TFTC: A Bitcoin Podcast - #761: Miners Own The Power Gold Rush with Brandon Bailey

Episode Date: June 22, 2026

Marty sits down with Brandon Bailey to discuss the convergence of Bitcoin mining and AI compute infrastructure, why energized power portfolios are the most undervalued asset in tech, and how the race for data center capacity is creating a generational wealth opportunity. Brandon on X: https://x.com/bitcoinbeezy Dimetrics: https://www.dimetrics.ai/thesis STACK SATS hat: https://tftcmerch.io/ Our newsletter: https://www.tftc.io/bitcoin-brief/ TFTC Elite (Ad-free & Discord): https://www.tftc.io/#/portal/signup/ Discord: https://discord.gg/yHGkvYxdqT Opportunity Cost Extension: https://www.opportunitycost.app/ Shoutout to our sponsors: Bitkey https://bitkey.world/ Aven https://www.aven.com/bitcoin CrowdHealth https://www.joincrowdhealth.com/tftc Unchained https://unchained.com/tftc/ Lygos https://lygos.finance/ Salt of the Earth: https://drinksote.com/tftc Join the TFTC Movement: Main YT Channel https://www.youtube.com/c/TFTC21/videos Clips YT Channel https://www.youtube.com/channel/UCUQcW3jxfQfEUS8kqR5pJtQ Website https://tftc.io/ Newsletter tftc.io/bitcoin-brief/ Twitter https://twitter.com/tftc21 Instagram https://www.instagram.com/tftc.io/ Nostr https://primal.net/tftc Follow Marty Bent: Twitter https://twitter.com/martybent Nostr https://primal.net/martybent Newsletter https://tftc.io/martys-bent/ Podcast https://www.tftc.io/tag/podcasts/

you've had a dynamic where money's become freer than free if you talk about a fed just gone nuts all all the central banks going nuts so it's all acting like safe haven i believe that in a world where central bankers are tripping over themselves to devalue their currency bitcoin wins in the world of fiat currencies bitcoin is the victor i mean that's part of the bull case for Bitcoin. If you're not paying attention, you probably should be. Brandon Bailey, welcome to the show, sir. Thanks for having me. Excited to be here. Excited to have you, dude. I mean, we've been, I mean, I've known you for what, probably like seven or eight years now at this point in the Bitcoin mining space. And I mean,

you've done an incredible job of of knowing what's happening inside and out starting a galaxy um moving on to nakamoto you just launched diametrics.ai to help people grasp what's going on with the bitcoin mining and ai compute themes sort of colliding with each other and i'm incredibly excited for this conversation because i think despite what uh many bitcoiners uh we'll get butthurt about is that ai is taking the wind out of the sails of bitcoin i'm incredibly excited about what's happening in ai and i actually think it's going to be massively beneficial for bitcoin overall and so having you here to help get a lay of the land of what's happening on the compute build outside i think is uh gonna be incredibly valuable absolutely i'm really excited

to dig into the conversation there's a lot to talk about well what uh a lot to talk about where do What do you think the best place to start is like the history of this emergence of AI compute? I think maybe starting there, like the the intersection of Bitcoin and energy infrastructure that really exploded in 2021 with the Bitcoin miners were able to do successfully in terms of locking down power and really ingraining themselves in energy systems. and then the appearance of AI compute really, I don't want to say throwing a wrench, but really accelerating things on that front as well. Yeah, let's jump into it because that history there, especially in the 2021, kind of 2022-ish era, is ultimately what led a lot of these Bitcoin mining companies to kind of stumble onto this sort of gold mine of the power portfolios that they ultimately amassed.

And so it was really around 2021, shortly after we had the China mining ban, which resulted in as much as 30% of network hash rate kind of coming offline and sort of this redonestillation, hopefully that's a word, of Bitcoin mining hash rate relocating to the US. So Bitcoin mining was largely dominated by China. That's where a lot of the network activity occurred.

After the China mining ban, we saw this sort of gold rush of reestablishing Bitcoin mining hash rate and compute in North America, which led to some of the first publicly traded Bitcoin mining companies. So that's where you had companies like Marathon and Riot and CleanSpark really start to emerge in that time frame. And so we were kind of seeing the institutionalization of Bitcoin mining during that era, which led to a lot of these companies acquiring massive amounts of power so that they could ultimately, you know, have a pipeline to build out these, you know, 100, 200 megawatt data centers that were all going to be allocated towards Bitcoin mining. which made a lot of sense at the time you know bitcoin ran from i want to say the lows like coming off the lows of last cycle i think bitcoin touched maybe around 4k like in the bear market post 2017 and then you know from that point ran up to the highs of 60k so the margins on bitcoin mining were just i mean incredible um during that that 2021 bull cycle um so all of the investment that was pouring in from these public companies acquiring that land and power made a lot of sense

given the economics at the time. And so that's what ultimately allowed these companies to be sitting on effectively gigawatts of power. And then as we've now seen AI really blow up, all kind of starting with the advances that were made with ChatGPT and et cetera, you've seen like um obviously an explosion and just demand for ai and you know we're kind of going through this massive capex bull cycle all of these bitcoin miners were super well positioned because they already had all of this energized power that is one of the biggest bottlenecks right now when it comes to just trying to stand up more compute yeah and i think it's uh it's been funny watching it all play out because you're seeing the i mean going back to the 2021

era having been involved in bitcoin mining back then and still to this day like the mad dash like the lessons that you had to learn to to acquire power were were pretty massive it was a steep learning curve and it's it's interesting watching the the ai world get into this obviously out of necessity and the amount of power that's needed is almost incomprehensible um and it's bringing a different caliber of of capital to it right because you have these hyperscalers you have fortune 100 companies really leaning into this putting tens of billions of dollars of capex trillions of dollars estimated um the next couple of years and it's it's interesting to see how they're entering this market and really trying to i don't want to say bully but just

like brute force their way in and really coming to uh understand the the limits of the energy infrastructure that exists in america that bitcoin miners have become very intimate with uh over the over the last 10 years or more specifically the last seven years and uh i actually think it's good overall because it's making the public aware that like hey energy systems are important and absolutely barrel into this ai future we really need to figure this out first this is like layer zero of what we're building here totally i i also would add to that as well like i think um it also kind of is touching on the fact that i think that there's a lot more education that's required right now when it comes to understanding like energy policy

how the grids work right um you know the the need for more generation which has been a talking point for a long, long time. And I think that there's a lot of FUD right now, which is really just a result of, I think, miseducation when it comes to the amount of power demand that is out there to ultimately serve this compute and what it ultimately means for local communities. I mean, we saw that with Bitcoin mining.

It's kind of interesting because it's like history repeats or history rhymes to a certain degree. So a lot of the criticisms we saw of Bitcoin miners entering certain communities with respect to the power demands you're seeing a lot of those same kind of arguments being made with respect to these ai data centers um and so you know i just think like the the tensions and the challenges you're talking about with respect to just getting like you know your your actual site energized or getting an interconnection agreement um there those are really really difficult challenges that you can't just always brute force

your way through or just throw more money at the problem and solve it yeah so with that in mind let's let's walk through this what i think we can do sort of like order of operations of how this actually scales starting with bitcoin miners that that lock down land and power um over the last five years what are the decision frameworks that they're operating now as the ai companies come to them and say hey you have these power deals we have a need for power what are the sort of economic decisions that are being made by the miners right now what's what's the opportunity cost and how do you think they should be approaching um the the question of should i mine bitcoin or should i put gpus uh in a data center with the power that i own

Yeah, that's a great question. So I think it really starts first with sort of the easiest way when you're thinking about this decision, you're kind of walking through this calculus, is you can just look at market comps first and foremost. So one of the things that I've been looking at just as an investor in this space is that most Bitcoin mining companies maybe trade in a range between four to six times EBITDA effectively. And you have more traditional data center players like a digital realty trust or Equinix that trade closer to 20 to call it 24 times EBITDA. And so there's a massive discount that is being applied to the valuation multiple for using Bitcoin mining as an offtake, as an offtaker of that power capacity relative to more traditional data centers, right, as an offtaker of that power capacity. And so when you look at that relative ARB there, there's a huge potential for these miners to just be re-rated by changing, you know, effectively the off-taker of that power or, you know, moving to AI versus Bitcoin mining, just purely from a multiple expansion standpoint. And one of the reasons why there's such a large variance between the multiples for those businesses is because with the data center space, and when you look at the economic terms of these agreements, you're getting a 10 to 15 year lease effectively that's guaranteed cash flow. If you look at historically the income stream of Bitcoin mining, it's very volatile. You have things like the halving, which are going to cut your economics in half.

And then you also have the fluctuations of Bitcoin price dynamics. And so you have periods of really, really impressive gross margins in mining. But you also have these longer lulls of more challenging economics. And then, you know, you also have more challenges with respect to the economic useful life of the ASICs. And so it really just boils down to the fact that you've got 10 to 15 years of locked in, pretty much guaranteed cash flow. Your tenant effectively in these leases are the most profitable, largest companies in the world. You've got a Google or you've got an Amazon, you've got a Microsoft effectively as your tenant. um you know these companies generate billions of dollars of cash flow a year so that lease is

essentially viewed as as being as good as gold or you know if you have a parent guarantee from one of those companies that lease is pretty much as good as gold and then the other big thing there as well is like you actually can get financing to actually do the build out one of the the challenges we had in the mining industry was you know how do you actually establish a credit market to ultimately support that industry. So you had a lot of these companies had to rely solely on equity dilution to ultimately be able to fund the build out.

And then you get into these massive questions of returns on capital. Are we actually creating value here given what's happening with the economics and the dilution that investors are taking on? With these data centers, it's the opposite. You're seeing companies able to finance the bulk of the CapEx cost

and to be able to do that at an incredibly favorable interest rate. So that's a lot of what these companies are looking at. And when you compare those two, it's, you know, it's almost like a no-brainer, you know, especially if you can land one of those hyperscaler tenants, it's, you know, you would do that deal all day. In your mind, who's done this the best so far, the transition from Bitcoin mining to HPC? um you know there's i think i think um i think for all of the ones that have signed leases i

think that they've done a really really excellent job so you know those companies are core scientific uh huday cypher galaxy terawolf and applied digital um i think you really have to come in core scientific because they're they're honestly they're kind of the pioneer in this they were the first ones to really make this pivot. They started the wave for these Bitcoin mining companies and helped to enlighten the market on the potential of this transition. And I think they have 590 megawatts of CRIT IT capacity, all leased with CoreWeave. And they've already begun delivering that capacity. So I think they've done a great job to date. I think Cypher has done very well, TerraWolf, you know, Hut8 as well,

Ash over there. I think all of these companies are going an excellent job kind of, you know, carrying the flag and helping to pave the way for other Bitcoin mining companies to demonstrate this ability. Right now, because the way that I would also characterize this is there's a couple different phases as we go through this transition, right? The first phase is

can you actually sign a lease, which is very challenging. The process of ultimately courting one of these hyperscalers or large neoclouds is a very tedious, arduous process. It's very difficult just because of the level of demands and expectations that they have. And if you haven't already delivered one of these data centers before, they're going to spend an incredible amount of time diligencing you right they've got to feel comfortable that you can actually deliver so phase one is really can you get the lease signed can you get to a definitive agreement then phase two is can you actually execute on delivering this project on time and that's kind

of where we're at with a lot of these companies course uh core scientific is the first to actually deliver um you know a couple energized buildings and a lot of the other companies are coming up on that that's really the other big risk vector which is can you actually deliver the the construction um and then after that it's really just maintaining and operating the data center um but the upside from an investor standpoint is really on phase one can this company actually sign a lease and then two can they actually deliver it um on time and like to me that's where i think that that's the the biggest window of an opportunity for investors that are looking at these companies um you know for their potential to ultimately transition that compute or that

power capacity and for phase two correct me if i'm wrong but it's a bit different than bitcoin mining where a lot of the bitcoin miners when they would lock down power and say okay i'm going to build a 200 megawatt facility a lot of them would i mean do a lot of home-baked solutions to to actually manifest that bitcoin mining operation but from what i understand with the the ai compute is that a lot of these providers already sort of have out-of-the-box solutions or maybe like design specs that they'll just hand over and say hey here's how we operate build this and it's not really um you're not really dependent on sort of getting creative and coming up with your own solution i feel like everybody in bitcoin mining in the 2021 to today was sort of learning on the

fly of like how to actually build a data center but i think to your point about the demands and the diligence that is necessary to get these these uh hyperscalers comfortable with with partnering with you it comes down so that can you actually build to spec what what we need and here's here's the design that's absolutely right it's it's really a whole different kind a philosophy and approach. Bitcoin mining is, it's like, how can we stand up this infrastructure the fastest and in the most cost effective way possible? Which in Bitcoin mining, you could actually be rewarded in a sense for cutting corners or finding ways to like, how do I just get this infrastructure stood up in a cheap way so that you can maximize that payback period?

And you wanted to do that in Bitcoin mining because you have difficulty, right? It's a race against the clock. You know more power capacity is going to be coming online or more hash rate is going to be coming online, and that's going to impact your margins. So the faster you could get your machines online and energized, that was only going to help you. With high-performance computing and these data centers, it's completely opposite, right? It is much more about can you build to the spec? Can we make sure that we have all the redundant systems because uptime is vital here, right? And so it's just a very different approach and sort of design philosophy.

And these data centers are much more complex than Bitcoin mining data centers and have significantly more redundant systems, the cooling systems, the intricacies of all of those components it's just a whole different sort of ball game when you're kind of comparing those two worlds yeah and what are your thoughts on the scale uh of the demand for compute the individual sites and the spectrum of scale that may may emerge because i think obviously you hear the headlines colossus 2 going to be a gigawatt colossus 1 was what 300 megawatts you have many yep paper scalers going out there and saying we're going to go build a gigawatt multi-gigawatt facility and i think we're beginning to see as the sort of supply gets tapped on these large

scale operations people beginning to look at smaller scale like 20 to 50 megawatt and trying figure out like are these viable for um for for ai compute data centers and that's i think a part of the market that many people are trying to explore and what are your thoughts on that spectrum of scale i think um the demands for power capacity and compute are enormous and i think that you're going to see, you know, sort of all, all parts of the spectrum be in demand. To your point, the early innings of this, it was all about the mega sites, the one gigawatt site, you know, hundreds of megawatts of scale. And, you know, what's, you know, what's really fascinating about this is like, you kind of have to really think about the undercurrent and what's driving it.

And it's really, to me, the way that I would describe it, it's the game theory that's at play here, right? And you kind of have this game theory playing out on two different levels. There's the game theory of, you know, nation states understand that AI is this massive revolutionary technology and that we need to be a front leader or, you know, we need to be the leader in this new technology, right? And so the U.S. is largely in an arms race with China on trying to be the world leader in AI technology, right? Which means that the U.S. needs to foster inside of its borders an environment that can allow this industry to flourish and ultimately make sure that it has the resources, make sure that the entrepreneurs inside of our borders have the resources and the access to, you know, the raw inputs such that they can go build and

create this to try to win that, right? So you kind of have this, you know, that game theory playing out the US versus China in this race. And then you also have the hyperscalers themselves competing with one another, right? Because these businesses had been, you know, more sleepy, less growth focused, just printing cash. The cloud business is just crushing at the margins of a Google Cloud, Azure, AWS, just crushing it. And those are massive cash cow businesses for those companies. But with AI, there's a massive risk now to some of the moat that they've established. And so you're even seeing these companies competing with one another. So you have Nvidia competing with Google, Google, Amazon, Meta, they all recognize that this is a massive

opportunity for them to sort of grab market share and also protect the moats that they've already established. So each of them are incentivized to spend a tremendous amount of money on CapEx, right, to make sure that they can protect their moat and also try to gain market share. And so those two dynamics to me are what are really driving the enormous demand for compute. And of course, you have SpaceX now as well. But all of those companies are competing. And what they can't afford to have is to say, we didn't invest enough money. And we allowed Google to have more access to data centers, which gives them just an unfair advantage, right, because they didn't invest enough CapEx. So to me, that's what's driving a lot of the undercurrent of the demand for power. So that's one component. And that's where we saw the demand for these one gigawatt sites, etc.

But now that you're seeing a lot more pushback, the new trend has been the social climate and the political climate around data center development. You're seeing a lot more pushback in communities around wanting these massive scale projects. And we've even seen some projects more recently be canceled or paused because of just the pushback in local communities. So that's where I think that there's more of an opportunity for these smaller scale sites where it's like maybe we don't go one gigawatt. Let's go 50 megawatts. Let's go 20 megawatts. Right. It's a little bit easier to get through. and get approved. So that's where I think you're starting to see more demand

or increasing demand for those sites. I think inference training is also driving demand for those smaller sites. So I think that there's a massive opportunity on that front right now for some of the smaller players. And I think that you're just going to see more overall demand across the spectrum, but I think it's going to be easier for people

to get things stood up in the smaller sites. And then the last thing I'll say is that I think that because of the level of difficulty with respect to just getting power energized, I think that you're also going to see the data center world take some lessons learned from the Bitcoin mining space with respect to these modular data centers, chicken coop style data centers, and using those as a way to just to try to get compute stood up more quickly um so you know there's a lot of interesting um early trends that we're seeing um across this space but um you know i ultimately think that you're going to see the demand across the boards so freaks this work was brought to you by good

friends at bitkey guys things happen things get lost you need to replace your phone life happens and bitkey has been designed with this in mind uh so if you're looking for the easiest way to secure your Bitcoin off the exchange. Go get a BitKey. It doesn't come with any seed phrases. There's no single point of failure. It's a two or three multi-sig. You have your device, you have the mobile app and block stores, a key in the server. So you have collaborative multi-sig there. On top of that, the new BitKey has a screen. So you can actually see and verify what you're approving. You can look at transactions, addresses, account changes. The difference between trusting and knowing has been built into the new BitKey with the screen. They've

change code delegation and other advanced features like inheritance, recovery. If you're looking to get your Bitcoin off exchange, you haven't done so, you're looking for the easiest way to do that, go get a BitKey. You can use our code today, TFTC, to get 10% off the new BitKey. So go download the BitKey app, use the code TFTC to get 10% off the new BitKey and start your self-custody journey today. This episode has been sponsored by our good friends at BitKey. Sup freaks, this rep was brought to you by good friends at ligos finance celsius block fi ftx they took your bitcoin and gambled it away ligos can't because they never hold it non-custodial lending on bitcoin's base layer your keys your collateral it's verifiable on chain go to ligos.finance tell them that tftc

sent you that's your point about the the hyperscalers the googles of the world it's funny how quickly not funny but just interesting to observe how quickly they went from like using their cash flows to buy back stock to the capex expenditure to the point where google what did they do 84 and a half billion in an equity raise that the berkshire hathaway and others participated in so literally issuing stock to to invest in in this capex build out and they're in full growth mode and and that's and i think that's a big question on everybody's mind is this a bubble and i i know i had my thoughts which i don't think it is like i think there could be bubbly aspects of some parts of the market but when you look at the demand for tokens today as it stands

with the agentic economy being what five six months old in earnest and then you think of robotics coming down the line and you think of the demand for tokens that that exists today and you just project forward as adoption continues to increase at the individual and enterprise level and then you get into robotics and i think i don't even think we've seen um the the tip of the iceberg in terms of how many tokens we're going to need to to effectuate this this agentic and ai driven economy i i totally agree with you um i'm my line of thinking is is pretty much align with you, which is like, it's not exactly the same as 1999. I mean, you're already seeing the demand, right? From like a usage perspective, you're already seeing the revenue, you're already

seeing like the demand side of the equation from a profitability standpoint, just looking at, you know, Anthropix revenues, if you look at like Google's revenues, even for like Gemini, like you're seeing the signs when these companies announced their earnings that the profitability element of this is real. And then I also agree with you that there are several different waves of this. Right now, there are more people that are not using AI than are using AI. We're still very, very early in getting people to just be using LLMs in some form or fashion on a daily basis, right? So I still think the adoption curve of using this technology is still very early. It's early from an enterprise level. It's early from just an everyday consumer

perspective. So I still think we have a lot more runway from that perspective. And then exactly like you said, you also have sort of the next phase, which is like, once we've built the intelligence layer, right? Now, how do we start putting that intelligence into things like robots And the demand for that is also going to be pretty, pretty insane. And, you know, when you think about that, too, it's like we're going to need a lot more memory. We're going to need a lot more CPUs, GPUs. Like there are so many elements of this overall AI trade that are going to have, you know, tailwinds behind it from my perspective for many, many years to come. Yeah.

And I guess that's the question. I mean, maybe I think obviously one of the big beans the last couple of months is your token usage has been subsidized by Anthropic in OpenAI, and they're going to need to really push the cost that they're bearing onto the end user, which is beginning to happen. um you have companies like uber saying we blew through our budget um in the first quarter first quarter and a half of this year first four months of this year and i think that's one thing i'm still trying to wrap my mind around it's like okay what is the actual cost of a token particularly from a frontier model versus an open source open weights model and how does that how does that affect the the demand for power and along like the point i'm trying to like this token usage gets so efficient and so cheap that the return on the capital invested in the the infrastructure um compresses over time or is the demand for tokens even if they are becoming more efficient

and cheaper just going to be so massive that it doesn't really matter like how are you thinking of that that calculus yeah i mean i'm also trying to wrap my head around like that efficiency dynamic with respect to um tokens per watt or or however you want to sort of characterize that efficiency metrics uh efficiency metric i think it kind of circles back to i believe it's javon's paradox that that people talk about which is like you know the cheaper something gets, the more you'll want to consume it. I feel with my own personal just usage of LLMs, like that's kind of where I'm at. I'm like, the more tokens you're willing to give me, the more tokens that I'm going to consume, or, you know, I'm going to look at it as like, okay, well,

I might have been restricted from doing these other things I want to do because I've hit my usage limit. If you give me more tokens now, there's more things that I can do. So I think that um you know as things get more efficient you will also have probably step changes in the overall consumption and demand that probably offset a lot of the efficiency gain and and continue to um keep the overall demand level or the the need um from a power um sort of perspective you know elevated or there right and you still have like i said you still have sort of that undercurrent of you know the game theory of you know i'm you know meta is competing with microsoft is competing with google is competing with amazon and they're all going to want to make sure that

they have enough runway such that they can protect their moat protect their margins um and then there's going to be all kinds of other things that i think that we haven't imagined as well that are just going to allow for you know more consumption more demand for using the tokens for other use cases um other applications so you know that's kind of where my current thinking is you know on it as we think about that but it's going to be very fascinating to kind of track that trend over time yeah and bring this back to energy infrastructure i mean it seems like i feel like in the next year all the nooks and crannies of available power on the grid that's willing to So that's either available to be acquired by companies looking to train or run inference on these models

or that is willing to transition from a use case that is not AI compute. We're going to hit that limit of where we've sucked all the energy, all the available capacity out of the grid and now we need to expand generation. How do you how do you view the generation expansion playing out? I think that that's going to be another big wave, which is like the, you know, bring your own power behind the meter power at a lot of these campuses. So, you know, I think to your point, the generation piece is going to be interesting to see how we ultimately solve that. You know, obviously, there are plans for like nuclear projects and things like that to try to bring more base load. But one of the big challenges we're already observing with some of that is the timing mismatch, right?

Like how long does it take to actually build out or stand up, you know, at least for a nuclear plant, it could take five years or longer. The demand is here. We can't wait for that. We need this demand now. But I think like the next phase of it is like, how do you bring more like gas peaker plants or other things online or whether it's solar or what have you, all different forms of generation to these data centers. And you're seeing some early elements of that. But I think that that's going to be the next sort of wave, just because I think the grid interconnection piece is going to become more challenged. challenged and then i also think if you are able to tell the narrative of having brought your own

power um to a community then you're not necessarily taking anything that you can make this point that you're not taking anything away from the local community so i just think that that's also just going to be viewed more favorably from um you know a social and political perspective um but that's also a way that you can increase the amount of capacity at where you you already have some of these existing campuses. So I fully, fully expect that to be another big wave. And we're already seeing companies kind of hint at this piece. I've seen Tyler Page on various talks really talk about the behind the meter power opportunity at many of their existing campuses. Core Scientific and Adam Sullivan have also talked about that. From an investor standpoint, I actually find that

Like that's an element that I don't really think is getting enough attention, which is what is the incremental power capacity potential from, you know, bringing additional or, you know, behind the meter power solutions to an existing site to expand the potential leasable capacity at, you know, an existing company's, you know, you know, sites or campuses. yeah it's so fascinating how big is this opportunity like what is what is happening right now like in terms of just like broad implement implications on on humanity and markets specifically again going back to everybody drawing parallels to the dot-com bubble i don't think the parallels are as as clear as many people think they are i think they're actually completely different and then there's a lot of doomers out there who are like it's a bubble going to pop it's going to pop look at spacex yeah it may be overvalued right now but again you look at what mid journey launched last night with that that mri competitor where you can do

scanning image scanning of bodies in a minute and it's like this technology is valuable if it works as advertised you could replace every mri um in the country in the world in the next few years and have a better product that that saves millions of lives uh and so there's a there there i use that's another thing we can get to eventually is like we're talking about the infrastructure build up but on the application usage like i know you up you have built a product using this and um we'll talk about diametrics but i think just first trying to um paint the picture of what's happening here from an economic disruption standpoint and the opportunity of wealth creation that exists?

It's remarkable. I think it's a generational wealth creation opportunity for people. I think it's already largely been that. If you just sort of look at how some of the various names across the the broader ai sort of bottleneck thesis or bottleneck trade have performed so i'm talking about you know look at nvidia over the past few years micron sandisk uh amd intel right like you know the the returns on some of these names i mean you're you're talking you're up three to ten x you know across a lot of these that you could have almost just picked any sort

of semiconductor stock and had, you know, generational return type of performance on some of these names. And so, you know, from an individual investor standpoint, or, you know, even if you're an institutional investor, you know, it's been incredible market performance just on the back of what's happening here with respect to the amount of CapEx that's being poured into the space. But then when you talk about, you know, so what does this mean for like everyday, you know, people's everyday lives? I mean, it's incredible. And it's still hard to almost fathom or imagine some of the possibilities. I mean, we'll talk about it. But like DI metrics is for me personally, one of those things. I've always wanted to build an application of some sort. I have no coding experience knowledge whatsoever. But leveraging these tools, I was able to actually take something, an idea of mine and actually turn it into some kind of tangible product that other people could use or some other sort of application.

So when I think of the power of this technology, it's a massive force multiplier for people, right? Just the extension of the amount of additional knowledge that it can help provide an individual, right? You can basically learn anything now, you know, and get that information instantly. Like prior to the LLMs, right, you could always go to Google and do a search. But that wasn't always effective. You can basically learn about any industry, any incredibly complex topic or subject and get an incredibly accurate or reasonable response. You could have it provide you direct sources to like, you know, peer reviewed papers, what

have you, and even have the system explain it to you, like give you an ELL5, right? Which is remarkable. So I think the tool really empowers people to learn about whatever they want, which is massive. I just think that that's massive for people. And it's really hard to quantify, if you want to put this into a GDP perspective, what does that actually mean for productivity? It's hard to actually quantify that at this moment in time.

but you know that it actually has massive implications for society just in terms of leveling the playing field, right? Intelligence is now a commodity. You can't say enough about the importance of that ultimately for the world and for civilization. All right, freaks. You know me. You know I don't take sponsor money from products I wouldn't use myself. So listen up. The Avon Bitcoin Visa card is one of the most interesting things I've seen in the bitcoin lending space in a long time here's the deal you get a line of credit up to a million dollars backed by your bitcoin without selling a single sat no gains no annual fees no minimum draws and your bitcoin is custodied by bitco which is one of the most trusted names in digital asset

security even never lends it out there's no re-hypothecation you stay in control and guess what you can lock in a fixed rate for up to 10 years that's 10 times longer than most lenders out there or go interest only for up to five years. Rates start at 7.99% APR for a product that lets you keep your stack and still access liquidity. It's hard to beat. I mean, the duration in the rates is the best I've seen in the market to date. You also get 2% unlimited cash back every time you use the card, spend fiat, keep your Bitcoin, the whole game. If you've been stacking for years and need liquidity without triggering the taxable event, this is worth a serious look. go to aven.com bitcoin that's a-v-e-n dot com slash bitcoin check it out freaks look at me i'm

glowing i've got like an angel's halo going around me you know why that is is i feel good i feel taken care of i feel blessed healthy happy and that is because i'm a crowd health member my family and i have been crowd health members for five years now literally this month five years ago we joined crowd health we've had two babies we've had multiple health events and we're never going back to health insurance crowd health is crowdfunded healthcare so you you sign up for crowd health you pay a monthly fee you help out with other people's bills uh and it's significantly cheaper than health insurance we were on cobra it's a family of three when i when i left my last job before i went full-time with cftc went on the crowd health now as a family of five we pay

uh i believe 700 a month it's significantly cheaper they're going to negotiate prices is lower for you. They've consistently negotiated healthcare prices as much as 50, 60, 80%. In many cases, they help out with babies. If you have a pregnancy, you pay the first $3,000 and the crowd covers the rest. If you have a regular health event, you pay $500 and the crowd pays the rest. Go to joincrowdhealth.com. Sign up today. Use the code TFTC. Opt out of health insurance. I'm uninsured, baby, and I love it. Use the code TFTC at joincrowdhealth.com. You'll get $99 a month for the first three months that you're on the crowd health platform in the community Bitcoiners you found sovereign money now find sovereign health and sovereign health care and so many people are

sleeping on it right now that's what I keep wondering uh what what does the the adoption curve look like or adoption timeline look like and is it the adoption just forced on people is it just looking at how some companies are implementing it and experiencing the same productivity gains others obviously implementing it i think that's maybe that's something we can talk about that's observing particularly the headlines you see out of uber like we're blowing through our token budget and the the trend of token maxing the ceo coming out like you're not spending tokens like you're you're not doing your job and i think one of the things that really stood out to me if somebody's been implementing this at our business here at tftc is like the

implementation details are very very important yes you can token yes you're token maxing um liberally without any intent or thought about what what the actual end goal or product will be which should be to like produce something that makes you more efficient and adds to your bottom line then you're you're just going to be blowing money and i think that's that's the phase we're in right now as people sort of trying to map the territory particularly on the implementation side to make sure they're actually getting value out of these LLMs. And I think that's a massive arbitrage right now that exists is those who understand what these things can do and how to implement them to do your job better. And those who are simply using them as like a new

Google search. I totally agree. I think that what you just laid out is sort of maybe the counterpoint to the, I kind of view it as a little bit of like the counterpoint to the narrative that AI is going to take all the jobs, which is like using LLMs is a skill. You have to learn how to maximize the output of the system. It's not something that you can just go to and say, I'm just going to give it a prompt and it's going to just do all the things. You actually have to work on your prompt engineering. It's one of those things where you just have to spend time understanding the system and how it works in order to get better at it. And I think that the people that invest that time

or token maxing, so to speak, you kind of almost have to go through a phase of token maxing so that you can learn how to use the system. What are the LLMs good at? What are they not good at? What additional context do I need to include in my prompt to make sure that I can one-shot this output? versus going through many iterations

and back and forth with the LLM. So it's a learned skill. And I think that that's where we're at because we're so early in this inning. People are still trying to figure out how to use the system, how to get the most value out of the system. But I think the people that are investing the time

to learn that right now are going to set themselves up in such a way that they're going to be some of the most valuable people for enterprises, right? Because companies are going to implement strict budgets, right? Everyone gets a certain amount of tokens. And then it becomes, right, that efficiency gain. How do I get the most output for, you know, the least amount of tokens possible that I can spend?

And like, that's going to be one of the, I think that's going to be the primary way that enterprises start evaluating individuals or employees, which is like, you know, how much output can you derive from leveraging this tool? And to your point about being forced to actually use it, if you're one of those people that are anti the technology or a laggard, you're just really setting yourself up to be at a tremendous disadvantage relative to potential, some of your other employees internally. And so it's kind of an interesting incentive mechanism where you're doing yourself a massive disservice if you choose to not use the tool. I mean, same with the internet age, right? Same with the internet age i think it's really no different um in this instance here what's your personal journey been like mapping the territory and getting used to these man it's been it's it's

like a roller coaster it started out as like wow this is amazing it can do all these things this changes everything to wow there's a you know like that that's how it started and then the more i used it i was like wow it's missing all of these it's missing things like i have to provide it additional context um you can't like i guess the way that i would describe it is like the llms aren't great at assuming like they're not great at seeing around corners i'll put it that way right like unless you give an lom like the context of i am trying to build this system We need to build a really strong foundation. These are all of the potential pitfalls I'm trying to avoid.

Here's why I'm trying to avoid it. Can you help me think of a way to craft the best possible system that can avoid these potential edge cases, right? If you don't give it that context, it'll just give you an answer without thinking ahead to where that thing could break down, which leads to a significant amount of iteration and back and forth and having to rebuild. And so that's where I think, to me, that's where it kind of comes back to that token maxing thing.

I had to go through a lot of that to get to a point where I understood what things do I need to provide this LLM to make sure that I don't have to spend a lot of time and a lot of tokens doing this back and forth. So for me, it's really been about how do I create the right processes effectively when I'm trying to build something to make sure that I'm setting myself up, you know, for success without burning a ton of tokens. And now that I've kind of learned how to do that a little bit better, I'm kind of like back on the upswing of like, you know, this is amazing. And you also kind of work through the evolution of the different models. So you kind of see the different step

changes as the models improve. And, you know, that just kind of reinforces everything. as well and the last point i'll i'll leave you with um which is like you know when you think about where we're at with the improvements to the models think about how much compute like opus 4.6 was trained on or like you know 5.5 was trained on and you think about how much more compute is now being energized right the bulk of what we've been talking about from a power capacity and utilization standpoint, like models aren't even training on the power capacity that we're talking about that's coming online. So when you really think about the future step changes of these models and what they're going to be capable of with all the new compute and power that's being

thrown at them, you know, you got to be really excited for what could become possible in the near future here yeah yeah it's it's insane and it's like the to your last point there it's like because the mom i mean i played with fable five before it got uh by the u.s government and it was like holy crap this thing is is really good to step up uh opus four six for for like the written word for like the like opus four six is the brain of our open call agentic system that we've built out here at tftc and it does very well like i can't imagine like what happens when when you have like two more step function improvements um at a at a similar cost to to what opus four six is today it's like uh it's mind-boggling to think of like okay how

much better is this going to get over the next year or two and then to your point about like that that learning curve too i think that's one thing that uh over the last two months is really going back to the context and and um making sure that you're prompting it the right way and i think having sort of persistent memory for context for your agent is is imperative and we've been in the process of building out our company brain for for the last two months and it is insane how just building knowledge graphs and semantic search functions within the server that our agent runs so that it can ping first before it burns tokens so it gets all the context from the knowledge graph and the semantic search system that we set up and it's just able to one-shot things in our

voice and it knows our business inside and out and i think once you understand the tooling that you plug into these llms that's that's when you really unlock the superpowers totally totally it's like the the llm wiki or like kaparthi's concept massive um that that's that's a huge one um the memory files i agree with you it's kind of like once you figure out that setup right it's like all the connectors the skills all of that stuff really unlock significantly more value for you and also allow you to reduce the amount of the token burn but like that's what you kind of have to go through the trial and error of like figuring out like how do you map out the system right it's like you kind of got to build your own system map for how you're gonna operate this

system and then once you've kind of perfected that you really start to see the fruits of that labor yeah wild times so let's talk about the iMetrics that he i mean he mentioned it this is was an idea in your head for many years and now with the tools you're you're able to build it and i've been playing around with it this week and if you're a nerd on the forefront of following what's happening on the infrastructure build out this this tool that you've built is incredibly powerful yeah so um the way that i would the simple one-liner i would give for it is it's it's really a tool for kind of the individual individual investor that you know is is interested in the digital infrastructure space. So market intelligence platform for, you know, digital infrastructure

specifically. And the whole concept and project, you know, it started as a spreadsheet, like, you know, from my days at Galaxy and working in Bitcoin mining, you know, I would track a lot of, you know, these companies' sites and all of this, all, you know, the financial information about, you know, how much hash rate they had, how much Bitcoin they mined, and all of this stuff, literally just via spreadsheet. And as these companies were making the transition, I was trying to do a similar thing where I'm just trying to track, map out where do they own sites, how much power capacity, they signed a lease, doing all the typical work that an analyst would do if you're looking to be an investor in this space or in these companies. And it was with the

LLMs where I was like, maybe I can automate this workflow, right? It takes an enormous amount of time to ultimately comb through SEC filings and to go through investor presentations and keep up with all of the information that is required for you to map this out. And with every new company going into this vertical, it becomes even harder for you to ultimately be able to track and follow everything that's happening in in the landscape so for me i was like i want to take what i'm doing in spreadsheets and see if i can automate that workflow into basically a dashboard effectively um that i could just use to to monitor and track what's happening in this space um without having to commit so much time to doing the manual labor and um you know

So what I ultimately started building out was the backend database to support this, started trying to leverage the LLM to ultimately learn how to read through the investor presentations, basically map out this whole thing. And where I see the real value proposition for this dashboard is when you think about other market intelligence tools like a FactSet, like a Bloomberg, there's KoiFan, there are other newer ones as well that do an excellent job. of what they provide you. But what it is, is more high level information, right? They're giving you, you know, the, you know, here's the line items directly from the balance sheet from the financial statement. Here's, you know, what the total debt number is.

Here's what the cash balance is. Here's what the revenue is. Here's what the CapEx is. What I wanted to build was something that went super granular and super deep into the individual components of specifically, the data center space. So I wanted to build a market intelligence tool that was going to tell you what is every site that a company like Cypher Mining owns. What is every site they own?

What's the gross power capacity of that site? What's the leaseable power capacity of the site? When is that power going to be available? What's the energization timeline? Where is it located? who's the utility provider, I wanted to go super, super deep into creating a tool that would give you the industry level granularity, right, as it relates to these companies. So if you're an investor in this, you don't have to still comb through, you know, all of those filings to pull out this information. And so that's what the DI metrics market intelligence platform ultimately tries to provide and then it it ultimately is is trying to give you that level of information through the npc connection and so it's like how do you take that level of information

and incorporate it into whatever agentic workflow or process that you already are familiar with working with and like that's what i think the real value add or like the the biggest sort of feature is of the platform is being able to connect a DI metrics database to your cloud or Codex or what have you, and then tell it or ask it like, give me every lease that Cypher has signed, right? What's the lease rate? And then ask it like, how does that compare to TerraWolf? Or rank all of these companies.

Show me the top 10 companies that have signed like the most profitable lease from a gross margin perspective. Right? So that type of analysis would have taken many, many hours for you to map out as an individual. Now it's just a simple prompt. And like, that's the value proposition. That was something that I was ultimately just trying to work through on my own as an investor, as somebody that actively trades a lot of these names, and ultimately wanted to provide that type of level of market intelligence to a broader group of people. So I wanted to do that. And then the The other big thing that I wanted to do is, again, when you think about the broader AI bottleneck trade, I think of groups like Centrini Research, Fund AI, Semi Analysis that all do amazing, incredible, excellent level of work and research as it's related to this trade.

But a lot of what they're mostly focused on is going super, super deep into the chip component, the semiconductors, the hardware, the computer, and they do a phenomenal job with the research that they do. But I feel like a lot of, I feel like the data center space and more specifically, these miners converting their capacity are somewhat undercovered. They're not as strongly represented relative to, you know, the semiconductors, the microns of the world. And so that's something that I wanted to try to bring a little bit more light or shed a little bit more light on is the highlighting the opportunity that these companies present as a bucket within the broader AI bottleneck trade. And with the terminal element of DI metrics, I try to do exactly that, which is show you the performance of these Bitcoin miners relative to the semiconductors, relative to the AMDs, the hyperscalers, etc. And these companies have actually provided almost not quite as good of a return as the memory companies, but actually better than a lot of the other components like storage, etc. um and i feel like that is not talked about enough and i still think that there is an incredible re-rating opportunity for many of these names and so i really wanted to just try to bring

more attention to that as well as highlight exactly what is that opportunity and how do you think about it how should you think about this yeah i love it and it highlights like on application side like somebody like you an incredible analyst who's been analyzing the the infrastructure build out of bitcoin mining and now hpc compute or ai compute as well i keep making that mistake because bitcoin mining is technically hpc as well um but uh the ai compute like and you have this experience in this depth of knowledge that very few people have and you're able to leverage the tools to build a tool that other analysts can tap into and you can get paid for it and it's like that's like you have your knowledge graph of di metrics that only somebody

with your experience knows how to map the territory of this particular layer of the infrastructure build out uh the sub theme within the ai build out and you can leverage the tools to build a tool that others can leverage to incorporate there's definitely like you mentioned semi-analysis focused on chips like they can then expand their their depth of knowledge um and the ai build out into the infrastructure layer as well and uh on your point of re-rating like again bringing back like the fears of the bubbles like where would you say we are um in the the process of rewriting these companies that are earnestly making this transition are are going to execute and those who are execute, excuse me, those who are in the process and if

they do execute, like what do the re-ratings look like from here? Great question. So I kind of break it down into two separate buckets in terms of how I'm looking at these companies. There's the companies, the Bitcoin miners, if you will, that have signed leases and those that have not signed leases. And so the way that the re-rating process works, there's two big phases. The first phase is, can you sign an initial lease? We touched on this. That's the biggest re-rating upside you see. So once a company has signed its first lease, that's where you see the largest pop in a lot of these companies. That's been true for Cypher, Hut, Terrowolf. That's why some of these companies are up as much as five to seven X, right?

From the point that they had no lease to sign to signing that first lease and where they are today. And a lot of it has to do with the fact that in the early days, because it's changed a little bit, but just to give the context, the big opportunity was the fact that these companies were highly correlated with Bitcoin. And so if you look at Bitcoin's price performance,

more recently, let's say over the last 12 months, 12 to 18 months, you know, Bitcoin kind of hit a high and then it started to sell off. Many of these miners sold off with Bitcoin, despite the fact that they had announced that they were looking to pivot to HPC AI. And so the value of their power portfolio, the value of their megawatts was declining because Bitcoin was declining. And you basically had the market not believe that they had any real potential of converting to AI compute, which created a massive opportunity, right, from a value perspective. So then once you had Core Scientific sign its first lease, you saw this massive re-rating because the market was basically assigning like a 1% very low probability to that ever happening.

And so once you saw that first lease get signed, you saw a huge step up in the probability, which caused an enormous sort of re-rating or revaluation of the megawatts of those companies. So that was sort of the earlier opportunity that has resulted in a pretty tremendous upside. But then even after a company has signed a lease, there's still a pretty large discount that gets applied to even names like a Cypher, a HUD-8, a Core Scientific. And that second component is the market assigning a probability of them being able to finance the build out of the compute, and then them also being able to actually deliver on delivering the building. So the construction risk, right? And so once they raise the capital, which many of the companies have been able to do more recently, that de-risks the project. And so there's a little bit of a re-rating on signing a very attractive debt financing. And then there's a re-rating, again, once the company delivers a successful shell on time.

That construction risk effectively goes to zero. And so the easiest way to look at it, from my perspective, is if you look at digital realty trusts or these traditional data center players, that's your new benchmark. and these are effectively real estate plays and the way that you evaluate real estate is you can look at things through the lens of a cap rate so you could say a stabilized cap rate is roughly six percent right a DLR and Equidex they're being valued at a five and a half to a six percent cap rate these miners at any given time could be valued at a nine cap right like Cypher could be valued at an eight and a half cap or a nine cap right and the delta between where a Cypher

trading and like a digital realty trust that's all the market's discount on the probability of that that's the execution discount effectively that should ultimately trend closer to parity once a company has delivered right a powered shell once they've delivered on a lease and so what's really fascinating is that you can track that relative spread of the cap rate daily just just looking at the market performance and how these things are trading and so like that is a potential market signal so like that's one of the things that i look at and you could say hey um you know these miners have sold off exponentially we saw a lot of this with like um the volatility in the market just with like the iran war and you know the back and forth with trump's tweets

and every single time you see sort of a blowout in that spread incredible buying opportunity so that's been one of the ways that you could trade it. And now you're also seeing an emerging opportunity with the smaller names. We talked about this. So that's the smaller Bitcoin miners that maybe have 50 megawatts of power capacity. They're kind of been an afterthought. There's still a massive re-rating opportunity for them through the same type of cycle and phase, right? And so that's really what I'm trying to triangulate on and highlight as the opportunity, right and kind of talk through that sort of overall um you know revaluation process or timeline um but i'll pause there i know it's kind of a lot um if there's anything you want to dig

into i'm happy to more but that's kind of how i see the opportunity yeah well i mean it's a big land grab right now i guess that's like the next question i have is like how much leverage do these miners who have power and land have in these negotiations and like how much of this is a lot of ticket versus um versus like yes you may have the land of power but you you've got to execute on the back end and like bringing back the fact that a lot of these these ai compute the people that are looking for infrastructure for their compute come with a spec and design like what it like is the execution risk significantly high or is it like hey you have land and power you have the leverage it's like how hard is it to figure out how to get this

thing get a lease get the financing get it stood up and energized the execution risk is is significant and like that's why you kind of have to you have to bisect the field a little bit right so you know if you're talking about a hud 8 or core scientific at this point because they've already done it they've kind of proven it out, any incremental lease is going to be less risky than the prior one, right? So there's a compounding effect to this, right? Of course, for the smaller miners, yeah, the execution risk is even higher, just because they have less financial resources, maybe they have smaller teams, right? But that's sort of your risk reward upside. But But where it becomes really interesting is that the value of power that is already energized effectively or the power can already be drawn is so valuable right now because of the demand and the constraints and all of the other growing challenges that those companies could pursue a JV style structure.

or other structures where they could potentially contribute that land and power at a significant markup to where it's currently being valued. So I mean, you have some of these smaller miners where their power portfolios are only valued at $200,000 a megawatt to $400,000 a megawatt. They might be able to contribute that land and power into a JV at a value that's a million dollars or more a megawatt right and then lean on the balance sheet and financial strength of a jv partner to help de-risk the execution component right and then you know earn earn um you know cash flow um at you know whatever their pro rata share is through the jv but even a structure like that is incredibly accretive for these smaller miners just given the the literal markup that

they can ascribe to the immediately available power that they have. And that's what people aren't seeing. And it's a little bit of a snowball effect. Like I'm saying, once you get that first deal done, and you've proven that you can execute, it becomes a lot easier for you to get that second deal done. And you might not have to give up as much of the economics in order to get it done. So, you know, that just gives you a significant sort of tailwind and runway for what these companies could ultimately become. And it's really a lot of these smaller names that have not been covered, right? That's like, you know, it's a Sphere 3D, it's a Greenwich, it's what was formerly Mawson, but a big digital energy. That's a DigiPowerX, that's a DMG Solutions, that's a Saluna, and there's many, many others, right?

The subset of these companies is much larger than just TerraWolf, CoreScientific, Cypher, HUD-8, Wolf. And that's what I want to shed light on. There's a large opportunity here, and you can kind of pick and choose your spots across the risk spectrum. But the overall re-rating opportunity, just in terms of how the power capacity is being valued to where you see a stabilized project being valued is tremendous, tremendous upside. And I guess to wrap it up, just thinking about not only the opportunities that exist for these individual companies, but I think for the localities too. Wrapping up with, obviously, ERCOT's leaned into this heavily with Bitcoin mining and now AI compute. And there are some laggards across the country, some nimbyism going on. And I think to your point earlier about the narrative and the misconceptions around what's actually happening.

What's going to happen to the counties or states that say, we don't want this here? and what opportunity are they foregoing if they neglect to embrace this build-out? I think similar to Bitcoin mining, it's a bit of a missed opportunity for just job creation, but more importantly, to bring additional generation to your local county. To me, the simplest way I can explain it,

it's supply and demand. Right. Like everybody wants more generation, but generation is not going to come if there's no offtaker. Right. People have to be able to make money. And so if you're a county that's pro data centers, there's a way to kind of take advantage of of this this CapEx boom cycle and also find a way to bring incremental generation capacity. right i think to your county which could be net great right it's also a way for you depending on you know your your locality or what grid what have you it's also a way for you to maybe bring more renewable energy or or more baseload what whatever it is just more generation in general is great but it's also an opportunity for you to kind of think about that mix the the grid mix or the the energy mix and also find ways to help to to incentivize or shift that in ways that maybe

align with whatever your view is in that county um so like to me that's what i kind of think the the missed opportunity is but ultimately counties states they all have to compete and so you know i i think it's um it's fine if a county doesn't want a data center you're you're just choosing to not play in the game but that may come at future consequences of just you may struggle to get new generation. And you may actually end up seeing power rates increase in those counties that were anti-data center. I actually think that would be beautiful if you actually saw power rates drop in the counties that were pro-data center versus the ones that were anti-data center. But you know, time will only tell. You can see electricity dropping, property taxes maybe

dropping, because that's another thing I don't think people recognize, like the sales tax and electricity depending on where you are it's generating incredible revenue for for these counties proper conditions that's a massive opportunity i mean you could mandate however you want to regulate it but there's opportunities to say hey if you build a data center here uh you need to contribute x amount of capital into like education fund or or whatever it is but there are ways to take advantage of this growth and to to capture um some of the capital to invest back into the community in various ways like i think that's an absolutely excellent point yeah all right i lied that wasn't the last question uh the last question is where where does uh where where do

people mess up here because you're looking at like uh cues for interconnection reaching tens to hundreds of gigawatts um it reminds me a lot of ercot and 21 and 22 where bitcoin miners are coming and they're like or people saw the the sort of gold rush of the exodus out of china of hash rate to to the us and they were like yeah i've got land i've got power but they're really just in the queue of ercot um having to wait and then they were going on the back end selling the dream of i'm going to get this much power in a year or two and we're going to be able to build this massive mining operation of looking at what's happening with the ai build out particularly as it pertains to locking down power. It seems like that's happening again at a scale that's an

order of magnitude higher. How do you see that playing out? I think you're absolutely right. I think there's a lot of sites that ultimately won't end up ever being built. And I think we saw this exactly like you said in Bitcoin mining. But that's part of the challenge as an analyst, if you're trying to invest in this space, which is figuring out what's real and what's not when we talk about pipeline. And a lot of companies talk about pipeline as being real when exactly like you said, you just bought some land,

there's no load study that's been conducted, you don't have an interconnection agreement or any real visibility or line of sight into if you're ever gonna actually be able to draw power at that site. And if so, to what degree or to what capacity? And you have a lot of people that are marketing these pipelines without having any of those things in place.

And one of the challenges as an investor is understanding what risk weight or what probability do I need to assign to a company's pipeline and why, right? And what's the right probability given these various milestones that you could ultimately have in place. But I think that that's another element that makes me so bullish on the Bitcoin miners, which is, you know, the grid interconnection queue or just the request for connectivity are enormous. You know, a large majority of those are never actually going to be permitted, or they're certainly not going to be permitted on a timeline that is anytime soon. And so to me, I think it just reinforces the incredible value of having already available

power, which all of these miners do. And I think that as that plays out, and as more people realize that only 10% to 30% or some small percentage of the overall queue or request will actually be built, I think is just going to you know reinforce um the value per megawatt of the power portfolios of the companies that already have it and then you throw in there the political risk as well and that's just another sort of force multiplier on the value of the companies that already have the energized or approved zoned power capacity all right i lied twice but i promise you uh it's the last time i lie last question what does this mean for bitcoin mining moving forward ah this is this is this

great great question um what does it mean for bitcoin mining i actually it actually kind of makes me pretty bullish on bitcoin mining in the more medium to long term i actually think what we're seeing is just an acceleration to what many many miners talked about for many years now which is like bitcoin mining is going to gravitate towards the stranded forms of energy and i think that um the the massive race for for ai compute is just accelerating that so a lot of the grid connected power capacity is likely going to be allocated towards ai um the mega sites like we're moving away from these mega sites and i think that bitcoin mining is is going to gravitate towards you know those stranded forms of power and it's also going to be more distributed it's going to

be about your five megawatt site your one megawatt site here and there that is sort of more of a stranded form of energy, which you could argue is actually great for the health of the network because it makes Bitcoin mining a little bit more distributed and potentially decentralized, which I think is great. I also think that you could end up in a scenario where you just have less overall power capacity allocated to Bitcoin mining. So if you have bitcoin price recover rapidly the power element you're not gonna have as many people able to quickly plug in asics and so you could end up in this era where hash price is actually appreciating because people just don't have power availability to actually go chase those economics um which

could lead to a a very compelling golden era of of bitcoin mining economics which i certainly hope for um and i think that we should also end up in a scenario where we hopefully move away from the oversupply of asics like that's been one of the issues that has really played bitcoin mining which is just you know bitmain micro bt bitdeer they're all trying to preserve their their capacity at the foundries they have to continue to mass produce these asics despite there not being demand so you have this massive supply glut of machines effectively. And I'm hoping that we end up in a world where the supply demand between ASICs and the amount of available power ends up in a more balanced and normalized regime, which I think would make mining economics more durable

over the long run. And so that's kind of some of my medium-term to longer-term thesis for Bitcoin mining, but I'm pretty excited about it in the medium to long term. I agree there. I think it's overall bullish for the network. Many people, again, like I said in the beginning of the conversation, are like,

oh no, AI's taking the window of the sales of Bitcoin mining, that's bad. It's like, well, no. Everything's bullish for Bitcoin. We're going to distribute hash rate. It's going to be geographically distributed. This will force ownership distribution

to be more distributed. as well i think this is overall good and then i think also for countries outside the united states that aren't taking advantage of this uh ai compute build out like there's going to be opportunities for bitcoin mining to land there as well and while i do like my hash rate to be american made it is it's good to make sure that it is geographically distributed around the gold the the globe uh in different jurisdictions so i'm bullish as well brandon this was an incredible conversation thank you for taking some time out of your day to do it i think you're doing incredible work and for anybody listening make sure you go to dimetrics.ai to check out what

he's built and if you're curious or if you're on the on the beat of covering this infrastructure build out brandon's built incredible tool thank you it was a pleasure you know to to be able to come on the show i really enjoyed the conversation um you know as always awesome we'll do it again at some point because i'm sure this uh this theme's not going to slow down anytime soon definitely not definitely not all right peace and love freaks thank you for listening to this episode of tftc if you've made it this far i imagine you got some value out of the episode if so please share it far and wide with your friends and family we're looking to get the word out there also wherever you're listening whether that's youtube apple spotify make sure

you like and subscribe to the show and if you can leave a rating on the podcasting platforms that goes a long way last but not least if you want to get these episodes a day early and ad free make sure you download the fountain podcasting app and go to fountain.fm to find that five dollars a month, get you every episode a day early, ad-free, helps the show, gives you incredible value. So please consider subscribing via Fountain as well. Thank you for your time. And until next time.