The AI industry's existential race for profits

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Hello and welcome to Decoder. I'm Neil Ipatel, editor in chief of the Verge, and Decoder is my show about big ideas and other problems.

Today, let's talk about the looming AI monetization cliff and whether some of the biggest companies in the space can become real profitable businesses before they careen right off it. My guest today is Hayden Field, who's our senior AI reporter here at The Verge, and she's been keeping close tap than both Anthropic and OpenAI, and how those two companies in particular tell us a whole lot about the AI industry as a whole in 2026.

You've certainly heard a version of the monetization cliff story before. Anthropic, OpenAI, and all the other big AI startups are built off the back of hundreds of billions in capital investment. And they're linked to even greater amounts of forward looking investment in data center build out, chips, and other infrastructure spending. At some point, that return has to pay off, the profits have to materialize, or the bubble pops.

Maybe AGI arrives, maybe the economy crashes, who knows? If you've been listening to Decoder, you've heard me talk about this with tons of CEOs right here on the show, and a majority of them have hinted towards the bubble popping. They think some companies will fail in spectacular fashion, and others will succeed. But that the opportunities, and especially the money, are simply too big to ignore. The AI industry is gonna do this, whether we want it to or not. The market depends on it.

And so these last few weeks have felt like a very important inflection point, as both Enthropic and OpenAI have started to react to the reality of needing to go public. To make money. The catalyst for all this change is the rise of AI agents, products like Cloud Code and Cowork, the open source OpenClaw, and OpenAI's Codex.

They've all radically changed how these companies are thinking about their resources. And that's starting to affect how they behave, the products they support or suddenly kill, the restrictions they impose on customers, and the money they're willing to burn on the way towards the next big milestone.

That's because agents are valuable to customers right now, but agents also use far more compute. And so the way people are using agents is burning tokens at a rate way faster than these companies anticipated. And that's causing them to make hard decisions. We saw this most evidently last month when OpenAI abruptly killed its video generation app Sora, ditching a$1 billion Disney deal in the process. Why? Well it costs too much to run, and OpenAI needs a compute for Codex.

And we saw it again just last week when Enthropic decided it would no longer let Claude users burn through compute resources using the OpenClaw Agent Framework through a standard subscription plan, instead forcing those users onto a pay as you go plan, which costs substantially more.

As you'll hear Hayden explain, these are glimmers of a make-or-break moment for the AI industry, as both Anthropic and OpenAI barrel towards two of the biggest IPOs in history, and the pressure on these companies to make money has never been this intense. The projection these companies have made, which just this week leaked to the Wall Street Journal, tell a story of mind-boggling growth, to the tune of hundreds of billions in revenue and profitability by the end of the decade.

But the most important questions now are, can these companies pull all this off? And what compromises will they make to reach that goal and avoid crashing and burning? Before we start, a quick reminder that you can listen to this episode or any episode of Decoder completely ad-free by subscribing to The Verge. Just go to the Verge.com slash subscribe. Okay, Verge Senior Policy Reporter Hayden Field on the AI monetization cliff in the race to profitability.

Hayden Field, your senior AI reporter here at The Verge. Welcome back to Decoder. Thanks, it's great to be here. I'm excited to talk to you. There's a lot going on in AI world recently. It feels like we are at a very important inflection point for this industry. What what do you think

Yeah, we absolutely are. It's kinda like time to pay the piper in a way. You know, they've been raising a ton of money, raising a ton of hype for years, and now Um, you know, as companies prepare to go public and the competition is heating up more than ever and they're kinda entering all these different sectors and trying different side quests, it's finally time to really like face the music and see how much money they can really make and there's never been more pressure on them also.

When you say them, I I want to stay focused on open AI and Anthropic, which seem to be on different trajectories. Now there are obviously other big AI companies in the mix. Google exists, it's gonna do whatever Google does, but Google has a big business. already. It can subsidize finding product market fit with AI. It can subsidize making efficiency improvements on TPUs.

very different from in particular open AI and Anthropic, which have to become companies. Like they have to graduate into becoming companies, particularly if they're gonna go public and then they're gonna have shareholders and they're gonna have to show profit and loss and all this other stuff. Can you just describe how OpenAI and Anthropic are currently situated and where they might be going?

Sure. So yeah, I mean it's interesting because in some ways they're in the same position. They're both preparing to go public this year reportedly and kind of racing each other to do that. And they're both constantly raising a ton of money and hype. But where they differ is of course OpenAI has traditionally been really courting um the consumer-facing stuff and some enterprise and government.

But they've really been focused equally, if not way more so, on consumer. Anthropic has always been pretty focused on enterprise. And they have remained pretty steady on that focus. So, you know, they're not really doing as many side quests, they're not um, you know, rolling out as many other experiments or projects. They're just kind of laser focused on their enterprise.

um goals and their enterprise clients. Now are they only doing that? No. Sometimes they kind of it seems like get FOMO and they're like going into, you know Claude for healthcare and, you know, Claude for education, things like that. But it doesn't totally remove them from their goals of enterprise because like, you know, that's pretty focused on healthcare organizations or, you know, education systems are Enterprises too, as we know. So

you know, they're really laser focused on this. They kind of have the reputation of being the adult in the room in some ways because they're not as perceived as like going wherever the wind blows them. They're kind of on one trajectory and they're staying really steady, it seems like. Whereas opening AI kind of has the reputation of, you know, changing their focus a bunch. Internally and externally, people have said this. It's like,

you know, going on a ton of side quests, uh, you know, trying things, you know, throwing a ton of spaghetti at the wall, like consumer, enterprise, government, uh, everything, just seeing what works. And even Sam Ullman himself has described open AI as kind of like betting on a ton of startups internally and just kind of seeing which one pulls ahead.

But now they're finally having to realize, hey, maybe it's time to focus on the most money-making endeavors here and deprioritize some of these other projects, kill them off so we can just kind of compete with anthropic and focus on coding and enterprise.

Yeah. I think that brings me to the news of this week that really made me feel like, oh, we're at an inflection point. And that is anthropic. started raising its rates for people using tools like OpenClaw. They really want you in their system on their subscription plans using the tools and their pricing their way. And if you want to use Cloud to power other systems like OpenCloud, you're gonna have to pay in a different rate structure that to me feels like they don't want you to do it at all.

And then next to that, OpenAI killed Sora, which was their very buzzy video generation product that was basically deep fake nightmare. But they also had a deal with Disney for a billion dollars, which always seemed confusing, but they canceled that deal too.

Let's start with OpenAI. You're saying they're killing off all these side projects. They're trying to focus on codecs, which is fundamentally enterprise software, right? It is soft, it is a tool for software developers to make software. Why did they kill Sora and where did the sense of focus?

I think the sense of focus honestly just comes from the competition and the fact that pressure is building on them to generate more revenue than ever. They've never had more eyes on them in their balance sheet in their their whole company history because They're preparing to go public and because they had just raised

So many billions of dollars. Their post money valuation right now is eight hundred and fifty-two billion dollars. So yeah, I mean investors are saying, Okay, like what's the plan here? What's the plan for for returning our money? So In order to deliver on those promises, they are having to not only devote their time and like money and staff to the projects that are gonna make the most money, but also their compute.

So that's something that we saw execs at OpenAI talk about um when they killed Sora. We saw a couple internal memos go out. One of them was from Fiji Simo, the um CEO of AGI deployment, and she said that basically the company need to stop focusing on side quests and just really dive fully into enterprise encoding. And yeah, I mean, compute is super limited.

OpenAI it's always, always talking about how they don't have enough compute to fulfill what they wanna do or to scale appropriately. Sam Altman at Dev Day and um SF in October. said to reporters, I've just never seen him so stressed when he was talking about this about how

the compute constraints were stopping them from scaling appropriately and how they couldn't really deliver what clients wanted unless they just could somehow get their hands on more compute. I've never seen him more stressed out. And so yeah, that's you know, playing out now months later. Sora took up a bunch of compute and there wasn't really a big return there. And so they abruptly decided to cancel it, apparently.

30 minutes after working with Disney on a related project and then just suddenly pulled the plug with no notice. So, you know, things over there it seem like are in kind of a tailspin. It's like if you're pulling the plug on a project. with a huge company like Disney, 30 minutes after talking to them about like how it was going great. There's some some real uh some real issues there. I wanna come back to OpenAI, its management, which is all but turned over.

Since the last time you were on decoder and it's sort of strategic focus. But what really strikes me about the need for compute is I don't know, when you were on the show a year ago or a year and a half ago, all of that compute was pointed at training. Right. We gotta make bigger models. They're gonna be more capable. GPT ninety-five will come out and it'll be digital Jesus or like whatever it was.

And the idea was that we needed bigger models with more data. And the compute, the scale of compute necessary was gonna get us to the capable models and AGI in some way. Now it seems like the compute is all for in. Right. There's people that want to do things with these tools, particularly in software development. And if we don't scale up the compute to meet the demand, we'll get left out in a cold because our big rival is sitting right there waiting to scoop up all those customers.

Has anyone pointed that shift out explicitly that we've gone from all of the focus on training and capability in the model to the models are pretty good, everyone wants to use them, we need massive amounts of compute for inference. So in the numbers that leaked from investors in OpenAI and Anthropic this week. You know, there are a ton of crazy charts showing just how much of their money and profit is going or lack of profit is going towards um inference.

training, the way they break out these categories is just really interesting. It's not always apples to apples, but it's like, Anthropic is going to spend one third to one quarter on model training compared to OpenAI, but OpenAI's revenue is expected to hit like 275 billion in 2030. But Anthropic says it's revenue will hit one hundred and fifty billion in twenty twenty nine. So it's kind of like Anthropic seems to be spending a lot less um on the same categories as open AI.

and growing slower, but OpenAI is spending a ton and then just hoping that's gonna lead to a return on investment, which kind of tracks with the way the companies have been operating for the past couple of years. Yeah, anthropic seems to be much slower and more focused and constantly worried that it's gonna kill everyone in the world with every successive model. Pedal the metal all the time.

Yeah, but Anthropic isn't worried enough that it'll stop.'Cause they just took uh um out their frontier safety pledge and said, Oh, actually we're gonna stay competitive even if we think it's a little dangerous. Sorry. The the race to an IPO makes a lot of people rethink a lot of their values apparently. We need to take a quick break. We'll be right back. Need a vehicle that isn't afraid to make a splash? That's the Volkswagen Taus. Capable and confident, the Volkswagen Taus

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We're back with a virgis senior AI reporter Hayden Field talking about Enthropic and AI's race to profitability. The other piece of news, right, this is again pricing, compute usage, enthropic. changed its pricing structure to make using Claude with OpenClaw much more expensive in in different ways. So if you have a Claude Pro or Mac subscription, you can't just hook it up to OpenClaw and go, you've got to buy tokens on top of that.

In some ways felt inevitable. In other ways, obviously made a lot of people very upset. It made the developers of OpenClaw upset. They said they could only delay the decision by a week. What's going on there? So when I talked to an economist about this this morning, he said that's a good thing.

Agents have just changed everything. And I talked to an another couple of tech leaders about this, and they said agents are consuming hundreds of thousands more tokens than basic chat models have been. So it does make sense.

even if it's frustrating because it seems like, you know, the way Anthropic put it was, hey, you know, our infrastructure isn't built for this. Like we didn't plan for this. And yeah, I mean, if you're using OpenClaw with Claude, Obviously, like, you know, you basically have an agent on your behalf like prompting Claude for you and

delivering those prompts back to cloud and saying, no, do this, no, do this. So it's like way more than a human would be able to do. And Anthropic's point was, hey, like we only really built this for humans to be able to prompt. Claude right now, unless it's for our own products. Obviously it's a money grab. Like of course they don't want a third party tool um doing the same stuff that they want their own. Right. Uh they want people using cowork.

Yeah, of course. So it's like basically they just want to keep it like a walled garden. They want it to be a moat. That's kind of the only advantage that um AI companies have right now. trying to keep their users engaged and keep them on their own platform, build a moat of some sort, because otherwise, like, you know, everyone loves to switch between whatever model is the best that day, that week.

So yeah, this is just anthropic looking to like deepen its moat and also You know, it Compute is constrained everywhere, so they don't really want a a third party tool prompting Claude way, way, way, way, way more than a human would be able to. They don't seem to mind when it's cowork doing the prompting. Right. Because you're inside of Claude and then they can monetize you in whatever ways that they come up with to monetize. Exactly. They want to monetize it if they can.

Is there a path either in enterprise for anthropic or consumer for open AI to actually make a dollar in profit? That seems to be the the big question everybody has. Yeah, that's a really good question. And it's something that um when I was chatting with economists, they didn't feel that it would be that

easy or likely, but they think that one or two LLM providers will come out on top and the rest will have to consolidate. So yeah, there's a chance for sure. Anthropic and OpenAI are both projecting some form of profitability in twenty twenty nine, twenty thirty. Anthropic said maybe this year it'll also like be slightly in the green and then go back in the red and then go back in the green for twenty twenty eight.

twenty twenty nine. But yeah, I mean I think that They've all realized that if that is ever gonna happen, it's going to be via the boring, unglamorous back-of-office stuff, enterprise, military contracts, government contracts.

All that stuff because consumers just honestly, yeah, they'll maybe pay for a two hundred dollar a month subscription if they're a power user, but There is no way that stuff is ever going to add up to the amount of money that's involved in these enterprise or government contracts.

This seems to me like the point at which open AI faces just a fork in the They were made to be a consumer business, as as you've pointed out. It seems very much like they wanted to bite off some of Google's business. Google search, one of the greatest successes in business history, maybe the greatest business that you can run in world history. They haven't really succeeded, right? They might have shifted some search behavior to ChatGPT.

But they haven't taken meaningful dollars away from Google. Google just keeps doing better and better and they keep lacing Gemini into everything that they make. And eventually the idea that you would open ChatGPT to do a search when Google's gonna deliver you something substantially the same.

That's going to get harder and harder for OpenAI to to compete on. Are they just pivoting away from consumer entirely? They hired all those meta people to do ads, and the ads have come to approximately nothing from what I can tell. Yeah, it's still early days for that, but I mean it is, it's it's funny. I don't I'm really interested to watch the ad stuff play out, but no, they're not pivoting from consumer. It just looks like they're trying to really front load their resources, their compute.

and their staff into the the enterprise encoding effort. So Consumer, it's already built. It's not that crazy to keep it maintained and just like keep rolling stuff out. But it seems like most of their efforts are still gonna go towards catching up and closing the gap in enterprise encoding, especially because Reputationally, they also have a gap to close there. Anthropic, for better or worse, has the reputation of being.

Pretty trustworthy, pretty brand safe. That's what a lot of um startups were telling me when I talked to them about this a few months ago. They all were afraid of like the risk associated with. Especially XAI and somewhat OpenAI as well. Anthropic, they felt pretty safe using it. They didn't feel like they'd be on the hook for reputational risk.

So yeah, OpenAI has to close the gap in terms of like actual usage, anecdotally what people prefer, the hype that's involved with Claude Code and and all that that brings, and then also the reputational stuff that anthropic kind of has going for it just because of its steady, slow growth. That steady state for anthropic.

Is kind of reflected across the company, not just in product development or strategy, but in terms of employee retention or the ability to attract people from across the AI industry. A lot of people just head towards anthropic. I would contrast that to open AI, which you're pointing out has a different reputation. And then just in the last week or two weeks. Feels like it's turned over its entire executive.

Fiji Simo, who you mentioned is CEO of AGI deployment, her title like a minute ago was CEO of application. And they switched to the AGI deployment, which I don't understand at all. And now she's out on medical leave. I wish her well. They have other executives who are out and leave. Their head of marketing just left. Right before all those people left, they bought a podcast called TV PN. I what's going on over there? Is is this like a stable company right now?

It is a it is pretty crazy right now. I think they're going through a huge strategic shift and it's just It's a question of whether this is gonna be like every other shift we've seen in the past, with them kinda going all in on one thing, going all in on another thing, going all in in parallel on five things. Um, is this really gonna last? That's kind of what people are asking. And we don't know. I mean,

I think if they are entirely focused on coding and enterprise, yeah, it makes sense that there'd be a lot of upheaval. But they're also like, you know, really into building this super app and um Greg Brockman just took over uh charge of that while um SEMO is out. And then uh on the business side, their CSO, their CFO, and their CRO are gonna take charge. And then their CMO just stepped down due to health reasons. Their um head of communications stepped down in January and there's still no

uh replacement there. And that I think is part of why they bought TBPN. There's been a lot of bad press about OpenAI in the last few months. They've had a lot of public controversy and a lot of just drama playing out. And that does not And that is not good for their quest to, you know, have a reputation as a company that enterprises and the government can trust. And so I think that's part of why they bought T V PN. They said that literally they wanted to help

shape the narrative AK help control the public narrative playing out about AI. And so, you know, what better way than to hire the people that are being watched three hours every weekday who are talking about it? Plus T V PN is now gonna help um like with open AI's comms and marketing um in their free time. So yeah, I mean, it's really an aquire situation.

Yeah, I have a lot of thoughts on that. I I think a lot of the other AI companies who put their executives on T V PN certainly have a lot of thoughts about that that I've heard. We'll set that aside. The idea that it's just a marketing problem or a narrative problem, the last time I heard that was uh was Uber executives complaining that Uber only got bad press. And most of the media that I knew at the time was like, No, you just keep doing stuff. याप याप याप

It d it's not the narrative, it's literally what you are doing all the time that is getting you the bad press. You can't just yell at us into liking you. It's not quite the same with OpenAI. They they are darlings in a very specific way. But the bad press or the perceived bad narrative, in my opinion, has everything to do with their strategic confusion. Right. Right? The the media is not out to get AI. It's when you do the polls, the broad public in the United States.

Is like AI is less popular than I R like there's a gap in how people feel about these tools, even though they're exposed to them all the time. Is that all on open AI? Is that across AI in general? To me it feels like it's very much open AI r in particular Sam Altman running around all the time saying, like, I might destroy the world by accident if you don't give me all this power.

Yeah, I think it's really interesting to like look at how the general public feels versus how people that are in tech feel because They kind of feel they feel different ways, but there is some overlap, but it's for different reasons. So I remember when I was chatting with um a firm that charts like public perception of things in the last couple of months, they said that.

Yeah, the general public really didn't like AI for the most part. They broke it out by generation, by gender, all sorts of different things. But for the most part, yeah, like the general public was not a fan. And they noticed that the more well known an AI company was.

the worse the public perception of them just because they were more aware that it was an AI company. So open AI had a worse reputation by this firm standards than Anthropic per se. But as Anthropic's like public perception was on the rise,

opinion of it was going down. So that was just interesting. It's like if if you're known as a household name for being an AI company, like the general public right now isn't really a fan for the the majority at least. But within tech, people are looking at the business angle and how these companies are conducting themselves, what the CEOs are saying. Maybe Sam Altman isn't a household name for the average person in America. I think a lot of people know who he is, but

I will be talking to people in the wild and say Sam Alman and they're like, who's that? So when I say CEO of Open AI, they get it. But yeah, I think it's interesting like, you know, just comparing the tech reactions to the general public's reactions because in the tech industry. Yeah, people are really raising an eyebrow at OpeningID's business strategy and at Sam Alman going around saying, like, oh, I couldn't.

raise my child without Chat GPT or oh like, you know, if you if your job gets replaced by AI, like maybe, you know, you should think about switching jobs. And, you know, Dario Amade has said kind of us things as well. So I mean, uh, you know, no AI leader is is doing comms entirely right. Uh, but it is interesting to see kind of, yeah, the difference between the general public's perception versus um people in tech. Субтитры сделал DimaTorzok Hi, I'm Brene Brown. And I'm Adam Grant.

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We're back with Verge senior AI reporter Hayden Field discussing the AI industry's make or break year and what might happen next. This kind of brings us to the make or break moment, right? These companies are both headed towards IPOs. both of their their financials have all leaked. We can see their cap tables. We can see their revenue projections. And it it feels a little bit like tortoise in the hair, right? You you've got anthropic committing to being an enterprise company.

kind of change the entire nature of software development. You have OpenAI with codecs that thinks that it can eat a piece of that market as well, shutting down consumer applications that aren't working. Maybe it will figure out ads. Maybe it will actually bite off a piece of Google search. Who knows? But they're still just hopping all over the place. Like it's just pedal to the metal opening eye all the time and anthropic just continues moving along its rip.

How do you think that plays out, not, you know, over the course of the IPO timeline, but in the short term? Do you think OpenAI can recapture it a sense of focus? I think I think it's going to try very hard and I think it will be able to. The question is just can it hold on to that focus? You know? I mean, I've seen them change their strategy just like this in the past and usually it just falls by the wayside a couple of months later or a year later.

So what I'm wondering is how long they can hold on to this. Like Anthropic has, you know, committed to one thing, stuck with it for the most part. OpenAI, whenever they commit to something, like a year later, things shift, you know, teams will be disbanded. Um, they'll have a reorg. You know, anthropic's also seen a ton of change, but it's always had this one goal and kind of stuck with it. And I've been tracking both these companies for

so long that it's like, you know, you can kind of see the trends there. So maybe this is a big step change for open AI and they're really gonna pivot. And maybe that's why we're seeing all this executive restructuring and um the side projects being killed and trying to really like

force them to commit. But it is interesting because I don't know the rate at which they'll be able to catch up with Anthropic when it comes to enterprise encoding because I've even seen anecdotally like a bunch of startup founders switching entirely over to Anthropic when they used to be, you know, testing both. Um you know, we did a piece

a couple months ago about how Cloud Code was having a moment and most of the founders and company leaders I talked with in a ton of different sectors preferred anthropics products for this stuff. So I mean To uh OpenAI's credit, it has been working really hard on getting its coding models up to date, more improvement. We've seen people start to prefer that sometimes. So I mean they've made a huge uh advancement here. It's just can they close the gap? That's what we'll have to wait and see on.

Yeah. It really feels like Software development is product market fit for these tools. And that's a very lucrative market. That is a lot of jobs that might go away or change substantially in some meaningful way. And everything else is like wait and see. You anything that kind of looks like software development might get product market fit, but software development is such a big category, that's in particular what a bunch of these companies are going to focus on.

I'm very curious as the pressure on turning these companies into real businesses goes up. As they get closer to an IPO and Anthropic has to monkey with pricing even more to make sure that they're running an actual business and not a token subsidy operation. And OpenAI has to cut down on more projects.

that pressure, that pricing pressure, that monetization pressure changes the companies in any meaningful way. Like you've been thinking about this and even talking to people about this. Do you see glimmers that that that's about to happen? I think so. Just because I mean, the pressure is building. You know, when I was talking to economists, there's no way that things can continue the exact way they are now. Um, I was chatting with a couple um execs this morning about

the price has kind of been passed on to enterprise clients and how that's shifted. So, you know, a lot of um company leaders are thinking about moving to open source instead, or at least moving to open source for a lot of their simpler tasks or queries, um, and kind of like building their own evals uh to see what it makes sense to like pay top dollar for for either anthropic or open AIs like

more complex, more powerful models, which ones they can kind of route to the simpler models and which ones they can just go open source for. So it's interesting that, you know, in order to kind of combat these uh pricing shifts and uh just the amount that they're paying these two labs every month.

Um, they're starting to just build their own internal infrastructure and tests and evals just being like, Okay, let's really budget here. Like, what do we really have to pay top dollar for? And what can we kind of like you know, skimp on, but it'll have around the same type of answer. So that's what I think is interesting, like this cottage industry of like charting this stuff out internally and then just like keeping that close to the vest and using that as a guide.

Yeah, I mean that's kinda why I was asking about inference at the beginning. If the models today are good enough to be this disruptive to software development, there's no reason that a distilled model a few years from now that's much cheaper to run or you can run locally. wouldn't be as good. And that the the bleeding edge model is unnecessary because it's so expensive. And it I don't we haven't like run this industry long enough to know how those pricing dynamics play out.

But it feels like the additional capability from the next model, the next model, the next model is unnecessary if the current models are already so disruptive to at least the industry of software. And I I'm just very curious to see how that pricing plays out because the incentives to keep burning money on training go down if the products are good right now.

And I I haven't really seen the labs talk about it, but you can see the bigger companies that are that have to be much more tightly run, like Google, starting to understand, oh, we can deploy a lot of different models for a lot of different uses and lower costs across. Right. And it's funny too that, you know, these labs do promise like, oh, you know, as the years go on, prices are gonna drop. Don't worry, we're gonna offer these models and access cheaper and cheaper. But

That doesn't really square with what's gonna have to happen for them to turn a profit, especially one that investors won't like roll their eyes at. So that's what's gonna be interesting. There's a lot of tension here that we'll have to track over the next six months or so because You know, that this is gonna be the big year for uh paying the piper.

Yeah. Well I mean there's only two ways to do it, right? You can increase the number of people paying the amount they're paying now, or you can increase the price. Which one do you think is gonna? I it's funny because that's exactly what an economist was telling me this morning. He's like, Well, like you either gotta expand to basically the entire general public globally Or um you're gonna have to raise the prices a lot and then even then it may not square with like what you actually need. So

We'll see. It's gonna be a really interesting year. Yeah. Like I said, it feels like this past week, real inflection point as we saw anthropic. starting to play with pricing in a way that shifted user behavior, I think somewhat meaningfully. And then OpenAI realizing it needed to get into the more lucrative part of the market and abandon some things that got it a lot of attention. But ultimately had no path towards money. What do you think happens next?

I think we're gonna see OpenAI further um, you know, can kinda consolidate resources into these two focuses and lose a couple of other side projects. So, you know, we've heard maybe Atlas is gonna go by the wayside. Um, probably, even though they haven't said this, um, some safety research, I would guess, or at least, you know, doing what they tend to do, which is

kind of uh reassigning people on a certain safety research team into other departments. And so they say they're not actually, you know, diminishing the research, but who knows whether they are or not. Um, you know, so I think we'll see some changes to its research org and maybe people studying long term risks. They've gotta keep some of them around'cause it's good PR, but you know, I could see them definitely kinda like on the D L, uh reassigning some of those people. Um, and then yeah, I mean

It's all about just devoting more compute to the things that are gonna make the most money so that they can make investors happy. And so, you know, wh and whatever ways they can do that, that's what we're gonna see probably in maybe another funding round before they go public. Um, OpenAI is also reportedly trying to go public before anthropic. That's something Sam Altman is apparently really serious about. But he's apparently ro the information reported uh like kind of uh

sparring with it CFO Sarah Fryer about that. She apparently doesn't think it's ready to go public. as quickly. So yeah, we're gonna see maybe some more leadership turnover. Who knows? But you know, we'll be the I think that the next couple of months are going to be very interesting for executive turnover, um, which projects get killed off and

Also like probably some top engineers going from one lab to another or vice versa. And w tracking who's moving and to where and what team they moved from is gonna be really telling as well. I feel like we could do another full hour of Decoder on just how much the AI industry is driven by Dario and Sam hating each other specifically. I don't know if that's today, but you're gonna come back and do that one soon. Hayden, thank you so much for being on Decoder. Thanks so much.

I'd like to thank Hayden for taking the time to join the Coder and thank you for listening. I hope you enjoyed it. To like let us know what you thought about this episode or really anything else at all, drop us a line. You can email us at decoder at the verge dot com. We really do read all the emails, or you can hit me up directly on Threads or Blue Sky.

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Decoder is a production of The Verge and part of the Box Media Podcast Network. The show is produced by K-Cox, Nickstat. This episode was edited by Xander Adams. Our editorial director is Kevin McShane. The decoder music is by Breakmaster Cylinder. We'll see you next time.