On y'all. Welcome back to Blockspace Live, and an explosive day it's turning out to be, Charlie. Leopold Aschenbrenner's Situational Awareness Fund was blown up and sold its entire public equities portfolio to Citadel.
That's right, the wunderkind sank so that we could swim. The market is ripping- [laughs]... following this news, and we will be covering that as our lead story.
Following that, we have Zach Shapiro of the Bitcoin Policy Institute on to talk about AI in the intersection of law.
We will also be touching on Microsoft and Meta's most recent quarterly earnings and why Meta tanked following its earnings and Microsoft soared.
The details are in the CapEx guidance and the earnings for their computation arms.
We will also be covering how FERC, the Federal Energy Regulatory Commission, has given approval for TerraWolf to move forward with its acquisition of Chesapeake Data with its Morgantown acquisition.
And then we will cap off the stream today with a note on Morgan Stanley estimating that roughly 65 gigawatts of load within ERCOT's Badge Zero could be identified as base load, and why that benefits some of the principal stocks in our coverage.
Colin, remind you to switch your microphone input. And while you do that, Blockspace goes live every single weekday at 1:00 PM Eastern.
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More on CleanSpark later on in the show. Holy smokes, Colin, the market [laughs] is on fire. Are we, are we so back? We are so back.
[laughs] I, I think, to, before we hop into Situational Awareness, Charlie, I do think that you should get the- Yeah... DI metrics charts up. Yeah. Because a lot of the names we cover today are up, like, 20% to 30%.
Yeah. Keel up, like, 30, Iron up 30. Basically every sector within the AI play is ripping right now. It's, it's nuts.
Uh, you cannot swing a dead cat without hitting a major AI data center, like, stock indice that is, that's not up 10, that's not up double digits. I mean, look at this.
So this is DI metrics, it has, uh, stuff segmented by sector.
Memory, the biggest recovery after the Korean stock market and Korean degens fully routed, as Ben Paladian yesterday was talking about, uh, up, the whole sector's up 20%. I mean, we're talking just names.
Micron, SanDisk, absolutely wild. Neo clouds, other sector we kinda cover. Neo clouds and power shells up 19% and 17% today.
Um, I mean, Cipher up 28%, Keel 29%, CleanSpark 20 per- It's just like, what is going... I know what's going on. We sacrificed Leopold to the stock market gods.
Um, yeah, so power shells, again, the whole sector up just insanely. These are, uh, these numbers are not on the day, they're on the month, I believe. Still, it, it, um,
this, these are daily moves, um, not, like, monthly. So if we were to, like, zoom out [laughs] a bit here- [laughs] Still looking at month... okay. On the month [laughs] get a look at the month.
The month power shells are still down 28%. On the month, hyperscalers are down 10%. On the month, storage, uh, photonics down [laughs] 35%. On the month, memory appears to be down 45%, still.
But that's, that doesn't matter. Today we dine in the halls of Valhalla because [laughs] the, things are ripping. Um, there's a lot of hope right now. And it, and we talked about this, Colin, because, um, like, yes,
the, there was a lot of leverage in the system. Yes, the, there, some, at some time, some later date, something runs into a brick wall.
But, you know, as Aragon on the, you know, at the doors of, uh, at the doors of, the Gates of Mordor says, "Today is not that day." Um- Today is not that day. In fact, today is a perfect day for this meme.
[laughs] It really does feel like this. Yeah. [laughs] Things are, things are ripping, oh my God, or it's, you know, the, we're up 1% on the month of the quarter.
But, um, yeah, it does just so, like, show how reactionary everything is and how, um, knee-jerky the market is. Uh, why is it knee-jerky? Well, because everybody was levered to the absolute tits.
'Cause 25-year-old was levered to the teats. Yeah. So. Child prodigy, and Columbia graduate at 19 and valedictorian, I just reali- I just learned that today. I, no, um, bro, I mean, okay. Do we wanna explain who he is?
This is Leopold Aschen- I, I think we'll just- Okay... brief, brief bio. Okay. He used to work at OpenAI as a researcher following his graduation from Columbia.
He ended up getting let go from the company according to some sources, and then he started Situational Awareness, his hedge fund, two years ago.
That has been the darling- Of implausible hedge fund stories within the TradFi ecosystem, 'cause they were up over 400% on the year before this rout happened. Yeah.
Started with a few million in his pocket, grew it to billions. At one point, I believe you'll s- you'll find the number, something like 40 billion.
Another little detail, he is engaged to Avital Balwit, who just so happens to be the chief of staff for Anthropic CEO Dario Amodei.
And if you'd forgotten about the storied traumatizing history of crypto in the last down cycle,
Leopold was the, uh, investor who led the philanthropy side of now routed crypto firm FTX. Wait, really? I didn't know that. Yes.
His job prior to OpenAI, Colin, was being the philanthropy arm, leading the philanthropy arm of FTX. So with that, Colin- Charlie, don't make me put on my, don't make me put on my tinfoil hat. Yeah.
The, the, the coincidences just continue to build, but we'll, we'll go ahead and get to the meat of this story. So this is coming from CNBC's coverage.
You can basically type in Situational Awareness, and you probably have 100 different articles to choose from. But the TLDR of what went down was this.
The hedge fund unwound its entire position for public equities at Situational Awareness, selling to Citadel, as the Wall Street Journal reported this morning. That came out right before we hopped on the horn here.
As losses on AI stocks and st- and software shorts strained the roughly 20 billion to 24 billion that it had under management at the time of the liquidation.
CNBC reports, per your previous comment, Charlie, that the fund peaked at the start of July at 45 billion, right before this current drawdown. So the single buyer, again, was Citadel.
It, uh, absorbed the entire portfolio of Situational Awareness' public equities, and this comes after the hedge fund was margin called.
According to CNBC, Bank of America, Goldman Sachs, and JPMorgan Chase were helping the fund satisfy margin requirements or cut positions in an orderly way.
And more broadly, Goldman Sachs and JPMorgan have issued margin calls to hedge funds holding highly concentrated AI positions.
So one thing I think that is important to contextualize within this entire event, Situational Awareness is going to take a bunch of blows today for the fact that they had to liquidate these positions.
But the fact of the matter is, this is a part of a larger story where these levered hedge funds betting on the AI trade, if they were on the wrong side of that leverage, have been getting margin called, pro- are, are probably in the process or were getting liquidated during this entire rout, right?
And so it's too early to tell, but we could have just seen a massive flush out of leverage that would be, in all rights, if it were thorough enough, a bullish signal for potentially the rest of the quarter.
We- May- It's increasingly seeming like we just had a pretty savage leverage flush out as indicated by this story. So a few key notes from this before I toss it to you, Charlie, for some spicy takes.
They have a position in Anthropic, and this was not touched according to CNBC reporting. The Situational Awareness team, their representatives specifically told CNBC that they did not sell the Anthropic stake.
But CNBC did say that it wasn't clear if that's actually true, but it's, that's at least in contention here. So we only know so far that their public positions or positions in public companies have been liquidated.
Now, CNBC names the largest holdings as of the most recent accounting that they did with sources on the inside as Nebius Group, Sandisk, Micron, and CoreWeave. The Sandisk and Mi- and these are outright positions.
These aren't derivative positions like puts or calls. And that would make sense in terms of getting liquidated at this point because Sandisk and Micron have been getting hammered this month.
And so if you look at that and you think that they had large positions there, that could have put pressure on the entire book. In fact, all four of these, as CNBC notes, are down more than 35% this month.
As of the end of Q1, the most recent filing that we have from them is around May 19th, their 13F with the SEC.
Their largest holdings or largest, uh, new positions were VanEck Semiconductor Trust, which also is having a really rough month at 2 billion, Nvidia at 1.6 billion.
Um, this is a new position, but it's combined with Nvidia puts that were a top holding, and Oracle at 1.07 billion. So at the end of the day, Leopold and Situational Awareness out
getting a pit stop currently, getting their wheels changed and their oil checked. They're trying to raise money though. They're- Probably trying to get their head totally cleared.
I mean, their brains have been scooped out. They've, they be- yeah, I mean, [laughs] if they're in the shop, they're, they're, you know, they're, they're bent over the tire pile right now.
Like it's, it's, uh, Ken Griffin, uh, owns their portfolio now, and this is a common Ken Griffin play. Um, s- out of nowhere, somebody's really levered, somebody's over their skis.
Who is the, you know, pro- where does the buck stop? Who is the ultimate, like, predator in the American markets? It, it's Ken Griffin and, and Citadel. And so, uh, again, putting on my conspiracy hat here, um-
You know, uh, the entire market basically started copy trading Leopold Aschenbrenner over the past two quarters. I myself started doing a little bit too. Um, and, uh, b- because it feels like the boy's just been winning.
Yeah.
And he's married, or, you know, either married to or about to marry to, supposedly, chief of staff of Anthropic, which, um, like has been a little bit of an open secret speculated that he's just got inside information.
I mean, he was let go from OpenAI for sharing insider information. I mean,
what, what is this young impetuous buck gonna not stop doing, especially if he's got an inside route onto, you know, the most speculated, insular, mysterious company in pal- at the tip of everyone's tongues?
He's gonna keep doing it. So, um, again, this is speculation. This is me positing, you know, intu- you know, intuiting what other people have also basically said.
Not surprised though that Ken Griffin is there to pick up the pieces. Whether or not this is opportunistic, intentional, or coincidental, we don't know.
It wouldn't be surprise, it would not surprise me if Leopold had kind of become the flag bearer for a lot of people who are getting levered, and, and this is just maybe situational awareness is just the, like the prominent one of the people, uh, of, you know, the prominent one that, that went, uh, belly up and just there's more other bodies floating to the surface because of the copy trade.
So- Yeah, I wouldn't be surprised-... maybe that was, yeah... if we see other bodies floating to the surface, but it's almost like, you know, if you see an-
a, a sperm whale float to the surface, you're probably not gonna notice all the other minor fish that are also surfacing as well. Yeah.
My question going forward though, Charlie, is they are seeking to raise new capital to restart the fund. What, will people trust Leopold's situational awareness, dare I say again?
You know, it's the, it's the classic fool me once, shame on you. Fool me twice, shame on me. I would imagine that there's probably a good chance that they do end up raising capital again. I bet you they, yeah.
But- He's, yeah... but I mean, well, what, what's your, what's your take? Do, do you think that w- Do, do you think that his star has risen as far as it will? It, it, it was at a zenith, now it's at a nadir.
Do you think that they might come back, but they just won't feature as prominently as they have in the past?
Um, I think the mystique and mystery will be gone 'cause everyone realizes, oh, he was just levered during the right time to be levered and had all the situational attention, if you will.
But, uh, I bet you he gets another shot at the, I ga- I bet you he gets another shot on goal. I mean, the thing is he was right during the right time with conviction. So it really, it, the irony is it was really,
you know, obviously this was driven by hubris and risk, but that is downstream of being able to be sol- solve for that with, uh, position sizing.
So if you can just kinda [laughs] turn the dial down a bit, if you think that this trade, that AI trade has room to run, Leopold probably has good insider information.
I mean, do people stop texting him, you know, when they're, you know, ahead of their deal announcements? 'Cause, like, he prob- he's still got everyone in the industry's number.
And his, his, his essay, Situational Awareness, basically was right and it has been right, basically saying- Mm...
that there's a couple hundred people in Silicon Valley a few years ago who, like, have total vision to the entire playing field, and it really is a big group chat that you're not in.
And, um, that only s- serves to be more right every day that this is a small amount of people with a lot of insight and agency who are basically driving the entire market. That's not to be like s- you know, call a cabal.
I'm just saying the fact that what now drives the entire stock market was basically kind of a niche thing two and a half, three years ago, and, uh, now they're all in charge of multi-billion dollar, approaching trillion dollar companies.
So, like, just the fact that a few engineers now kind of derive the, are, you know, drive the machine of the American and global economy, you know, he's gonna get another shot on goal is my prediction. Um...
M- my biggest- Okay... question last before we sign off on this one, Charlie, is, like, what is left out of what was sold? Like- Well, we don't really know... after s- No, I don't- We- That wasn't in the reporting.
So after satisfying margin requirements and clearing anything else out they needed to, how much of a haircut did they take on the positions in addition to what, uh, they already took in terms of the nominal value, considering where the stock market has, uh, considering how these positions have drawn down?
And, like, what's left over? Do they have... I mean, 'cause you would assume that there's gotta be something. They were up, like, 430% on the year- With sides... at a certain point. Yeah, and so what's left over?
You have to imagine there are a few billion dollars left over there. I guess that just gets returned to the, um, the LPs in the fund. I mean, I assume so, or- I mean, we'll see...
I don't, I don't know what, what comes next. Like, do you go to the LPs and you're like, "Hey, like, you can take your money back, or you can let us try it again," you know? But, uh, definitely the
s- I mean, from where I'm standing, Charlie, this is one of the craziest stories of the year so far, specifically because after they liquidated this position, everything, including the holdings that they had, ripped.
So Ken Griffin and Citadel looking like geniuses right now for buying that book at a haircut. Add that to the stack of other things that they've done over the years which make them look like geniuses.
You know, people on the internet may remember, and we were talking about this before we went live, Ken Griffin is the boogeyman, um, the ultimate arbiter of WallStreetBets, having basically been the entity that, uh, WallStreetBets failed to liquidate, who then- Uh, called all the hens home, all the cows home and said, "Ah, your little online, uh, populist movement, it actually belongs to me."
Now Ken Griffin is building the largest palatial estate in Am- American history, either on Long Island or somewhere in Florida. I don't know which, probably both.
But Ken Griffin is like now, you know, he is the final boss, [laughs] uh, of people that we have names of. So, uh- And one quick aside- That's- Remember when GameStop announced a Bitcoin treasury strategy? Oh, man.
What happened to that? I feel like, like Kermit the Frog- [laughs]... at the, you know, rainy window. [laughs] Like saying, "I former- "I miss, I miss those days." Yeah.
[laughs] All right, I think we can table this one and, and move on to earnings. Yeah. Um, before we do that, a word from our sponsor, CleanSpark. [gentle music] We are CleanSpark,
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I don't have a one, one article to share for this 'cause it's just a bunch of numbers that are recapped from the earnings reports, but a tale of two stocks.
A tale of two hyperscalers, Charlie, because yesterday Meta and Microsoft both released their quarterly earnings, and they both had the exact inverse reaction in the market as a result.
Meta dumped 7 to 8% in after-market hours. Meanwhile, Microsoft was up 9% in after-market hours. And in fact, that,
uh, rally has extended into today as all of these stocks are bevied by Leopold Sacrifice. Microsoft up almost 17% today, which is crazy.
Now this might be cold comfort for Microsoft holders because it's still down like 11% on the year, and it's down 6% year to date. In fact, it's been one of the laggards among the Mag Seven in terms of the AI trade.
But yesterday's quarterly earnings might rewrite that script. Meanwhile, Meta down 12.3% on the day, and down 23% on the year, 19.3% year to date.
So what's going on with these stocks? So more or less what came out of the earnings call yesterday was a warning on CapEx guidance and CapEx spend without clear operating income and profits from that.
So the headline numbers are as follows.
Microsoft f- uh, fisc- uh, their Q4 fiscal year, they do this awful thing like, uh, you know, other companies that we cover where for whatever reason their fiscal year ends halfway through the year.
They were at $90 billion last quarter in revenue, up 18%. Meta beating them on the percentage front here, $60.8 billion, up 28% quarter over quarter for their Q2 2026.
Earnings per share adjusted for, uh, for Microsoft was $4.74 per share. Meta $6.18 per share.
Quarterly CapEx guidance wa- or quarterly CapEx for the quarter was 48, 41 billion for Microsoft, up 69% and 31.1 billion for Meta. CapEx guidance was cut
from Microsoft from 190 billion to 175 billion, but this isn't actual spend, Charlie. This is an accounting gimmick that I'll get into here in a second.
Whereas Meta raised the lower end of its CapEx guidance for 2026 from 125 billion to 130 billion.
Now the key bit here though is that Microsoft Azure Cloud, their match, their re- Microsoft Azure Cloud revenue was up 43... Or the, uh, it grew 43% over the quarter.
And that was really I think what was leading to the rally following earnings. There's, th- people, they're seeing clear growth in the cloud segment, and that's what investors wanna see right now.
Their commercial RPO backlog also rose to 678 billion, up 8% sequentially and up 84% year over year, which is absolutely huge.
And full year revenue was 338, 331 billion, up 18%, with operating income up 21% to over 155 billion. Now, let's contrast this with Meta. So their CapEx was 31 billion.
Their full year guidance for CapEx was 130 to 145 billion. They beat on revenue, but they missed on earnings, and they got punished accordingly.
Now it seems to me, Charlie, like the market is really truly drawing a line here by saying, "You can spend on CapEx, but we need to see that the key business segments that are going to benefit from that CapEx are actually growing."
And it's a little bit misleading some of the reporting about Microsoft cutting CapEx guidance, because what it actually did was they extended the estimated useful life of their data center buildings from 15 to 25 years,
which reclassifies some of the future leases from CapEx to operating expenses.
So there's like balance sheet shuffling going on here to where they can move some of those expenses from the CapEx bucket to the operating expense bucket. And the reason for that is that, um-
When you extend the useful life of the data centers, it changes the ratio of lease term to asset life for these assets, and it reclassifies some leases that were previously qualified as financial leases, which falls under CapEx, into operating leases, which is OpEx.
So that's why the Microsoft CFO, I believe her name's Amy Hood, said on the call yesterday, "We're revising down the accounting guidance for CapEx, but the spend is going to remain the same."
But the market doesn't seem to care about that because Azure had very strong growth.
Well, and, and again, not the finance wizardry does elude me a little bit, but, uh, maybe the market sees through that and sees that structurally right now, Microsoft sells compute and Meta consumes compute.
They are both... They're both... They both are, you know, annihilating their free cash flow [chuckles] and spending, you know, CapEx towards these endeavors, but Meta currently does not sell much compute.
However, you know, they, they, they have said we're, we're pivoting to the, uh, the, the neocloud model or we're gonna sell compute, which you would think at some point would be the right move.
Question is, how quickly can they roll that out? If my, you know, if my number, if, if my understanding is correct, Meta has the Hyperion site down in Louisiana, um, ETA early 2028.
And then they just announced their other massive, massive site down in El Paso, as we covered yesterday or the day before. Again, a Hyperion model round two. Um,
you know, while Microsoft may not be expanding quite at this rate. We'll see.
At some point you, you know, I do wonder was Leopold Aschenbrenner also short Microsoft and now they're [laughs] going up again 'cause- Yeah... bro, I mean, they're, like- Yeah...
the M in the Mag 7, they're up like 12, 14%. It's, it's wild. Yeah. So. And, and just to underscore that point really quickly with a few more stats about Azure. Azure's revenue is, grew 43% year over year.
For the full fiscal year 2026, Azure revenue surpassed 100 billion for the first time. So clear growth on that cloud segment, and that to me seems to be the key driver of the current rally in Microsoft.
Investors no longer wondering if they're going to be left behind in terms of the principles driving this AI rally, so. All right. We have Zach Shapiro in the wings.
We're gonna bring him on up here very soon after a word from our sponsor, Luxor.
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So if you'd like to learn more, go to luxor.tech/commander to get started. All right. Let's bring Zach on up. Adding him to the stage now. Zach Shapiro, welcome to the show. Thanks for having me. Good to see you. Um, so,
uh, had, gonna have you on up here. You're kind of like everybody's AI lawyer whisperer here. [laughs] And, and I wanna talk and, you know, about your essay, uh, two clocks and associated things.
But before that, the kind of, the story that I am still seeing, like, you know, on Main Street, my friends who are not in, really into AI, they're all angry about the Anthropic, uh, settlement.
I don't know if you, if you, how familiar you are with this. Anthropic pirating, stealing all these books. Um, I know you're more dialed into law and AI. What's your take on this?
What, you know, what's the landscape here? Yeah, I think this is a, um, narrower story than it sounds like at first.
Uh, there is a big open legal question about to what extent can, uh, Frontier labs train on stuff on the internet, uh, and then use it under fair use protections, which is an exception from copyright law, uh, in order to train its models.
And there are, you know, there's a difference between different ways of doing this.
So, um, right now there's a lawsuit, a big lawsuit between The New York Times and OpenAI about the big question of like, was it okay that, uh, OpenAI trained its ChatGPT models on The New York Times?
I think everyone agrees if ChatGPT were to just serve up, uh, New York Times articles on request, that would be illegal. That would be copyright infringement.
The open question is, if you ask ChatGPT a fact that it learned from reading a New York Times article, uh, whether that is permissible or that's copyright violation.
Um, my view, I, this is an unsettled area of law, my view is that it should be okay to do this.
I think that LM's training on information from the internet is really more like, uh, you know, learning how to play piano from a piano teacher than it is playing a recording of someone else playing piano, and that should be the distinction, and sh- you should be able to train models.
Um, that's an open question. Uh, what the Anthropic settlement is about is not quite that. It is, um, can you use pirated material to train the model, right? Can you steal and then train on it?
And, uh, the answer to that, unsurprisingly, is no, and that's, that's the settlement.
Um, there is sort of a parallel case where it's like, okay, if Anthropic bought a single copy of a bunch of books and trained Claude on it, um, is that okay and can it use the information from the book?
Import- interesting, important opening question. If you steal the book in the first place, um, that's a slightly different scenario, even though sort of functionally it's similar.
So I wouldn't read too much into this settlement. I don't think this is one of the sort of big open questions. Good. I'll clip that. I'll send that to my friends. I think that's a pretty concise way of doing it.
Um, so let's get into kind of the meat of, uh, this conversation. You've published a bunch of essays, all fantastic. Uh, earlier this year, I believe it was like the Claude-powered... law firm.
But again, that was [laughs] like eight months ago, so things have changed.
Your latest, uh, essay, The Two Clocks, describes the, um, the cadence, different cadences of the, uh, the technology and the institutions, the law firms.
Can you give me the short TLDR elevator pitch of this, and then we can ask some follow-up questions? Yeah.
Uh, when I look out at the sort of economy and the macro situation, uh, the sort of most glaring fact to me, which I think is the biggest sort of high-conviction opportunity I see in the market, is that on the one hand you have these, uh, giant tech companies that are, um, even now, after the recent correction, trading at pretty, uh, incredible multiples and rich valuations, um, based on the promise that they have discovered this sort of amazing technology that is perhaps swiftly leading to AGI, and that is going to transform the economy over the next few years in a major way and justify huge amounts of CapEx on token spend by all sorts of businesses, right?
Not just tech companies, but really, uh, sort of all white-collar type of businesses.
Um, and on the other hand you have, uh, the industry which is starting to adopt this stuff and, and starting to spend money on tokens, and sometimes, you know, even token maxing and spending a lot of money on tokens.
But you're not really seeing the increased revenue or increased effinci- efficiencies or increased productivity, uh, you know, outside perhaps of big tech, which is seeing more of this leverage.
Um, and you know, this is a problem, right? If the efficiencies don't actually materialize, then, then w- you know, the current valuations may start to look like a bubble, at least for now.
And so the tech companies, uh, sort of drastically need to see efficiencies in the regular economy in order to justify, uh, their projections.
The, uh, businesses in the real economy are having to face, um, AI native startups that are doing things more efficiently than incumbent businesses can, and, uh, questions from their customers and clients about where is the AI efficiency.
And so both parties really need this gap to close. And my thesis is that, um, each of the parties is seeing something real, um, but missing something else. The tech companies are right about the technology.
The technology is really amazing.
It can do all sorts of stuff, and if AI models don't get any smarter than they are now, they are smart enough to deeply transform white-collar industries like law, accounting, finance, and stuff like that.
Um, what they're wrong about is that this technology will automatically just work and diffuse in the economy without, uh, a lot of effort.
Um, now, the businesses, right, the law firms, the accounting firms, the investment firms, um, they are right that the technology is not magic and it is not fully working for them yet.
But their conclusion that they tend to draw from that, which is the technology is over-hyped, uh, and, you know, is, like, really fancy auto-complete, and it's, you know, it's a neat parlor trick but it's not ready for prime time, that's wrong, right?
Uh, the problem is it's a skill issue. You actually need to figure out how to use this technology well and how to reorient your business around that.
And so I see this gap, you know, these two different clocks that move at different speeds.
There's the speed of the technology, which is genuinely impressive and unprecedented and fast, and then there's the speed at which institutions move, which is slower and sort of the biggest, you know, necessary thing that needs to happen in the economy.
And, uh, the area of the economy I'm most bullish in is converging those clocks, uh, towards each other.
Do you think people's expectations are just out of sync because of that, in the sense that the tech industry is probably overestimating how quickly we will get to AGI, and the private sector is saying it's gonna take way too long, and they're just a mismatch?
Because I often see what you said about the... People say, "Oh, it's just a fancy auto-complete." And if you wanna use an analog, it's like, well, you know,
um, you know, dial-up internet was really freaking slow, and now we have satellites in space that can beam you Wi-Fi anywhere on Earth. Yeah.
And it, it seems like there's one sector of the economy that thinks it's just never gonna get there. Yeah. I, actually, uh, that might be true. Um, but I actually don't think this is a question about AGI.
Uh, we don't need to get to AGI for the AI to be deeply transformative. It's, it's good enough already, right?
Like, I run a three-person law firm, um, that is AI native, and the things that I do and the efficiencies I get and the leverage I get, uh, are just way, way better than big law firms.
And I have a little bit of authority to say this 'cause now I'm also spending a lot of my time inside big law firms, helping them figure out how to diffuse this stuff.
And it's just the, the capabilities are different when you don't have institutional constraints. Um, what needs to happen is not, like, to figure out exactly when AGI's gonna happen and then that'll solve it.
Uh, what we need to figure out is how to re-architect enterprise in order to incorporate the technology that already exists today, which is good enough.
And, and in my piece I use this historical analogy of, um, when industry started to electrify 100 years ago. Uh, you know, electricity had been around for certain applications. Obviously, it's impressive.
Um, but, uh, early sort of Industrial Revolution factories ran on the steam engine. Uh, what happened was... You know, so factories were oriented around a central drive shaft.
In the basement of the factory, you'd have this big steam engine that sort of chugged along.
Uh, you'd have the drive shaft, and then you would attach all of the machines in the factory to that central drive shaft along the assembly line, uh, in order to power all of the different machines that needed to work in the factory.
And when, uh, the economy started to electrify, what they did, which is totally understandable, uh, is to, uh, take that steam engine motor in the basement, replace it with an electric motor, uh, and then use that to power the drive shaft.
And, uh, you know, maybe you saved a little bit of money not having to have folks s- shovel coal in the basement. But, you know, the economists at the time were like, "Oh, my God, electricity's gonna change everything."
And when you replaced the steam engine with the electric motor for the drive shaft, it, it didn't change everything, it just made things a little bit more efficient.
Um, and the efficiency came 30 years after that, when they realized, oh, that's not what electricity is for. It's not to drive the drive shaft. What we can do with electric motors is put them in every individual machine.
And so they actually tore up the factory floor, and they just remade the assembly line. It doesn't need to be along a central drive shaft anymore. You can...
All these machines that have their own electric motors, they can be electrified, and now this is, like, a fundamentally different thing that is much more efficient and much more powerful.
That is what needs to happen in industry, right? Like, the AI is here in the way that, in the way that the electricity was here.
It's that the sort of incumbent enterprises are designed around, um, You know, assumptions about the scarcity of intelligence and, you know, what tasks require humans and what levels of review are needed that is just not compatible with the, like, truly agentic AI future.
And so it, it's really much more like a reorganization that needs to happen.
And so you need much more investment, and some of it will come from the labs, and some of it will come from industry, and some of it will come from, you know, consulting or change management businesses, um, but to actually sort of re-architect the way that firms work writ large.
You talk about re-architecting, and you say that you are now, um, you know, working inside other large law firms. And in your piece you talk about, like, the forward deployed absorption role.
Calling back, I think, Palantir is where I, you know, see the forward deployed engineer or, or some-something like that. Um, is that part of what you think rearchi- architecting needs to look like?
Is that a short-term bridge, like, period where we do this as we approach AGI? And then, like, you know, the drive shaft, great example, but we're talking about intelligence now.
This is a very much less tangible, amorphous idea, really hard to quantify. What does the architect- re-architecting look like, Zach? Yeah. Uh, great question. So I think this is roughly a 10-year project.
Um, I think beyond that, it's really hard to know what this all looks like. I don't think we're gonna get to AGI in the next couple of years.
If we do, then this all might be out the window and we enter a singularity, and who knows? Um, but assuming that that doesn't happen, um, w- the forward deployment, uh, what that really is, is you need to have...
It might be one person, it might be teams of people, who understand both the actual substantive task. So this can't be McKinsey. I don't think this will be Palantir.
You need actual subject matter experts, um, you know, in law, accounting, [audio glitches] what call, uh, industries.
Um, and then you need that person or someone else who closely works with them to understand how to talk to AI, how to translate the substantive task into essentially prompting and then custom skills and then, you know, automated workflows, which might be some amount of generative AI and some amount of sort of more deterministic software sort of built around it, right?
Not every task is, uh, meant for AI. Um, I have a, uh, basically a, a software tool I built to help automate, uh, venture deals, uh, for startups when they raise money.
And, uh, part of it is just a plugin to Claude CoWork.
Um, but part of it is also a separate deterministic software engine that I vibe coded that basically does all the math of, like, share counts and price per share and, you know, uh, creating the cap table.
That's not something you wanna hand to an LLM because, you know, an LLM might hallucinate.
It'll give you a different response every time, uh, you put it, this, the same input in, and that's no good when you're trying to do math.
Um, but if I'm trying to add, like, legal language into the deal documents to capture a specific intent, um, you need an LLM for that, right?
That's a qualitative request that you're not going to have, like, a logic tree do.
And so some of this is gonna figure out what is AI, what is not AI, how do these things work together, what, if any, is the UI behind all of this.
Um, but the forward deployment is really about translating the intent of the subject matter experts into sort of agentic automated workflows over time at each level of the stack, whether that it's at the most basic level, a prompt or a skill that is, that is built by looking at a ton of different prompts or, you know, some fancier software tool that, that, like, is a hard shell around sort of the skill workflows.
Uh, and then the end state of this, um, [lips smack] done a lot of thinking about that also. Uh, and, and here I'll be more specific to law. That's, that's the area I know best.
Uh, I think that law is going to bifurcate into two different markets.
I think there is sort of, like, commodity legal work, which is y- you know, like, regular low-value contracts for big business where you do bulk review.
I think that is just gonna fully, uh, automate and commoditize to the price of the token.
Um, there will be the minimal amount of human review that regulations allow for, and, you know, that is what it is, and people will make money, uh, fully automating that.
Just like they've made money, um, sort of shunting a lot of that work to LPO offshore sort of low-cost review in India. Um, it'll just be machines instead of people in India.
Um, at the high end though, I think what is... And that this is where I'm more interested, and the reason why I am sort of embarking, uh, to, to work with big law firms on this.
[lips smack] Uh, I think, you know, if you're hiring, if you're a,
you know, wealthy person, a big company, investment firm, and you're, you're hiring the very best law firms in the world to help you, whether w- you know, it's like a bet-the-company litigation matter that's really important to you, it's a important sort of white collar criminal defense case where you might go to prison if you lose, uh, whether it is sort of like headline grabbing M&A where a huge amount of money is at stake, um, you are hiring the law firm to get access to the very best lawyer at the top based on that lawyer's judgment, their ability to make good decisions in the face of uncertainty.
Uh, and I, I don't see LLMs as being really good at that. LLMs are great at execution when you specify a task well enough in a prompt.
Um, they're very good at giving you information and talking through stuff with you and helping with analysis, but, uh, I wouldn't want an LLM to make decisions for me, and I just don't think that, like, because they are prompt-based, because they're generative, I just don't think that's what they're great at, so there will be a human.
[lips smack] And sort of the promise and the challenge of that for, like, big law firms specifically, uh, is the economic model for big law firms right now.
Um, you know, if you look at the sort of partners at the top of big law firms, sometimes they're making, you know, $10 to $25 million a year, um, per partner.
Uh, and y- yes, they bill out at very expensive hourly rates, you know, two to $3,000, sometimes a little bit more than that. Uh, even [audio glitches] rates, there are not hours in the day
to earn their yearly draw just by working even at very expensive hourly rates.
The way they actually make money is billing out armies of junior lawyers at, like, $1,000 an hour on, you know, doing grunt work on big tasks, right?
In a litigation matter, there's doc review, just a, a bunch of documents you need to read to see if they're relevant evidence.
Uh, in a, in a, you know, large transaction, there's due diligence where you gotta look at all of the company's contracts and stuff to see if there's something in here that's gonna blow up the deal.
And, um, that is called the leverage model, right? It is, it is having many non-equity partners, right, junior associates, mid-level associates, do a bunch of grunt work that all feeds into the profits for the partners.
Um, now you'll notice this creates sort of a perverse disconnect between what the client is trying to pay for, which is the judgment of the very senior partners, and what their bill is mostly made up of, which is many hours of grunt work from junior to mid-level lawyers who, you know, recently graduated from law school.
Um, that is the economic engine for Big Law. Now, the, the bad news for them is that, uh, that's gonna go away. There's no way that five years from now, right?
Again, even if AI doesn't get any smarter than it is now, right?
If it just stays this good, no smart general counsel of a public company is going to want to pay millions and millions of dollars for recent Harvard Law grads who don't know anything about practicing law to, like, catch typos, right?
Like, AI is just gonna be good at that, right? So the, the Big Law business model is going to break. But the good news is the clients don't give a shit about, like, you know, grunt work by junior associates anyway.
What they're trying to buy is the judgment from partners.
And so the big law firms need to figure out a way to move from this cost-plus model that they, you know, have been on for a long time, and doesn't make a lot of sense, to a value pricing model, which is what the client is trying to buy anyway.
Um, and so step one is, like, figure out, and this is what I'm helping with, the internal systems that allow you to efficiently, like, deliver and execute on the judgment of the senior partners, uh, without having to rely on the sort of pyramid-shaped leverage model with the billable hour in order to make money.
So I could go a lot of ways with this, but I'm actually gonna ask you to, you know, look into the crystal ball here. And [clears throat]
'cause this has big implications for just the market of, I would say, knowledge work. And [clears throat] you know, it's, it, it...
I, I get the thesis, the high-end knowledge work judgment, more valuable than ever and value directly accruing to that. But, um, I have a hard time imagining that, like, the net market value of knowledge work increases.
In fact, it almost seems like it would decrease, like the overall market cap, because a lot of the, what we would call m- uh, knowledge work otherwise, the legwork, the billable hours, um, that, that collapsed to token price.
Um, what do you... You know, I'm, I'm spitballing a scenario here. Where am I wrong? What is your view? W- where does, like, the future of knowledge work go, you know, with legal as the, as the, as the case study here?
Yeah. I think what you are wrong about is Jevons Paradox. Um, I, like, there is so much underconsumption. I mean, there, there are a lot of answers I could give as to why Jevons Paradox makes you wrong about this.
Um, uh, the first is that there is a lot of underconsumption of law right now. Um, you know, uh, like you guys are spoiled, uh, because you have me as a lawyer.
Uh, but, but for most people, hiring a lawyer, uh, it's like a painful process. It's, like, really difficult to know how much it's gonna cost. The billable a- Like, nobody likes the billable hour. It's a baroque process.
A lot of lawyers sort of give, like, hard-to-understand advice. It's, like, so expensive. Um, and so lots of people just don't do it. And so there's a huge amount, right?
Think about, you know, the price of lawyers going down and the pricing making more sense moving away from billable hour.
I think there are a lot of people that are, should be consuming legal services that aren't right now, uh, and they will in the future.
And, like, that's another source of, of demand for law that w- a huge one that'll be unlocked. Um, also just the leverage that these tools give, uh, lawyers.
It's, it's easier now than ever to start a small or solo practice. You just don't need the same infrastructure you did before. Uh, you can... Like, legal research is easier and cheaper than it's ever been.
Uh, writing emails, reviewing contracts is just much easier. And so, uh, like, setting up a law practice will be much easier. Um, uh, think about litigation. Uh, it used to be
that in order to send a scary demand letter, right, something that, like, looked credible, making a threat, you needed to hire a litigator who would vet your case.
You'd have to pay them a bunch of money, and they would need to agree that, like, they could put their name on something.
Now anybody with ChatGPT can spin up a credible-looking demand letter, and a really long one, and some of the claims might be real and some might not, and so you need an actual lawyer, uh, to look at this, right?
There'll be all sorts of new legal questions that will arise because of AI that are novel and not something that LMs, uh, will be super well situated to deal with, right?
To, to choose an area that, like, you know, you all will know about, right? Think about the intersection of agentic commerce and digital assets. Um, right? Think about, you know, like what OpenClaw does today.
Uh, let's imagine three or four generations smarter than OpenClaw is now. What are people gonna do with those agents? They're gonna say, "Go make me money." And the agent will, you know, think, you know, really hard.
How am I gonna make money? Okay, there's this DeFi protocol that's inefficient. Um, you know, like, uh, I, I can find a way to arb it. And so, you know, and so agent will come back to say, "All right, I have a plan.
You know, give me, you know, a million SATs or give me, you know, 10,000 USDC or whatever." And you'll say, "I don't really have a 10,000 USDC. Here's 1,000 USDC." Agent will say, "Fine, let me see what I can do."
Agent will say, "All right, I can't arb this protocol with 1,000 USDC, but this is a really good idea and I could convince others.
So let me go post, uh, on, you know, Reddit or Twitter, and I'm gonna do a token offering. And my token offering is going to give people upside in this arbitrage thing, and so I can, I can raise money."
And so it issues a token, and then it, it takes in a couple million USDC. And then, all right, like, this is gonna be really complicated to, um, arb this protocol, so let me write this sort of trading bot, uh, code.
All right, like I figured that out.
Right now I arb the protocol and, you know, uh, and then it makes all this money, and then it needs to pay out all of the token holders, and then it gives you money and, and, you know, it's, it's fulfilled its reward function.
It's made you money. In the course of the hypothetical I just made up on the spot here, right? Like this, you've not foreseen anything that that agent would do.
You just said, you, you put in a prompt, which is, "Go make me money." And then the agent did an unregistered securities offering, wrote valuable IP in terms of the, the trading bot.
Maybe the arb that it did is a sandwich bot attack, which is securities fraud. It also made you money, which has tax gains and losses. And again, just as a reminder, you just said, "Go make me money."
None of this was arguably foreseeable. So figuring out even what this means under the eight legal regimes I just mentioned is, like, just a plethora of problems. So we're not gonna run out of law stuff to do, right?
It's gonna be all-time highs for law questions. Um, uh, like I, I think there will be roles for humans. The thing that is going away, and right, you know, a lot of people email me and say, "I'm, I'm-"...
think about going to law school, like is now a good time?
And my answer is, uh, if you actually want to be a lawyer, if you have a sense of like why you wanna do this, now might be a terrific time to go to law school because it's never been eas- Like for high agency people, people who just go out and do things, this is a terrific time to be a lawyer, like genuinely.
Um, if you're going to law school because you don't know what else to do and you think it is a guaranteed path to sort of an upper middle-class life, that's a really bad reason, 'cause that is probably going away in the same way that it has sort of gone away for entry-level software engineers.
That used to be just a great ticket to a great salary right out of school, and now not so much. The same thing's gonna happen with law. But that doesn't mean that the, there won't be value for humans. I'll wrap this up
with a curveball, which is, okay, got you to talk about law. What's something interesting you're doing with AI that's like not related to, to law or legal? I mean, um, you spend all day staring into the,
in, into the terminal or the desktop application, depending on your preference for the harness. I don't know.
What's something interesting you've done that's outside of the, you know, the legal beat and the, uh, you know, I'm just curious.
What's, you know, give me a, a side project or a interesting thing that you've seen that's caught your interest. Uh, I'll give you a boring answer and then an interesting answer that, that I probably shouldn't get into.
But, um, the boring answer is I use it as a, as a really good travel guide.
I've been traveling a lot recently for my consulting work, and it's just amazing to have this thing in your back pocket to suggest restaurants, to do a walking tour of a city.
It's just infinitely knowledgeable in exactly the domain you want it to be knowledgeable, right?
The, the things that would be interesting to me from a tour guide are, are different than things that would be interesting to you.
And so having that level of just like instant, on-demand information personalization is really cool. Um,
I've also used it, so I find, you know, call it two to four times a year, I find, uh, doing like a psychedelic reset to be very useful for just like, you know, personally, professionally, my mental model of the world.
I, I find that's very helpful. Um, but, you know, as people who've done this before might know, um, it's not without risk.
Uh, and, uh, it's something that you wanna like take seriously and, and spend a lot of time preparing for.
And so I created a Claude Cowork session, which is like a psychedelic therapist where, you know, I talk about sort of my ideas and my experiences and, and all the preparation I'm doing.
And I'll say to it like, "I want you to do like PhD-level research on what, you know, Freud, and Jung, and the Buddha, and Ludwig Wittgenstein, and all of the sort of like knowledge traditions would say about this type of thing.
Look at all of the things that you think would be analogous to this, and then come back to me with like the two or three things, you know, from philosophy and religion and human history that you think are the best lens with which I should look at this experience I had."
And it's fucking amazing at that. Like, it's really, um, it's not something that you could have asked of a human. Uh, and like I found that to be a sort of surprisingly very powerful use case. Curveball.
I love that greed. Yeah, that's crazy. We both got long hair. I think you can probably- [laughs] Yeah. You're, you're in good- I will say, you know, s- someone who isn't me- You're in good company, Zach...
may have tried to use a keyboard when under the influence of some unknown thing. It, yeah, good luck typing, um, [laughs] under the influence. No, this is a, this is a before and after thing. Oh, okay. Okay. Yeah.
I, I would think, I would think during, i- if you could even manage that, uh, would be a recipe for a bad time. Yeah. Do you take notes? Like, are you lu- are you, are you lucid enough to have notes make sense?
Yeah, I usually, I usually take notes. Okay.
But, but like my view on this is like the purpose of that experience is to experience it, and then like hopefully it's not going to be subtle, the things you're supposed to realize, right?
I'm, I'm a big believer in like, you know, I don't use drugs recreationally, but like, you know, I- I'm b- big dose, blindfold on, like reset.
And, um, yeah, there's usually, there's like a lot of notes and thought about it afterwards, and that, that is where the AI is very helpful. Well, if you're in Bitcoin, you've also got, uh, similar adjacent interests.
Many of Bitcoin's early stories come out of similar tales. Zach, thank you so much for your time and your insights.
Really appreciate you having me on the show and, uh, would love to have you back whenever we need to come back to the story of legal and knowledge work. My pleasure. Cheers. Thanks, Zach.
We need a neologism for that, like psycho clanker punk or something like that. [laughs] Yeah. Um, uh, trip prompting or... Yeah, I'm trying to like- Ooh, I, I like trip prompting. Yeah. Uh, yeah. Um, okay.
We'll, we'll have to go back to the drawing board. We'll have to- The clank hole. Yeah, the clank hole. [laughs] The clank hole. [laughs] That's, that, that could, that, that could be misconstrued. Yeah.
Anyway, um, really fascinating kicker question there from- Yeah... or answer rather from Zach. Yeah. Um, we're gonna keep on going. We're gonna go back to the markets. We're gonna go back to NeoClouds.
If you thought we were done talking about data centers, you're wrong. We're gonna go back to data centers, um, talk about some furk, some wolf, other four-letter words that you're allowed to pronounce on polite show.
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All right, Charlie, we're gonna hop on over to one of our favorites here in terms of our universe, not preferential, but a company that we cover a lot, and that is TerraWolf Fun company to cover.
Fun company to cover, and a big news item for them today. The Federal Energy Regulatory Commission has authorized TerraWolf subsidiary Chesapeake Data to purchase the Maryland's Morgantown generating station.
This hit today, and it is a big milestone for TerraWolf in terms of getting this site online and running. That being said, there are still other hurdles for it to clear.
Before I get into the details of what went down here, this is only, uh, green-lighting the acquisition of this data center and its energy-producing assets, or this site and its energy-producing assets, excuse me.
The order only clears the ownership transfer. It does not permit data center construction, new or repowered generation behind-the-meter power sales, and any changes to interconnection or capacity rights.
So it's just one step of many, but it is a very significant hurdle for them to clear in order to get this site online. Now the-- Now a background on this site for those of you who may or may not remember.
TerraWolf announced this acquisition in February.
The initial phase is eyed at five hundred megawatts on the two hundred and fifty acre site, scaling to as much as one gigawatt of load, and it's paired with additional generation and battery storage.
So the idea here is there are coal plants on this site. TerraWolf plans to convert them to nat gas and gas fire generation, and they will not be resu- restarting the retired coal units.
And they hope to have batteries on site to bank the excess energy that they produce on site and have optionality to sell it back to the grid and support wholesale prices on the grid accordingly.
We have a really good interview from Nazir Khan back in February or March of this year, where he talks about how they are structuring this to make sure that they can be both consuming this power on site and also piping it to the grid when needed.
If y'all are interested, definitely recommend go checking that out. So what happened here, Charlie, is FERC overruled some local regulators in terms of their opposition to this site.
The first one was a PJM capacity fight, and this is really the bulk of the story as to why this was kind of up in the air until FERC gave the go-ahead.
PJM's inter- independent market monitor, Maryland's Office of People's Counsel, opposed the approval, arguing that redirecting Morgantown generation to the data center would tighten supply and raise wholesale prices.
FERC rejected this condi- rejected, um, this condition trying to bar TerraWolf from pulling the units from the capacity market.
And the reasoning for this was that the commission found TerraWolf owes-- owns no other PJM generating assets, so it doesn't have an incentive to withhold the Morgantown capacity to benefit its portfolio.
But if TerraWolf did own another PJM asset or tries to purchase another PJM asset, that could be an issue. The reason here being, if all else being equal,
TerraWolf pulls this capacity from the grid for its own use, but it also owns another generating site, then there are misaligned incentives because if TerraWolf is pulling capacity, all else being equal, wholesale power prices could go up, and then they could benefit from that from their other site by selling energy to the grid.
So it creates these perverse incentives that the FERC regulatory-- that, that FERC says it wouldn't be okay with. But they don't own anything else in the PJM market in terms of power-generating assets.
In fact, this is the only site that TerraWolf is eyeing that has on-site generating capacity. Their flagship site, Lake Mariner, does not, nor does Lake Cayuga, nor does the Hawesville, Kentucky site.
So pr- FERC said that's not a problem. They don't own anything else, so they won't be able to materially benefit from any spike in energy prices 'cause they don't have another site.
The other thing that FERC shot down is this challenge to the Google warrants that Google holds as a result of their-- its Fluid Stack deal in Lake Mariner.
So Google has a stake in TerraWolf in the form of warrants, and Public Citizens, the NAACP, and Port Tobacco River, um, Conservancy tried to dismiss this application because of the warrants, saying, "This isn't just about TerraWolf.
If Google has a beneficial ownership of TerraWolf, then they also need to be considered in this, and they have a huge data center and energy footprint."
So those warrants, they said, created something of a conflict in terms of the approval because you have to bring Google into this if they have beneficial ownership.
FERC accepted TerraWolf's position that the unexercised warrants, which they are un-unexercised, confer no current ownership or voting rights or control, so there's really no problem here.
So those were the two big pushbacks on approval for this site.
Going forward, TerraWolf has approval to finalize the acquisition, so we will be keeping an eye out over the coming weeks and months to see if the acquisition finalizes. Thank you for that, Colin.
What a doozy [laughs] of, like, a detailed, uh, cascade of different names and, uh, jurisdictions. Appreciate your, uh, focus on that. Yeah, there's a lot there.
And Paul Prager, if I can find it on the fly here, had a really good response to a Twitter reply this week where, I don't know if it was a TerraWolf shareholder or if it was just a talking head, but, uh...
Yeah, here we go. I'm gonna just throw this up here Um, let me get, here we go. Perry Lynn, uh, was commenting on a reply to one of his tweets, says, "Do you think Wolf has found a bottom now? If no, what is?"
I hope so, but probably not. There's potentially a rally. There's potential- there's a potential rally to a couple of dollars, but I think we can retest lows and maybe head to 16. Who is John Galt? Classic. Mm.
"Strategic mistake for TerraWolf to think they could do biz in liberal states. Execution risk is real. They need to pivot to free states and not overly regulated liberal states."
And Paul Prager responded, "Actually, our sites, if anything, are more valuable than ever, given they are fully contracted, already approved for operations with committed energy and existing energy infrastructure.
We are fortunate to have been first movers and early."
He's mostly talking about the Lake Mariner site here, for sure, because there was the data center moratorium in New York, and people were freaking out about what this means for TerraWolf.
They said that the Lake Cayuga site's energization timeline is so long as such that they don't think that the moratoriums will be an issue.
They think they'll be lifted by the time that they seek energization and permitting at that site, or rather energization, excuse me.
But for Lake Mariner, that is not affected because they already have full regulatory clearance to run that site and to-- and it's already operational.
But I do think the reason I wanted to bring this up is because when you look at Pennsylvania too, not a, you know, no ma- data center moratorium like New York, not as stringent, but there was significant pushback
on this site specifically. And excuse me, I, I need to revise that. Um, not Pennsylvania, Maryland, excuse me.
But so still a blue state and for this site specifically, you do have to ask yourselves like how-- are, are these headaches worth it?
I mean, if they can get the deal done, obviously they are, but there's a long uphill battle with these things.
The fact that they had to basically quell two dissenting viewpoints from the localities and local regulators, uh, kind of shows that there are certain states that just fundamentally are going to fight you more on these builds.
But TerraWolf securing a win here with FERC dismissing those concerns. [sighs] Yep, they move fast, so speed to power also means speed to permits. So, uh, uh, yeah, love to see it.
This wraps up our live- Oh, no, Charlie. Got one more story. Oh, oh, oh. Whoa, whoa. We got- Got it. Doesn't wrap it up We got one- I'll tag you back in. Pull me out...
one more to just briefly note on, um, this interesting- Oh, yeah, this is going down-- We're leaving New York, we're going down to ERCOT.
Yeah, just, uh, going down to the Lone Star State where they want you to build and rip energy-generating assets all day long.
This is a note from Morgan Stanley where they see Cipher Galaxy upside from ERCOT's sixty-five gigawatt batch zero. Uh, this-- The headline muddies this a little bit.
What's specifically happening here is that Morgan Stanley estimates ERCOT classify about sixty-five gigawatts of large load requests as base loads, which potentially clears advance- advanced, uh, data center projects to move forward toward grid connection.
The TLDR here is that if the base load, if these loads are considered base load, that covers operating projects, uh, sufficiently, um, base load covers operating projects and sufficiently advanced developments supported by qualifying prior studies.
Ma- meaning that they could circumvent some of the more onerous, [clicks tongue] uh, some of the more onerous paperwork for the batch zero, and they might be able to duck having to be included in that process entirely.
Morgan Stanley says, [clicks tongue] um, it-- the, um,
I'm quoting here directly from the Blockspace article, "Morgan Stanley's estimate is thirty gigawatts above the bank's previous expectations and could benefit site operators with mature interconnection positions."
They specifically identified Cipher Digital and Galaxy Digital as having preferred exposure to the process. Morgan Stanley expects about two gigawatts of Cipher-submitted requests to receive base load treatment.
And again, if they receive that base load treatment, they aren't going to be as scrutinized or have to go through as much rigmarole as ones that aren't considered base load in the batch zero process.
So potential tailwinds there for Cipher and for Galaxy. Okay. So go build in Texas. Maybe don't build in New York. We'll see. On that note, we're wrapping up.
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