Hello and welcome to another episode of the OddLotss podcast. I'm Joe Weisenthal.

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

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 top

AI? Some of the headlines. I have also learned a bunch of new words like exploding offer and aqua hire. And I always thought exploding offer sounds dangerous. What you want is an explosive offer that you can't turn down.

But I take it the exploding hire is like one that lasts like 5 minutes.

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

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.

Really? No, but I kind of

I just think it's probably made up of like all this weird equity structure

comp, 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 just AI, I would say uh journalism, finance, etc. where it's like the sportsification of a lot of different industries, individual talent, the demand for individual superstars on anything doing very well. 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.

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 going to be speaking with uh John Kugan 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, John and Jordy, thank you so much for uh coming on.

Thanks for having us.

We're so excited to be here.

I love by the way you guys like 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 highlevel 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.

Yeah, the league or the mag seven 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 mult there's seven trillion plus dollar companies now. So there is an inordinate amount of money to flow around. And if you think about investing.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's 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, but we 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 any question.

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? So, so, so taking a little bit of a step back, talking about kind of the sportsification of of tech and business, which has been a huge catalyst for our show. I think we realized early on people would call TVPN 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. Uh I'm in my late 20s, John mid30s. And and and we've followed tech in business the way that our college friends follow sports. So the com 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 uh 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 a hundred AI researchers and rank 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, etc. 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 medicine list, probably unrelated, but who knows? He's basically saying that AI researchers and a and engineers, we're just going to call them engineers now. And that's makes a lot of sense for someone like Elon to do as somebody who's always been you know 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 making $2 billion of carry on some deal or this founder, you know, IPOing. Today we have, you know, the Figma IPO and uh, you know, there's bunch of people that are going to make billions of dollars there,

but you don't hear about the hundth engineer that was hired making a$und00 million signing bonus. And all of this makes a ton of sense in in the context of what John said because you look Meta's up, I checked this morning, $195 billion new uh market cap and think about how many hundred million dollar signing bonuses you can make against that kind of market cap.

Should we answer your question about who the who's the best I want to have in my collection?

The uh who is the white whale from the novel? Don't say anything about whales or whale products or hunting large

tired tired of me hearing about perhaps he's the white whale perhaps he's the Michael Jordan of AI researcher but Ilaskver is really he's at the top of our list for a variety of reasons and he if you're if you're not familiar with Ilia Sitzkver 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 is 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 a 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 chat. 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.

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

Yes. And if you're familiar with what the more the more modern so the first arc of LLMs and these chat bots 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 that particular algorithm. You need to marshall the capital to say we're going really really big and we're going to build the big data center. We're going to spend a lot of money 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 Alman ouster and return he was working on a project that was cenamed.

And there was a lot of speculation about what Qstar was. Was it the secret superintendent?

Everybody was saying, "What did I see?"

Yes. Yeah. Because he he was going back and forth in support of Sam Alman and then leaving and then and then it was back and forth and there was a lot of drama there.

Always keep them guessing.

Always keep them guessing for sure. And so there was there was a lot of rumors but what it wound up being was just reasoning which is now what is available in uh if you use any of the O3 models in Chat GPT or you use DeepSseek R1. And it's it goes by a number of different names. the project was rebranded strawberry and then the oer and um you can think about this as the 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 then 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 Super Intelligence SSI and he's gotten that company to what a $30 billion valuation billion $32 billion valuation

which ties into the talent war because uh I think it's I don't know that it's been officially announced yet but people are expecting uh Daniel Gross to join Meta at

who was the CEO and co-founder of that company SSI and so back to your back to the white question

think about the dynamic here

if you guys get together. They start a company. Within a year, it's worth $32 billion.

Yeah.

And one of the people on that team decides to actually leave and go join Meta. It sounds insane. Probably leaving billions of dollars on the table. But the you can kind of trace the this talent war actually back to the OpenAI founding team. When you think about all the different players, right? You have Meera Marotti who's now uh with Thinking Machine. She was the CTO of OpenAI. You have Ilia Sutzkver 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 that's really kind of the the origin story in the Genesis and it's been amazing to see OpenAI's progress despite, you know, the 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 Ilia and uh Mera.

So, a few stats. We're recording this, by the way, July 31st. Meta came out with uh earnings last night. The stock is up like 10%. It's up like 150 billion more dollars. The other thing is, and I think this gets ties into the uh 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 or set up a big computer rack for

you can pay for very quickly 5% less, right?

This exa this is% what just happened instantly pay then you instantly pay for your salary. I could say because and this is different from the B2B SAS era, right? Because you can there's these huge capeex costs. If you can just marginally improve the efficiency of that, that pays that 100 million seller salary.

Yeah. And and so this this literally just happened right before uh Mark Zuckerberg went on the talent acquisition spree that he's been on for the last few months. Meta's 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 pre-training scale insanely costly. So, so they've released a part of Llama 4, but they have yet to release Llama 4 behemoth, which is their biggest model, the most the most aggressive, and they had just like little details in the implementation, little choices of how you chunk the attention in the transformer model. You know, we're operating at this level of abstraction up here talking about, you know, it's 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 outcome.

Your electricity bill goes up by 100 million.

one thing is is a lot of these projects will be energy constrained too. So efficiency is going to matter a lot. 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.

Yeah. M can you talk a little bit about what happened with Wind Surf cuz this is 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 um the show script or something where all the employees were gathering expecting to hear that they were going to be bought by Open AI and then they find out that actually their CTO has just been bought by someone else completely different and they're sort of left in the

CEO. Oh, was it the CEO? top

CEO and top 50. Well, how about I give some prehistory on acquires 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 different 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

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 these 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 dduplication 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 FDC 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 Nome Shazir who was

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

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

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 atscale 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 employeeowned. 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? You even Elon is is competing there now. ChatGpt gets used as a companion, 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 to4 billion dollars in uh run rate this year. They're they're pacing to be somewhere around 10 at the end of the year. And so that's a Googleiz market, right? Google's going to ultimately care about codegen. So it made sense for them to say, hey, let's get, you know, 50 more hyper talented engineers. This is winter we're talking about.

The issue though is if you didn't get brought over to the Google ship, you were on what I what I was calling a ghost ship. John, everyone who was pro the strategy, they would call it the remain coordin but but imagine you're at a company and 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, seen this meteoric growth. The last reported number they had was some 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 I they might technically own shares or or options depending on how it was structured but they as I'm sure everyone here knows you often times like some sometimes founders would 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, you know, employees that Friday were like crying and there was a ton of confusion and chaos and everybody was learning facts kind of over that 48 hour period. Luckily, our friend Scott Woo at Cognition, the company that ultimately bought the remain co, 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. would 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, right? So they're like we're going to film this for posterity and then it turns out to be something completely different.

Yeah. Yeah. I believe the timeline is that you know Windsurf launches a year ago is in a knockout dragout fight with Curser. Curser is doing very well. They're also growing to 80 million or so opening up. Cursor is in the hundreds of millions of revenue. And so Windsurf was very clearly the number two player in the AI IDE market.

Yeah. And so Curser 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 is continues to be ongoing. And then when 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 FTC risk, the 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 based on your ownership." So, if you own 01% of the company, you you would expect that you get X of the headline number. And yes, it's coming to you. The weird thing about the wind surf deal was that that was not messaged. And so there was there was like this the zombie ship was more zombified.

So like

Well, yeah. And and imagine imagine you're in a you're in a hyper competitive market where you're competing with Google and Anthropic and Cursor and and all these different players and then you lose your CEO and your top 50 engineers and they're like, "Guys, 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 Google. But you guys are going to be fine. Good luck, guys. And so and great. Thanks. Thanks for the help.

But but this but like okay cognition came in. It sounds like all the employees will get something. It's not the end of the world.

Yes. Because there was cash on the balance sheet that got dividended out.

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 SAS 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 right because the so the I 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 wind surf employees did fine but going forward there's no guarantee that they could have and so I'm wondering from either a VC perspective or a future employees 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.

So the first question is like this kind of is the example you gave of like buying the team that built the dentist B2B SAS because Windinsurf does not train foundation models and Google is exceptional in training foundation models with Gemini and Deepmind. The deep mind team is is extremely well staffed on AI researchers and continually seems to push the frontier both in qualitative and quantitative metrics.

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

Exactly. And so this is the like I don't want to be like they're just product people. Um Windsurf has some amazing AI researchers, some amazing AI engineers, but what Windinsurf really did, they did not train a frontier model that was about to disrupt Gemini. Yeah. Deep Mind'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 or another foundation model.

And ultimately, I I don't I don't think it's a systemic risk to the social contract of our industry. And the reason for that is that when when you see a deal like the 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 get there's no real aqua hire value there. the aqua hires that are getting done in hard techch 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 multiund million 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 m you know the reporting from this week was that and it was kind of hotly debated but that people at thinking machines mirror Marott's company former CTO of open AAI were turning down these sort of hundred million multiund million dollar there was a rumor that somebody had turned down a billion dollar 5-year contract and I don't believe that those deals will be getting done 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 Mag 7 CEO, like that doesn't feel hyperainable. Either Tim Cook has to make more money or research to make less.

Tim Cook is looking in existences on Wall Street where like a top trader, top deal makers consistently make more than or will often make more than the CEO. Citadel.

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

Yeah.

Can you talk a little bit more about I guess the fungeability 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? I bet

almost all of it.

Yeah. I guess this is like this is a long way. That's exactly why they're paying that much money. This is a long way to think of saying how many lawsuits are we going to get after all these aqua hires.

So I think one one way you can look at some of Zuck's deals are like unauthorized aqua hires. It's like the other CEO is 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. doesn't matter that you're kind of piecing it all up from a uh 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 and large language models are somewhat different in that you have to look at what is the the AI product that these companies are going to sell. How much of an impact is that individual engineer researcher going to have? And you know, it's fairly obvious with OpenAI, they're a consumer tech company, right? They sell subscriptions to chat GBT. They have some other use cases. It's obvious at companies like Anthropic where they're in the code 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 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.

We should just point out the Wall Street analogy is not perfect, right? Because if you're a high-f flyier at a Wall Street firm, either client-f facing or if you're trading, if you join someone else, you usually have 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 off and on an enforced gardening leave for a really long time.

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 uh stole some code and they sent and he had it on his hard drive. You know the story?

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

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. I didn't know that.

The other the other high-profile SV example was the guy going from Google self-driving to Uber.

Oh, yes. Yeah. And and and so 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 you're leaving a company and you're and you're just you're you're leaving with like a mindset of of like the right balance of capex to opex or something. And then what was the recent Jane Street example that came out in that lawsuit around was it the the trading strategy where it only we 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.

Yeah.

Can we talk about like 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 last thing because I think it's pretty interesting. So we put out the medicine 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

This is the beauty of ranks. You you get so much sourcing.

Amazing. I understand why every firm puts out market.

This is the beauty of ranking. There's one uh there there was one example that was interesting where somebody that was 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 back now now like got you know this incredible

can you factor in soft skills into your rankings? Well, yeah. And and it was it was more of like a technical ability thing. It was not even I think soft skills are getting a little bit uh you know, they don't they don't you don't care that LeBron James like might get a little angry at somebody if they underperform, right?

Yeah. Sorry.

No, no, no, no, no. this guy. 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 the 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 etc. 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

yeah there's something interesting going on in tech where the idea of a company going from a hundred 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 page rank, and then once you had Google humming at a hundred billion dollar market cap, getting to a trillion, not to, you know, knock at 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're seeing the comp packages increase that way.

You have 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 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 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 that what that does is it it it just changes, you know, the power dynamic between media companies.

Leverage come in through financial markets. If you can lever up or or just marshall 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 like unless you get into true like art territory. But there is this interesting question about like what's up next. And we were kind of noodling on like 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 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 a much steeper power law in in law. And there's a 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 outcome in terms of earnings.

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 to 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 track we track them just for fun. We're not in the business of like calling calling the top or anything like that. In 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 preed 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 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 that have been, you know, 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 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? 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. Um,

don't do it.

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

Are we going to get AI talent agents? Not AI agents. We have those already. But AI talent agents because like

we do.

So

we do they're called venture capitalists.

Oh well this

but yes I I

this was going to be my last sentence. 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 itself?

Indentured services. Yeah. Yeah. You 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. Just

what are they called? Just talent agents

called venture capitalists.

No, no, no. So, so, so, so you can you can I if you find if you 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 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. other scouts going to like Carnegie Melon Carnegie Melon and like going there and like finding you know the sophomores who are like

oh absolutely absolutely

it's now it's now so normalized to invest in college dropouts that you actually see people

like investing in high school students

I'm not kidding about this so the IMO gold medal is the math olympiad and there are venture capitalists who will give calls to every single student that performs well on the on the math olympiad and these are high school students

so do they What are these investments exactly? Like are you're funding their tuition or

No, no, no. It's it's it's I am taking 10 or 20% of of a company of a Delaware COP most likely that that you will build something in and who knows where it goes. Maybe it turns into a great business. Maybe it turns into aquaire, but the downside is extremely limited because there's always this at least right now there's this aquaire there's this aqua hire on the table where

it used to be

but to be clear that is only in AI and it's only for the the people that that you would consider to be the top 500 in their industry to go back cursor wind surf thing like Instagram was the power law winner got the billion dollar acquisition from meta hipeatic was the second largest photo filtering app did not get a billion dollar aqua hire from 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.

Yeah. Yeah. And there's a lot of talent acquisitions, traditional aqua 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.

Um, can I ask a a TBPN question? Um, 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, um, I can build tbps for X. So, like that's 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 where are you going with it? What uh what are your plans?

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

We like to joke. We invented TV. We invented media. We invented

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

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 10 years ago around the time that you guys

Um, no. And it's still you're going to stick around forever. You're locked in.

But if we if we tried to clone this, everyone would be like, "Why is that a knockoff? There's nothing new about this. Nothing fresh about this. Like, why why do I want to go on your knockoff? I just go on the real thing."

Yeah.

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 10 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 we were happy to compete with a bunch of people that were part-time.

Yeah. You know what? Actually, I was wondering in 2021 or 2022 that craziness. Um, someone once reached out to me

and they're like, you know what, you should like

Bitcoin Treasury, you know, you should go direct. It was probably the P.

No, this but this was the 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 guest that you could get, you would get really act good access to deal flow. But it seems like basically

it was very uncomfortable to me because I'm not gonna like highlight startup founders and say, "Oh, you're the perfect guest." And it's like because like I have like 5% equity in them. But I'm curious about because you mentioned doing angel the sort of link. TBPN at some point be like so angsting platform.

Angel investing I look at as as a hobby. It's not a great financial activity, right? Locking up capital.

locking up I mean like you can generate great returns but it's not the most 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 uh people in San Francisco with angel you know people across the country sports uh betting addictions San Francisco you know uh angel investing addictions are I think uh real but for us uh 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 fund coming? When's the fund coming? And and that's been a way to monetize an audience within tech. If you have an audience, go raise a $100 million fund. You get the fee streamers do that.

Uh you get a bunch of upside. And we joke uh because we have the shows every single day. We go live at 11:00. We have to eat. We have to

work out, prep 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 a 100k allocation, but if you have a $100 million 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, we'd smoke them because we'd be 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 why don't you let them put in like 200k?" So the thing is for when the VC fund is coming is when you start reducing your live hours. That'll be the sign.

Yeah. And 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. And

actually was the key insight was that not enough people Well, yeah, it's very fun, but not but very few people in tech were actually taking media seriously.

Yeah.

It it was everyone had a fund. Everyone that was the high status thing and doing media was like lower status or people didn't think it could have as much of a power law outcome as it very clearly can. And so this idea of of just what if you actually took it completely seriously and just made it the main thing and

so we've had a bunch of people copy our format you know major legacy media companies all the way through friends of ours. Uh it doesn't really bo I mean it bothers me more than John but but at the end of the day if you want to spend

you're the Tracy by the way.

It bothers me too. I totally get it. And and so it's like we basically know so so John and I John and I

basically hang out for 12 hours a day and the entire time

the entire time we're thinking we're thinking 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 a 100 hours a week in

go by all means go for it. Like this probably your life's work but if it's not

good luck

it doesn't matter. Yeah,

John Kugan, Jordy Hayes, thank you so much for uh coming on OddLots. That was a blast. And um and good luck and looking forward to continue watching uh TBPM.

We'll be live uh from NY later.

Oh, nice for the Figma IPO.

Figma IPO and Odd Lots in the same day.

What a day. What a day. And in the wake of meta,

pinch me.

Yes, pinch me. Pinch me.

All right.

Thank you for having us. Thank you so much for having us.

Tracy, that was a lot of fun.

It was a little bit media naval gazing. That's fun.

A little bit media naval 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. they're 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 right 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

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 the economics of why you're paying such massive money for someone who's able to like ek out even a slight efficiency ends up being massive.

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, etc. And I'm sure there's progress being made on the literal design of like how you string together uh Nvidia GPUs, etc. And so if you could get some marginal if you know have that know how to get some marginal improvement out of it and this is fundamentally what was

$1 trillion for you but 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 yes 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. Yeah, and I take their point that okay, VCs exist and they're already investing in some ways in specific talent. But I do kind of wonder if you're going to get some sort of like specialized head hunters at the very least who are going to like seek out these big AI talents and try to like graft themselves onto them.

Yeah. Or just uh people whose expertise is in reading through undersited undersited AI research papers

approach to AI research.

Yeah. We can't give you Sam Alman, but what if we could replace Sam Alman in the

sky has 50 citations in the following papers. Um, should we leave it there?

Let's leave it there.

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

And I'm Joe Weisenthal. You can follow me at the stalwart. Follow our guest, Jordy Hayes. He's at Jordy Hayes and John Kugan at Johncouan. And check out TBPN at TBPN. Follow our producers Carmen Rodriguez at Cararman Arman Dashelbennet at Dashbot and Kalebrooks at Kalebrooks. And for more OddLots content, go to bloomberg.com/odlots. We have a daily newsletter and all of our episodes and you can chat about all of these topics 24/7 in our Discord, discord.gg/odlots.

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