The AI Industry Is Becoming Like Professional Sports

Summary

Odd Lots Podcast Summary
Episode: "The AI Industry Is Becoming Like Professional Sports"
Release Date: August 4, 2025
Hosts: Joe Weisenthal and Tracy Alloway

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Introduction

In this engaging episode of Bloomberg's Odd Lots, hosts Joe Weisenthal and Tracy Alloway delve into the evolving landscape of the AI industry, drawing parallels between AI talent acquisition and the world of professional sports. They explore the burgeoning "sportsification" of AI, characterized by intense competition for superstar talent and unprecedented compensation packages. The episode features insightful discussions with industry insiders John Coogan and Jordy Hayes from the live show podcast TBPN.

The Sportsification of AI

Joe Hager opens the conversation by contemplating a career pivot to AI research, sparking a broader discussion on the current state of the AI talent market. Tracy Alloway elaborates on the intense competition for top-tier AI professionals, highlighting terms like "exploding offers" and "aqua hires."

Notable Quote:
Joe Hager [02:08]: "But I kind of just think... we seem to be in a moment where it's actually becoming like the sportsification of a lot of different industries."

Compensation Packages and Talent Wars

The hosts and guests examine the staggering compensation packages being offered to AI researchers, with some engineers reportedly receiving up to $100 million or more. John Coogan addresses the reality of these offers, asserting their legitimacy despite widespread skepticism.

Notable Quote:
John Coogan [05:35]: "They seem like they are very real offers and they are indeed happening."

The discussion underscores the capital-intensive nature of AI development, where even marginal improvements in efficiency can justify exorbitant salaries.

Notable AI Researchers and Their Impact

The episode spotlights leading AI researchers, particularly Ilya Sutskever of OpenAI, who is lauded for his pivotal role in advancing transformer architectures. Coogan praises Sutskever's ability to identify and execute the most promising paths in AI research.

Notable Quote:
John Coogan [09:17]: "Ilyas Sutskever is really, he's at the top of our list for a variety of reasons."

Acqui-Hiring Trends and Case Study: Windsurf

A significant portion of the discussion focuses on the trend of "acqui-hiring," where major tech companies acquire smaller firms primarily to onboard their elite AI talent. The case of Windsurf is examined in detail, illustrating the tumultuous process and the strategic maneuvers involved in such acquisitions.

Notable Quote:
John Coogan [20:22]: "When these deals happen, this just happened with scale AI and Meta."

Jordy Hayes recounts the Chaos surrounding Windsurf's attempted acquisition by OpenAI and its eventual acquisition by Cognition, highlighting the emotional and professional turbulence faced by employees.

Economic and Legal Implications

The hosts explore the broader economic and legal ramifications of the AI talent war. Issues such as intellectual property (IP) transfer, non-compete agreements, and potential litigation from "acqui-hire" activities are discussed. The conversation touches on historical precedents in other industries, emphasizing the unique challenges posed by AI's rapid advancement.

Notable Quote:
Tracy Alloway [34:52]: "What are we going to get AI talent agents? ... but AI talent agents because like we do."

Venture Capital and Investment in AI Talent

The episode delves into how venture capital (VC) firms are adapting to the AI talent war. Instead of traditional investments in products or services, VCs are increasingly investing in AI researchers themselves, betting on their future acquisition by tech giants. This shift reflects a new investment paradigm where individual talent becomes the primary asset.

Notable Quote:
John Coogan [45:42]: "We're happy to have you join the team...you just get the bag."

Future Outlook and Conclusions

In wrapping up, the hosts and guests reflect on the sustainability of current compensation trends and the long-term implications for the AI industry. They ponder whether AI's "sportsification" is a transient phase or a lasting transformation, considering factors like the increasing capital requirements and the potential for legal constraints.

Notable Quote:
John Coogan [31:15]: "Something sustainable either Tim Cook has to make more money or researchers make less."

The episode concludes with a consensus that while the AI talent war mirrors professional sports in its intensity and rewards, its unique economic dynamics present distinct challenges and opportunities for the future.

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Key Takeaways

• Sportsification of AI: The AI industry is increasingly mirroring professional sports, with intense competition for superstar talent and substantial compensation packages.

• Exorbitant Salaries: Top AI researchers are receiving multi-million to hundred-million dollar compensation packages, driven by the high capital demands of AI development.

• Acqui-Hiring: Major tech companies are acquiring smaller AI firms primarily to secure their elite talent, leading to significant industry consolidation.

• VC Investments in Talent: Venture capital firms are shifting their investment strategies to focus more on individual AI researchers, anticipating future acqui-hires by larger corporations.

• Economic and Legal Challenges: The rapid expansion of AI talent compensation raises questions about sustainability and potential legal hurdles related to IP and non-compete agreements.

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Notable Quotes with Timestamps

• Joe Hager [02:08]: "But I kind of just think... we seem to be in a moment where it's actually becoming like the sportsification of a lot of different industries."

• John Coogan [05:35]: "They seem like they are very real offers and they are indeed happening."

• John Coogan [09:17]: "Ilyas Sutskever is really, he's at the top of our list for a variety of reasons."

• John Coogan [20:22]: "When these deals happen, this just happened with scale AI and Meta."

• Tracy Alloway [34:52]: "What are we going to get AI talent agents? ... but AI talent agents because like we do."

• John Coogan [45:42]: "We're happy to have you join the team...you just get the bag."

• John Coogan [31:15]: "Something sustainable either Tim Cook has to make more money or researchers make less."

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This summary encapsulates the core discussions and insights from the Odd Lots episode, providing a comprehensive overview for those who haven't had the chance to listen.

Transcript

[Karen Moscow]

Bloomberg Daybreak is your best way to get informed first thing in the morning, right in your podcast feed. Hi, I'm Karen Moscow.

[Nathan Hager]

And I'm Nathan Hager. Each morning we're up early putting together the latest episode of Bloomberg Daybreak US Edition. It's your daily 15 minute podcast on the latest in global news, politics and international relations.

[Karen Moscow]

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[Nathan Hager]

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[Karen Moscow]

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[Nathan Hager]

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[Karen Moscow]

Find us on Apple, Spotify or anywhere you listen.

[Tracy Alloway]

Hey Odd Lots listeners, the Wall Street Journal has a podcast for you. WSJ's take on the week cuts through the noise and dives into markets, the economy and finance.

[Nathan Hager]

Do you think we will see 2%.

[John Coogan]

Inflation again anytime soon? Gosh, until you put on the anytime soon, I was gonna say absolutely yes. Probably not.

[Nathan Hager]

I'm Gunjan Banerjee and I'm Telus Demos. From breaking down the big trades to talking with key players, every week we'll get you set up with what you.

[John Coogan]

Need to know in the worlds of market.

[Tracy Alloway]

Subscribe to WSJ's take on the week. Wherever you get your podcasts.

[Nathan Hager]

Bloomberg Audio Studios Podcasts Radio News hello and welcome to another episode of the Odd Lots Podcast. I'm Jo Weisenthal.

[Tracy Alloway]

And I'm Tracy Alloway.

[Nathan Hager]

Tracy, I love doing the podcast, but I'm kind of thinking about becoming a PhD level AI researcher. If I do a career pivot, it seems something I'm curious.

[Tracy Alloway]

It's the place to be.

[Nathan Hager]

Have you seen have you seen like the salaries supposedly? I still don't actually believe them, but have you seen like the salaries and comp packages that supposedly Meta and a few others are paying for?

[Tracy Alloway]

I have seen some of the headlines. I have also learned a bunch of new words like exploding offer and aqua hire. Oh yeah, I always thought exploding offer sounds dangerous. What you want is an explosive offer that you can't turn down.

[Nathan Hager]

I take it the exploding hire is like one that lasts like five minutes.

[Tracy Alloway]

Yeah. So you have to make a decision right away and the company that you're currently working for. Can't counter offer.

[Nathan Hager]

So I read these headlines about some engineer or something getting paid 100 million or 250 million. I actually literally don't believe them. Like, I actually literally think that's fake news.

[Tracy Alloway]

Really?

[Nathan Hager]

No, but I kind of just think.

[Tracy Alloway]

It'S probably made up of like all this weird equity structure.

[Nathan Hager]

But I'm sure it's not all up front. Anyway, we sort of seem to be in a moment and it's actually not. Not just AI, I would say journalism, finance, et cetera, where it's like the sportsification of a lot of different industries. Individual talent, the demand for individual superstars on anything doing very well.

[Tracy Alloway]

I have a bunch of questions when it comes specifically to AI, such as what makes an AI talent? Because I assume if you're Mark Zuckerberg and you're trying to assemble your AI dream team or something. Okay, sure, you have like a level of technical insight and maybe you hear people talking about, oh, this one guy is fantastic. But I assume it's not like you can look at their, like, individual levels of code and you can't see what they're doing on like a daily basis. I don't know.

[Nathan Hager]

I don't know either. I don't know anything about this stuff. But I'm really excited to say we do have the perfect guests. A couple of guys who are right in the middle of all of this and also who have sort of been ahead of the curve in terms of this, like I said, the sportsification of the industry. We're gonna be speaking with John Coogan and Jordy Hayes. They are the co hosts of tbpn. It's a live show podcast. It's become one of my favorite new media properties. It exists and I'm really excited we have them both in the studio here with us today. So, Jon and Jordy, thank you so much for coming on Outlaws.

[John Coogan]

Thanks for having us.

[Jordy Hayes]

We're so excited to be here.

[Nathan Hager]

I love, by the way, you guys make these, like, baseball cards every time. So it's so clever. For those who are not paying attention, why don't you sort of give the high level overview of like, what you see happening in this, like, crazy talent war. For people who don't know about this, what is actually going on, this, this talent war for, for people who know how to do AI or train a model or whatever it is.

[John Coogan]

Yeah, the League or the Mag 7, the serious teams are all worth over a trillion dollars. Tesla's in a different kind of boat some days, but pretty Much. There's multiple, there's 7 trillion plus dollar companies now. So there is an inordinate amount of money to flow around. And if you think about investing 0.1% of your market cap to make your business potentially 5% better, that's a trade you take all day. The number is staggering. But now you're seeing companies pay hundreds of millions of dollars. I think you mentioned that, you know, there was a lot of debate over whether that was fake news or not. They seem like they are very real offers and they are indeed happening. And there's a whole bunch of different ways that you can kind of underwrite that. Could start with going through just a little bit of the history here of how we got into this place or what these AI researchers are actually doing. I'm happy to kind of answer any question.

[Tracy Alloway]

Okay, well why don't we start with the baseball analogy then? If I was collecting AI engineer cards, who's the most valuable? Like who do I actually want to have? And then secondly, what are the stats that are printed?

[John Coogan]

For?

[Jordy Hayes]

Sure. So taking a little bit of a step back, talking about kind of the sports ification of, of tech and business, which has been a huge catalyst for our show, I think we realized early on people would call TBPN the Sports center for Tech or some analogy like that. We were a little bit, it sounded cool. We didn't really know what that meant. John and I don't watch sports at all from, for, for basically, for basically like two decades now. I'm in my late 20s, John mid-30s. And we've followed tech and business the way that our college friends follow sports. So the comp in sports you have players, personalities, coaches, managers, leagues, teams, and, and people obsess over all the details. I never fully understood that. I mean I, I understood kind of the draw, but it just was never for me. Whereas John and I would pick up the newspaper as teenagers and we were tracking the, the talent, the CEOs, the companies, the markets, the industries. And it's just something that we obsessed over. And so this year has been amazing as these AI researchers have been getting these sort of superstar max contracts, which is what we would call them. We would start joking on the show and be like, look, this guy just went over to Meta. It's probably, you know, four year contract, you know, one year cliff. And it just got more and more and more real as the kind of demand for world class AI researchers completely outstripped the supply. And we actually put out something a couple days ago called the Metis list. And John can go a little bit more into, into the name behind that. It was kind of our take on the Midas list, which was we built a list of top roughly 100 AI researchers and ranked them on a bunch of different factors. And so when you talk about what goes into what makes a great, you know, AI researcher, there's a bunch of different factors. One that you can get right into the numbers with is like citations. So if somebody's a researcher, they've been publishing, you know, studies, papers, et cetera for quite a while at this point and you can just see quantitatively what their contributions have been to the industry. And so that's like a good starting point to understand. And historically Elon even said earlier this week, honestly it was like an hour after we posted the Metis list, probably unrelated, but who knows. He's basically saying that AI researchers and engineers, we're just going to call them engineers now. And that makes a lot of sense for someone like Elon to do as somebody who's always been very engineering focused, less focused on, you know, entirely net new innovation, more so how do we make the best possible versions of products that exist. And it's not to say that he hasn't innovated in a bunch of different ways, but it is a really wild moment in time and it's been a fun moment because historically you hear about this Midas List investor, you know, making $2 billion of carry on some deal or this founder, you know, Ipoing today we have know the Figma IPO and you know there's bunch of people that are going to make billions of dollars there. But you don't hear about the hundredth engineer that was hired. Yeah, making a $100 million signing bonus. And all of this makes a ton of sense in the context of what John said because you look meta's up. I checked this morning. $195 billion new market cap. And think about how many hundred million dollar signing bonuses you can make against that kind of market cap.

[John Coogan]

Should we answer your question about who.

[Tracy Alloway]

The who's the best?

[John Coogan]

Who's the white whale? Who is the.

[Nathan Hager]

Did you say white whale? From the novel Moby Duck.

[Tracy Alloway]

Don't say anything about whales or whale products or hunting large mammals.

[Jordy Hayes]

Tired of being about Moby Duck.

[John Coogan]

Perhaps he's the white whale, perhaps he's the Michael Jordan of AI researcher. But Ilyas Sutskever is really, he's at the top of our list for a variety of reasons. And if you're not familiar with Ilya Sutskever, he is an AI researcher who was at OpenAI for a long time and there's a few different ways to characterize him. He is both coming up with new ways to implement AI algorithms, the way you train the model, but he's also very good at, for a long time identifying which, the shortest path in the tech tree. So there are, there are branches of choices that you need to make as you develop the new AI models. And he was very early at, while he was at OpenAI, he identified that the transformer paper from Google, he didn't invent that, it was at Google, but the transformer technology was extremely important and that it had the ability to do remarkable things when scaled up massively. And so he was the driving force between kind of identifying the transformer as the correct path. Now we look back on attention is all you need, which is the name of the paper that defines the architecture that is used in these modern large language models that you use when you're in ChatGPT. There were 25 other potential paths that we could have gone down. He, you know, the story goes is that he really identified that and said, let's go really, really hard on that.

[Tracy Alloway]

So he can sort of scale it, identify the innovation, what's new, and then also identify the most efficient path to actually execute on.

[John Coogan]

Yes. And if you're familiar with what, the more, the more modern. So the first arc of LLMs and these chatbots scaling up were really this pick the transformer paper, understand that that's the correct architecture and then scale it up really, really big. So you need to be able to not just write the code to implement that particular algorithm. You need to marshal the capital to say, we're going really, really big and we're going to build a big data center. We're going to spend a. But it's going to be worth it because we understand the trade offs here. Then the second kind of innovation or correct call he had was during the Sam Altman ouster and return. He was working on a project that was codenamed Q Star. And there was a lot of speculation about what Q Star was. Was it the secret superintendent?

[Jordy Hayes]

And everybody was saying, what did Ilya see?

[John Coogan]

Yes. Yeah. Because he was going back and forth in support of Sam Altman and then leaving and then he was back and forth and there was a lot of drama there. Always keep them guessing, always keep them guessing for sure. And there was a lot of rumors. But what it wound up being was just reasoning, which is now what is available in, if you use any of the O3 models in ChatGPT, or you use Deep Seq R1 and it goes by a number of different names. The project was rebranded Strawberry and then the O series and you can think about this as test time. Inference is the other buzzword, but basically the LLM, you're using the same foundation model, but you're running it a ton more to come up with a bunch of potential answers to questions and narrowing that down and essentially applying what's called reinforcement learning to the transformer architecture and the pre training that's happening. And so he was very critical in leading that project and so that's allowed him to eventually, once he left OpenAI, go start a new company called Safe Superintelligence SSI. And he's gotten that company to what, a $30 billion valuation? $33 billion. $32 billion valuation.

[Jordy Hayes]

Which ties into the talent war because I think it's. I don't know that it's been officially announced yet, but people are expecting Daniel Gross to join Meta, who was the.

[John Coogan]

CEO and co founder of that company, sfci. And so back to your, Back to.

[Jordy Hayes]

The white wheel question, the dynamic.

[Nathan Hager]

Yeah, yeah.

[Jordy Hayes]

A few guys get together, they start a company, within a year, it's worth $32 billion.

[Nathan Hager]

Yeah.

[Jordy Hayes]

And one of the people on that team decides to actually leave and go join Meta. And it sounds insane, probably leaving billions of dollars on the table, but you can kind of trace this talent war actually Back to the OpenAI founding team. When you think about all the different players, right, you have Mira Muradi, who's now with Thinking Machine, she was the CTO of OpenAI. You have Ilya Sutskever with SSI, you have Elon with XAI. And not to mention you have these sort of hyperscalers who are also competing for the same talent. So yeah, that's really kind of the origin story in the genesis. And it's been Amazing to see OpenAI's progress despite, you know, the recent reporting is around, you know, losing a bunch of top researchers, which is real. But it wasn't that long ago that they lost like two very, very, very key senior execs. In Ilya and Mira.

[Karen Moscow]

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[Nathan Hager]

And I'm Nathan Hager. Each morning we're up early putting together the latest episode of of Bloomberg Daybreak US Edition. It's your daily 15 minute podcast on the latest in global news, politics and international relations.

[Karen Moscow]

What's special about Bloomberg Daybreak is the immediacy of the news we bring you each day in your podcast feed by 6am Eastern Time.

[Nathan Hager]

This isn't a deep dive on yesterday's news. Instead, you get the latest stories with context.

[Karen Moscow]

And that's something you don't get from other news polls podcasts. So join us for the best from Bloomberg's 3,000 journalists and analysts around the world, with reporting backed by data and journalists at the center of the stories we cover.

[Nathan Hager]

Listen to the Bloomberg Daybreak US Edition podcast each morning for the stories that matter with the context you need.

[Karen Moscow]

Find us on Apple, Spotify or anywhere you listen.

[Tracy Alloway]

Hey Oddlocks listeners, the Wall Street Journal has a podcast for you. WSJ's take on the week cuts through the noise and dives into markets, the economy and finance.

[Nathan Hager]

Do you think we will see 2%.

[John Coogan]

Inflation again anytime soon? Gosh, until you put on the anytime soon, I was going to say absolutely yes. Probably not.

[Nathan Hager]

I'm Gunjan Banerjee and I'm Telus Demos. From breaking down the big trades to talking with key players, every week we'll get you set up with what you.

[John Coogan]

Need to know in the worlds of markets and Money.

[Tracy Alloway]

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[Nathan Hager]

So a few stats. We're recording this by the way, July 31st Meta came out with earnings last night. The stock is up like 10%. It's up like 150 billion doll billion more dollars. The other thing is, and I think this gets ties into the logic behind the comp so they're going to spend like something like another 70 billion on capex and stuff like that. So we know these are incredibly computationally intensive things. They're electricity intensive things. You mentioned paper citations, but also actually having the experience of one of these runs, and it does seem very highly intuitive to me that if you've done it before and if you could even cut down the cost of a training run, set up a big computer rack for. You can pay for yourself very quickly 5% less. Right.

[John Coogan]

This exact. This is exactly what just happened in Meta.

[Nathan Hager]

Instantly. Then you instantly pay for your salary. I could save because. And this is different from the B2B SaaS era, right?

[John Coogan]

Yeah.

[Nathan Hager]

Because you can. There's these huge capex costs. If you could just marginally improve the efficiency of that, that pays that $100 million salary.

[John Coogan]

And so this, this literally just happened right before Mark Zuckerberg went on the talent acquisition spree that he's been on for the last few months. Main AI model is called Llama and they've released a series of versions of that model. And Llama 4 was the latest and greatest and it didn't go very well. And the rumors about why it kind of failed to deliver on expectations was that they kind of went down the wrong path in the tech tree and they focused a little bit too much on free training and scale. Insanely costly. So they've released the a part of Llama 4, but they have yet to release Llama 4 Behemoth, which is their biggest model, the most aggressive. And they had just little details in the implementation, little choices of how you chunk the attention in the transformer model. We're operating at this level of abstraction up here, talking about it's a prediction model and then we talk about transformers a little bit. There are sub algorithms within these systems that you make the wrong decision and you could get a vastly different algorithm.

[Nathan Hager]

Your electricity bill goes up by 100%.

[John Coogan]

Exactly. So all of that money that was spent on that electricity and that build out, of course, medicine absorb that. But when you think about the cost.

[Jordy Hayes]

Of getting correct, one thing is, is a lot of these projects will be energy constrained too. So efficiency is going to matter a lot. Oh, it hasn't been the core focus today. If you talk to anybody at the big labs, they are focused on maxing out intelligence at the cost of efficiency because they know they can. You know, you want to be on the bleeding edge. You want to have the smartest model, you want to be. You know, there's debates around which benchmarks actually matter how important AI benchmarks really are. But energy is going to. You know, a lot of people are saying Zuck won't even be able to spend as much as he wants to spend on data center development purely because of the energy constraint.

[Tracy Alloway]

Can you talk a little bit about what happened with Windsurf? Because this is the one that seems to have like captured everyone's attention in part because there was the drama of. It almost seemed like it came out of like a Silicon Valley the show script or something, where all the employees were gathering expecting to hear that they were going to be bought by OpenAI and then they find out that actually their CTO has just been bought by someone else completely different, and they're sort.

[Jordy Hayes]

Of left in the CEO.

[Tracy Alloway]

Oh, is it CEO?

[John Coogan]

Top CEO and top 50? Well, how about I give some prehistory on acquirers and you can take. Take us through that actual weekend. So there has been a trend of sort of these zombie aqua hires. Everyone has names for this. But effectively, when a very large company, usually a hyperscaler, wants to go and acquire a company that has AI talent, they used to just buy the whole company. And this was part of the Silicon Valley social contract that even if I am in operations or sales or finance or hr, if I join a hot startup and it gets acquired, I'm coming along for the ride. I get the exit and I get the job at Google, at least for a little bit. And then, yeah, if I underperform Google or Meta or Amazon, they might lay me off. But even if I'm somewhat redundant, I'm coming along for the ride and I'm cashing out my shares. And the reason that you go and take the risk and take the little bit of the rougher ride that is a startup, you don't get as many amenities, but you get the lottery tickets in the form of stock options that hopefully pay out. But there's a big question about how much of this is the acquirer just not wanting to deal with the deduplication of the back office. There's also the question of the ftc. A lot of the FTC rulings have made it much harder to get these, these big acquisitions across the finish line. And even if they, even if the FDIC does approve, they can often hold it up for six months. And we're in a race where if you deliver the best model today, you're going to make more money, you're going to be the hot company, you're going to acquire. It's all this big snowball. So companies this started with, there were a few, but Character AI was the big one with Noam Shazir, who was.

[Jordy Hayes]

And very, very interesting situation where so Gnome wanted to go back to Google, which made sense. Google wanted him there as well.

[John Coogan]

He's one of the greatest AI researchers of all time.

[Jordy Hayes]

Yes. And so having him go back there made a lot of sense. I think he had built this platform, he built like the first at scale AI companionship platform. If you look at Character AI's site traffic today, I mean it's, it's one of the largest sites on the Internet still, which is wild. But I think he realized, I want to work on AI research, I don't want to work on AI girlfriends, boyfriends, that, that kind of thing. And as part of that deal, Character AI effectively became entirely employee owned. And they had a really strong balance sheet. They had a crazy amount of users. They weren't monetizing maybe that well yet. But I think a lot of the employees in that situation were like, this is pretty cool. We're basically running a co op where we all own a lot of this company. We don't have investors, we don't have the same kind of pressure to perform. And that space is competitive. Right. Even Elon is competing there now. ChatGPT gets used as a companion, but, but not competitive like CodeGen. And so that was the dynamic here, that was insane because Google clearly cares about code generation. They see anthropic adding, they went from 1 to $4 billion in run rate this year. They're pacing to be somewhere around 10 at the end of the year. And so that's a Google size market, right? Google's going to ultimately care about cogen. So it made sense for them to say, hey, let's get, you know, 50 more hyper talented engineers. This is Windsurf we're talking about. The issue though is if you didn't get brought over to the Google ship, you were on what I was calling a ghost ship.

[John Coogan]

Everyone who was pro this strategy, they would call it the Remain company. And George, I was calling it a ghost ship.

[Jordy Hayes]

But imagine you're at a company and the dynamic with Windsurf was fascinating because the company, if you had joined in August of last year, Windsurf, you could have. The product hadn't launched yet, so you could have worked and worked up to the product launch, launched it. Seeing this meteoric growth, the last reported number they had was something like 80 million of ARR. You have a term sheet to get acquired from OpenAI for $3 billion. And that falls through and then all these employees are looking around and they're like, wait, I didn't even hit my, I haven't even hit my one year cliff yet. I don't actually have a right to. I mean, they might technically own shares or options depending on how it was structured. But, but they, as I'm sure everyone here knows you oftentimes, like some, sometimes founders would try to accelerate their employees, get them compensated as part of a transaction like that, but there's not necessarily a contractual right to do that and it's part of a negotiation. And so in this case you have this team that's effectively split up and we were covering the whole thing live because we were hearing that employees that Friday were crying and there was, was a ton of confusion and chaos and everybody was learning facts kind of over that 48 hour period. Luckily, our friend Scott Wu at Cognition, the company that ultimately bought the Remain company, flew to meet the Windsurf team, the new CEO, Windsurf, and basically spent the weekend doing this insane deal. And it ended up being a great outcome, I think, for everybody involved.

[Tracy Alloway]

Didn't Wind Surf have their like marketing department in the room or something when they made the announcement, the initial announcement, and everyone was like. Because they were expecting to be bought by OpenAI.

[John Coogan]

Right.

[Tracy Alloway]

So they're like, we're going to film this for posterity. And then it turns out to be something completely different.

[John Coogan]

Yeah, I believe the timeline is that Windsurf launches a year ago, is in a knockout drag out fight with Cursor. Cursor's doing very well. They're also growing to 80 million or so open Air.

[Jordy Hayes]

I mean, Cursor's in the hundreds of millions of revenue. So Windsurf was very clearly the number two player in the AI IDE market.

[John Coogan]

And so cursor is staying independent, but OpenAI wants to continue to get a foothold in this space, so they make an offer that falls through. The rumor was because Microsoft would have had IP look through exposure via the more complex OpenAI structure, which is ongoing, which continues to be ongoing. And then when Google came through, they said that they wanted just to buy the team, leave the Remain co because it's potentially cleaner from an FTC perspective, but there's a whole bunch of different reasons and no one really comments on exactly what happens. But when these deals happen, this just happened with scale, AI and meta. The CEO, even though there's some sort of amorphous ofTC risk, the CEO, if they're going through one of these zombie acquisitions, does have the Ability to kind of set the team up with certain expectations and say, hey, we're going to take care of you. Trust me. You're going to get a check that you would expect, expect based on your ownership. So if you own 0.01% of the company, you would expect that you get X of the headline number. And yes, it's coming to you. The weird thing about the Windsurf deal was that that was not messaged. And so there was like this, the zombie ship was more zombified.

[Nathan Hager]

So like, well, yeah.

[Jordy Hayes]

And imagine, imagine you're in a hyper competitive market where you're competing with Google and Anthropic and Cursor and all these different players and then you lose your CEO and your top 50 engineers and they're like, and you guys are going to, don't worry, you guys have a strong balance sheet. You guys are going to do great. And we're also going to be, we're also going to be competing with you at, at, at, at Google. But you guys are going to be fine.

[Nathan Hager]

Good luck, guys.

[Jordy Hayes]

And so, and great.

[Nathan Hager]

Thanks, thanks for the help. Yeah, but this, but like, okay, cognition came in. It sounds like all the employees will get something.

[John Coogan]

It's not the end of the world. Yes. Because there was cash on the balance. She got dividend out.

[Nathan Hager]

But it didn't have to be that outcome. And so there's two things here that strike me. One is again, this does not seem like the B2B SaaS era where it's like if you created the hottest billing product for dentist offices and that was gathering traction, no one would like just buy the talent that built that. So that's really different because, so the ability to take value out via the talent channel rather than buying the product itself. But then also, and I'm just, you know, the knock on effects, okay, fine, the Windsurf employees did fine, but going forward there's no guarantee that they could have it. So I'm wondering from either a VC perspective or a future employee's perspective how this is going to change the sort of calculation that anyone makes when participating in a new AI startup. The fact that the enterprise may not be where the value actually is.

[John Coogan]

So the first question is like this kind of is the example you gave of like buying the team that built the dentist B2B SaaS. Because windsurf does not train foundation models and Google is exceptional in training foundation models. With Jeff, Gemini and DeepMind. The DeepMind team is extremely well staffed on AI researchers and continually seems to push the frontier. Both in qualitative and quantitative metrics.

[Jordy Hayes]

And if they were weak anywhere, it was maybe product.

[John Coogan]

Exactly. And so this is the like I don't want to be like they're just product people. Windsurf has some amazing AI researchers, some amazing AI engineers. But what Windsurf really did, they did not train a frontier model that was about to disrupt Gemini. Yeah, DeepMind's foundation model they were going after, you know, would you use a Google product? No. You would use Windsurf on top of Anthropic or another foundation model.

[Jordy Hayes]

And ultimately I don't think it's a systemic risk to the social contract of our industry. And the reason for that is that when you see a deal like the Google Windsurf deal get done, it was very concerning. A lot of people were extremely angry. It ended up being a good outcome. A lot of employees were looking around, probably concerned about you know, is the million dollars of stock that I've been working for for years worth anything at all? I think that was a good question to ask. But I think there's two things. One is this is AI is a category and of course it's touching kind of every category of venture in the private markets. But we're not seeing, you're not seeing a defense tech founding team or engineering group group get. There's no real aqua hire value there. The aqua hires that are getting done in hard tech are hey you, you clearly have good engineering capabilities. We're happy to have you join the team. But there's no like real premium being placed on that kind of talent. Might be able to get a great comp packages but they're certainly not getting these sort of multi hundred million dollar premiums. The other factor here is like we have a set like right now if you are one of the top 100 AI researchers, you could probably get a hundred million comp package like within a week if you really wanted it. Right. And there's even people that are at thinking, you know, the reporting from this week was that and it was kind of hotly debated but that people at Thinking Machines, Mira Marathi's company, former CTO of OpenAI, were turning down these sort of hundred million, multi hundred million dollar. There was a rumor that somebody had turned down a billion dollar five year contract and I don't believe that those deals will be getting done in, in three years. Now I might be wrong and there's going to be like probably some exceptions but the idea that the 30th AI researcher on your team is going to make more than a Mag7 CEO like that doesn't feel hyper.

[John Coogan]

Something sustainable either Tim Cook has to make more money or researchers make less.

[Nathan Hager]

Tim Cook is looking on Wall street or like a top trader. Top dealers consistently make more than or will often make more than the CEO.

[John Coogan]

Yeah, Citadel.

[Tracy Alloway]

Oh absolutely, because they're the ones that get the money in the door.

[Jordy Hayes]

Yeah.

[Karen Moscow]

Tired of spills and stains on your sofa? WashablesOfAs.com has your back. Featuring the Annabe Collection, the only designer sofa that's machine washable inside and out. Out where designer quality meets budget friendly prices. That's right, sofas start at just $699. Enjoy a no risk experience with pet friendly stain resistant and changeable slipcovers made with performance fabrics. Experience cloud like comfort with high resilience foam that's hypoallergenic and never needs fluffing. The sturdy steel frame ensures longevity and the modular pieces can be rearranged anytime. Check out washablesofas.com and get up to 60% off your Anna Bay sofa backed by a 30 day satisfaction guarantee. If you're not absolutely in love, send it back for a full refund. No return shipping or restocking fees. Every penny back. Upgrade [e-mail] Offers are subject to change and certain restrictions may apply Bloomberg Daybreak is your best way to get informed first thing in the morning, right in your podcast feed. Hi, I'm Karen Mosc.

[Nathan Hager]

Nathan Hager each morning we're up early putting together the latest episode of Bloomberg Daybreak US Edition. It's your daily 15 minute podcast on the latest in global news, politics and international relations.

[Karen Moscow]

What's special about Bloomberg Daybreak is the immediacy of the news we bring you each day in your podcast feed by 6am Eastern Time.

[Nathan Hager]

This isn't a deep dive on yesterday's news. Instead, you get the latest stories with context.

[Karen Moscow]

And that's something you don't get from other news podcasts. So join us for the best from Bloomberg's 3,000 journalists and analysts around the world with reporting backed by data and journalists at the center of the stories we cover.

[Nathan Hager]

Listen to the Bloomberg Daybreak US Edition podcast each morning for the stories that matter with the context you need.

[Karen Moscow]

Find us on Apple, Spotify or anywhere you listen.

[Tracy Alloway]

Hey odd lots listeners, the Wall Street Journal has a podcast for you. WSJ's take on the week cuts through the noise and dives into markets, the economy and finance.

[Nathan Hager]

Do you think we will see 2%.

[John Coogan]

Inflation again anytime soon? Gosh, until you put on the Anytime soon? I was gonna say absolutely yes. Probably not.

[Nathan Hager]

I'm Gunjan Banerjee and I'm Telus Demos. From breaking down the big trades to talking with key players. Every week we'll get you set up.

[John Coogan]

With what you need to know in.

[Nathan Hager]

The worlds of Markets and Money Money.

[Tracy Alloway]

Subscribe to WSJ's take on the Week wherever you get your podcasts. Can you talk a little bit more about, I guess, the fungibility of the IP here in both the practical and legal sense? So if I'm a VC or some sort of investor, I invest in an AI company because I get to own that technology, that intellectual property. But then let's say the main guy walks out the door, gets hired by Google or whoever. Like how much of what he learned at his original firm or developed is immediately going to be replicated at Google?

[John Coogan]

I bet almost all of it.

[Tracy Alloway]

Yeah, I guess this is like, this is a long way.

[John Coogan]

And that's exactly why they're paying that much money.

[Tracy Alloway]

This is a long window of saying how many lawsuits are we going to get after all these acqui hires?

[Jordy Hayes]

So I think one, one way you can look at some of Zuck's deals are like unauthorized acquihires. It's like the other CEOs not even participating in the deal. But you know, Zuck is able to come in and be like, would I pay if this, if these 10 people were working on a company independently, would I pay a billion dollars to bring them onto my team? 100%. Okay, let's do the deal. It doesn't matter that you're kind of piecing it all up from a. I think going back to like the kind of Wall street example of like a top trader who maybe is like putting up consistently incredible returns with some sort of like differentiated approach that person can go. And as long as they have capital at the new company, they're going to be able, I imagine, to continue to just follow that same type of strategy. I do think that AI and large language models are somewhat different in that you have to look at what is the AI product that these companies are going to sell. How much of an impact is that individual engineer researcher going to have? And it's Fairly obvious with OpenAI, they're a consumer tech company, they sell subscriptions to ChatGPT, they have some other use cases. It's obvious that companies like Anthropic, where they're in the co generation business, they don't really have a consumer business. And at Meta it's a little bit less clear right now because the sort of ongoing product strategy is not entirely clear yet. The thing that is obvious is that if you can make a $20 billion training run more efficient then you pay for yourself pretty quickly.

[Tracy Alloway]

We should just point out the Wall street analogy is not perfect. Right. Because if you're a high flyer at a Wall street firm, either client facing or if you're trading, if you join someone else, you usually have of a non compete agreement in one form or another. So you can't take all your existing clients with you. And then B you're often on an enforced gardening leave for a really long time.

[Nathan Hager]

Oh yeah.

[Tracy Alloway]

I imagine in the massive race that is AI at the moment, there's no gardening.

[John Coogan]

Also the nature of the intellectual property I believe is a little bit different still I think of this, I think it's a 2012 example from Citadel in Chicago where a high frequency trader stole some code and they sent and he had it on his hard drive. You know this story.

[Tracy Alloway]

Yes, it was really famous when it happened. He like sent it to himself or something.

[John Coogan]

Yeah, yeah, so. So he exfiltrated some code, some very, you know, definitive code of how to make money in the market and get an edge and they, he figured out that they were on his trail and he threw his hard drive into the river and they sent scuba divers into the river and got it back.

[Jordy Hayes]

I didn't know that the other high profile SV example was the guy going from Google self driving to U. Yeah.

[John Coogan]

And so taking specific code that's not happening. There's probably going to be like one example of this that pops up but mostly it's just you get someone who says I understand that at my previous job we scaled up the transformer a little too far and we didn't focus on reasoning enough. And so we need to shift this spend to test time inference and it's almost like you're leaving a company and you're leaving with like a mindset of like the right balance of Capex to opex.

[Jordy Hayes]

It's different than what was the recent Jane street example that came out in that lawsuit around it was it the trading strategy? Yeah, it only, we only really all learned what was happening because there was this lawsuit over over basically the team bringing over some type of IP or methodology.

[John Coogan]

Yeah.

[Nathan Hager]

Can we talk about the broader sort of economic world right now? Because there's a bunch of other sort of things going on and things that you talk about touch on them last.

[Jordy Hayes]

Because I think it's pretty interesting. So. So we put out the Metis list. I think it was Monday and we immediately had a ton of inbound from a lot of these researchers basically like critiquing like the ranking, right? And the ranking was like we got, we got people that work in AI to kind of like rank them. We did.

[Nathan Hager]

This is the beauty of ranks.

[Jordy Hayes]

You do.

[Nathan Hager]

You get so much source.

[Jordy Hayes]

It's amazing.

[Nathan Hager]

I understand why every venture capital firm.

[John Coogan]

Puts out market maps.

[Nathan Hager]

Now the beauty of ranking.

[Jordy Hayes]

There was one example that was interesting where somebody that was ranked, ranked fairly high that I know has gotten one of these nine figure comp packages and somebody that worked with him basically said this person was kicked off of every team they worked on and just like effectively like over a multi year period, like consistently demoted over and over and over and got the bag. Now, now like got, you know, this incredible.

[Tracy Alloway]

Can you factor in soft skills into your rankings?

[Jordy Hayes]

Well, yeah, and, and it was, it was more of like a technical ability thing. It was not even. Because I think it wasn't just he was a jerk. Soft skill, getting a little bit, you know, they don't, they don't.

[John Coogan]

No one cares anymore.

[Jordy Hayes]

You don't care that LeBron James like might get a little angry at somebody if they underperform. Right?

[John Coogan]

Yeah. Sorry.

[Nathan Hager]

No, no, no, no, no. That's great. So this phenomenon of like superstars, like it's not just, it's not just in tech. And like we see it, I mentioned in journalism where you know, this sort of like median reporter job in a newsroom, a lot of that's hollowing out. But you have some people who become insanely well compensated either because they're really smart and they write a great newsletter, or they're really good looking and they can do front facing video, et cetera or you know, like the four of us, you know, like can do something on video or something like that. You see it in a range of areas. And then like the amount of betting that's going on, which of course adds to this. And so the fact that all of these events, there's some market out there that you can bet on that. And I'm curious like from your coast, you know, you're here in New York, but from your coast. What does the world look like in terms of just like the state of this economy?

[John Coogan]

Yeah, there's something interesting going on in tech where the idea of a company going from 100 billion to a trillion seemed unfathomable. And there's this. Take that. In fact, that was the easiest 10x of all. Where the hardest 10x was going from zero to one from going to zero to a million dollars and getting these systems, inventing PageRank. And then once you had Google humming at $100 billion market cap, getting to a trillion, not just to, you know, knock on the work that they did to get that, but, but these, the, the numbers have just kept growing and growing at Internet scale, at Internet speed. And so the, the leverage that you're getting from an AI researcher is ever more increasing. And it just adds 10x every couple years. And so you see the comp packages increase that way.

[Jordy Hayes]

We have a couple things like the Internet is the greatest distribution engine for information and digital products and apps and services ever. And so at least in venture, that just means that everything is faster now, even in media too. If you're, if you are somebody's working at a, at a legacy media company and they set up a substack, they can get a million dollars of ARR on the first day that they launch. If somebody is working at a media company and really good at a certain type of YouTube video, they can launch, and immediately the YouTube algorithm will serve that video to all of their fans within the first week. And what that does is it just changes the power dynamic between media companies.

[John Coogan]

You see this leverage come in through financial markets. If you can lever up or just marshal more capital, one idea can generate billions of dollars in value. Same thing in technology, but we aren't seeing it everywhere. I don't think we're seeing it in hard skills woodworking unless you get into true art territory. But there is this interesting question about what's up next. And we were kind of noodling on there might be a law firm in the future that's extremely high leverage in the same sense that you might have a lawyer who's so good at what they do, and they are so good at resolving these and the connections and everything that they're doing. They're making billions, but they have a very, very lean team. And so you see a much steeper power law in law. And there's a number of other professional services that are going through like a transformation with technology bringing increased leverage to the profession. And that could drive more of that power law outcome in terms of earnings.

[Jordy Hayes]

Yeah, the, the thing, you know, in the private markets on, on the west coast, which is the dynamic right now that's fascinating is like, I feel like a lot of people have like a little bit of PTSD from the 2020-2022 era, where many of the things that in hindsight were incredible top signals are like all pop, popping up Again right now. And like we like, we like trap, we track them just for fun. We, we're not in the business of like calling, calling the top or anything like that. And in many ways it feels like, you know, there's so many positive indicators. But the interesting dynamic in, in venture is like as, as an angel investor, I've invested in probably 65 or so different companies at the precede to series A stage. And there was a bunch of deals that I did in 2021, 2022 that ultimately like I paid too much or, or just like the team wasn't good enough to execute against the vision they had. But there was also just like a handful of deals that I did that have been performed so well that it doesn't matter that I did a bunch of silly deals. And so venture right now is this interesting kind of dynamic where everybody knows that it's crazy, right? You have hundreds of billions of dollars of value created in the private markets that there's a lot of real revenue growth, but there's also hundreds of billions of dollars of value tied to zero revenue. Right, right. And I think that there's something that we've been tracking is like this underlying kind of feeling from people that are maybe under 30 of there's like this meme that's become very prevalent and I think it explains a lot of economic activity today, which is young people feel that they have two years to accumulate capital to escape the permanent underclass. And so I think that drives a lot of investing activity today in that, you know, you'll see young people on the timeline saying that like you'd be stupid not to use leverage, you know, and they're, and they're just like, you know, they're not a professional investor in any capacity.

[Nathan Hager]

Don't do it.

[Jordy Hayes]

And you know, any. Anytime you have people in venture making public market stock predictions, we get a little concerned.

[Tracy Alloway]

Are we going to get AI talent agents? Not AI agents, we have those already, but AI talent agents because like we do.

[John Coogan]

So we do. They're called venture capitalists.

[Nathan Hager]

Oh well.

[John Coogan]

But yes, I was going to be my sentence.

[Tracy Alloway]

So if the money is no longer in, you know, I invest in a startup and eventually they get the exit, they get acquired or they list or whatever. If the money is in, eventually the guy that started the startup gets bought by someone like Meta or whoever, wouldn't I invest my money in that person versus in the startup indentured services?

[John Coogan]

Yeah, yeah, you can't quite do that. But there are a ton of roles that are indexed to These high performance packages. And yes, there are people right now in Silicon Valley who are effectively talent agents who get a cut of those big packages and they help negotiate.

[Tracy Alloway]

What are they called? Just talent agents.

[Jordy Hayes]

Called venture capitalists.

[John Coogan]

No, no, no. So you can find a great researcher and you think that okay, maybe they will build a business but I'm sure that they are going to be worth hundreds of millions of dollars a year and you can just invest in their company. You will will almost certainly see a good return on that investment even if the product never gets to scale. Because when they get an Aqua hire you will get a payout.

[Nathan Hager]

Other scouts going to like Carnegie Mellon, Carnegie Mellon Gold medal and like going there and like the IMO's, you know the.

[John Coogan]

Oh absolutely, absolutely.

[Jordy Hayes]

No, it's now, it's now so normalized to invest in college dropouts that you actually see people like investing in high school students.

[John Coogan]

I'm not kidding about this. So the IMO gold medal is the Math Olympiad. And, and there are venture capitalists who will give calls to every single student that performs well on the Math Olympiad. And these are high school students.

[Tracy Alloway]

So what are these investments exactly? Like you're funding their tuition or whatever.

[John Coogan]

It's. I am taking 10 or 20% of a company of a Delaware C corp. Most likely that you will build something in and who knows where it goes. Maybe it turns into a great business, maybe it turns into aqui hire. But the downside is extremely limited because there's always this. At least right now there's this Aqua hire. There's this Aqua hire on the table where it used to be that.

[Jordy Hayes]

But to be clear, that is only an AI.

[John Coogan]

Yes.

[Jordy Hayes]

It's only for the, the people that, that you would consider to be the top 500.

[John Coogan]

Yes.

[Jordy Hayes]

In their industry.

[John Coogan]

Windsurf thing like Instagram was the power law winner. Got the billion dollar acquisition from Meta. Hipstamatic was the second largest photo filtering app. Did not get a billion dollar Aqua hire from Google. Google. Right. But now we're in the market where if there's a leading product with a bunch of AI researchers over here and they get a multi billion dollar acquisition for the product and the product's working and it's growing and it is a great business and you buy it for the value of the business, then the second best team might get acquired just for talent. Which is a completely different downside protection.

[Jordy Hayes]

Yeah. And there's a lot of talent acquisitions. Traditional acqui hires where it's only the talent that benefit. Right. In the sense that they get basically A job offer at the new company and VCs get some capital back or in some cases a small amount of money.

[Nathan Hager]

Can I ask a TBPN question? This should be like the ultimate compliment, which is that I got a DM from some random person, I had never seen them the other day and he said, I can build TVPNs for X. Yeah. So like that stack, that sort of live thing, which means it's sort of like it's become like Kleenex or one of these things where it's like a category and, and where are you going with it? What, what are your plans?

[Jordy Hayes]

It's, it's so funny that people are calling it TVPN for X because our show, while it's unique in a variety of ways, looks very much like traditional, which is interesting. And so we can't, we can't take credit for.

[John Coogan]

We invented tv, we invented media, we.

[Nathan Hager]

Invented live streaming before. And like normally it doesn't really. I don't know, it's like, why would I watch cable news on.

[Jordy Hayes]

I think the thing that's exciting is that in the private markets and venture and tech, if you had a podcast, there was one format which was a once a week interview show. And it was a great strategy to do that. Ten years ago, around the time that you guys. No. And it still works.

[John Coogan]

You're locked in, established. But if we, if we tried to clone this.

[Nathan Hager]

Yeah, yeah.

[John Coogan]

Everyone would be like, why is that a knockoff? There's nothing new about this, nothing fresh about this. Like, why do I want to go on your knockoff? I just go on the real thing.

[Jordy Hayes]

Yeah. And so, so our edge in, in launching the show at the beginning of the year is that media is not zero sum. Content is not zero sum. We have a friend that jokes that he, he's so competitive, he wishes, he wishes media was zero sum, was truly zero sum. But our edge early was that we just took it ten times more seriously than anyone else. So everybody that was creating content for the private markets was doing it as a part time gig and, and we were happy to compete with a bunch of people that were part time.

[Nathan Hager]

Yeah, you know what, actually I was wondering in 2021 or 2022, that craziness, someone once reached out to me and they were like, you know what you should like?

[Jordy Hayes]

Bitcoin Treasury.

[John Coogan]

No, go direct. It was probably the pan.

[Nathan Hager]

But this was the interesting thing. He said you should go independent and what you should do is attach a VC arm to it. And that because of the quality of the guests that you could get, you would get really accurate act, good access to deal flow. But it seems like basically it's very uncomfortable to me because I'm not going to like highlight startup founders and say oh you're the perfect guest. And it's like, because like I have like 5%. But I'm curious about, because you mentioned doing angel, the sort of link TVPN at some point being like, yeah, so angel, angel invest to an investing platform.

[Jordy Hayes]

Angel investing I look at as, as a hobby. It's not a great financial activity, right? Locking up capital. I've heard locking up. I mean like you can generate great returns but it's not the logical way to invest your time. But it's really fun. Like we just enjoy supporting founders early when it's an idea and a team and it's, it's just, it, it is genuinely addicting. I always joke about people in San Francisco with angel, you know, people across the country, sports betting addictions, San Francisco, you know, angel investing addictions are I think real. But for us, for us that was, you know, as we started having some success, a lot of people, they would probably get a message a day. When's the fun coming? When's the fun coming? And that's been a way to monetize an audience within tech. If you have an audience, go raise a hundred million dollar fund, you get the feast. Substackers do that, you get a bunch of upside. And we joke because we have the shows every single day. We go live at 11, we have to eat, we have to work out the show, we have to prep the show, we have to talk with partners, we have to manage our team. There's all these different things and so somebody might immediately think, okay, these guys talk to six founders and investors a day. They have this like media property that like I think everybody in venture now is going to see our content like once a week in some form or another if they're, if they're online. But I joke with them, I'm like so we're live for three hours every single day during the middle of the day. And so if, if you think that we with a show would, would effectively compete at VC is about winning allocation, right? You can be cool and, and connected and have an audience that might get you 100k allocation. But if you have a hundred million dollar fund, you need to be putting size into deals. And so I know that if John and Jordy have a VC fund and we're competing with these other guys that have a live show that they're live for three hours a day. And they have a VC fund one. We'd smoke them because we were like, okay, while they're live, I'm going to fly to the founder, I'm going to meet with them and we're going to win this deal and we're going to be like, yeah, why don't you let them put in like 200k?

[Tracy Alloway]

So the thing to watch for when the VC fund is coming is when you start reducing your live hours. That'll be the.

[Jordy Hayes]

Yeah, I think, I think we, we didn't get into this to start a fund and I think there's a lot of people that get into content because they see it as a way to do that. And we just love talking about tech.

[John Coogan]

It actually was the key insight was that not enough people. Well, yeah, it's very fun, but very few people in tech were actually taking media seriously. Everyone had a fund that was the high status thing and doing media was like lower status or people didn't think we could have as much of a power law outcome as it very clearly can. And so this idea of just what if you actually took it completely seriously and just made it the main thing?

[Jordy Hayes]

And we'll say we've had a bunch of people copy our format. Major legacy media companies all the way through, friends of ours. It doesn't really bother. I mean, it bothers me more than John, but. But at the end of the day, if you want to spend.

[Nathan Hager]

You're the Tracy, by the way.

[Tracy Alloway]

Yeah, it bothers me too. I totally get it.

[Nathan Hager]

And so it's like it doesn't.

[Jordy Hayes]

We basically know. So. So John and I, John and I basically hang out for 12 hours a day. And the entire time, Tracy, the entire time we were thinking, we're thinking about, about the show. We're just talking about the show. Doesn't look very different than when we're hanging out offline. And so I just joke. I'm like, okay, if you want to compete with us and you're willing to put 100 hours a week in, go by all means. Yeah, go for it. Like, this is probably your life's work, but if it's not good luck, it doesn't matter.

[John Coogan]

Yeah.

[Nathan Hager]

John Coogan, Jordy Hayes, thank you so much for coming on Odd Lots. That was a blast and superfluous and good luck and looking forward to continuing you watching tbpn.

[Jordy Hayes]

We'll be live from Nicey later.

[Nathan Hager]

Oh, nice.

[Jordy Hayes]

IPO and Odd Lots in the same day.

[Nathan Hager]

It's really what a day. What a day. And in the Wake of meta earning.

[Jordy Hayes]

Pinch me.

[John Coogan]

Yes, pinch me.

[Nathan Hager]

All right, take care. Thank you for having us.

[John Coogan]

Thank you so much for having us.

[Nathan Hager]

Tracy. That was a lot of fun.

[Tracy Alloway]

It was a little bit media navel gazing, a little bit fun, a little.

[Nathan Hager]

Bit media navel gazing. I mean there is this thing that's happening, it's been happening in media for a while and of course it happens in Wall street, but and now happening in AI where you just have a lot of talented people and they wonder about the degree to which they need their existing platform. Their, you know, like a star banker can take a book of business or a star lawyer can take a book of business. And in the case of AI, it's not taking a book of business.

[Jordy Hayes]

Right.

[Nathan Hager]

Because they don't have like their individual clients, but it's this knowledge and transport it and it's instantly worth a lot of money for someone somewhere else.

[Tracy Alloway]

The thing I thought was really interesting about that discussion was the emphasis on how capital intensive all of AI is. And so that kind of changes the economics of why you're paying such massive money for someone who's able to like eke out even a slight efficiency ends up being massive.

[Nathan Hager]

This is huge. This was like this. It suddenly is what made it all made sense to me. Right. Because we know about like how costly one training run is, right. And we know just the insane numbers for data center setup, et cetera. And I'm sure there's progress being made on the literal design of like how you string together Nvidia GPUs, et cetera. And so if you could get some margin, if you know, have, know how to get some marginal improvement out of it. And this is fundamentally what was $1 trillion for you. Maybe not a trillion, no, not a trillion yet. But like this was not the case when tech was not so capital intensive in the 2010s where yeah, I'm sure talented people always made a lot of money and there's always improvements, but where it's. So that link between some sort of efficiency gain and instant cost savings is so linear and so straightforward.

[Karen Moscow]

Yeah.

[Tracy Alloway]

And I take their point that okay, VCs exist and they're already investing in some ways in spec specific talent. But I do kind of wonder if you're going to get some sort of like specialized headhunters at the very least who are going to like seek out these big AI talents and try to like graph themselves onto them.

[Nathan Hager]

Yeah. Or just people whose expertise is in reading through under cited, under cited AI research papers approach. Yeah, yeah. Well we can't give you Sam Altman, but what if we could replace Sam Altman in the aggravate?

[Tracy Alloway]

It has 50 citations in the following papers. Should we leave it there?

[Nathan Hager]

Let's leave it there.

[Tracy Alloway]

This has been another episode of the Odd Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.

[Nathan Hager]

And I'm Joe Weisenthal. You can follow me at the Stalwart. Follow our guest Jordy Hayes, he's at JordyHayes and John Coogan at John Coogan. And check out TBPN at TBPN. Follow our producers Carmen Rodriguez at Carmenarmon, Dashiell Bennett at Dashbot, and Kell Brooks at Kel Brooks Brooks. And for more Odd Lots content, go to bloomberg.com oddlots we have the daily newsletter and all of our episodes and you can chat about all of these topics 24. 7 in our Discord, Discord, GG Oddlots.

[Tracy Alloway]

And if you enjoy Odd Lots, if you like it when we talk about the sportification of AI talent, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes episodes absolutely ad free. All you need to do is find the Bloomberg Channel on Apple Podcasts and follow the instructions there. Thanks for listening.

[Karen Moscow]

Bloomberg Daybreak is your best way to get informed first thing in the morning right in your podcast feed. Hi, I'm Karen Moscow.

[Nathan Hager]

And I'm Nathan Hager. Each morning we're up early putting together the latest episode of Bloomberg Daybreak US Edition. It's your daily 15 minute podcast on the latest in global news, politics and international relations.

[Karen Moscow]

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[Nathan Hager]

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[Karen Moscow]

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[Nathan Hager]

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[Karen Moscow]

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