Why AI researchers are getting paid like NBA All-Stars

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Hello and welcome to Decoder. This is Alex Heath, your Thursday episode guest host and deputy editor at The Verge. Today, I'm joined by Hayden Field, The Verge's new senior AI reporter. We're going to talk about the AI talent wars and why some researchers are suddenly getting traded like their NBA superstars.

If you've been paying attention at all to the industry this past month, you've likely seen stories about the hiring frenzy that's been happening between big tech research labs and AI startups. Leading the charge here has been Mark Zuckerberg, who has been making some truly unprecedented job offers to try and lure top AI talent to meta. But there's a whole lot more to this story.

Hayden and I have been reporting on this for the past several weeks to get a sense of how big some of these offers really are, why companies like Google are opting to hire instead of acquire. and what it means that some of the most sought-after AI experts in the world are no longer motivated by money alone. Hayden, so good to have you on the show. Your first Decoder appearance. Welcome. Thanks. I'm so excited and honored, especially to be talking about this. It's just crazy out there right now.

It is crazy out there, for sure. Before we jump into this, Hayden, since you've only been at The Verge for, gosh, what is it, a couple months now?

Talk a little bit about your beat. What are you focusing on and what are you excited about? What should people be reaching out to you about? I've been on the AI beat for about five years now. It's been insane to see how much it's changed in that time because I started before ChatGPT was even a thing.

I think the most interesting part of the beat to me is the power dynamics involved and the societal implications. It's crazy how much money is at play here in the hands of so few people leading the charge. And the fact that this is one of the only industries now where you can get a ton of funding, a ton of buy-in without even having a product yet.

So I would say, you know, interesting things about bias and systems ways they're affecting our everyday lives right now that maybe the public should know about. And just crazy stuff about the power dynamics involved, whether it's the executives and how they handle their power and the way that they advance these systems forward with or without the...

opinions of the people building them, their employees, and also just kind of the societal implications and how this is starting to affect everyone's everyday life when a few years ago it maybe wasn't. We've both been talking to sources.

around the AI industry for the last month or so about this talent war that's going on, these crazy offers that researchers are getting. People have seen this mostly as it pertains to meta and the you know 100 plus million dollar offers that mark zuckerberg's been making but there's actually a lot more going on underneath the surface and it gets to that power dynamic that you just talked about the amount of money

is eye popping and hard to make sense of if you're not in the industry. So we're going to talk about all of these key things. I think I would like to start though with meta, just because it is the way that people have seen.

the talent wars manifested in the last month or so, what Zuckerberg has been doing. I think it's important really to step back and think about like, why is meta doing this specifically? And why are they being so aggressive with going out and trying to hire people and spending amounts that surpass what the highest paid CEOs on the S&P 500 make?

I mean, it's obvious if you follow this that Meta is behind in AI. Llama 3 was a good model, was well-received, and then Llama 4 earlier this year was not. And actually, internally, what I heard was that Llama 4, in the user's eyes, was worse than Llama 3. And it actually hurt the engagement for meta AI, which is Zuckerberg's would-be chat GPT killer.

And considering that everything is AI these days and that the stock value of these trillion dollar companies is tied to their AI initiatives, that's not good. And if you're behind on the model race, you're behind on potentially winning. AGI, super intelligence, whatever you want to call it. And Zuck was obviously not wanting that to happen.

He's going out and canvassing and has basically hit up every hot AI startup and respected AI researcher you could think of, finally assembled a team. And yeah, I would be curious, Hayden, when you saw... These headlines first coming out about meta. What was your reaction? So I think that's a great point about Zuck wanting to avoid being embarrassed. I think he already put so much into the metaverse stuff. He was like, I can't lose on AI too. But when I first saw these headlines coming out.

I was thinking I wasn't surprised in some ways because there's so much money flowing in the industry right now, whether you're pre-profit, pre- product pre-everything right now, that it didn't surprise me that some of the biggest movers and shakers, the biggest builders in this space are getting recruited this hard. What I was interested in is how many people are really getting these crazy offers versus

How many are just getting normal offers? Normal for the AI industry is still obviously really high, but nowhere near these crazy numbers that we saw from a select few. So yeah, when I did some digging, I saw... All is not really what it seems here. Only the real top brass, the top AI researchers that have built, you know, the viral products that we all know.

have been getting these crazy offers. AI researchers specifically, not just engineers, it's specifically researchers are mostly getting these crazy offers. Yeah, as you brought up. buyouts and performance metrics are a big part of this too. There's a lot of unseen kind of

There's caveats in these offers. So it depends on your performance, how long you stay. And some of them are pretty subjective. So I think that's an interesting, you know, kind of side part of the story here. Subjective, you mean in terms of the performance aspects of the offers?

Right. Some of them are tied to specific performance metrics that may be a little bit vague or may be decided upon by the people above you. That's what I'm hearing, at least from people that have turned down these offers. weren't fully sure on what it would really entail. And so, you know, they would rather just stay where they know what's what. It's important to distinguish the researchers from the engineers, the people who are researching frontier models.

There's not a lot of them. This is actually a supply and demand issue based on my conversations. It's easy to say that there's probably less than 2,000 people in the world helping build a frontier model from the research perspective. So when you have that kind of imbalance of the amount of money that is invested into the space and the people who can actually build it.

they become a very, very hot commodity. So that makes these numbers less crazy in the context of the money that's being spent when Meta, Google, Microsoft are spending tens of billions a year. on data centers, on data to build these models, spending a few billion on the talent to run all of that is not as crazy. The meta offers are interesting. And you talked about this.

They're not as just clear cut as people make them out to be. Like Zuck is not just walking up to a respected AI researcher and giving them a guaranteed half a billion dollar payout over four years. These are mostly. performance-related stock awards. In many cases, they have aggressive clawbacks where if someone leaves early, they have to forfeit a lot of the money, even that signing bonus that a lot of people are getting, which is really the thing that I've heard a lot of AI researchers.

competing labs are lured by is getting $100 million up front to just join a company. But it's not really... guaranteed if you leave you have to pay it back if you don't hit certain performance metrics you won't be guaranteed that full payout so It's more complex than it's made out to be. And I think in that context, the offers and the numbers are not as crazy. They're still crazy, I think, to anyone who's not in the AI world, but they're not as crazy.

Right. Exactly. And there's also a lot of boomerang and bouncing around. Like I was talking to an AI consultant and he knew someone hired for, you know, a couple hundred thousand dollars as a growth executive at an AI firm. So not a researcher, not an engineer, but.

flown to an international offsite and then he was cut two months later due to lack of sales. So those performance metrics affect everyone, but they obviously uniquely affect those people that are getting those huge signing bonuses. And, you know, it's going to cut you back a lot if you don't deliver. Yeah, and delivering for a company like Meta is realistically adding trillions of dollars in market cap.

It's getting to super intelligence, whatever that means. I'm not sure the industry actually knows what that means, but building this kind of all seeing all powerful AI and making meta the. undisputed winner in the consumer AI race, which means when you think of AI and interacting with it, you don't think of ChatGPT, you think of meta. That's going to be a very hard goal to crack. Especially with the name meta. On that note we have to take a short break. We'll be right back.

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Welcome back. This is Alex Heath talking with The Verge's senior AI reporter, Hayden Field, about the big talent wars bursting out all over the AI scene. Many of these companies are spending absolutely ridiculous amounts of money to hire top talent outright, but that's not the only way they're poaching folks.

Big tech has gotten its way through acquisitions for a long time, but now there's something else happening where companies like Meta, Google, and Amazon aren't buying up whole startups. They're just buying the parts they want. Let's move on to another aspect of the talent wars, which is all of these interesting acquisitions that are happening. And they're acquisitions in a different way.

Recently you had a great scoop for us here at The Verge about Google sweeping in to steal away a team of a very hot AI startup. Talk about that. We saw OpenAI's deal to buy Windsurf that had been, you know, really reported over months and months suddenly off. And instead, Google swooped in and hired the CEO, the co-founder and a lot of their R&D employees and just brought them onto the Google team.

mind team to build agents. So they're going to be working on Gemini. Google's not going to have a stake in Winserv or Control, but... It's going to take a non-exclusive license to some of Windsurf's tech. So it's been pretty crazy. Their head of business became their interim CEO. They had to suddenly name a new president. And a lot of the employees were kind of shocked by this because they had been pretty close for a long time.

long time it had been a team that had known each other for a while it was a perfect example of how soap opera-esque these hiring wars are starting to become you know when you're at a company and you've been there for a while maybe you're employee number one employee number two you

see on Twitter that most of your company, the talent of your company is being sold to Google and you're just kind of left with a shell. It's really, you know, just an example of the time we're in right now. Let's unpack that a little more. So Winsurf is... you know, one of the hottest AI coding startups. They were going to sell to OpenAI. That deal fell apart. And then, like you said, kind of like a soap opera, the team gathers and finds out that Google is actually hiring away.

the CEO and the core AI engineering team. So 40-ish people, the company is like 250 to 300 people. These people are already leaving. They're already out the door. And there's a new CEO and you all figure it out. And then over that weekend, Windsurf sells the rest of itself to another AI coding startup called Cognition. This happened in a period of like two days. over a weekend. And that shows, I think, how sought after these people are that are building these leading AI startups that

The moment there's a flare set up that there is a group of people looking for a home, someone will swoop in and immediately find them that home. And in the Google case, you know, this wasn't an acquisition, but I think we should call it what it is. Google avoiding antitrust scrutiny. Years ago, they would have just acquired all of Winsurf and not used the parts of the company that they didn't want.

Big tech can no longer make these kind of acquisitions for the most part. And so Google came in and said, we'll take the best people for us. We'll pay you a quote unquote licensing fee, which is really just money that then pays back the shareholders as if it was an acquisition that can also be used to pay back employee stock as if they were getting their company sold.

And what's left is, like you said, this shell of a company without its beating heart, so to speak, the people that build the AI models and the AI technology to then scramble and pick up the pieces. This is actually a pattern that's been playing out. It started with Inflection and Microsoft. Microsoft hired away the CEO of Inflection to run its AI group, Mustafa Suleiman. And then Amazon has done it twice with two different AI startups.

Google did it with character.ai. Meta just did it with scale.ai to bring in their new head of AI, Alexander Wang. And Google just did it with Winsurf.

I'm curious with these reverse acquihires that are happening, Windsurf and Google being the latest example, how does this impact the people on the ground at these startups, the people who either decide to go? or don't, or get left behind without a choice, how does it affect them and then just the broader ecosystem? Because this is a new thing that's starting to happen in Silicon Valley.

It's interesting because AI engineers, AI researchers, anyone in that industry has a sense of loyalty a lot of the time to where they... work. You know, sometimes they'll stay somewhere for their whole career so far, or they've known the founders for a long, long time, and that's part of why they took a job. So yeah, there's definitely a sense of you know, rejection or sometimes betrayal when things like this happen and you're left at your shell company and the person you...

got that company to work for, maybe one of the main reasons you made that decision is suddenly gone. We saw one engineer who said he was employee number two at Windsurf go viral on X for saying he got a... offer from Google that exploded within a day, you know, according to some of the replies, including people from Y Combinator, it may have been a

$20 million offer as part of a buyout. He said he forfeited his vested shares. He ended up going to Cognition instead. There was some confusion on whether he accepted the offer from Google or whether he turned it down, but either way, he ended up

at cognition. So yeah, we're seeing people jump ship when things like this happen to them, when they are left with a shell company. We're seeing some of them kind of ride the ship down and say, you know what, I'm going to see what happens. I still care about some of the people here. Scale is going through the same thing.

you know, after the big deal we saw. So it's kind of a new thing for these AI industry people to be contending with because it's not something that has happened in their industry before. To my knowledge, I don't think any of these startups that have been reverse-acquihired so far are doing objectively better than they were before. Big Tech came in and stole the founding team. Character AI is a great example.

It was a pretty viral chatbot kind of companion platform created by two early Google senior engineers. And, you know, since those guys went back to Google, you don't really hear about character as much. Zuck just hired the CEO and some of the core team for Meta AI's new lab, just did layoffs. Windsurf had to sell itself within days from Google sweeping in. So yeah, there's this, I think, interesting second order effect where big tech is coming in to these.

often really well-funded, well-positioned startups that are really red hot. They take the team and then the startup is left to pick up the pieces. And in many cases, they can't. And again, this is like...

This is a brazen like middle finger to regulators. Like scale is a great example. My understanding of the scale deal and why it happened so fast and was structured that way is Zuck wanted. Alexander Wang in the office immediately. And he was in the office within a few days of that deal being announced, working on setting up Meadows New Lab. There's an expediency to how these deals work where the acquirer

can get the people in its tent ASAP. And because the AI race is so red hot and every day counts for who is going to have the best model, who is going to be at the frontier, that speed. really matters. What's interesting with Google, though, Google feels like it's in a pretty good spot. I think Google's feeling, you know, they can come in and do the reverse aqua hire with Winsurf when they want some talent that's available in the market. I've heard that their DeepMind org is not really...

Getting into bidding wars with Zuck, like some of the other labs, like OpenAI, where a senior researcher compared it to a home invasion, what Meta was doing. Google is, I think, their bench of talent is so deep. And Gemini is considered to be such a good model right now.

That they feel like they can afford to lose people if need be. And they don't want to get into these crazy bidding wars. So that's been an interesting thing I've just observed about Google recently. I'm curious, especially, I think you've been reporting more on Anthropic recently. is another huge nucleus of talent that so far seems to be withstanding Zucks poaching more than OpenAI and others. Is that another one that we think is in a relatively good spot from a talent perspective, Anthropic?

I think so. built their reputation on caring a little bit more about safety. As we've seen, people disagree on how different their mission really is from open AIs. Over the years, it seems to be getting closer and closer. But either way, people who work there really feel that their voice is

heard about safety stuff. Top AI researchers really care about safety and they really care about how their work is being used. So, you know, whether it's making it up the chain or not, the fact that they feel they can talk about it, their voices are being heard, I think is leading to less turnover. And that's what I've seen. I mean, I was looking at a recent report of employee turnover at AI firms and anthropics was very, very low compared to open AIs and even deep minds.

I think they are set up pretty well to keep most of their talent for now. They also reportedly just got a way higher valuation, nearly three times their valuation in March. So, you know, people are making money. They feel like their voice is heard, at least for now. We'll see where it goes. But yeah, it does seem like they're pretty set up for now. Yeah. I mean, if you're a leading AI researcher and you're evaluating a...

really big offer from Meta, potentially hundreds of millions of dollars, but it's heavily tied to performance, right? And you're thinking about the upside to that offer. What are the odds that Meta adds another trillion in market cap versus Anthropic tripling its valuation in the next 18 months? It's probably more likely that Anthropic's going to go way up faster because Anthropic's just starting from a much smaller valuation. It's still huge, obviously, but it's small in relation to big tech.

Especially when the competition is so steep, like you said. I mean, everything OpenAI does, Anthropic and now even XAI are immediately following. They released a government product. Anthropic and XAI both released a government product.

Coding Help, Enterprise, those are their biggest moneymakers. And now that market is being like, you know, cut in three instead of them just cornering it. So it's definitely interesting to see. Yeah, I don't think that they have as much runway as they did before in terms of. the runway to growth and tripling that type of valuation. We have to take another short break here. We'll be back in just a minute.

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And that's exactly what your members can count on from CVS Caremark. More ways to maximize their benefits. Go to cmk.co slash stories to learn how we help you provide the affordability, support, and access your members need. Welcome back. Hayden and I are talking about the hot market for top AI researchers right now.

Before the break we were chatting about some of the incredibly lucrative cash offers folks are getting from the biggest companies but at a certain point maybe money really isn't everything.

You and I have both talked to researchers who have turned down offers that I think to most people, they would say, what in the world are you thinking? I talked to someone who got a personal reach out. from zuck and didn't respond which i was like props what motivates these researchers besides money i do think more motivated by money than they want to let on i think when you get to these kinds of numbers it's impossible to not be

But at the same time, someone just not responding to a Zuck reach out, I think, says a lot about the industry and the way that these researchers are motivated. What have you learned about that? So something that I've seen is pretty constant over the last few years in AI reporting, but is more evident now than ever, is that a lot of these key...

AI engineers or researchers are what you might call post money. Like they make so much that making more isn't in and of itself a motivator for them. Yes, they're motivated by money, but after a certain point, you know. It's kind of all fake. You know, you're making millions. OK, what's another few million? So they care a lot about how their work is being used, who they're doing it with, who they're doing it for, what their company's vision is in terms of.

accelerationism, societal impact, safety, risk. A lot of them have differing views on that stuff, but it's important to a lot of them that their company or the... leader of the team they work on aligns with them on whatever those views are. So yeah, we're seeing people turn down crazy offers, personal reach outs from execs. You know, I've heard OpenAI CEO Sam Altman always

calls at least most technical hires, potential hires with an offer, you know, to personally pitch them. These people know how in demand their work is, you know, because like you said, you know, there's maybe less than 2000 people that can do what they're doing right now and pushing the industry forward.

They really care about how their stuff's being used, who they're doing it with, what their work-life balance is. Maybe not so much the work-life balance because they're all working a lot, but at least what their work culture is, you know, how happy they are day to day and how much they believe in what they're doing.

So that's what I've thought is really interesting. Some of these people won't even consider an offer if they're already pretty aligned with their current workplace and, you know, not much could get them to leave. Yeah, the person I talked to who didn't respond to a Zuck reach out basically was like, I just, I can't work for that guy.

These CEOs, especially these founders like him and Elon, are very polarizing. And if you have the pick of wherever you want to work and you can name your price, you can afford to... to have it be a principled decision in that way. That makes sense to me.

The other thing I think is funny is that it's such a small world in this industry. A lot of people have worked together. And if you haven't worked with someone, you know, someone who has. So it's very gossipy. You know, like you said, that guy said, I wouldn't work for Zuckerberg.

a lot of other people that have said to me, you know, I couldn't take this meta offer. I couldn't even respond because I have friends that work there and their lives are... crazy they expect so many personal sacrifices whether on like your value systems or work-life balance he said you're expected to give pretty much your whole self to meta ai which is true for a lot of firms but personal relationships go a long way here whether

you're trying to get someone over to your company, or whether you're not responding to an offer. Even at Anthropic, you know, they have a couple teams where the people have worked together for years and years, some of them have gone to college together. There's a lot of like inside baseball here. and kind of hiring your friends and people you admire that you've known for a really long time. So yeah, it definitely is a small world. There's another aspect of this too, where...

The AI researchers are probably the hottest commodity in AI, but I think a close second is GPUs. A big pitch that these labs make to potential recruits is your access to GPUs and that access being guaranteed. OpenAI has been public about needing to divert GPU allocation away from research to product because ChatGPT has just gone parabolic with its growth. So if you're a leading researcher and what really motivates you is pushing the frontier.

achieving AGI and, you know, really pushing forward these benchmarks, you need those GPUs. And if someone like Zuck can say, look, I'm dolding, you know. a data center the size of Manhattan, I'm going to guarantee you more GPUs than you can be guaranteed anywhere else. That's a huge draw, is what I've heard, because it's basically the GPUs are the fuel for the work, right? And I don't think that gets talked about a lot.

But that to me is just almost as important as, you know, how people feel about the mission of the company. Definitely. That's true. Because, I mean, people get frustrated when. Those types of resources are diverted away from their team. There's infighting in that regard. You know, we saw that at OpenAI. When you're promised a certain amount of compute and then you're deprioritized, that can lead to leaving. There's also, yeah, a lot of disagreement.

When you're at a startup that doesn't have access to a lot of computing, you feel like you can't build what you're trying to build or you can't do the job you were hired for. They're all trying desperately to kind of hold on to who they have and, you know, just kind of. give them more compute, give them more money, whatever they can do to, you know, keep their talent in house. If you can lock up.

a considerable amount of talent, right? Like the new chief scientist for his lab was the co-creator of ChatGPT and GPT-4, right? If you can lock that guy up for four plus years with a package, a compensation package that can't really be matched by anyone. that has aggressive clawbacks, that is performance-based, you're taking players off the market, right? You're taking, you know...

athletes off the field, so to speak. It's a defensive move as much as it's an offensive move. I was talking to an AI exec at Databricks late last year, Naveen Rao, who is always, I think, really prescient on this stuff. And he was telling me something really interesting. a quote. He said that the leverage that a researcher has in an organization is unprecedented. One researcher's ideas can completely change the product. That's kind of new. He compared it to semiconductors.

And that being the last area of tech where this kind of leverage from a specific individual was possible, where if you invented a new transistor architecture, you could potentially create billions and billions of dollars in value. I think connected the two. And for me, that makes a lot of sense. You know, if you come up with a new scaling paradigm for one of these models that leads to Meta having to spend billions of dollars less on its data centers to...

run inference for its model, you've paid for yourself, you know, potentially 10x, even if you're making a billion a year. Yeah, it's a huge investment. And, you know, one that... often will pay off depending on the right person. That's why they're being so choosy about who they get these big offers to, especially an investment. Like you said, that you can lock up like a target date fund. You're like, we're going to invest in this guy for four years, at least see what he gets us. And then.

reevaluate. And that's why I think there's still so much gossip and craziness around meta poaching Daniel Gross, the former CEO of Safe Super Intelligence or SSI, Ilya's startup. Ilya then had to step in and become the CEO, because that guy was leading one of the...

biggest dark horse new competitors in AI. And now he's at Meta. So they must have done the exact same thing, you know, just offered him something he couldn't say no to, lock him up for a few years and see what kind of he can get them. It's really crazy how much... outsize influence one person can have at one of these companies when you're actually building the stuff that they want their entire company to focus on.

For people who don't know, Ilya was the co-founder of OpenAI, the chief researcher, tried to fire Sam Altman, now has his own AI lab. It is pretty amazing. Zuck wanted to buy that whole lab. Ilya said no. Ilya is definitely in the post money. category of AI minds and instead Zuck hired away his CEO. And like it's savage, but it's, you know, you're going to get who you're going to get. Let's end here by going back to where we started and this idea that bidding on

top AI talent now looks something like the NBA transfer market. So we already covered how some of these numbers are maybe not as eye popping as they seem at first, because there's a lot of caveats involved and there's. really not that many of these top AI researchers in the world. But even with those disclaimers, I think it's still important to put something like $100 million per year offer in perspective, because a number like that can just start to make your mind turn to mush, at least for me.

Some of these key AI researchers are getting hundreds of millions of dollars over several years, often. $100 million signing bonuses, right? That is more money than the highest paid CEOs in the S&P 500. Apple CEO Tim Cook, his pay last year was about $74 million. Satya Nadella at Microsoft was about $79 million. And when you compare this to like the NBA, they're making more than like Steph Curry, who's the highest paid athlete in the NBA. His total earnings were about $155 million.

for the last NBA season. The numbers for Tech though are just... they're way bigger, right? It is also crazy to see, you know, TBPN announcing these researcher moves like their trades or, you know, huge athlete movers. I mean, we saw even, and I'm also wondering how...

these employees are dealing with the limelight. You know, I can't even imagine if I announced on LinkedIn, I was moving to a new media startup, if all these like huge Twitter accounts are like, oh, Hayden Fields moving, like, what's she doing? And you know, they're maybe not equipped to deal with this. Like two anthropic employees that were not even the top researchers of building.

Claude itself, but two liters of the coding product, you know, left Anthropic for a big signing bonus, I hear, at AnySphere, the developer of Cursor. But then they came back two weeks later and it was all over Twitter. You know, every news account is tweeting about it. internal tech podcast. And it's just interesting to see, yeah, these moves reported like they're like, you know, big athlete trades.

I mean, they are. They're bigger than athlete trades. They're bigger than any NBA superstar making a trade. And like the impact that these people can have is it's not as entertaining as watching a game, but it is bigger from an economic and tech perspective. So it is a new thing though. I would say like this summer is the summer of, you know, AI researchers being talked about like superstar athletes. You're getting paid three to $500 million.

in a total package to join Meta, there are public companies, that's their annual revenue, like Wix or Squarespace. So like you are a stock. in that sense, as an individual. I am wondering where all this goes. This feels like maybe peak AI talent bubble. Maybe not. You know, if AGI does happen, maybe it's not. But for right now, everyone I've talked to keeps saying people have been around, people have seen different tech super cycles.

are all saying, we've never seen anything like this. And I'm just wondering where it goes. And I think Meta is a great kind of bellwether of, you know, they bring all these people in, they pay billions of dollars to assemble this elite team. If it doesn't work, what does that do to the industry, right? Do you feel like there's room to run? Like these offers are going to get bigger? Or do you feel like we're kind of at peak hype here?

I think we're at peak hype, honestly. I think this is like a Hail Mary situation. They're doing all this. They're seeing if it pays off in a few years. And then after that, we see where it goes. I think it will not get bigger. It'll either stay the same or go lower. The other interesting thing... to me is that I think as we see this industry progress and advance as quickly as it has been, the kind of amount of

seniority you have to have in order to really be desirable is going to increase and increase you know we're already seeing open ai and anthropic talk about how their models are close to or pretty much can already replace an entry-level engineer at their companies. The people that are going to be in demand are those that can shape and guide and deal with the big picture of these models rather than doing entry-level jobs to help train.

them and, you know, kind of deal with more of the minutiae. So it's going to be interesting to see the titles that are more in demand just kind of keep getting higher and higher rather than, yeah, those kind of entry-level AI hires. I'm glad you brought that up. And that dynamic you just explained is why I kind of agree with you and I kind of don't. I think that there won't be as many people getting these kinds of numbers offers in the AI world.

But I think the fewer people who are getting them will get more money because the leverage continues to grow per individual as AI starts to do more of the underlying work. So maybe it's like 50 people who are each getting $3 billion offers. Honestly, people I've talked to say that is a feasible future to imagine given the rate of change.

I can see that. Like you said about individual people being stocks here. Yeah, I mean, you know, they're going to see how that stock performs and then use that to inform future offers. So you're absolutely right. Well, Hayden, this has been great. Thank you so much for coming on Decoder. And given the AI news cycle, I bet we'll be having you back on here very soon. Yeah, thank you. This is a blast.

I'd like to thank Hayden Field for taking the time to join me on Decoder. I hope you enjoyed it. If you'd like to let us know what you thought about this show or what else you'd like us to cover, drop us a line. You can email us at decoderattheverge.com. The team really does read every email. We also have a TikTok and an Instagram. Check those out at decoderpod.

If you like Decoder, please share it with your friends and subscribe wherever you get your podcasts. And if you haven't already, don't forget to subscribe to The Verge, which gets you access to my newsletter, command line, and a bunch of other great stuff. Decoder is a production of The Verge and is part of the Vox Media Podcast Network. Our producers are Kate Cox and Nick Stat. Our editor is Ursa Wright. The Decoder music is by Breakmaster Cylinder. See you next time.

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