The end of the network effect

Hi, I'm Tony Cameron. And I'm Benedict Evans. You've finally written an essay that you've been thinking about for what six months? Yes, messing about for six months exactly. Yes. Pressing publish today? Yeah, pressing publish, well I've got to write the summary paragraph and then I'll first publish yourself. No, having started six months ago saying, well why are all these products identical? What's the product strategy? And then pushed forward and just about to publish something now about chat about open AI and chat to you and how it impedes. And it's well just saying before we dive into the conversation that I think this has been the most fascinating thing about all of our discussions and with anything related to AI is that it feels like we're going round and round in circles but we're not. It feels like it's just the conclusion or having that aha moment of, oh this is what I'm trying to articulate just seems to be taking a little longer than we're probably used to, which I just find in of itself really fascinating. Well, it's a hard part is always working out the question that's not the answers. Yeah. And when something is puzzling and confusing and near then the hard part is working out, what exactly is it that you're trying to work out here? Working that out is easy. It's working out what the question is. It's hard. And one of so, as we were chatting, I thought like a good place to go would be to think about network effects, which is, and the point here being that all consumer tech for since the 80s certainly has been based consumer computing has been based on network effects that we had Windows and Intel and then we had with the web we had Google and then Facebook and Amazon and then the things that Facebook bought and we had at the iOS and Android, which again are based on network of their dominance is based on network effects and Google search is based on network effects. And then we look at generative AI and from ground zero from day zero you can't see network effects. There are no network effects in building the models yet. There may be in the future but at the moment we don't know. And so then you say well what is the basis for you there where one company could pull ahead of all of the others or two or three companies could pull ahead of all of the others, where is there a when it takes all effect, where is there some mechanism whereby everyone has to use your stuff like it or not, everyone has to build for you and also your product gets better than everybody else's name out of how hard they try. Yeah. What you see with Google is Google search is just better than everybody else's search because it has more market share and that means the search gets better and everyone has to use iOS or Android and every developer has to support them because these are the platforms and you know every now and then someone relies another one and it can't break in and Windows phone fell away and so on. And Microsoft has spent God knows how many tens of billions of dollars on Bing and it can never catch up with Google. Yeah. So that's been the kind of the base dynamic of every mature sort of consumer tech we've had since the 80s and we don't see a way that you can have that in the model and so that raises a question. Presuming it doesn't emerge is we are likely to have scale effects to the extent, I mean, we'll see we already have scale effects in building the models. It's billions of dollars and the infrastructure is hundreds of billions of dollars. Like the big four platform companies spent $400 billion on capital exhaust year and they've announced something in the region of $650 billion this year, maybe more, we'll find out. Yeah. And that's the conversation we had last week of like that sheer amount of money and that scale is probably why we're continuously having these conversations as well because the numbers are same. It is, it is yet. So the scale there, but then there is a question of well does that give you leverage further up? After all, like to us and see isn't just, you know, so, so running back and so. So it seems quite likely that all of that will settle out at some point with some kind of oligopoly where like the laws of gravity and the laws of financial gravity kicking and while this is the amount of money that the revenue that you can get and this is what it costs and this is therefore this is a number of companies that and this is how hard it is and therefore this is a number of companies that can be supported in this space with this and I can with this margin and that's forwardly something between three and six just picking a number. Yeah. And they will reach some kind of price of equilibrium, which is what's happened with the cloud and some kind of margin equilibrium. Fine. Does that give you anything further up the stack? Because Intel had network effects but didn't really have much control further up the stack. TSMC has a monopoly and people don't like TSMC apps. No developer in the San Francisco, it ever heard of TSMC before before the AI boom kicked in. And so what all generally happens is controlling the low loads of the levels of the stack, the whole point of a stack is that it's abstracted. Like Cisco didn't get much say in what the websites were, even though it might all have been running on Cisco readers. And so okay, great. Open AI manages to break in, but the secular argument, even though they don't have any existing business, they get into the $100 billion multi-hundred billion dollar CapEx club. Yeah. Five years time, there's three, four foundation models. They're expanding X, $100 billion a year on this stuff and managing to support that with revenue fine. And what's built on all of that stuff are those companies effectively the new hyperscale is, or indeed the existing hyperscale is selling this at commodity infrastructure at low margin at marginal cost. And then the thousands of stuff that are built on top of it and run on top of it, the way you've got thousands of stuff built on top of and running on AWS or Azure or Cloud. Or is it more like the thousands of iPhone apps in Apple's in control and the thousands of Android apps and Google's in control? And they set the agenda and everyone has to use iOS. And you look at the stuff that Open AI have published and they say, well, yes, this is going to work like Windows. We're going to be a platform. And you think, well, that's a great thing to say, but it is a developer. I had to build a Windows app because all my users are on DevWindows. And as a user, I had to buy Windows because all the software was for Windows. If I install Snap on my iPhone, I don't know. In fact, I honestly can't remember which cloud it runs on. Is it on Google or Amazon, maybe both? Who cares? There's a user you certainly don't have to know. Is it an enterprise when you buy enterprise software, it's running in the cloud. Fine, which one? Why would you care? Yeah, it's gotten to support today where we don't care about that underlying. Why would that mean anything to you? That's not the abstraction that you care about. I mean, maybe you have like, you know, sovereignty issues or compliance issues or something. But otherwise, that's not your problem. And so you're not Windows, your AWS, except you're not AWS competing with Google Clouds that can't execute, you can't execute enterprise, you're competing with Google and Amazon and Microsoft, a bunch of people who want to build clouds and want to serve this stuff. So it does sort of seem like, in principle, that yes, the providing AI in the cloud will be the new hyper-scaler thing, but that will reach a cost equilibrium, maybe high margin, maybe not. But then everything else will happen on top. And so then that gets you, this gets you back to looking at open AI or indeed anthropobic and think, well, what's your path to being Microsoft or Apple? What's your path to being Google? What's your path to being the actual platform? You know, the thing that's more than just a layer of infrastructure. How is it that you're going to compete every entrepreneur in the tech industry, trying to build a cool new smartphone top of these models? You don't have the existing feature set that Google and Meto and Microsoft and Apple and Amazon and everybody else have where they can add sales force and, you know, work day and, you know, shake them and everyone else. Some of which will survive some of which will be destroyed. But you don't have surface area where you can make the signature or where you can make it distribution. You're not going to outcompete why a combinatoria coming in with cool new ideas. So what's your path to making yourself, to breaking into the club of the big four fully integrated vertical stack companies? What is it that you're going to be building? And how is it you're going to invent that? What is interesting is you started talking about the fact that there is no network effect, but we've also started talking about vertical integration and the examples that you give Apple being a perfect one is that those overlap in practice. And in the case of Apple, it has both that vertical integration and that network effect. Are you saying that if we don't have network effect? What is your idea? Is the idea here that if we can't find network effect with the AI products today, that then the vertical integration and that vertical stack maybe becomes even more important for a company? Well, I was almost actually putting it the other way around, which is that the vertical integration doesn't seem to come with network effects. Okay. So, you know, providing the full stack of tooling doesn't mean that anybody has to use the full stack of tools. Which wasn't the case previously. Yeah. Okay. So, the challenge then is you are out there competing, everybody's out there competing in this industry against each other. Without sort of fundamental strategic advantage that nobody else has. Yeah. You don't have that approach and you don't have that adoption model because you don't have the network effect. Well, it's not too much of that. It's not too much of that. Apple is doing this thing that nobody else could do. Because they had this completely unique operating model. Google was doing this thing with search that no one else could do because no one else had Google's once, flywheel starts going. Nobody else has a virtuous circle, the network effect that Google has. So, it doesn't matter how much money Microsoft spends on being and how many people they hire, being can never be as good as Google. So, what was discussed at length in the antitrust case. Yeah. And so, the issue here is, you know, you can hire, you have a whole bunch of really clever, really aggressive, really driven people and you have to execute. But then you're doing this thing, you've got this strategy and you're following the strategy and that is what's delivering fundamentally the defensibility and the sustainable competitive advantage of your company. It's the strategy is not hire lots of clever people. Yeah. Yeah. Because that's something you do in a commodity industry. You know, your strategy is something else. You know, Facebook's strategy, you know, there's lots of ways you can talk about Facebook strategy, a lot of which is about great execution. But, you know, it's all there are other things going on there. There are the network effects of social networks and the continuous willingness to disrupt yourself and plan jump onto the next network effect. The same thing for Amazon Amazon famously published this flywheel diagram of, you know, more volume, more customers, lower prices, better service, more selection, all of which are self-reinforcing. At the end of last year, I published a diagram of that they said, this is our flywheel and the flywheel says, more cap-aids, more infrastructure, more revenue. That's not a flywheel. Yeah. That is not a virtual circle. And it's interesting because Amazon, well, it's going to make it go by comparison with Amazon. The Amazon fly diagram does not say more warehouses, therefore more inventory, therefore more revenue. Yeah. That's not the Amazon flywheel. Yeah. And all of this sort of gets you to, well, you don't have those lock-ins. It's not ordinary. We don't know what the strategic, we don't know what the fundamental strategic differentiation and competitive advantages would be of running an LLM. They might be other stuff you have, like you've got a search engine. You've got all these other user grades, but the model itself is not clear what you could do to pull ahead. Because it used to be pretty clear, I mean, especially in the example of social media, of just that it's about users creating value for other users. I don't see how. But it should be for something like an AI product or an AI, you know, a Claude or a chat GPT, you would think that users creating value for other users is the perfect scenario. But when that's not happening. But, well, at the moment, that's not how the models work. Yeah, that's it. And there's a sort of theoretical question of, we know, with something like continuous learning or various other things, can you get to a point that more users would make the models better? At the moment they don't, at the moment the companies all say, "We don't train, we don't use our data to make the models better." Partly because the amount of user data involved is isn't enough to make the relative to the broader scale of the training data. But whatever it is, this is the thing that I was puzzling over like last summer is, well, what's the strategy for why you would win other than we just going to be better? Yeah. Because historically that wasn't enough. That wasn't, yeah, everyone's strategy is to be better, but you were doing something that other people couldn't do. It's like saying, "Well, what was Samsung's strategy to compete with Apple to be better?" Well, fine, but that's not a strategy. You know, we will out execute is not a strategy. Now, of course, you can take the counterpoint here and say, "Well, if you look at the reality of Microsoft or the reality of Meta, they would never thought they'd won. They're always looking at those shoulders there for always paranoid." And they're always jumping onto the next thing. But they're always doing that form this position, this is what we've got, this is what we're going to do with it, these are the leaders that we're going to pull that other people can't pull and how we're going to do it. And I don't know what those would be, we don't see what those would be in genitive AI. Now at the moment that you've got stuff that's built on top of it, that's some other product, like if you could make some, you know, a solid word, there is a strategy for how you could make something that nobody else can do. But it's much as apparent what that would be in this field. And the, no, I was just looking at this and just listening to one of many podcasts with many people in AI. The revolver carries a turn every page, but he didn't have to deal with, you know, a million three hour podcasts to listen to or read the transcripts off. But there's a comment from Fiji Simo, which reminded me of something that I heard last year, I heard both Kevin Will and Mike Krieger say, which is basically you get your head of product at open AI or an antelope, but Mike Krieger was both of those people on our left. Your head of product, you get into the office in the morning, you open your email. And there's an email from the researcher that says, hey, we've got this cool thing, what can you do with it? What are you going to, how are you going to use in chat? And there's a quote that I put at the beginning of my essay from Fiji Simo saying, you know, Jacob and Mark set the research agenda and then like six months later, research emails me and says, hey, I've got this cool thing. What are you going to do with it in enterprise and consumer? And I just think that's really, really interesting because what that's saying is the head of product isn't setting the product strategy. It has no idea what the product is going to be in a month's time because there's going to be stuff coming out of the research lab that they don't know about, that the research that I doesn't know about, but they certainly don't know about, that's going to shape what it is that you're going to be building. So you don't really know or control your roadmap. Now, I've paired this quote from Fiji with the classic quote from Steve Jobs from 1997 or so when he went back to Apple and he said, you can't start with a technology and work to the user experience, you've got a work start with the user experience and work back to the technology. And what's happening with all of these labs is you don't know what the technology is going to be next month and the technology emerges in completely changes what's possible. And so you're a strategy taker, not a strategy setter. But it's an interesting one because if we also don't have the network effect, who's set it, so who's setting the agenda? Well, the problem is that what the problem is is what's happened so far is that people leap frog each other over a couple of weeks or a month or two, but because everyone is basically building the same stuff, nobody has anything unique in the models. And of course, we've said before, if you're spending all day using this stuff every day, then you have, you think that's nonsense. Yes, of course, there's a huge difference between this and that. And certainly if you're like, if you're doing image generation or code or something, then there's differences. But if you are, you know, the 95% of people who aren't paying for chat, EPT or the 80% of people who are using it only once a week, not every day, every couple of days, not every only using it once a week or every couple of days and not using it every day, then you don't see those differences and they will kind of the same. And how do you do, how do you, you know, it's the, it's the, the net scale comparison. Again, how do you differentiate it when the technology is the same and the product is basically the same? Is it possible to make the product on top of the technology different? Could you make your web browser different from someone else's and the answer was no? So it came down to brand distribution, which is why Microsoft was able to crowbar where they're way in. I mean, hate to say it's having work for market in recent, but you know, internet explorer 3 was better than net scale. Net scale got really bloated and slow. But fundamentally, the reason that Microsoft was able to crowbar their way in was because the browser itself was just a browser, it was a commodity. And so that becomes brand marketing and distribution. Unless there's some other thing that happens or some other layer of products on top of that. And it does become interesting that then the market, this is where the marketing teams are rubbing their hands going and it's on to us now. It's all down to us of how we market these products. What I found absolutely fascinating is depending on who I talk with, what products seem to be top of mind. And for people who are not in tech, I found it absolutely fascinating how anthropics Claude seems to be just top of mind in the way that they've built their whole branding and their marketing around this lifestyle product. And it's been just fascinated of people that are not in tech that aren't using AI who are just like, I went to this Claude cafe and I'm like, wait, what are you talking about? This is the marketing experience that's been built by the marketing team of anthropics Claude. It's fascinating to see the different avenues that the marketing teams are going to take in terms of. Claude is interesting, Claude is an interesting case study here because I mean, we were always chatting about this earlier that if you look at the new survey data on usage, it's chat GVT and then it's sort of two thirds of that to a half of that is Gemini and a meta AI. Even the meta AI is a fiasco. Lama 4 is a fiasco. The new models haven't launched yet, but consumers don't know. As far as the consumers concerned, what's the difference? They're all kind of the same. And meta benefits from that sort of kind of network effect. Well, it's a displeased, they have surface area they can use as distribution. And then Claude is a running error. Bounces between 0 and 1%, even though the models are at the top of the benchmark charts because they don't have consumer awareness. And the super bowl ads. And the consumer awareness that they do have is with people who seemingly aren't using this products on a day-to-day basis. Yes. Which is fascinating. There seems to be a gap of just like, there's these people who know about your product, but they're not the ones actually using it. But I guess you're getting a good product awareness out of it. Well, the other thing is fascinating and slightly hilarious because they come up and they say, "Well, we're not going to do ads. Adds are bad." But we might do them in the future. Okay, so why have you just wasted my time? Plus, of course, it's easy to say you're not going to do ads when you don't have a consumer audience. Yes. And I've had an announcement. I posted a picture of Don Draper saying Sterling Cooper will no longer take cigarette advertising after they've just been dumped by Lucky Strike. Like, well, it's easy to say, "No, I didn't dump you. You didn't dump me. I dumped you." No, we're not, you know, it's not that we can't get any advertising because we've got no users. And there's something also interesting because I've all weird tangentially little F1 parallel. Here, I've always said, the sponsorship in Formula One is a reflection of our time. In the '70s and '80s, it was tobacco, then we had spirits, then it was oil giants, then we had crypto and tech. And now it's all AI. And actually, now, I think of it, Claude, and Tropic and Claude have become a big sponsor for the Williams Formula One team. And it's just fascinating. I'm very curious to see what they're hoping to get out of that advertising. And is it just like, okay, Formula One? Is it just brand awareness? Exactly. Or, and look, they've positioned themselves as the thinking partner. I think the thinking partner of the Williams Formula One team. So I think there's going to be a use case of how they embed and use AI and their product with the team. But it was a fascinating one for me. I was just like, oh, but again, very lifestyle, very of the moment versus. Yes, it's a brand of marketing conversation. It's a brand of marketing conversation. And I think, you know, this one should be clear. The technology, when the technology is, there's a sort of a slight different point here, which is, in the technology is basically undifferentiated. The product is undifferentiated and you've got radically different market shares. That tends to be an unstable situation. And, you know, even, you know, we talk, we've been talking about network effects, even, you know, the canonical example of the failed first leader of my space. My space had a network effect. And it turned out that network effects in social are actually quite fragile. And you have many of them, so you can have Instagram and TikTok. But, you know, here we don't have any of that. And so you have these, you know, pick your, you know, Gemini and Tattie PT and Meta AI. There's also GROC, which you know, and outside America, who's ever heard of, except as a place that you can get child porn. And which apparently is free speech. Sorry, we should make that clear. That's free speech. Oh, good God. Yeah, I know. But you've got this differ, big difference between the technology being basically the same, the product being basically the same. The consumer awareness being radically different, the adoption being radically different. For all that, you know, open AI, I'm sorry, Antelope is now trying to do a, do a column's push. You know, you go and look at consumer awareness or even something simple like, like Google Trends and no one's heard of it outside of tech. That may change. I mean, it's not clear whether I'm swapping, I mean, I'm slightly puzzled by an topic because I'm not clear whether they actually do want masculine adoption or not. And I really don't understand what my career has been doing there for the last year. I tried to install Claude Kowork in it asked, I tried Claude Kowork in it asked me to install Git at the command line. I'm like, yeah, you're not really looking for consumer adoption here. Whereas I think I use it in a very different perspective and I like the product and I like the UI and I'm just like this, this works for me. But, yeah, the product is fine. But the point is the product is complete. The product, you know, they have not attempted to get distribution or consumer awareness until now. Now they went and spent a bunch of money on it on a Super Bowl ad. So at least people in America have heard of it. I guess the question I had for you at the start when we were previously talking and again, maybe it is the wrong question is, so do we need to figure out network effect? Us, we not being us, but do these companies need to figure out network effect for us to always do something else? Well, some sort of strategic, some form of strategic leverage wherein you're not purely dependent on turning up every single day and being better than everybody else because you can't plan for that would be good. And I'm sure everyone would like that. Yes. And I'm sure that's on everyone's mind right now. But at the moment, we don't know what that would be and this is sort of part of the kind of the thread of the piece that I've just really just published when people are listening to this. Is it your opinion? I, you've got, don't fundamentally have a technology lead. Your first and last equals at best, you've got this giant user base that's not, that has very shallow usage and engagement and isn't really, it isn't locked here and it doesn't have a network effect. It's very clear that there's a whole, there's a whole bunch of other stuff is going to get invented around what all of this is and how it will, how all of it works. And there's no particular reason why it would be you versus anybody else that invents out because you're competing with the whole tech industry to invent all of that stuff. It's as though you're, you know, your net scape in 1994. And then like you're trying to work that out without having the existing feature products that you can use as distribution and where you can add your stuff, its features that Google and Meta and everybody else has. Not that they're doing a great job, but they're starting from a different place to you. You're starting from a blank, completely blank, blank, blank, blank, blank slate. Also, you don't have the cash delays that they have. And so you're, or even though you were first and you've got all these users, you're still kind of back at the starting line, surrounded by five or ten other giant companies plus two or three thousand entrepreneurs, go trying to work out what happens on top of this infrastructure. And meanwhile, as I said, your strategy taken or the strategy given because in the end, like, stuff comes from the lab, like you get an email tomorrow, get an email next week, you can email next month, maybe, maybe not, I don't know. Well, something come, well, something not, what will be used. So building a bunch of advantages is going to look a lot different potentially. What is your strategy? What is your plan for why your product will be better than everybody else? Having better people, I mean, that's kind of a plan, if you can't get a better one. Yeah, I feel like that's an incredible place to end. Like, having the, how are you? Because what's your plan to have clever people, the anthropic and Google and meta and Apple and Amazon? I mean, you can sort of, I mean, we saw like half of Grocks founders have just left in the last month or two for a whole bunch of different reasons. So what is, how can you plan to, and you know, there's some of this as you can look at Google and say, well, Google clearly was a massive execution machine in 2000s. And Facebook was a massive execution machine. And Apple was a massive execution machine. But that's not why everyone uses Apple devices. It was not just we've got Tony Bleven and he's going to do better procurement deals with Shenzhen. And it's not just, you know, Craig Fettie-Riggy is going to be really great at having a regular cadence of shipping. Yes, you execute really, really, really well. But what are you executing or executing something other people can't do? And there's no stuff other people can't do in this field yet. And if there is, you're going to have to work it out. You don't have it now. I like it. It feels like, good, that's become I think are the themes of our podcast. It ends on a good, good couple of questions to think about. I mean, this is the thing we were talking about that, you know, what does it mean when you say platform or what do you mean when you say power, ecosystem or leverage or lock in? Do you have something that other people can't do that makes your product better in your company more successful? And at the moment, I'm not clear that anybody in this field really has that. There we are. 28 minutes, not two and a half hours. You see what happens when you don't have answers? It's great. You don't have to go round and round. I love it. Fantastic. This is very interesting. Good to chat. Good chat. Bye.