Yet Another Value Podcast - All things AI, Power, and Corporate Governance with SemiAnalysis's Doug O'Laughlin

Episode Date: October 28, 2025

Doug O’Loughlin of Fabricated Knowledge and SemiAnalysis returns to the podcast in to dive into all things AI, Power, and Corporate Governance. On the AI side, they discuss where we are in the cycle, if AI is a bubble, and what will drive the next leg of growth. On the corporate governance side, they discuss using signals like off-cycle PSU grants to reflexive incentive structures to find investments, as well as diving into some topical examples. (PS- Doug’s last appearance was podcast #166 on AppLovin $APP, which doubles as the best performing pitch in YAVP history).LinksDoug's AppLovin $APP podcast appearanceDoug's Webinar with AlphaSenseFabricatated Knowledge: ____________________________________________________________[00:00:00] Podcast intro and Doug’s background[00:02:36] AI sector partying vs. value sadness[00:04:06] AI’s capital cycle and bubble setup[00:07:04] Oracle’s shift to debt-fueled capex[00:09:45] Why capital intensity changes multiples[00:11:48] TPU vs. Nvidia: a real challenger[00:13:07] Google’s evolving TPU go-to-market[00:16:02] AI scaling walls and RL progress[00:18:24] Reinforcement learning and Dota AI[00:20:15] Token economics and GPU monetization[00:22:02] OpenAI, profitability, and token resale[00:24:00] AI’s deflationary impact and services[00:26:51] Revisiting the power bottleneck thesis[00:27:44] Power grid constraints and worker shortages[00:31:33] Industrials benefiting from AI buildout[00:32:22] Generalist vs. specialist investor gaps[00:33:47] Specialist traps in relative valuation[00:36:36] Doug’s obsession with board behavior[00:38:19] Do boards game investors with PSUs?[00:41:12] Reflexive incentives at Broadcom example[00:42:17] Mimification and pump incentives at Opendoor[00:44:46] Performance incentives vs. job requirements[00:46:19] Biotech boards failing shareholder alignment[00:46:42] PSU timing around Target Hospitality’s drop[00:52:09] ICE contracts and bed shortage opportunity[00:56:54] Housing workers for Texas data center boomLinks:Yet Another Value Blog - https://www.yetanothervalueblog.com See our legal disclaimer here: https://www.yetanothervalueblog.com/p/legal-and-disclaimer

you're about to listen to the yet another value podcast with your host me andrew walker i guess before we get into it it look it means a ton if you can rate subscribe review the podcast wherever you're watching or listening to it but for today i think you're really going to enjoy this one we have dougo loflin he is from semi analyst he's from fabricated knowledge he is just an absolute absolute expert on all things semiconductor AI power all of that just an absolute expert he is at the center of the field. We have a really fun conversation. And here's a bonus. He's really effing good at corporate governance, spring loads, all that type of shenanigans, where if investors are really reading through the 8Ks and stuff, they might find a management team that all of a sudden

flips really bullish or signals that they're going to sell the company. Obviously, nothing's guaranteed. You can see the full disclaimer. Nothing's invest advice to you, the full disclaimer at the end. But we have a really fun conversation on the back end about some of the crazier corporate governance signals and everything we're seeing. So that's the podcast today. I'm going to get there in one second, but I'll just roll right into the advertisement. This podcast is sponsored by AlphaSense. Alpha Sense is obviously a fantastic sponsor of mine, but one of the reasons Doug is coming on the podcast is because, A, he's a friend, but B, he is doing a webinar with Alpha Sense that is going to go live. I'm posting this podcast on Tuesday, October 28th. It will go live Tuesday,

October 28th. So if you kind of like what you're hearing from Doug here, I'll include a link in the show notes, I'll include a link on the blog, all that sort of stuff. You should go sign up for the blog because, again, here's a little secret. Semi-analyst, Doug, if you were a random pod shop guy who wanted to talk to them about what's happening in semiconductors and AI, this podcast is free, the Alpha Sense webinar is free. I promise you, Doug's time ain't free. You would be paying quite a good bit of money. So look, anytime Doug speaks, I listen, I think he's super thoughtful.

I think you're going to enjoy this. And if you enjoy this, I think you'll enjoy the Alphasense webinar. So you should go check that out. See a link in the show notes. And with that said, we're going to hop on into the podcast. All right, hello, and welcome to yet another value podcast. I'm your host, Andrew Walker, with me today. I'm happy to have on from Fabricated Knowledge,

semi-analysis, everything. Doug O'Loughlin, Doug, how's it going? Good, man. I'm worried that I have to follow up one of the best episodes of yet another value blog ever, but we'll try. We'll try. Maybe I have another 30-bagger accidentally, you know? I'm laughing because the last episode I published

was me just talking to a camera for 30 minutes. So I assumed you meant, being the narcissist I am, I assumed you meant the episode of me, talking not no Doug is referring to literally the best pitch on yet another value podcast episode 166 app loving Doug pitched that what like 15 it's at 35 or something yeah something stupid I don't even know I don't own anymore so it's like whatever it's just I see it I get sad yeah honestly disbelief uh yeah I remember I remember that one too I think that that I was like super delayed on that one and then we're like fuck it we'll do this podcast um on that one so here we

I'm a little sick today after the semi-analysis retreat, but we're here to chat about AI. Yeah, I remember being quote-unquote sick in college a lot too. So to be clear, to be clear, I was actually hungover. Like, dude, I was, so I probably drank like eight days, eight of the last 10 days, if I had to guess. So, yeah, yeah, I deserve to be sick. And I have been hungover, but I know distinctly what is hungover

and what is sick. I am sick. And actually, someone on my team is sick. And so everyone got sick. And this is a bioprocessing bottom pitch, and that's where I'm doing with this. All I hear is when I hear drank out eight of the last 10 days. And Doug, again, at semi-analysis, I just hear, oh, man, the AI guys are partying so hard. And the value guys are just so sad all the time.

Look, I want to talk to about so much stuff. Before I get there, quick disclaimer, remind everyone, nothing on this podcast investing advice. Always true, particularly true today because Doug and I are going to talk about a thousand things. And I just want to remind you, even though the last time Doug stepped on this podcast, he pitched a 30-bagger. That's not investing advice. See the full disclaimer at the end of the podcast. Doug, tons of stuff we want to talk about today. I want to talk corporate governance.

I want to talk AI. You want to start with AI just because that's probably the buzziest stuff and then we'll flip to corporate governance. Yeah, let's do it, man. I mean, as you know, AI isn't everywhere. AI stands for artificial intelligence and it's everywhere all the time. I'm just naming. But yeah, it's pretty hot, dude.

You want to hear my bubble pitch, honestly? Because it feels... I would love to. Okay. This is something that I feel like I've been, every day I feel like I have 20, 20 vision, and I feel like I'm lucid. And I'm like, this can't possibly be happening, yet it continues to happen. This capital cycle is just incredible.

And I really do believe that if we look at like, because I've been, and after I read the railroad bubble books, maybe I'll have a different take on this. But like the one thing, I read a lot of telecom bubble stuff. what I wrote, I wrote a really good telecom bubble thing. I want to say like two years ago. And I think the one difference between the telecom bubble on this is how much debt is involved, which until very recent is like effectively zero. So Oracle kind of showed us what's possible.

There's a lot of debt available. And we are cutting, whoever gets the next job at the Fed is the guys as the lowest number. US treasuries are only a 5% discount to the Microsoft's tenure. and so you kind of have all these things. Oh, and there's like even more stuff. I saw today that the government wants to not have as much capital requirement growth for whatever the risk capital. And you're just like, wow, everything is kind of coming together.

OBBB is effectively an incentive to invest more today. There's just so many things. So because you have the double depreciation, every single possible incentive for you to invest in a capital heavy GPU, Data Center today is happening today, and everyone wants to do it. So here we are. Doug, I'm so glad you started with that because the first note I had is you wrote, as you said, after the Oracle deal was announced, you wrote, the bubble is starting. And exactly what you said, you said, look, everything to date, even though everybody says

bubble, bubble, bubble, everything has been out of cash flow, right? Facebook, Microsoft, Google, all these guys, yes, they're investing tons, but they're doing it out of operating CAFLO. Oracle was the first person who said, we're going to go, we're going to take up debt. We're kind of going to bet the firm, right, by doing this. And once one person does it, guess what, it ain't stopping there. Everybody's going pedal to the metal. So I guess, and then as you said, so we've got that people are starting to use debt instead of equity. That can blow the ball up huge. I mean, you and I were laughing before. President Trump, literally, if you're an executive and you go into, the first thing he's going to say is, how much are you investing into data

centers in America, right? He has a NOBCEO and no, he was like, uh, we don't do data centers. So I just feel like it's all speed ahead. Everyone's just pushing this to a big bubble and everyone can party. Well, yes, there might be a big hangover as you have right now. There might be a big hangover in three years, but it just feels like we've got a long way to go. Yeah. It kind of terrifies me that that's the conversation starter. But like there's just no way that you can't have a, I mean, it's like you can't go bankrupt on a debit card, right? And what we've been doing up until now has been all debit card financing, meaning it's like cash in the bank and maybe securitized Nvidia GPUs if your CoreWeave or something.

Yeah, maybe, maybe securitized. But even then, CoreWeave never built on spec, meaning they only build if they have a contract. So they would go out, they would win a contract, then find the financing. And with the DDTL loan, which is like the delayed term, delay drawed out term loan. Yeah, yeah, specifically focused on the GPU financing side. That was only done, it's like a flexible revolver, focus on GPUs after you win. So it's still, you know, it's different than what we're, what really would be kind of crazy, meaning everyone goes and builds on spec.

And so we're still kind of in this like early, relatively early stages that everyone has been doing this on the beautifulness of how much cash they've raised from the most valuable businesses and the history of capitalism. them, dude, 500, like, all the hyperscalers are still cash flow positive. And I think the thing that may be slightly underestimated or underappreciated, and this is something where you see this and you're kind of like going crazy. For example, they're like, oh, price or earnings is actually not that high compared to history. Because it's fine.

They're all like mid-20s, but they're growing 20, 30 percent, even. And you're like, well, this doesn't seem that crazy. But maybe the one difference that I think is maybe underappreciated is price or earnings is a really, really good metric when everything is super capital light, but right when something goes from capital light to capital heavy, price to free cash flow blows out. And so you, so you have these price to earnings, like it's pretty hard for price to earnings to go up from, or sorry, to really expand or rather the earnings don't flow in mechanically because you have these ginormous cash outflows that like, you know, and that will be,

sorry. Let me push back on that because I think a bull would say, hey, Doug's right, right? This huge AI superclosure that Google's building is a lot more CapEx heavy than Google Search, the best business in the history of the world. But I think a bear bull would push back and say, hey, right now they're taking all the losses up front for these giant AI spends. So yes, in the future, like cash flow isn't as good, but they're bearing the losses now.

So when you say 20 or 25 times for Google, that's probably 10x for Google search plus, you know, minus 10 for all the Google Moonshot bets plus minus 5. for the AI, I think would be my big pushback there. I, okay, so that's probably fair. Hey, the cash flow, you know, you cash burn today for reward tomorrow. And that works when you, when we know supply demand, there's more demand than supply today. Like, feel very empathetically yes on that. And so, yeah, I agree with that.

Like, hey, you're like, oh, they're under earning and they'll over earn or they'll earn their right share tomorrow. That's what accounting's for. But I just think it's really crazy that it happens all at the same time. and the capital intensity shift happens right as double depreciation kicks in. So effectively get to expense this stuff. So it looks, you know, so it's just this weird, it's just a weird dynamic that everyone's price to earnings are really low, right, when everyone's business model changes

into a more capital intensive business. And you can be like, well, what, what's the big deal? Dude, capital intensive businesses tend to trade at low multiples of earnings. Like, that's just how it works. As someone who generally buys capital intensive businesses, I know. I know, Chuck. Yeah. So, I mean, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's,

it's, it's, it's, it's, it's, it's really interesting. And if we're talking about like, well, and, and, and actually, while we're here, because I'm going to just, you know, I'm going to do, I'm going to do, I'm going to do. The thing that I think maybe, because I don't, you definitely know if all the space probably as deeply as we do. The one that is definitely coming, are hitting, hitting, hitting the newswires a lot more right now is this you, um, and we have been one, semi-analyst has called this out in, and, like, I don't even know, I want to say July or something like that. We were really early on that.

And we were very excited on the TPU opportunity because it's the second best cheap. It's the second best chip of all time. And so if you want to do the real bull case on Google, it's, you know, a trillion for the TPU, you know, whatever. GCP accelerates and that's like a WS. Waymo and search is free, bro. That's the real. That's the real bowl case. I'm just kidding.

But like, I really think, yeah, I think the TPU. I mean, again, I'm a mouth drooler, but you're saying the TPU is, it has the possibility to be competitive with NVIDIA is basically what you're saying. It is definitely, it is definitely competitive with NVIDIA. It is number two. It is number two. There's no other... Number two does not necessarily mean competitive, right? Bing is number two to Google.

It is not competitive to Google. Is this Bing or is this, you know, Android and Apple? Okay, so let's, it's time for some AI rumors, okay? The best pre-training team in the world is a TPU. Everyone says that, and one of the reasons why is, because of how TPU is a much more stable, a stable version and scalable version for pre-training specifically. So there's a lot of advantages, and the tech tree that the TPU has gone down

has a lot of resilience and advantage for software that makes it very, very attractive at scale. And I'm going to try to do this justice, but pretty much the NVL-72, which is 72 GPUs, all tied together, has a real. really big blast radius has a blast radius problem that's like kind of complicated and it doesn't really work. Meaning if one of the GPS fails, they're like, what the hell do I do with the other 70? 71 of them will get stopped or paused. The 3D Taurus, which is like, you know, you're going to have to freaking Google this, but it's very complicated. Like it's a 3D, it's like a 3D cube where all the pieces of the queue. You just gave the bookcase for Google, right? You said Google this

while you were pitching the Google TPP. Yeah, there you go. Sorry, chat GPT this. You know, it's an all-to-all mesh that you can make slices of TPUs. And so you can scale this very, very big. And so they're like kind of two different philosophies on how to scale into really, really, really large clusters. But they are both very competing and valuable philosophies. And I think TPU could be very price competitive. It is just straight up a margin question.

I would argue that at some price, I would definitely take TPU over Google over NBLink. all things being equal with software. And it's actually a product that runs inference production at scale, training inference production at scale today. Like it's a real competitor. You can argue it's number two. And I think at the right price, it would be number one for me.

Mid Journey, for example, allegedly uses all TPUs. So there are companies at scale today who are stoked to use TPUs. And I think that that's going to be, that's going to be, I don't I don't know. That's going to be a big and new, interesting competitive vector that I think people don't appreciate or haven't been appreciating because, yeah, Google's been, I mean, I've tweeted about this for years. Google's go to market. It's like, you know, you don't want to bet on those PMs because they killed by Google.com is like one of my favorite websites. But I think something has changed in the last year because in the beginning they really were

like, oh, we're going to have the best AI. It's going to be done on the best infrastructure. That's ours. And you're going to only be able to use it in our Google properties online. And I think they've been willing to open the aperture by willing to do Gemini on Siri, willing to sell TPU externally, they're willing to open it up so that they can have more customers, and then that means they can have a real chance of being a true number two. Killed by Google, it's one thing to kill Google friends or Google Meet or whatever, when, you know, it would be a nice business, but it's not, it's another thing. Like, AI is existential for them.

Every big tech company has clearly realized that, and I'm sure they had a vision last year, but at some point you start to realize, hey, we can't do this all internally. Like, it's too much of a skill game. It's too much of a moat. I will be honest, that was super interesting, but we are like at the far limits of my technical knowledge. So even though I, if I was a better interviewer and better at this, I would dive into so many more questions, but I'm going to back up to my dumb, dumb brain and ask you something else.

For the past year, if I would talk to, you know, I'd leave more value investor than semi-analysis growth investor. When I would talk to a value investor friend, and they would say for the past year, AI bubble, AI bubble, AI bubble, they would all point to the models are stalling out, right? Inference is selling out. The models are stalling out and everything. I don't know where we are on that, but I just want to ask you, if I got an AI bear on here and had them, the first thing they would say is the models are selling out. They're not improving. We're hitting the limits of scaling. What would you say to that question? Okay, so that's a great question. It's pretty hard to answer. So in December, specifically, scaling laws are done on the pre-training side was probably pretty valid. I think there's a lot of hype right now in the Gemini 3. It's supposed to be coming, I was told Gemini 3, which is the newest and best model, is going to be the newest and biggest model in existence. And that, I think, comes out some time this month.

So that's the big proof is in the pudding. A lot of people are very excited about it. We'll kind of see. But there's been multiple, like multiple scaling vectors of how these models are are getting better. And I think we've become a lot less focused on AGI, which is going to like superhuman intelligence that's going to like zap your little brain

because you can't even understand to almost like essentially all white color information knowledge is free or the marginal cost goes to your GPU. And that's really the focus of where things are going right now. Specifically what this is, the entire infrastructure or the entire industry is very excited. on is RL. RL means reinforcement learning. And so in the same way, you and I learn how to do stocks good or bad on a very low end size data set of like, you know, our history, career,

whatever we like, dude, this setup really works for me and I do a really good job. Pretty much the goal is that you do training on these models too to be like, hey, this setup does, like your job is to check out, you know, check out this book from Amazon in the least amount of clicks. And so, you know, in the beginning, it literally clicks everything, it does all the kind of crap and it doesn't, but you can kind of just say, hey, no, bad job, bad job, bad job, good job, bad, and then all of a sudden, it gets to the point where it can click on all the things and check out your book really, really easy.

And anything that is verifiable, meaning that there is an outcome to be desired, and you can effectively, you know, guide it along a path to figure out the answer is probably a solvable problem. And you're like, well, that works for an Amazon book, you know, or something like that. And Amazon already is blocking all the agenetic stuff, by the way. That's, like, going to be a war, I'm sure.

But you can say that. But the reason why people really liked opening eye to begin with was the original RL thing they did using reinforcement learning was making these superhuman Dota 3 players. So like the, yes. I was going to use that as an example. Yeah, yeah. Yeah.

And so these superhuman Dota 3 players are better than humans. And you're like, okay, well, you know, they won't be able to be like in these complex things. Like, that's a pretty, I mean, I've played enough Dota 3 to be like, this is really complex, and I'm going to be bad at it, and I know I'll never be better at it than these bots. And so that's pretty, that's probably enough. That's probably enough, meaning you use URL to kick the shit out of a lot of like

verifiable domains and tasks, and you just scale it to the moon. And that's the plan going forward. And you'll see these like multiple, there's like multiple roads of progress. Pre-training is slowing down, but it will get a little bit better. test time compute is probably not slowing down, but no one really wants to spend the compute budget. And so everyone's like, give us more compute budget. And then all this post-training and RL stuff is definitely not slowing down.

And that's where people are excited. And so what happens is this new vector kind of hits an asymptote, and then all the stacked vectors get better in an aggregate. It definitely is happening faster, meaning the returns to scale are slowing down a lot quicker than like the AGI cases. But I think that you look at the history of, improvements in technology. It's pretty damn fast, dude. I agree with almost, with everything you said, let's just say that, almost everything, everything, whatever. I do have one question. You said the

returns to investment are slowing. How are they measuring returns to investment, right? Because I would even hear an open AI guy talk about the returns on investment stuff. And I'd be like, how the fudge are you measuring this? Because you don't have any, it's not like they have of no revenue or anything, right? So I'm sure that they are getting better. And you'll hear all these guys talking about their returns on investing in AI. The only one I really believe has any is Facebook and maybe Google because I know Facebook's using it for a lot of internal training and targeting stuff, but I hear returns on spending coming down, but still very positive. I'm like, I don't know how they're measuring it. So this is, okay, so this is actually a really good question and

something, I got to pump my stuff. Inference max.com. A.I. We have this thing. It tells you how many tokens you can get and how much cost. If I can pause you, I mean, people don't understand. we've got Doug on. If you were a pod shop trying to have this conversation with Doug, this podcast is free. It would not be free. It would be a lot more than not free. So this is highly valuable info we're getting here.

Okay. So, so inference, Inference,x. I kind of talks about how much tokens at how much cost you can make, and that assumes it's paid. So Inferencebacks. We made this benchmark. It's really cool.

It shows AMD versus Nvidia. It kind of shows how AMD is catching up, blah, blah, blah, blah. We're not going to go into that. But the takeaway is, if you could sell the tokens that that's happening on one Gb 200 in a year, and Invidia took this and they turned around this in their marketing material, one GV200, which costs like, let's say, $3.5 million,

makes you like, you know, $5 million a year. So it's like well over one-year payback period. The raw unit economics of this stuff is extremely high. Like, insanely incredibly high. The problem is, how much are you able to actually get paid the entire stack? That's the real issue. Let me push back in one way there. So I hear you, because you're renting out, you take the NVIDIA GPU, you buy $3.5 million, you rent it out to, well, Cori would be the one renting out, but they're running it out to some AI startup, right?

That's how they're getting generated their return. I think where people would say, you know, all the classic value investors things where they've got the search protector plugging into itself, what they would say is, hey, they're running out to an AI startup that has no revenue. So how is that AI startup evaluating their return on investment? because that is where you kind of get into the dot-com bubble fiber. Like, it's all just a house of cards, circular reference, blow up on itself. Okay, so, yeah, let's talk about it. Because I think an aggregate, a token that is sold, is profitable in the aggregate by a meaningful amount.

Because TSM makes a 60% margin. Invitya makes a 75% margin. A Neocloud makes a 40% margin, just buying those and renting it out. And then all of a sudden, Open AI makes negative. of like, what, 50% margin? So I think if you aggregate it, it actually is, there is like, you know, whatever, the token sold out is actually pretty profitable. And I think specifically to Open AI, like, you're probably right, they can't afford it.

But on a unit, so how you justify, you're spending all this stuff, you got to improve the technology, the capabilities is like no end. But on a unit economic basis, specifically going back to that rack example, if you were just to buy a rack and inference the models, You sell it to people, even on a subscription service basis, it's pretty, it's pretty fucking profitable. Like, I think, you know, some of them, assuming that it's a deep seek model, like, you can kind to do the entire global infrastructure of open AI, all the free guys for like, I don't know,

man, probably like a few billion, a few billion, 10, 10 billion. So let's just say you're supporting a billion user, a billion active, monthly active users for 10 billion bucks. And you're telling me you can't make a 10 billion bucks off a billion users, I feel like that's a skill issue. They'll be able to monetize that. That's not like a crazy, crazy number to me. Is Open AI, and I ask this from personal experience, because I'm actually going to do a post at some point, but a lot of apps that I would pay the apps were $10, $100 per year for, you know, backing apps, whether it's food tracking, workout tracking, other stuff, I just pop it all into

Open AI for free. Is AI insanely deflationary? I, yes, yes, I think it is. So let's actually, this actually some, I've had this whole debate for a long time. I think AI is insanely ridiculously, stupidly and deflationary, with the exception of if you like, if you're trying to power your lights. Yeah, yeah. Well, yeah, but you have to, yeah, keeping paying for energy. I think the next leg that makes everything a lot more healthy is if you sell things as services. And that's why we've been very bullish on like this agentic purchasing thing. So my favorite, you know, chat GPT5 is set up for monetization is like a post we did on

semi-analysis. Yeah. Pure, dude, pure my schizzo posting straight up, Fiji works at Instacart, gets chat GPT Instacart to work. She leaves Instacart to go work at ChatGPT. And she's like, we are definitely going to be monetizing this stuff soon. And so that is an example where I think you can massively have a very profitable business that is done on a service basis that isn't deflationary and has high margin, meaning that, like, hey, we're pretty programmed to pay, take rates if it's convenient.

So I want to go by, you know, my entire, you know, make me a keto weekly shopping list and purchase it on Instacart, right? $150 or something like that. I don't, well, we'll just say, we'll just do $100. So it's like a raw number. And it's like, okay, well, you know, Instacart will take some platform fees. They'll share it with, you know, let's say 10%. They'll share some with chat GPT because it has, it does increase all this stuff.

Hey, I want to have a, you know, a vision check up. And it does like all that top of funnel stuff where you just take a Vig on it effectively is like, dude, that I think is a very valuable thing. And you could be massively deflationary, but it's a service and it doesn't like, you know, you don't like deflate the entire economy away because that's the. real, that's the real concern, man. Like, we have these things that are, it's kind of, it's kind of terrifying, but, but this same thing has happened over and over again in the history of time.

Hey, railroads were an order of magnitude better than canals. The classic, right? Yeah, the queen didn't want to bring sewing machines in because what happens to the poor sewers? Well, guess what? You get with the times or you get run over. Yeah. Yeah.

So it's going to get run over. It's going to be really deflationary. And then on the other side of it at some point in time, it blows up and there's like all kinds of new stuff. You know, I hope it's like not where we're not like just all talking to our AI girlfriends and there's something more less of like, you know, more positive something than just my eight month pregnant wife, she knows I use AI a lot and she had a friend who actually had a friend who got like really into the day. And she was like, please telling me you're not using AI as a girlfriend. I'm like, girl, have you met me? But I can understand the concerns.

I have two more questions on AI and then let's hop into some of the corporate governance that I think you and I both have a special place in our heart for it. Yeah. First question. Actually, I'm going to skip the power stuff. I will just tell you guys, I'll ask one power question just so I can give this anecdote. A year ago, you and I probably talk once a quarter, but you can tell how highly I think of you because I remember the Oracle thing and I remember this conversation.

I was doing a lot of work on the Bitcoin Minor to have power play, and you were doing it separately from me. And I called you up and I was like, hey, man, like, I feel like it's got a long way. to run. But man, these things have really run. And I think people don't understand like how much worse the Bitcoin miner assets are than like normal data centers. How much your room is there to run? And you were just like unlimited demand, buy them all to the moon. And APLD is about an eight bagger since then. I think that's the one we were really talking about. You can pick your share of anyone. But I'll just, I want to give that anecdote. So I ask one question. How much more room can this

power trade possibly have to run? This is something, you know, we had a we had a DM before we started this, talking about where I think things are maybe off sides in the markets. My belief is power is much more off sides than semiconductors because I, like, semiconductors are really scalable, TSM is really scalable. They can add a ton, like, they can add a ton more capital equipment and make probably double the chips. Taiwan can do that. Taiwan can make double the chips in like two years. I 100% believe that. We cannot double the power in two years, just like straight up. I don't think people appreciate or understand that at all. And I think that's where the biggest disconnect comes from when I talk to investors, when I talk to people, is that like, all the chips

guys are like, yeah, the orders are good, you know, invidia is going to crush, blah, blah, blah, Taiwan's going to figure it out. There's a lot of technological trees. And they're like, yeah, I think we're going to get to a megawatt per rack. And you talk to a data center guy and they're like, are you fucking kidding me? A megawatt per rack? Like, this isn't real. And you're like, I don't know what else to tell you, man. Everyone else is bought in except for a data center guy. And so there's a lot of really fast-moving data center operators who are doing very, very, very well in the space. I don't know if you have met Switch, like the Rob Roy guy. He's a, he's a billionaire. He was like, actually, I remember this IPO very vividly from when I sat at my byside shop at like

Bui Capo. I remember reading this and like, this guy is a crackhead. And he was like, we're going to make high density racks. That's the future. And I was like, I guess. And he is like always been about high density racks. He's been crushing it because the second you heard about this, he's like higher density. In fact, I'm going to three megawatts. Like, we're taking the dials to 11. Exactly. He's like literally, I'm at an 8 and you tell me I can go to 11. He's going straight there. And so I think like the DLRs of the world are like still shell shock that we're at 120 kilowatts. And then the really fast moving players like, let's say, Vantage or Crusoe, they're all being like, how do we get to 500 kilowatts per rack? And that to me, like 500,

500 kilowatts per X kind of a crazy number. Like, I mean, you just start to, like, my mental math year, six gigawatts is New York City. And so everyone is saying, and all the chips that are being purchased will support all this power. Like, straight up, we know the power that it should support.

And the data center, the power side, is just not moving fast enough. There's a lot of ways you can, you can ring efficiency from the grid, because the grid is focused on, you know, But when we talk about peak versus trough and utilization is going up, and that's like batteries, backup power, pretty much shaving the hottest days out of the year

or the coldest days out of the year using peakers. That is all working, but I still think, even with all that, we are still talking about a lot of, a lot, a lot of demand. We just add to p times Q equals more power from here. And I think, oh, the last thing I want to say specifically on this, on the stock-wise, you know, the power, the miners probably still like every weird little minor that hasn't run, probably still works from here to whatever, we'll say, Iron being the craziest

or applied in Iron being the crazier ones. But the other one, too, is like the incrementals on industrials is what really interests me the most. Probably one of my favorite company's comfort systems. You can look at their print yesterday. They're like, the revenue goes up 40%, and their EBIT goes up 80%. And their EPS goes up like 150%. Maybe not 150%. But like, all of these businesses, they're growing the fastest in their highest margin segment, and they often are massively capacity constrained. And what that does for EPS is like relatively modest. And what I think it does from here, like, you know, on the power and accelerates. And so you're like, dude, there's accelerating on these businesses with these crazy incremental EPS stories. And so how you

underwrite it is very, very hard. Yeah. I'm laughing because I can't cry on a podcast publicly, because I have notes. I actually looked because somebody was tweeting about comfort, the ticker is fixed. They were tweeting about their earnings this morning. I had notes from about four years ago, and the stock price that I had in there started with a nine. And the stock price today, after this big earnings beat,

starts with a nine, there's just an extra digit in there now. So, you know, it's a 10-bagger in three years. But, okay, two last questions on this. I ceded these to you, so hopefully you've had time to prep. If not, we'll just go to the corporate governance. But I am a generalist investor. What is one thing? I is a generalist investor.

and you talk to everyone in the space, from generalists, the pod shops, to the company themselves. What is one thing I, as a generalist investor, would not understand or might have a perverse perspective on versus kind of a specialist investor who really spends all their time here? I still think, I mean, I feel like the thing that is,

it's just the power and scale, the infrastructure stuff is just really, really, really hard to grasp your mind around. Yes. I've done enough data center toward, visits to be like, like, literally I do a data center tour, and they're like, yeah, there's a 100 megawatts in here. And then in my mind, I'm like, this is a baby data center.

So, like, the scale, it really helps to understand, like, how much we're trying to deploy here. I also think that I think that the capacity and willingness of Taiwan to make ship, like, it feels like this entire ginormous industrial revolution is happening, but it's not in the cities. It's usually like in rural-ish or outside of the core. And so no one gets to see it, but tens of thousands of people are working on these data centers buying GPUs. I mean, you saw the last thing, the last quarter of a GDP growth was like 190, like 190

bips contribution from freaking data centers and GPUs driving everything. It's just insane. Okay, let me ask the question slightly differently. Special investor. And what I'm referring to particularly is I think you guys talk to a lot of pod shops, tech focused, probably trading the quarter more than anything else, but they are very heavy in the least here. What is one thing that you think specialist investors have a different opinion on versus kind of the industry people, the hyper-scalers, the actual people doing this when you talk to them?

Pods versus industry, I think design loss and inertia of big products, it's like we're probably past the like, oh, a good chip or like, you know, a good product can win scale anymore. For example, maybe even, we'll, we do the HBM drama life because HBM 4, like, there's been this qualify, is it going to qualify, is it not, Samsung's crew, is it not? And then Sam Altman goes and says, hey, I need just like, you know, 50% more. So I think what's kind of in this thing where I think, let's say, specialist versus like industry is maybe the absolute versus relative. A lot of people who I talk to on the specialist side are very focused on like, well, isn't this bad for someone else? And you're like, dude, a rising tide is lifting every fucking boat

that could possibly be. And every industry guy is like, yeah, I'll take that total garbage data center power stuff because I need it. I need it. I need it. And like a good example is maybe the anthropic Amazon thing. People are, a lot of people are really freaking out about it because they're like, well, doesn't that mean trainium screwed? Will they, won't they? Like one of the most galaxy brain thesis is if they just give up on training and they buy GB to hundreds, revenue is going to freaking roof it. Like, they need as much possible. And I feel like it's up in a shortage, any, any supply is going to be massively valuable.

And I feel like there's almost too much relativism going on here because they're like, oh, well, you know, this is going to be good or bad. Like, I mean, we got a little tripped up on this at semi-analysis. Like, we're very bullish, boom energy on time to market. And then we got really deep into the on-site gas space. And we're like, man, on-side gas is just like so much cheaper, more reliable. well, why would you ever do this? And the answer is, you're going to do both because they want both.

And so I think that that's where a lot of specialists have kind of tripped themselves up in the last year specifically. I'm not a specialist, but I just, again, back to our thing on energy. And I remember having this call with you. And I was like, look, applied data is that big plant they've got is out in, it's out in North Dakota, if I remember correctly, right? Yeah, it's got a lot of space, but nobody wants to do North Dakota. And I was like ticking through all of these Bitcoin miners and their assets.

And I was like, I was basically like they're not all A pluses, right? This is a B minus asset. This is a D plus asset. And I think you were rightly, like, dude, it just doesn't matter. The demands there. And we were early to it. And every single one that we talked to is at worst, the seven-backer. And at best, I mean, oh, my God, the lost fortunes.

Okay, putting that all to decide. People say I do a lot of stuff. But, Doug, I have no clue how you have the time to run semi-analyst and be a corporate governance slash shit co-master. So let's put our corporate governance at. on. I've got some questions here, but I'll just let you cook for a second. If you want to talk anything, corporate governance, signals and spring loads, whatever you want to go with it. Okay. So I will, I will admit, I do love it. Semianalysis has been taking a larger and larger

and larger share of my brain in time. Unfortunately, I think I, probably my absolute peak in terms of, like, edgness is like well over a year, like past because I was like really sharpening the edge until then. It's a little dull, but let's be real. I love it. I just love boards. What can I say. I just love when the people part of the equation get into it, and you can really, really, really see how weird decisions. Doug has some master model for detecting off-cycle PSU grants and RSU grants and everything. And I'm trying real hard to recreate it. I have not had a lot of success, but one day I will come for you on the trackers. Yeah, please, please do. I mean, I guess then we can, then it'll be the beta era, you know, the PSU hits and we, the stock just

roofs it into the thing and then we're good to go. That was my first question for you, actually. So, look, when we're referring to this corporate governance stuff, we're talking about companies, you know, the classic is it's, you know, a company normally gives out their share grants in February. They give out an off cycle grant in August. Well, guess what? Why are they going to do that? Because they're going to smash earnings when they report them two weeks later. Have you seen companies start to gain, like you and I would see that.

We'd know, hey, this is probably a buy and we buy that. Have you seen companies start to try to game investors by giving off off cycle PSUs to try to get. people excited and then hit them with an equity offering because I will tell you, spinoffs, about 10 years ago, companies realized investors would buy spinoffs hand over fist no matter what. And I think they started spinning off garbage segments with toxic liabilities to take advantage of that. So I could see how everything is game theory. I could see how companies respond to this to take advantage. Have you seen any of that? I think that that's a pretty good observation and something I've been thinking about for a long time. You know, can I mention the event we all into?

And please, anything you want. Cool, cool, cool. So we went to this event in New York. It was cool. It was like an activist thing. And I definitely think, I mean, I had, thank you, by the way, for the invitation. It was, it was very interesting to see how the investors thought about it because I was like, oh, we're very, everyone's pretty clued in.

Everyone's pretty clued in on the PSUs, man. Like, you know, show me the incentives. I'll show you the outcome. And a lot of activists are very focused on throwing in incentives to make sure outcomes happen. But at the end of the day, it's like, you know, you're it's it's hard because I think boards are snowflakes right some boards are really really really outstanding and they actually are trying to practice shareholder value corporate governance and some boards are total fucking crooks and you know if we're talking about like you know and

sometimes the the compensation packages aren't even aligned right that's one of the issues that I think is a huge thing is like what happens if you're you know you're just getting PSUs like there's not even a, there's not even a performance. It's just share units. Guys just getting RSUs and getting paid out. Like you, you see that occasionally too and you're like, whoa, wait, how does that have any signal? So there's just like whole problem where, you know, the board alignment is almost like the third thing is like, how much grift or how much alignment do they even care about at the end of the day? Because there's stuff that there's a lot of control over. And, and that's where I think it, like, the art of this even happens at all. Because, you know, I've seen like Hail Mary grants

where you're just like, dude, a company is about to go bankrupt. And they're like, let's just give them more out of the money, crazy PSUs. And they just go bankrupt. And you're like, you know, is that the board who has the bad judgment? Is that the management team pitching their compensation package to the board? Is it a compensation? There's like this whole thing where I think there's like a little, like there is a layer of fundamental analysis to be done because, you know, the board could also just be stupid as hell.

That also happens all the time, too, where it's like, oh, they're about to springload. oh, it's definitely coming. And the same board that's like, well, we're going to turn around this company as it's been like slowly eroding into a total shitco, you know, are you trusting the same judgment of the board that got you there? That's one of the issues I think that like kind of makes this like become really complicated and fuzzy. I think a lot of the time to make it a higher signal game is to really focus on when fundamentals

actually line up. Because if there isn't a fundamental story and it's just a board giving PSUs, hoping that they're saying, hey, we're all aligned, that can get really tricky really quickly. And actually, I'm going to bring this into the semi-tukter world because Hock-Tan recently has this ginormous PSU where he's like, dude, I make $10 billion. Or I forget the number. It's like, it's a multi-billion dollar package. Hock-Tan is the Brockcom guy?

The Brockcom guy. Yeah, and to be clear, he had these crazy share price vesters that hit in like a little over a year, it's like, oh, if you could double a share or like, you know, if you can two and a half X the shares in a year and a half. get paid out, like, effectively what is now a billion dollars, and he did it in like a year and a half, like all this acceleration, all this stuff. And so he goes to the conference and he says, you just saw my compensation package. I've got to sell a lot of AI.

And that also kind of lines up to the anthropic thing I was saying earlier with the TPS externally. But like, he's like, look, I got to sell a lot of AI revenue, like ASAP in order for me to get paid. And you're kind of in this weird spot where you're like, that feels a little too reflexive. Like, you know, the feedback loop is almost too close. The, what, when this really works is when, you know, a board team that's really good and understands the challenges in their business really tries to align the management team on what really matters to pull the lever to make shareholder value. Instead, when the board says, I'm going to like essentially pump up a target, give it to the CEO and the CEO then is going to go like out into the public to pump it. It's almost like reflexive.

You know which one reminds me of this? I actually had this on my list of ones to ask you, open door. I don't know if you looked at it or not. Yeah, I haven't seen it. It goes from 90 cents to $9. They bring in the new CEO. They pay the new CEO a dollar, and they give them these RSUs, or PSUs, I'm sorry, that invest at crazy, crazy prices, right? 9, 13, 17, 21, 33.

And if you look at the fundamentals of Open Door, you're like, no. There's no way. There's no way. Unless you, you know, your Galaxy brain door. And maybe I'm wrong, right? Because some of these have worked. But I have wondered, you know, are companies starting? to bring the memeification of certain companies into their PSUs and like kind of encouraging them

as you're saying to go out and be pumpers and the incentives get really perverse and weird. Yeah, for sure, bro. I mean, I mean, just because Open Door CEO is super on Twitter or X, right? And he is pumping the crap out of his stock. So I would argue that you, you, if you're like in some of the really aggressive compensation schemes, you are also pulling a third lever, which is pump your stock. Right. And that could be good or bad. Hey, if you have a really cheap, underappreciated asset,

maybe pumping your stock isn't a bad thing. You can argue that that's just, you know, investor communications, right? Getting your story out there. But if you have a really, really, really crappy fake company and you're like, I'm going to put lip, I want to put lipstick on a pig and tell you that it can fly. And I trust me, bro. That's just promoting, right? And so that's kind of the, I think that that's probably like the,

short-term versus long-term problem, there are a lot of these compensation packages where I've looked at it. And I've been like, dude, this was a really good job. This actually made a lot of sense. You created a lot of value and like a really goaded board, which effectively says, you know, my company is really hurting because of X, Y, C. Probably the best, actually, example of this is leverage. I really like the levered companies. Because the problem is what's the external versus external factors, right? The levers you can't, like, you should, the best possible compensation package you can have is when you have a lever that is internally pullable, and then you essentially award them to pull that lever. Making a compensation package to get good on a challenged

business is very hard. It's like, okay, I need you to magically accelerate McDonald's organic sales to double digits. Yeah, I don't think you can do that. I'm completely with you. The other one that sucks is when it's something that the company so clearly needs to do, and they get paid for doing it anyway. I can't say it. Like, I know companies like, hey, we have debt that's due in 18 months. We're going to get a bonus if we refinance that debt. I don't see why you should get a bonus for doing something like the company goes bankrupt

if you don't refinance that debt. Now, if there's some magic lever, you can pull, but like you're kind of just doing your job, but I, I understand because you can argue where it's like, that's just wrong. That's just incompetence where it's like, oh, do I have to. literally have the hamster press every single button to get fed, right? It's like, hey, if you don't press the button, you die. Like, it should be pretty clear. And it's like almost like, if we're talking about the, you know, the award, the participation

trophies, you know, the real participation trophies that they're handing out. These board members are handing out participation trophies to management teams across the nation, bro. Look, earlier this year, I went crazy on all these biotechs that were trading below cash. And I was like, all these boards, they own. no stock. Many of them, I had some letters that were ready to get real spicy. It was like, hey, guys, you've made $3 million as a board member over the past 12 years and your stock is trading for half of cash and you own zero shares. Like, how are you going to tell me that

you're here for shareholder value? You're not here for shareholder value. You're going to tell me you're here for science. You're not here for science. All your science failed. All you're here for is you're a 74 year old man. You're here for a retirement package. Like, that's all you're doing and you're just trying to prolong it. One of my favorite takes is that, um, Independent board directors are independent because they're looking out for themselves. That's a really good one. Okay. We're almost at the end of our time.

And again, for those who don't know, Doug Charges quite a bit for his time if you're a pod shop analyst. But fortunately, he's a friend. So we get him for a few. Give me one spicy corporate governance example you're looking at right now. So many. Should I do, should I do my work hat, the semi-cutter ones? No, no. Let's go with something more fun.

I, there, I'm going to just, I'm going to, I'm going to, I'm going to a parent one that non-Gap just posted. The elastic one, I think is really interesting. This is ESTC? ESTC. If you've ever been involved with this name, I actually remember the, I remember that IPO. I remember trying to convince my boss to buy it. It's been, um, quite a bit of brain damage if, um, and, but they did this ginormous off-cycle

PSU, and I do think that there might be some kind of lever in consumption, specifically focused on AI that they might be trying to really incentivize or say that, no, no, no, no, the search API really, or the search is really going to work out for us. That one is, I mean, that's like to the extent, I mean, maybe that's like to the extent I have no fundamental knowledge on that one. Maybe if we're going to talk about one of the ones, I'm trying to think of one. Do you want to talk about, well, no, I don't even know enough about this company and back you.

You schooled me on what the hell they do. I don't follow it closely anymore. And I hate to give negative you back on. Well, you know the one I really have spent all the time. Go for it, man. Even though it's one of my worst reporters at all time, Cohn stab that knife into my chest. Yeah, I'm not trying to do this to you because I will be honest with you.

It's been pretty fateful as a shareholder this year. Target hospitality. That's probably, T.H. T.H. Yeah. And, unfortunately, I don't know it anymore. Go ahead. Yeah.

And Andrew knows quite a bit about it. I think they are a very incentivized management team to get the share price higher. Not only are they extremely incentivized. they're extremely closely owned by a private equity firm that owns over 50% of the stock. Historically, private equity is probably one of the hardest core offenders of executive compensation. Because if you own the majority of the thing, you can do whatever the hell you want. Who cares with the shareholders? The shareholders that really only matters is the one guy who really controls the board.

And often for private equity, if they're a public company and private equity owns the majority of it, they're looking for a liquidation. So they can line up some really interesting and weird things. And I think the thing that I'm most interested are kind of focused on is, one, they've done really aggressive PSUs in the past. And they've won some aggressive contracts from the government. And they had this year-to-date that the pain has been on the fact that they got their ginormous. They also had a sale process. They try to almost go take private again.

You were involved with that. Yeah, that's where I got really hurt. They had a sale process. The private equity owner who owns 60% plus offered to take them private. They lost not one but two contracts in the middle of that sale. process, if I remember correctly. And the process got pulled. So that's kind of where the pain for me came, but my pain might be Doug's gain here.

Yeah. So they lost the, so they lost not one but two contracts. And then they lost, like, I think the real one that they just lost. Their big daddy one, yep. The Pico's Children's Center, that was the really, really, really painful one. I think the total contract value on that thing at one point was like $2.5 billion. That one got canceled in Doge. But let's just kind of even focus a little bit on the compensation aspect of it because the week after, I mean, the timing is way, way, way, way too precise.

The week after, they effectively do this ginormous compensation package again. And they have the same aspect of ginormous price vesters. And hey, maybe this is just maybe this is the board is completely delusional, which maybe it is the case. And the board also has been owning this thing for so long. so they do know quite a bit. But, you know, on February 28th, which is, you know, literally. I'm looking at the A.K. Oh, yeah. Yeah.

And, I mean, let me look at the stock price when it happened. But I think they lost it like, yeah, they lost it on February 21st, okay? February 21st, it's February 24th. The stock goes down 40%. You're telling me that they were so ready to do this compensation package. They had it. They, you know, they cleaned it up. They called a board meeting and they voted on it in four days.

no way dude that timing is too freaking tight no one can do that kind of stuff so if i can back up so for those who maybe don't know the obviously you and i are very well versed in it what how yeah they they lose the contract from memory i think the stock goes from like eight to five right four days later they announced this is a giant PSU grant they give the CEO two million two million PSUs that don't kick in until the share price hits 20 on the low end and 30 on the high end so let's just say he's going to hit the high end. They give him $60 million if he can hit this. And I can't remember the timing, but timing is generally like three to five years on these. But they give him $60 million if he can effectively five X the share price in five years. And what Doug is saying is, hey, these pay packages

are not awarded willy-nilly, right? Like, they have to be in the works for a while. So they're probably working on it. And these pay packages, they're not just awarded willy-nilly. You don't want to award, you generally don't award a CEO of pay package that they have no shot of hitting. A lot of times because these are kind of friendly, you award a CEO, a pay package that calls for the stocks go up a lot. And you kind of know in your back pocket there, there are a lot of things on the come that are going to help get there. So I think that lays out, why don't you tell me they just lost their big payco's contract, right? What are the things on the come for this company that has lost two to three big contracts in the past 18 months? What are the big things on the

come that could get them to a five-x stock price? So this is where you have the two most secular trends of our time and one public company, okay? ICE detentions and data centers in West Texas. That is that. That's the story. Okay. So they lost the Picos facility. As you know, it's,

TH is a modular housing play, specifically focused on man camps. Their historical business is oil field services. If you're familiar with the shale boom, they reaped money then. I think there was enough, they were public or there someone else was? And I think they're back.

You're thinking of civvy, I think is here. Yeah, I'm thinking I'm civvy. And so they have a modular man camps and you go look on Google and you can see them. They're literally just like, they're just bunks where they can, you can sleep. And so they won this ginormous contract specifically on the government. The government does about 60 bucks a day and it's a little bit lower ADR, like average daily rate, but it's pretty good margin historically about 50%. And so they lose this contract.

It's majority of their revenue, but now they have 6,000 beds and they've been telling anyone who will listen, we're keeping those. beds weren't we're paying the maintenance capics on them we're paying the energy we don't want it to we don't want the facilities to go bad because they're trying to keep them active until the until ice potentially takes them and ice has been telling anyone who will listen as well they're they want 100,000 beds this year 100,000 beds is a lot of beds I think I think detention beds before the big OBBBB is like 50,000 so you want to double the beds there's not many beds like quickly available they have 6,000 ready to go and

And, you know, OBVB passed, and they funded $45 billion for beds. I mean, that's the entire ICE budget, I think $30 billion of which is attributable to structures. And so you're telling me, you have 6,000 beds available. You have $30 billion of funding to buy some freaking beds. They're ready to go. And you have a management team that is incentivized to win those damn beds. If you go look, they're re, they're re-reactored. many of these contracts for like old prisons they turned offline.

For example, I think Geo and Core Civic announced on October 1, which is the fiscal new year for some new beds. There's even an ICE detention center where they're doing over a hundred bucks a bed for these detention beds. And so they'll tell anyone who listens that they think they will win this contract. They're on a special purchasing vehicle for detention beds. But now we roll into the current problem, which is. one, ICE was completely out of money year to date.

They overspent their entire budget. And October 1, they could spend some of the budget, but they had to requisition this new asset. This is going to be a totally new contract. Well, the government's been shut down. So this is like a weird government shutdown play slash, you know, when the government unshutdown, in theory, they should be able to requisition with the $40 billion they have

just lying around saying that they're going to buy beds. and the management team is obvious, like chalked to the gills with incentives. Now, that fixes their big contract. Well, I mean, it's going to come in at a much lower rate, which is like bad for them. But that's a big, big, big hole at, let's just say, 100% utilization, because these guys will figure out. And I don't think they can sell all the beds, actually. Some of the beds will be support. Some of the beds will be primary.

But even, you know, we're talking, we're talking like, you know, 80 to 90. 80 to $100 billion of revenue a year at 50% EBIT on margins on a front rate basis. That's like 25% of their revenue today. And it would be a huge swing in their company. So that's the first leg. But I think the thing that gets me more excited, actually, is the data center opportunity.

So as you guys know, I'm all over the data center AI story. They're trying to add 80 gigawatts of power to Urquat. 80 gigawatts of power is like, you know, a lot, a lot, a lot, a lot of power. that is, you know, hundreds of data centers effectively. And these data centers take a lot of HVAC technicians, a lot of electricians, a lot of builders. And so when you're actually building, my estimate of this is on average, you need about 2,500 workers per gigawatt.

So, you know, and a lot of these in the middle of nowhere, that's average rate, not peak. Peak is a little higher. So let's just say 20 of them are in West Texas, which I think is reasonable based on the work I've done. And then you're doing an average. you're talking 50,000 workers need to be in West Texas building these freaking data centers. And a lot of them are in places that are so remote and rural that you can't, like, it's larger than the county population.

Shackleford's a good example. Yeah. When I was doing the work on this, because I remember doing the work, this was in last year, but this was when the data center stuff was really starting tramp. And I remember I was just like, hey, there's all these huge data centers that are getting announced, like right down the street, basically, from where these big things are. And at the time, we were worried about government contracts. So, like, could they switch it into housing for the data center?

And I was kind of like, eh, I don't know. But now it's like, it's so in demand. And you can go, you don't even meet satellite imagery. Go Google Maps, like one of their places and then a data center. And you're like, oh, my God, there's nothing. Like, people are going to be driving an hour and a half out here. Or a company can say, hey, TH will pay you guys, you know, a rounding error of a rounding error of one cluster of GPUs to house this entire workforce for, you know, know six months yeah that and that's the plan and i think uh to be clear they've already announced a

big contract um that first big contract for the sort uh they it's like their most recent a k it's uh and then the other thing too is the the average daily rate is twice the government so you're talking about like you know these are really really big numbers like let's say 50 000 people potential of average um they're not going to win at all but like if they're all $120 a day, you know, that's, you know, that's like $2 billion, $2.1 billion of annual data center housing in West Texas, not to mention the middle, like the rest of everything else. And so I think that there's just a huge opportunity there. And it's, you know, there's huge opportunity.

They have all the modular stuff. They have the historical footprint. They have a massive incentive to figure it out. And effectively, if they don't, they are, you know, this is the biggest bag they've ever fumbled in their entire lives. and so like that's yeah that's that's my pitch but i love stories like that like that's what i really like is where you have a clear opportunity a compensation that really aligns into the opportunity and a clear catalyst which makes a lot of sense like i feel like we have all the letters

in the alphabet except for x or something and you just need an x so if they can't figure it out then shame on them you know it's good all right well hey we got to hop it's been over an hour you're sick but you've thrown in MJ flu-like symptoms type performance here. Where can people find you just because you've got multiple hats on? Where would you like people to pop in? Yeah, so follow me on Twitter, Fab Knowledge. That's one way. I still write Fabricated knowledge when I remember to do it, but obviously semi-analysis.

As a song, that hurts, man. As a song, that hurts. Hey, hey, I have some good stuff. I actually have some good stuff in the pipeline, but of course I'm freaking sick of. But I think that the other thing I was going to say, you know, semi-analysis, really, you know, I'm very, very proud to be part of the team. It's a really cool company. We're building something really special.

I think we're going to be a singular research firm of a generation. And so that's really where I spend all my time at with... I mean, I'm just a dumb generalist, but you've built it out, right? Like, you are the go-to place for semiconductor analysis, new sources, analysis, all that sort of stuff in the space. And we want to, I mean, we want to scale to pretty much everywhere AI touches. So, you know, that could be anything. apparently so everywhere yeah it's uh it's like uh we're you know when software ate the world

you know that's that's the plan so we're i'm really proud of the stuff we've done already and what we're planning to do and yeah i don't know the team's pretty great so well thank you so much for coming on i'll give one quick plug one of the reasons duck came on is a he's a friend and i told him he had to but b he's doing a webinar with alpha sense who's sponsoring this podcast if you want to listen to the webinar here all of what doug has to say on the future of ai and semis follow the link you can sign up there. But Doug, this has been awesome. Thanks for enduring the flu and coming on and looking forward to chatting soon. Yeah. Nice seeing you, Andrew. We'll do this soon. A quick disclaimer. Nothing on this podcast should be considered investment advice.

Guests or the hosts may have positions in any of the stocks mentioned during this podcast. Please do your own work and consult a financial advisor. Thanks.