analogy, which is wildly imperfect analogy that I use is it's like we had hired the best kind of screw, if you match our job as a screw, screws into wood, we hired just the best people at using manual screwdrivers to screw screws into wood. And then all of a sudden we invented an electric screwdriver. It came along, we were able to buy it. And for most jobs, not every job, but for most jobs, using electric screwdrivers is better.
And you can get a lot more done with it. And again, people early in their career were the ones who adopted or the people who were kind of late in their career were adopting it. And so the first thing that we started to do back in 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.
But 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 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 they also start to use these tools, we found that one place where AI just shined was in measuring things.
And I think one of the places where we don't talk about the advantage of AI enough are that AI is bias, but the biases are uncorrelated to the rest of the organization typically. Whereas humans have biases like crazy, but a group working together has biases that are massively correlated together. Even if you're working on internal audit, you're supposed to be kind of the bad guy who's looking over at one shoulder. Like you still got a lunge 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, Heather was our investor relations team, and what she would do, she would 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 up 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 would then distribute during earnings to all of our investors. And Heather was like, I 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 less mistakes. And our tools are auditing all of those different things. And so for those 20 people, we looked for other places for them. But a lot of them, what they liked doing was that sort of work.
And they would be great at doing that sort of work as the Heather at some startup or somewhere else that was there. But we just didn't need some of the functions that were there. And what it tended to be were all of those functions that were largely measurement. And 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 kind of the Harvard Business School number is that on average, you should have every manager have like six direct reports. We found the tooling, we could actually be much more efficient with managers and that the right number for us started to feel like we enabled managers to have more tools to better participate in surface issues early and see how their team was doing. 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 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 organization is. And so again, we could use these tools to say, hey, let's flatten the organization, which is maybe 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, actually, no, we've got to get rid of these jobs. And so the question is, do we do it now? Or do we do it later? And the problem with doing it now is like we feel very exposed, we feel very alone.
The number of death threats that I got, not even for our employees, but just random people who were sort of anti-AI was really coming 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. They're great people. Place them at other positions around.
And we've been very successful at doing that across the board. Or it's better to kind of cover our own ass, wait until everybody else in the industry is coming to the same conclusion. And by the way, that's coming in Uber, just did a layoff the same rationale. You're going to see across the industry, not just in tech, but everyone starts to get to this realization.
I think we were early. But it's 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 realize that, we're 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 in other places, because they're great people. And 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 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. And there are still some measures on our teams 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 that sooner that you can do that is the kindest way that you can be to your own team. One other 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 is your structure changed? And how has that changed your culture? Well, the first thing is we've just flattened the organizational app.
There's a lot of middle management that went away. And not just because we laid people up, 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. And it's wild to see all these really senior managers that are leaving big jobs to go to an 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 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, this is going to make sense to have those two separate tracks. Maybe that all merges together into one thing, because even individual contributors now are managing a fleet of agents that are working on their behalf.
And so I think the biggest thing is that we've flattened the organization quite a bit. And then the other thing is that we've centralized through something we call CloudFlowerOS, which we've now open source because enough of our customers are 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 CloudFlower. The things that have to be true, the things that sort of inform our decisions. And then anyone on our team to have access to a wide range of the different tools that are out there. But then continuously 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 or record that we have at CloudFlower, being able to pull that into one consistent interface has just allowed a lot of teams to be significantly more productive and a much better at cross collaboration. There's something here which maybe is just the nature of a software company. And that's the way it is. It's a world view that I understand because of software companies and tech networks 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 of your piece. As CEO, I've never had better tools to measure exactly how the business is performing, including identifying our rising stars. The symposium rising stars are producing data that can be measured by an AI and then they can tell you these people are rising stars.
There's something about that that is fascinating. Not every company works that way where everyone's job is to tell Slack everything that's going on or tell CloudFlower OS everything that's going on. 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 think with all it, various times worked in jobs where we were 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 over-recognizing and I'm not, and maybe I don't.
I've never felt over-recognized. I can get some more. That'd be great. You're doing a great job.
Now, can you get your chatbot to tell me how to get a good job? Because I'll be really good. I think that the, again, I think it is absolutely the case that there have been great people who've worked at CloudFlower that we just missed in the past. And for a million different reasons.
Maybe they're part of the organization that we just didn't recognize and have a great manager. 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.
And that has to be legible to the system. AI is going to watch every co-commit and say that person's doing a lot. Or that person is the nicest to their agents in Slack. Or you have to watch them in some way.
There's all kinds of signal that is inside of every organization. I'm running on time, I'm starting around. 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. I mean, obviously code commits and all kinds of things. But those are gameable in various ways.
And so you really want to look at 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 better kind of collaboration across the team. And again, you're right because we have signal because we are a very digital company. We're able to pull that.
But I think every company has signal in various ways. I think that you're going to just be able to see if you're a supermarket, if you've got cameras that are saying things, you're going to see the person who sees the spill on the floor and cleans it up. The manager may never see that, but the camera did. And if the AI can say, hey, that person is cleaned up a spill without having to be asked.
Of course, we should be rewarding that stuff. Now, there's plenty of black mirror, horrible ways that this stuff can go wrong. And we're not, we're very privacy respecting. We're not trying to, it's not a gotcha thing.