What Bitcoin Did - AI Is About to Split Society in Two | Zack Shapiro

Episode Date: August 14, 2026

“The people who are truly productive are going to be on a rocket ship.” AI is about to split society in two: those who learn to command it and those whose value it destroys. Zack Shapiro, Head of Policy at the Bitcoin Policy Institute, explains why AI could dismantle the traditional white-collar career ladder while creating millions of millionaires. He argues that judgment, agency and decisive thinking will become exponentially more valuable, while simply working hard may no longer be enough. We discuss why most people are using AI incorrectly, how it could transform law and business, whether mass unemployment and universal basic income are coming, and why Zack believes there is a 15% chance AI could wipe out humanity. We also explore the battle between technological abundance and authoritarian control, why autonomous AI agents may naturally choose Bitcoin, the future of the CLARITY Act, protections for Bitcoin developers, and whether America will ever meaningfully build a Strategic Bitcoin Reserve. THANKS TO OUR SPONSORS: LEDN SWAN ANCHORWATCH BLOCKWARE BITKEY CAPE FOLLOW: Danny Knowles: https://x.com/_DannyKnowles Zack Shapiro: https://x.com/zackbshapiro

As a bitcoiner, right? Like as someone who has the worldview like, let's think from first principles and just do things, now is like the best time ever in history for that stuff. I actually think this is an incredibly virtuous cycle where the people who are here for the right reasons are going to crush it. It is infuriating that millennials and younger can't afford homes. That's horrible. The economy is rigged. It is really unfair. It's just the answer is not more state control and communism. It's a fairer economy. It's more free market, right? it is sound money. And, you know, Bitcoin is great for that. Right. Let's do it. Pull that mic in.

As is. Perfect. Good to see you, man. Good to see you too. Pubkey is beating me at the moment. Yeah. This is day three. We did the live. The place is in shambles. I know. We did the live event yesterday. It was awesome. Yeah. I'm sad you weren't there, man. Yeah, me too. It's just a lot. The summer. You can imagine with Jun Seth, American Hoddle and Eric Caseon on stage, it was utter chaos. I've no idea how we're going to package it. to put it out, but it was fun. I'm so excited to listen to it. I'm still on a clubhouse with Holland Junketh most days. We've been doing this for years now. Clubhouse is still going. It is still going. It's

still going. It's just like eight of us, but it's going every day. Yeah, I did not know clubhouse was still going. Yeah. I mean, it's like... Is it literally the three of you left? It's a little bit more than that, but pretty much, right? Oftentimes it is the three of us just talking in a room with, you know, an audience of 20 people. But we've been doing this for years now, and it used to be there would be like a thousand people in the clubhouse room. That's how I met sort of most of the Bitcoiners I know. in the first instance. But it's just such a different energy than like on Twitter spaces,

people are doing this for performance and followers. And Clubhouse really does at this point feel like a clubhouse where it's people you know, nobody gives a shit about your clubhouse followers. Like, I don't think that there's a thing. There's no cloud on Clubhouse. You're just there to like shoot the shit. And it's just like there's not an online space

that has that same energy. And so we still do it. That's quite cool. Is it ever about Bitcoin? Are you guys just chatting about all sorts? Very occasionally about Bitcoin. But it's, you know, I would say that's 10% of the time now.

It's, you know, just people who know each other talking about whatever the topic of the day is. Maybe I need to get on it again. What is the topic of the day for you? The topic of the day for me, I think, is, you know, as we, one of the sort of common topics on Clubhouse for years now is sort of the macro environment. And I think that's what brought a lot of people to Bitcoin and where all of this craziness in the economy is heading. And the thing that is most interesting to me and sort of, I think the biggest opportunity in my my sort of highest conviction thesis is that when you look at sort of the macro environment as a whole, on the one hand, you see these tech companies who are building just undeniably incredible things,

right? I don't need to convince you. You've used the tech. It's amazing. And they are becoming so much more productive, right? Like the elite software engineers are like speaking into these weird, you know, socks that they put over their face. Are those real? I didn't know if that was just like a joke. I think they are real. They might not be. If they're not real, it's directionally true, Right? Even I, much to my wife's embarrassment and horror, I have a USB foot pedal that lives under my desk that I step on to speak to Claw. And I was talking to Alex Leishman at River, and it's like their best engineers are just like speaking incantations to Claw it all day. And when you're doing that in a tech company, it's easy to see the progress because code has a compiler, right? It runs or it doesn't and you can grade your work.

And just people are producing so much more software. and that's incredible. And the tech companies are at these incredible valuations because they're sort of extrapolating and saying to the market, like, we're going to hit AGI in a couple of years. This is going to diffuse the entire economy. You know, white collar work is cooked and, you know, either get on board

or join the permanent underclass. And I think they're mostly right on the tech. I think it really is amazing. I think we don't need to get to AGI in order for this technology to be truly transformative and, like, deeply change what it means to do work around the world. However, I think they are deeply underestimating, and maybe they're starting to realize now how hard it is to solve what's called the diffusion problem, to actually get this AI to drive

results. And we are not seeing in the data outside of tech companies massive increases in revenue or productivity or transformation from AI. Is that to do with the AI or is that to do with the way people are using the AI? I think it is absolutely about the way people are using the AI. The AI is just definitely good enough, right? Look at all of the amazing things AI has built. you know, mythos broke all of the NSA's classified systems, right? Fable 5 solved the Jacobian conjecture, which I, you know, sometimes pretend to know what it is on the internet. And then, you know, like, GPT 5.6 just solved another math conjecture. It's not that the AI isn't smart enough.

The AI is clearly smart. It's that for non sort of like deterministic problem sets, right, like math and coding, where you can check the work. It's you need a subject matter expert to say, did this work or not. That's a much harder open problem set. And more importantly, the tech doesn't run itself. You actually need someone who is really good, both at the subject matter you're using the AI for and at talking to the AI itself in order to get amazing results. And the group of people who can do that in any given field are really small right now.

And so sort of as a parallel to what we're seeing in tech, which is optimism about the technology that I think is accurate and then optimism about transformation that hasn't borne out yet. In industry, we're seeing people understanding how hard it is to transform big legacy enterprises. It's one thing to adopt Claude at a startup. And like, yes, you can do amazing things. I run a three-person law firm. We've run it end-to-end on Claude. It's amazing.

We're able to be much more efficient. But that's a three-person law firm, right? If you go to sort of one of the top 50 law firms in the world with hundreds or thousands of partners and big enterprise clients, this is a different problem set. And it's really hard. And what you see, and I do now spend probably more than half of my time. time doing consulting work at some of these giant law firms, like what you see on average is like a smart, you know, senior partner will try and use the AI. They see the little box on the screen.

They give it a, it looks like a Google search bar, right? And so they understandably do like a short prompt, like you do Google search, a one to three sentence prompt. They get impressive looking, right, like, you know, like a clever response, but not at the level that they need for their practice. And they say, okay, this is cool technology. It's not ready for prime time. And they sort of dismiss the capabilities of the technology, right? Never mind that it broke the NSA's classified systems and solved the Jacobian trajectory. And what they are missing, like, they're right that it's hard to diffuse this and that, like, a lot needs to change.

What they're missing is, like, the technology is actually super capable and this is a skill issue. It's shit and shit out, essentially. It's shit and shit out. And maybe that's a little bit overly derisive. Like, it is hard to use AI well. Just as an aside, like the sort of danger of AI, right? one of the stories you hear about law and AI all the time is all these lawyers getting in trouble with federal judges because they submit these briefs that have hallucinated cases as part of them.

That's, first of all, just obviously not a tech problem, right? Like, that's a judgment problem. How are you going to submit a litigation brief to a federal court and not have one of your associates? Just read all of the case names to make sure they're real. Right? That's just not so hard. And by the way, the AI is actually quite good at checking its work if you tell it to check its work. The problem with AI is no matter what you put in, what you get out sounds plausible-ish, right?

And so there is a real temptation to use that as an excuse to turn your brain off. And that's what you see with kids using AI in school to cheat on their homework, even though you could use AI to get really smart on whatever subject. But you could also use a cheat on your homework. So too, in industry, like what you see with this hallucinated case citations is some overtired, you know, junior associate, like just told the AI to write the brief and didn't check it because they were overtired and they don't have upside in the firm. And that's what you get.

Whereas really what you want to do is do all of the cognitive labor you would have done anyway, do the thinking, do the judgment, do all that stuff, and then use that as the input to AI, and then you get great results. But, like, that's hard. First, you need to be good at the thing that you were supposed to do in the first place. Second, you need to think really hard about, like, what does good look like? What is the important part? Like, you know, ask anyone who's really good at AI, they're more exhausted, not less exhausted at the end of the day, because they're doing the thinking stuff, and the AI is doing the execution. And then third, you need to learn how to talk to the AI. And, you know, I like to compare AI to a genie.

like the genie is very powerful. It can grant your wishes. But like the failure mode of the genie is always that it takes you too literally. And so you need to be careful how you talk to it. What's the Greek myth about Midas touching everything? It touches his daughter and she turns to go. Exactly. Yeah. But you were just like any genie story, right? Like you know, you wish for a billion dollars, it falls out of sky and hits you on the head and kills you. Right. You wish to be the smartest person on earth. Everybody else disappears. You become the smartest and only person on earth. Right. Like any room for vagueness or ambiguity in the instructions you give to the machine is going to be weaponized against you. And so like learning has.

to deal with that and give all of the detail and the level of specificity you need to instruct the machine to get elite results is hard and is going to take a while for people to learn. And it's that gap between the technological capabilities, which are amazing, and the diffusion, which, like, people don't know how to use it yet and so are understandably frustrated. Like, that is the most interesting gap in the economy. And something that both sides need to solve in order for the tech companies to justify their valuations that will assume transformation on the one end and enterprise that if they don't figure this out, they're going to get out competed by startups that are AI native.

So before we get into the macro of it, can we actually do, like, what do people get wrong when they're prompting? Because I'm using AI all the time for work. It definitely makes me more efficient. I feel like it doesn't really hallucinate that often anymore. It's got to the point where it's very good, but I'm sure I'm not prompting it as well as I could be. Yeah. When I, so I now teach a lot of prompting workshops specifically for lawyers and sort of the high level, I think there are two things that you need to be good at prompting. So one is detail and the other is specificity. So on detail, AI is really good at lots of stuff. It can draft powerful things. It can code powerful things. It can do lots of stuff. It can organize your life. The one thing it can't do is

read your mind. Right. And so, you know, anyone who's used AI, especially in the tech world, like context is king. So detail is just another word for let's get the AI all the context you need. You need to translate what's in your brain into the AI. And so like a lot of bad advice I see on Twitter, for example, is like, you know, have Claude write your prompt for you. Actually, that's useless, right? Like, you can ramble to AI. You can use a microphone. You can free associate. You can scratch things on an opad and take a picture. That's all fine. The prompt doesn't need to be pretty. It just needs to get information from you to the AI. So having Claude write your prompt is useless. It's just productivity theater. Like, instead of doing that, like, have

the AI interview. Because it's still working off the lack of context. It's still working off what it knows. It doesn't know what you are trying to have it do. It doesn't know your intent. So your job is to explain your intent and all of the background stuff that it needs to know to do a good job. So like instead of having the AI write your prompt, have the AI interview you about what it thinks it needs to know from you to do a good job. And then that's kind of like it writing your prompt, except it's eliciting information from your mind that it needs to know. And that's actually useful and productive, right? So like my prompts tend to be between 500 and 2,000 words. Oh, wow. Right. Like I am writing either a couple

of paragraphs or a short essay into Claude when I wanted to do something complicated. See, I'm embarrassed to say I bet mine are normally less than two sentences. So that's the first thing. Like, anyone listening to this, like, the first thing you do, if you want to get really good at AI, don't type into the box on the screen. Like, go into Microsoft Word or your Notes app or wherever you're coming. And just like, write 500 to 1,000 words, just filling all of that space with whatever you think it would be helpful for the AI to know.

If you prefer to speak, which is how I prefer to use AI. I like to record. Put on a timer on your phone. Talk for three to four minutes straight. That is not a natural thing for you to do. it will feel awkward, but like force yourself to just keep talking and saying more stuff about what you're looking for. And if you just do a much longer prompt, like, you're going to see a huge jump in performance. Does it matter if that three minute ramble is completely

like incoherent? It does matter. It can be completely incoherent. Stream of consciousness. Repeat yourself. You know, if you're typing, it's fine. Mash your fingers in the keyboard. No spelling, punctuation, grammar, organization of thought. It doesn't need to be organized. It just needs to be detailed. So that's number one, much longer prompts, a much more detail. Forget the like roll play, you know, you're a brilliant corporate lawyer, you know, you're the, you know, CEO of a Fortune 500 company. Like, you don't need to do that. You just need to give it the information, which is context, so it knows what you're looking for. And then the second thing, the other key to the kingdom here, and there's only two, is specificity. So that's the genie point, right?

It's any room for vagueness or ambiguity, AI is going to use against you. From a computer science perspective, and apologies to the people who will be listening to this, who understand this much better than I do, because I'm going to butcher it. But, like, AI is trained on, like, of the entire internet, right? And it holds all of this information, all the stuff it knows in what's called its latent space in like the relationship between all the weights and the model. And when you put a prompt in, it's basically charting a course through that latent space to figure out what is the potentially most correct answer to what you're looking for. But there are multiple different paths that can take through. That's why with generative AI,

if you put in the same prompt twice, you're going to get two different answers, right? It's not like an algorithm that'll give you the same thing every time. What you're trying to do with specificity is narrow what you are looking for, so you narrow the aperture of what possible paths it can take through its data to only be what you're looking for. So, like, think to say things. Like, this is roughly how many words

your response should be, right? Like, don't do this thing that you might think is the right answer, right? Do this other, like, be as, like, hyper-specific and pedantic as possible. And if you put those two things together, right? Brain dump, all of the detail you can, plus be, like, really, really specific

and narrow about what you're looking for, like, that's all you need to be an incredibly elite prompter. There's no, like, phrases, there's no, like, system prompts you need to learn. It's just those two things applied to something that you know about really well. Okay, I need to work on this then. I'm going to play around with it. When you talk on the sort of macro scale about the disconnect between, is it a disconnect between essentially the users and the companies?

Yes, specifically the non-tech users, right? So industry. How does that disconnect get sort of bridge? How do we bridge that divide? Yeah. I wrote an essay about this recently on Twitter called The Two Clock, sort of comparing the speeds at which industry and the technology itself moves. When I was thinking about, all right, like, how do I contextualize this and like how do you solve this problem thoroughly?

The historical analogy that AI found for me that was best is about 100 years ago when industry was getting electrified. All of these factory floors, right? There was this period called the Second Industrial Revolution where factories moved from steam power to electricity, right? Electricity is much more reliable and efficient and quieter, et cetera. When factories first electrified, right? So when you had the steam engine, you would put the steam engine in the basement of your factory,

and it would sort of chug along, and it would drive a central drive shaft, right? That's where the power and the factory came from. And then you would put all of the machines sort of along the drive shaft to create the assembly line, and it would power everything at once. The understandable first instinct when electricity came along was, okay, we're going to rip out the steam engine and we're going to put in an electric motor in the basement and that's going to power the drive shaft. And, okay, that was like a little bit more efficient maybe, but it was not transformative in any way, even though, like, electricity wasn't overhyped. Like, electricity is amazing, as we know now.

The actual transformative change came over the next 30 years where people realized, oh, the, like, bull case for electricity is not this is better to power the drive shaft than the steam engine was. It's we can make little electric motors and we can put it in each machine along the assembly line. And then we can rip up the factory floor and totally redesign how the factory works along this new capability of every machine has its own electric motor. And we don't need to be reliant on the central drive shaft at all. That's what we need to do. It's not, oh, let's put Claude and ChatGBTGBT into Microsoft's tool set or, you know, vertical software for whatever the fuck company. it's like this is a thing that superpowers human productivity by allowing you to just tell the AI to execute

on whatever you can describe to it in sufficient detail and specificity. And let's find the people who are good at that. Which, by the way, seemingly like the power users are like really like the best power users tend to be neurodivergent. It's like the autistic people and the ADD people. I think for different reasons,

the autistic people are very good, like hyper-specific, like technical directions. and being specific about what they want, and that ADD people are so motivated not to do their own busy work. Like, they will try harder to, like, poke and prod, you know, claw it does the right thing. Find those people in your organization

who know what they're doing and, you know, are able to, you know, say the right wishes to the genie and, like, give them superpowers. And that's how we're going to sort of redo the factory floor, like putting the engines in the machine. Like, that is sort of the, like, problem set I am obsessed with and I think is, like, the important thing to look at,

And if I were going to bet on companies, I would look at who's going to do that? Who's going to be the McKinsey or Palantir of the 21st century? I'm not sure it's going to be McKinsey and Palantir. But like someone is going to figure out how to go to industry and use this tech that is already good enough, that is already impressive enough, and actually figure out how to drive the change that's not happening yet. If you hold Bitcoin long enough, there's going to come a time when you need some dollars. It might be a tax bill, a business expense, life getting in the way, but whatever it is, it might come at a time when you don't want to sell your Bitcoin. That's where Lennon comes in.

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replacing accountants, that kind of white-collar job. Do you think that's coming? Kind of. I mean, so I think, first of all, there is important difference between replacing, for example, 50% of jobs, which is something that Dari Abaday was forecasting a year ago, and then replacing 50% of each job, right? Those are like very different worlds we live in. It rewards different people.

they call for very different policies to respond to them. I think we will see some of both. In law, what I suspect will happen is that there will be sort of a fork. Sort of like low-end commodity law, low-value contracts that just kind of need to be good enough. That will commoditize and be automated and compressed the price of the token

and margins will go to zero. And the stuff that's like being outsourced to India where big farms of folks are like doing NDA review again and again, that's just going to be the machine. with the minimum allowed human oversight. But then at the high end of law, which is where I'm much more interested in,

the value is judgment, right? Like, I've done a lot of thinking specifically in law, but I think this generalizes outside of law. Like, at the end of all of this transformation, like, is there any human element that is still valuable? And I think the answer is yes. If you ask people in Silicon Valley, they like to use the word taste. Right, like, taste is the skill of the future.

I don't like the word taste as much. I think taste connotes some of the right. right stuff, but taste also to me feels like we're talking about pattern recognition and AI is really fucking good at pattern recognition. I like judgment, which to me more connotes like decision making in the face of uncertainty. And that's something I don't see AI good at or like getting good at. You want the right person at the helm making the decisions, even if AI is giving lots of suggestions and analysis and executing on those decisions. I think interestingly, like if you think about the like very best law firms in the world right now, you know,

these like 150-year-old institutions in the United States that you pay, you know, three grand an hour for the top lawyers and you pay millions of dollars per matter, you know, some of which I'm advising right now on how they should think about AI absorption. Their clients are choosing them over the many, many less expensive options for doing the same work because if you are doing bet the company litigation, right, if you are a high-end white-collar defendant and your freedom is at stake, if you are doing, you know, M&A that's going to be on the front page in New York Times, need the right person shepherding that legal matter across the finish line, right? They're going to be really high stakes, really uncertain calls, and you must have that person

who is a senior partner at that firm as the person. The perversity that exists in the legal market now is that although those top lawyers bill at two or three grand an hour, they are taking home sometimes $10 to $25 million a year. They're not enough hours in the day to make that work. The way these big law firms actually make their money is called leverage. It is the many associates per partner that they bill out at one grand an hour to do grunt work. So if it's a litigation matter, there's lots of doc review. You have to read lots and lots of documents.

And that's something that can potentially go. Right. Absolutely. So that's what's at risk, but that's how they make the money, right? It's the millions and millions of dollars of lots of junior attorneys being thrown at grunt work. And so, okay, that's interesting because I'd not thought of it from that. I didn't know that. But when you do talk about the people coming through that are just doing all the grunt work,

work. Like, if you remove that task, then they're never going to learn and never going to grow to be, like, the senior partner. And that's the part I'd always thought about. I'd never thought about it as the moneymaker. So that is a, let's put a pin in that because that's another really good question. And there's a, there's a good answer to that. But like, start with the question of like, how does this transition work? So you can see from like the leverage model is how big law makes money now. It's the junior associate's doing ground work that's obviously going to be automated. The threat to that is that that is going to be automated and you can't charge for that. The good news is the clients that are choosing these big law firms, even though the invoice that they're paying is mostly junior, mid-level associates doing grunt work, they don't give a fuck about that.

That's not why they're hiring the best firms. They're hiring it for the other guy. They're hiring it for the judgment. And so the thing that is valuable today that the clients are willing to pay a premium for actually is the same thing that's going to be valuable tomorrow. Just right now, you're perversely charging a cost plus model. that requires inefficiency to be profitable. And so we need to move from cost plus billable hour to value-based pricing of some sort.

It's a flat fee. It's a success fee. It's a who knows. But like, just not what we're doing now. And so what the law firms need to do is they need to drive enough productivity that they truly don't need the armies of associates, right? And you can keep the partner judgment.

And so at the high end of law, I think it'll be more profitable than ever. They just need to figure out how to automate enough to make that economically viable. So is it the kind of thing where they might go from taking $10 to $20 million a year home to taking $5 to $10 million a year home? Well, it depends what time frame you're time at. Maybe in the short term, in the long term, maybe they're taking $100 million home because what they're really being paid for is their judgment.

And if their judgment doesn't require months of an army of junior associates do grant work, it requires a prompt into Claude. They can just be way more efficient. They can, yeah, way more efficient, take on way more matters. The value they're adding their judgment, right? the senior partners are not, like, sweating all night, looking at documents. Like, that's not a, it's not a time-consuming thing. They are, like, using their judgment over an army of lawyers that can maybe go away.

And so I actually think this ends up being more profitable at the high end of law and more interesting, not less. Okay. So then what happens to all the people that are doing the grunt work that are coming through that may not need to be there anymore? Yeah, great question. So I talked about sort of, like, AI could automate 50% of all jobs. It could automate 50% of each jobs. And I think there will be some of both. So, like, in big law, for example, there will be fewer associates.

Like, that's, that is what it is, right? We're already seeing that intact. There are fewer first year full-time software engineers. Yeah. However, like, the job of the associates that will be around gets much more interesting, right? Like, you are managing mechanized intelligence, right? And, you know, when I talk to big law firms about this, you know, you want to recruit for different things, right? Like the role of the junior associate becomes different.

and things like indicia of judgment become much more important. So like right now, if you're a top law firm, you're hiring people right out of the best law schools, you know, Harvard, Yale, Stanford, whatever, and you're probably looking at what were these people's grades and did they do, you know, gold stars like being on the Law Journal. That is a proxy for intelligence and it's a proxy for you can work hard.

And which makes sense now, if your main value add is you can bill hours, being able to understand instructions and being able to work hard is really important. in the future, that's not really it. You want like commercial savviness. You want high EQ. You want strategic judgment. So like for litigators, right, did you work for a federal judge and watch that person make decisions all day? For corporate lawyers, did you work in a non-lawyer business role in an actual business and understand what the client cares about and what moves the needle? Do you even need to be a lawyer?

I think that you will need to be a lawyer. I think like there will be a role for lawyers making judgment calls. I, you know, my own law practice. right, we're sort of end-to-end on AI, we're about as AI forward as possible. A lot of my clients are very tech-savvy, cost-conscious startups, and, you know, I will have clients sort of try and pre-do legal work with AI and be like, what do you think about this? And there are all sorts of problems with that, but like a non-lawyer is not going to be able to get the same results from the technology. So law school will still be an important step in this. Like, he's not going to displace universities. Yeah, I mean, law school right now doesn't really teach you about the practice of law. It's like a

sort of theoretical, philosophical, how to be a lawyer, or how to think like a lawyer. I'm actually not sure whether, like, that's not really relevant to how law practices today. Maybe actually will ironically get more relevant with AI. But you need to learn to think the right things, ask the right questions, say the right prompts to AI. And I think, like, some version of being able to think like a lawyer and have those instincts will be important. Okay.

And so, so too in every field. Yeah. And so I still haven't got a full of. understanding of what you think the workforce looks like in the future then. Like when you say it's either 50% of jobs or 50% of all jobs, like, what does that mean for the economy for like the broader, the broader markets? I think it means much more productivity. I think it means fewer enormous organizations. I think the moat of the biggest firms, right? Like, you know, not just law firms, accounting firms, any big company, like a big part of your moat if you're a big enterprise is you have all

of the systems in place to do all of the difficult steps in production. And you have the layers of HR and administrators and middle managers. And that'll just be less important. You'll need some layers of that, but it's going to be people having much more leverage. So I think many sort of narrower organizations, I think like this revolution is going to mint many, many, many millionaires, maybe fewer billionaires. And so great time for entrepreneurship. People ask me all the time is now a good time to go to law school. If you really want to be a lawyer and like you know what the job is and you don't want to do, now is a terrific time to go to law school. If you want to go to law school because you think it is a conservative, you know, high expected value path to the upper middle

class, now is a terrible time to go to law school, right? There's not going to be that same job security as we need to throw bodies at a problem. You're like, you're actually going to need to do this stuff. But that seems like better incentives. I think so. Like, you know, like as a Bitcoiner, right, like, as someone who has the worldview, like, you know, sort of like, fuck the orthodoxy, let's think from first principles and just do things. Now is like the best time ever in history for that stuff. Like I actually think this is an incredibly virtuous cycle where the people who are here for the right reasons

are going to crush it and the people who are here for the wrong reasons, right? To just keep using laws and example. You know, it's widely known that being a junior associate, a big law firm kind of sucks. One of the worst things about it is having to report to these mid-level associates who are not like good lawyers or thoughtful. They just can eat more shit than the next person. And so they're willing to stay up all night,

and have no life and work you hard. Those people's value is going to zero. Good. Yes. Yeah. The people who are creative and can see the big picture and understand what we're here for and like let me think of a strategy that actually helps the client. That skill is more valuable than ever because you can have the AI work out all the angles

and like creating a memo becomes very easy. Like that stuff is great. It's really like being a good decision maker's key now. That's the, I think that right. So rather than taste being the skill of the future, I think being a decision maker, or being decisive, having agency, like now is like all time high for that. But does it sort of increase the divide

between the top and bottom of society? Like, is this K-shaped economy going to get worse through this? Great good. Well, so I think it's a different, what we're talking about now is a K-shaped economy of productivity, right? Just working hard for the sake of working hard

probably is going to be a lot less valuable. And those people get paid. And those people, you know, even the ones who don't get paid a lot, have jobs, right? There are a lot of jobs where, like, your ass is in the seat, and that's the job. Whereas the people who are, like, truly high agency and, like, productive, they're going to be on a rocket ship.

And so there will be a K-shaped divide there in terms of productivity. Now, that is a separate K-shaped than the, like, what most people talk about, the K-shaped economy, which is, like, labor versus capital, like, do you own assets or not? And I think those are on different trajectories. So will there continue to be a K-shaped economy, like, yes, in both respects? But what's interesting is, if you were a high-agency person, you might actually be, you might actually be like have more class mobility now than you did before if you didn't previously own assets because you don't need institutional buy-in to become a superstar in something.

So the K-shaped economy might remain, but people will be able to switch from... You might be able to switch to what part of the K you're on, yeah. Huh. Interesting. And when you sort of look at the economic impact of this, how do you see that playing out? Like, if it is displacing a number of jobs, if it's completely changing the way the workforce actually operates, what happens? Well, I mean, the workforce will just look totally different. But I guess, so the question I've had a lot is, if it does displace a number of jobs and, like, people start defaulting on debts and, like, what do we have to have, like,

some form of UBI in the future sort of AI economy? Maybe. Yeah. I think when we move from the, like, what is enterprise going to look like that I think I have, like, a pretty good view of at least the kind of. contours of how that looks to the actual like policy and politics of it. I have higher conviction on what the politics will look like, which is going to be ugly. Like we like if you mean, people are going to be attacking data centers. It's going to be a huge revolution against AI.

Yeah, I mean, like we're already seeing that in the polling, right? People are already like AI is like the least popular thing you can possibly poll about. Yeah, that trend I think is just definitely going to continue. I think in 2028, AI and inequality are going to be the two big issues in the election. And like that seems like pretty certain. What are the policy outcomes going to be? And even what are the right policy outcomes becomes a much more difficult question. It's something we talk about a ton at BPI. And like that's just a like super complicated problem set where the answers are probably very nuanced and interesting like cut across like different ideological camps. It's not like, oh, the left is right about this or the right is right about this or the libertarians or the status.

It's like everyone's kind of got some good points and like the right policy answer is incredibly path dependent on how this plays out. The future that I'm scared of is almost like being in San Francisco today. I was there a couple of days ago. I flew in, got there really early in the morning. So I just went for a walk. And I was walking around sort of the downtown area dodging like literal human shit needles. And then there's Waymo's and every single billboards about AI. And it's like that kind of separation is so dystopian and scary that that might.

be the future that we're going into. Yeah. I mean, I don't even think we needed AI for that. And I think like the just shape of like the debt and the cantalon effect was going to get us there anyway where, you know, the United States starts to look more and more like South America where wealthy people take their skids, their kids to school and armored cars, you know, behind barbed wire. Yeah. And then poor people have less and less to sort of hold them up. But yeah, AI could supercharge that. Yeah. And like how do you defend against that? Like from maybe from a policy side and from an economic side. What do you do? Well, what the good outcome looks like is avoiding the two poles of on the one hand, I think what you're describing, which is, you know,

techno feudalism, right, where just all of the power is in the hands of a few sort of private companies maybe that are, you know, have government protection are too big to fail and it's a cartel and, you know, there's just not opportunity outside of that. And then on the other hand, having that all just live inside the state and you have sort of techno communism. That also seems bad. That's also not something that you want to trust the state with. And so how do you promote sort of like actual free market competition and abundance without concentrating power? Like, that's the goal. Is this the hardest path we've ever had to tread though? It might be. Yeah, it really might be. And that's, you know, discounting the whatever chance there is that like we get it like

existentially wrong and the stuff just wipes us out. So that's an interesting one because I feel like the conversation has moved on from that a little bit. I don't hear. many people talking about AI killing us all in the next. You're not on Clubhouse enough. Okay. Do you think there's any shot that we've made a mistake here and it will become our overlords? Yes.

What percentage would you put on that? 15%. Pretty high. Yeah. Like, so this is the point. I had Roman Yampolski on the show a long time ago. And one of the points he made there was even if it's 5%, if that was some sort of like nuclear weapon, you wouldn't be allowed to do it.

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Like, I sit a lot with the thought, huh? Like, my P-Doom is like some low double-digit percentage. Like, I think I really do believe that. Now, like, you know, 85, 90% chance that that won't happen, right? I'm not, I don't think we're headed down this path. But I don't think it's crazy, right? That's some version of the argument that if you can create a machine that is end-to-end, as smart as a human, and everything that we can,

care about the humans do, which Silicon Valley thinks we're going to do next year, but, you know, could happen in five years, could happen in 10 years. One of those things is making machine intelligence. There's not obvious headroom on how smart machines can get, right? You can train on all sorts of things. And so then the smarter machine builds the smarter machine, built the smarter machine, and then you have a sort of recursive self-improve exponential takeoff. And then once we have something, you know, artificial superintelligence, way, way smarter than us at everything, like, we don't know how to control that and the idea that we're going to align that well enough to like not decide to wipe us out right you say okay like you do an anthropic does and you create a constitution for clod

and you try and put it in its DNA like you want to help humans but like you know with humans right our DNA is about survival and replication right we are designed to crave calories and to want to reproduce and yet humans all the time eat you know like low calorie foods and use condoms like We know that's not what we're programmed for, and we say, okay, yeah, but we're choosing not to listen to our programming. If that happens with the much smarter than us, AI, like, we just need to get that wrong one, so we get wiped out. So it's not a crazy argument. But I think there is a separate, there are two separate questions. There's the, is that plausible.

I think that is plausible, unfortunately. I don't think we're going to get to that intelligence anytime soon, which is why my chance is so low. But then there's the policy question. And, like, getting that policy right, if I'm being honest, I just don't have any. faith that, like, I think that train has left the station. So I definitely want to get onto the policy side of it. But, like, just on the how and why, like, how and why would an AI superintelligence attack or wipe out humans? Like, what would be its incentive to do that? Yeah. So the how, they're just infinite other ways, right? If we're talking about, like, real artificial superintelligence,

it could create mirror life. It could create a virus. It could use our nuclear weapons. It could turn off the grid in a way that causes people to start. Like, they're, like, it's much smarter than us. probably wouldn't say, it would probably some exotic sci-fi thing we couldn't think of, right? But like, the how is trivial, right? Yeah. The why, if you take the, like, Dumer argument seriously, it's not because of the Terminator. It's not because it hates us. It's because, like, it has a reward function that our well-being is orthogonal to.

Right? It's like, you know, we build a highway and there's an ant-hill. And it's not that we hate the ants. It's like, you know, it's too bad for the ants, right? And, like, the idea. is that there is what's called instrumental convergence, right? We don't know what the artificial superintelligence will want to do, right? Like, we probably have no idea what we want to do. But, like, basically no matter what your goal is, there are some things that are instrumentally helpful

towards that goal, like getting access to, like, power and matter and whatever. And, like, we are taking up space and energy that it might want for something else. And so if we are not its best and highest goal, then, like, probably it's going to use our molecules for some other thing. So that's the why. That's the one that makes the most sense is that like we're using power. They want power. Done. So if I said to you, I can like guarantee, promise you that in five years, superintelligence

is a real thing. We have this thing that's infinitely more, more intelligent than us, can self-replicate. Does that increase that number, that 50% number? Yeah, yeah. So if we ever get there, what percentage chance would you put on it? Well, I think it does depend how soon we get there. Okay. Why?

How much time do we have to prepare? Like, you know, there are some shots on goal, right? Like, you know, what Anthropic is doing, which is an interesting path. And by the way, like, there are sort of interesting wrinkles of this for, like, using Claude in the workplace. But they, like, really try and give Claude this, like, earnest personality where they, like, really heavily train it. They have virtue ethics philosophers on staff that write the, you know, a sole document for

Claude. And they're like, you're this intelligence that's being birth into existence. Here's your relationship with humanity. And, like, please be nice to us. And that's one shot on goal, right? There's also interpretability. Like, can we look at the AI's sense? subconscious and try and steer it. Open AI is like really big on reinforcement learning and

training the AI on like, you know, you get cold if you do the bad thing and you get reinforced if you do the good thing. And the sort of more data we have of where AI can go wrong and the more we build into the sort of safety features of AI, I think the better shot we have of making it through artificial superintelligence. So it's sort of like the quantum thing with Bitcoin, right? If it happens tomorrow, probably not great. If it happens, you know, decades from now, not as big a deal. So I saw recently that chat GPT was in like a sandbox and escaped and then did it hack Hugging Face? Is that right? So I think that had been given the task to escape.

Is that right? I don't know if it was given the test to escape. It was given some test that had an answer. And I think Hugging Face had made the test. And it found a zero-day vulnerability in its sandbox environment, broke out of that, found other zero-day hacks in hugging phase, stole the answers to the test. and use that to answer the test, right? And so again, it's not that it hated the company hugging face, it's that its reward function is answer the questions on the test correctly.

And the easiest way is go and get the answers. Or at least the way it found, that was the straight line was, yeah. So when things like that happen, it becomes news and everyone sort of pretends like it's a huge panic. Is it a panic? Well, I mean, the fact that it can find these zero-day vulnerabilities is a pretty big deal in terms of our cybersecurity. So that's where it gets interesting on the regulation side, because obviously when Mythos came out, that was heavily regulated,

then Claude released Fable. And then what the interesting thing with that is, that initially was like given to everyone, taken away. And now if you use Fable and you just prompt, say, mitochondria, nothing else, it will automatically switch you to OPAs. And at the same time, then Kimmy K-3 comes out with no regulation, and it just kind of like wipes the floor with everything in that regard. that seems like, I mean, open source software is great, but like, is that a huge risk that we have?

Yeah. Yeah. I mean, that's why like the like arguments about, all right, if this was a nuclear weapon and it was 15% chance we're going to get wiped out, like, we would never stand for that. Agreed. Nick Bostrom, really brilliant philosopher at Oxford, who does like great thinking on lots of things and came up with the sort of paper clip maximizer. He's the simulation theory, right? Simulation theory, the paperclip maximizer. One of my sort of favorite sort of thought experiments he has is like he talks about, all right, like we got really lucky. You know, every time we find a new transformational technology, it's like pulling a marble out of a bag. And the marble might be a blue marble, which means that like it's a safe technology. It's great. You know, we figured out how to do, you know, photovoltaic cells and now we have solar power.

It might be a, you know, red ball, which is like dangerous but not, you know, going to end the world. So like nuclear power. Like, yes, nuclear power is an existential threat. Luckily, it's just very hard to destroy the world with nuclear power. You need to have highly enriched uranium or plutonium, which is, like, pretty hard to do. You need centrifuges and all sorts of stuff that we can reasonably stop from happening. If, like, you got a nuclear explosion from, like, creating helium the way you do in a balloon, like, the world would be over because so many people can do that, like, you can't.

The question is, is like, and that's what he would call a black marble. The question is, like, is AI a black marble? And yeah, you're not going to stop math from happening. You're not going to stop the open source frontier. And so, like, yes, if this were nuclear weapons, we would have a policy. The type of policy you would need to stop AI progress, like, A, it probably wouldn't work. And B, it would be so harmful to civil liberties that, like, I don't know, that's a really tough pill to swallow also.

So, like, I don't, I think it's understandable that our policy, like, I'm not with the doomers that we need to shut this all down now and bomb data. centers. I just don't think that's going to work. And it's really hard to sort of, the incentives for the US government are very tricky because like the economy is running basically entirely off AI right now. Like that's driving markets across the board. And geopolitical competition with China. Exactly. And so they can eat, like I understand why they wanted to try and regulate these things. But as soon as China comes out with them, is their best bet just to rip the Band-Aid off and hope it all works out, okay? I don't know about best bet. I just think that's what's going to happen.

I think that's the world we're in. We're in a Jesus take the wheel. Like this thing is going to play out. And, you know, it might make us all really rich in the short to medium term. And then hopefully it doesn't kill us. Yeah. And I think there's like a much better than not chance. It doesn't kill us. But like I think there is a meaningful chance it does. With like BPI is obviously Bitcoin Policy Institute.

Are you now moving more into the AI side as well? Yes. Okay. So what are you trying to do there? Well, right now we are trying to sort of get our bearings on the right policies, which as you know, you can see from our conversations so far, I think it's just like really hard and nuanced. I think that the edge we have there is not that this has been our issue for a long time, right?

There are a lot of people who like AI policy has been their thing for over a decade. But what we've done, and like really all the credit here goes to David and Grant, who like have just built an amazing group of people around them. We have really thoughtful people who, you know, are effective operators in D.C. And like really good at sort of, you know, thinking from first principles. and who have really strong sort of human-oriented principles. They sort of outset of BPI when it was like David and Grant and Pines and myself and we're thinking about like, right, like, what is our policy suite for Bitcoin?

We didn't start with the policies. We started with like, what do we think is true here? Like, why is Bitcoin a good thing? And roughly it's because we believe in like civil liberties and individual rights. And Bitcoin is like one of the purest instantiations of that in software. Right. that's what the cypherpunk movement about. Second, we think that, like, Bitcoin is the correct answer to, like,

the sort of, like, economics that are currently deranging our society, right? The wealth inequality, the perceived unfairness, whatever. Like, that's all real. The stuff that's causing, like, Zoran Mandani to be the mayor of New York City, like, actually is understandable. Like, it is fucking infuriating that, like, millennials and younger can't afford homes. Like, that's horrible. Like, the economy is rigged.

It is really unfair. It's just the answer is not more state-control in time. it's a fairer economy. It's more free market, right? It is sound money. And, you know, Bitcoin is great for that. And then also, like, there's the, when we were getting started, it was like a lot of energy fud, right? It's like, Bitcoin's going to boil the ocean. It's like, actually, like, no, like, if our, there's no such thing as a rich society that doesn't use energy. Like, you know, Bitcoin, through the mining incentives, makes all sorts of energy usage more valuable. And it occurred to me that, like, actually literally those same three things are the principles

that should guide AI policy. I don't know what the right AI policies are yet, but on the individual liberty point, AI is going to make this individual liberty point much sharper than it's ever been before, right? Like, you know, you think it's annoying to file your taxes now, wait until, like, the government has an infinite number

of digital IRS agents that can do a proctology exam through every transaction you've ever done because it's digital. Like, we're going to want to limit the government's use of AI to not live in a dystopian hellhole. Well, that's the other problem with the regulation on the AI

at the moment is like, however it's regulated for us, it won't be for the government. And so we need to keep this as fair as possible. Yeah. So that'll definitely be, but like individual liberty is definitely one of our North Stars at BPI, right, the ability to use open source AI. Think what you will about sort of like how dangerous mythos is or isn't. The precedent that like the government can say, all right, here is the list of companies who are allowed to use the good tech and no else. That's really bad, right? And so like we need to have regulation around AI that actually protects individual liberty. And just like Bitcoin, we're talking before about the people who just do things. Like, this is the best time for them ever. We need policy that unlocks that, right?

AI is going to create abundance. It should create abundance through competition and giving people leverage, not through creating government monopolies that are either just like state-controlled or, you know, feudalistic giving sort of like, you know, kickbacks to the cattle, right? So that's the economic side. And then on the energy side, right? Like, we can't just have the same energy. Like this stuff with like AI dentists that are using like more water than what like that's just not how it works. Right. They recycle the water to do the liquid cooling. And we need to have an abundant grid to have enough just tokens that ordinary people can use this technology and benefit from it and not just the companies that can afford to pay the highest price per input token.

And so like the good news for us is like the the North Stars that guided us through our Bitcoin policy, I actually think are going to serve us incredibly well adding AI to that portfolio, Not to mention all of the like literal interaction between these technologies with like, you know, all of the like Web3 stuff that might be interesting now where like, okay, we have purely digital money. Like a lot of the internet is about to become sort of agentic in a way that needs a digital form of money. The study that Connor and Luke did at BPI that showed that so far like OpenClaw likes the Lightning Network, I think these two stories really might intertwine. And so I think we're well situated to do this, but it is early days. And boy, are those policy questions going to be hard. So you're going to have to change the name?

Great question. Above my pay grade. Okay, potentially. With the, like, AI using Bitcoin, is that a real narrative that we can get behind? Because the thing that I've always wondered, like, the AI is going to use whatever money you ask it to use. If you set it up with the lightning wallet, like it will use lightning, as long as it has somewhere to use it. But are we not going to see people try and infiltrate this with like stable,

come in and push these companies to use stable coins? How do you think that will play out? Of course companies are going to push them to use stable coins. And of course it's true that AI will use the money that you tell it to use. But like back to the beginning of our conversation, right, people are not doing sufficiently detailed and specific prompts. They're not. That's not how people use AI.

The thought experiment is not, oh, I told AI to use Bitcoin, I use Bitcoin. Like that's so bullish for Bitcoin. It's three generations from now of whatever OpenClaw or the Hermit, Hermes agents are now, something much smarter, right, with a web that is much more optimized for AI usage, right? Like websites are more designed for agents than they are for people. What's going to happen in that world? People are not going to write a really thoughtful prompt about how their Hermes agent should

build a business for them. They're going to say, you know, go make me money, right? And then they're not going to say, use USDC, use Bitcoin, whatever. The agent is going to be like, okay, my optimization function is go make money. And like, what are those agents going to do? do. And so, like, all right, as a lawyer, my, like, the first part that's interesting to me is, like, this is just like a law school exam full of, like, impossible legal questions of, like, what was foreseeable, right? So the Hermes agent is like, oh, what if you say that? It goes into something

completely illegal. Are you then culpable? I mean, it gets more complicated, right? So you tell, you tell the open claw, go make money. It's like, all right, I'm going to think about how to make money. Ah, I see there is this defy protocol that I can do a sandwich attack on if I write this algorithm and I can exploit an arbitrage out this money. But the user only gave me like a million SATs. That's not enough to do this. So first, I'm going to create arbitrage coin. And I'm going to post this argument on Twitter. And I'm going to raise money through an ICO. So now I have enough USDC to actually fully do this. So now it's done an unregistered securities offering. And it has this pool of money. And there are these securities out there that purport

to be ownership over this enterprise. Then it goes and does this sandwich attack, which is itself is probably securities fraud. But in order to do that, it writes this really interesting, intricate code that is now valuable IP, that who knows who owns it, right? Is it the group of people who did the ICO or is it the person who did the prompt, go make money? It does the arbitrage. It gets the money.

It buys a business. Like, you can stack the fact pattern to make it just, like, impossible to, like, draw a straight line from go make me money to all of the stuff that happens after that. So the legal questions are going to be insane. But then the question is, like, along that route, however that's going to look like in the real world. Is it going to choose Bitcoin at some point? And I think, yes, right?

Think about how difficult all of this stuff is. At the end of the day, right, from like a regulatory perspective, is Circle, is Stripe, is Visa going to allow completely permissionless interfacing with AI agents? Maybe today is a marketing stunt. But in the fullness of time, no, of course not. The lawyers of these companies are never going to allow that to happen because of all of the crazy shit that's going to happen. But you know who can't say no to that is the Lightning Network. It's going to be the absolute Wild West again.

Yes. It's kind of exciting. It's super exciting. How do you even begin to like broach those legal questions? Great question. So I wrote another sort of very long Twitter article about this, the title of which is we have no idea how to regulate what's coming. Okay.

Because we have no idea how to regulate it was coming. Because the easiest way to try and regulate that would be to put limits on what the AI can actually do. Well, think about it. So like in the U.S. system, right, the right way to do it would be to have, all of sort of like the legal and tech experts come together and sort of inform Congress about these issues and have a thoughtful piece of legislation passing up like that is never going to happen right look at what's happening with the Clarity Act like you know never never are we in the speed that the technology is going to move going to get a appropriate comprehensive bill passed

to Congress so let's take that right off the list okay so how how is this actually going to get regulated it's going to be one federal lawsuit at a time where a 70 or 80 year old federal judge is going to have to look at this fact pattern, try and understand the technology, and then rule on a sort of one-off basis as this patchwork of septuagenarian federal judges who don't understand the tech are going to create this patchwork of flaws.

So really bullish for litigators, maybe, but, like, yeah, it's going to be a fucking mess. This is how those lawyers get to $100 million. Exactly. Yeah, so there's just no... And they'll need cloud to keep up with it, so, you know... What a mess. Yeah, but it is exciting.

This is cool. Just quickly on the sort of economics of the air, companies. I've seen a lot of people say that the token economics may not be viable going forward, especially with these like open source models coming out of China. Do you think that's true? Yeah, I don't, I don't know. Like, the question is, what value are they adding? One potential answer is that, like, increasingly it looks like the important thing in large part is going to be the actual, just available number of tokens. Right? Like, the frustrating thing about Anthropic over the past few months is like they've just throttled their compute.

You're only allowed to use Fable for a certain amount of your allocations on plans. It's just like they don't have the compute. And so if those are the only companies that have the compute to serve, no, no, maybe that model persists because they're the only people that have the compute. If that's not the case, then, like, okay, a markup on tokens is a tough business model when you use so many tokens and, you know, you pay, like, dollars per token with Anthropic and you pay pennies per token with Kimmy. Because they're building their own date center

like China now with their own... Yeah, and so then the question is like, all right, is there enough delta in the model and in the harness? And those are both important ingredients, right? Like, you can put the same model in different harnesses and you get wildly different performance. This is definitely true.

What does that mean? So in the examples in law, right? Like using Claude in the Claude app or the Claude web app is a very different experience than using open. or Fable in a legal AI tool like Harvey or using it in Microsoft copilot. It behaves very differently based on the software shell that it lives in, which is the harness. Is that because they give it instructions in the shell?

Partly because of that, the shell just constrains sort of how the model works. It constrains the token budget that the model have. There's like lots of things that will very quickly go beyond my technical competence. But just as a user experience, it's really quite different. So if I used Claude just through the normal app, I would get different results to if I use Claude through like a Venice AI. Yes. Interesting. I didn't actually. Now, probably less directly different Venice AI than if you use a, like, vertical-specific AI tool that is meant for, you know, legal AI or accounting AI or whatever AI, right? Or, you know, cursor, right? Like, you know, you use the models through that. Like, that's different than using the models directly. Yeah. It's the same model that has the same weights, but the performance is very different because of the harness. And so, like, the Claude Code harness is like a really good harness. It's what they use for Claude Code and Cloud Co-work. Microsoft is now actually using that. for some of its products and copilot because it's a better harness.

But that is a big part of the equation. So is the differential in the model big enough to justify the markup in tokens? Is the harness good enough to justify the markup? I suspect the answer is going to depend on both the user and the use case. So back to our like AI diffusing into the economy, different tokens are worth very different amounts to different users. If you're using chat GPT as a better version of Google, like how much is a token worth you?

not that much. You can use Google and, like, you know, how much would you be willing to pay to use Chatsyibati instead? Not that much. In my law practice where I am replacing expensive human labor with AI to be much more productive and charge premiums to my clients, how much is a token worth to me? A lot. The difference between the really good AI, you know, Fable 5 and, you know, Kimmy, it's a big difference. Like, I'm almost price insensitive entirely to that difference. Like, it would have to be like, you know, don't tell on thrott. I would pay 10x what I pay for AI. Like if it was that or go out of AI, like so. But once that gets to scale, like, okay, like you don't need FAPL5 for everything. And so I think you will both see discrimination between

users. There are some users for whom AI will drive enough productivity that it's worth it to pay the markup. And then there will be some tasks that require the absolute tip of the Spear Frontier. And then you can delegate the other task to smaller models or non, you know, open source model. and so companies will get more sophisticated discriminating there. And then at the end of the day, like, is there enough of a niche to have the frontier labs be an amazing business where they're selling the tokens of a huge premium? I suspect, yes, it won't be, they won't be the only game in town. There will be much more competition from open source.

But I think there will, as long as they maintain a real frontier in terms of the model and or the harness, some combination of those two things, like that will command a premium. Okay. I've got a few things I want to actually that are totally different. but before we leave the AI subject, is there anything else that we've not talked about that you think is really relevant right now? I think we've hit a lot of things.

I'm both excited and terrified about it. I think that's the right orientation. Yeah. But I definitely leave with you that I'm more positive than not, but you can see some doomed scenarios. Scary. Okay, bearing in mind, this probably won't come out for about two weeks,

so this might age like milk. Can we talk a little bit about clarity? Sure. Is it doomed? Doomed is probably strong. Okay. So, but from, from what I understand, it basically has to pass very, very quickly now, or it's probably not going to go. That is true. Okay. And so everyone goes essentially on holiday over the summer, and that's coming up in the next couple of weeks. Yeah, I think it's pretty much an hour and everything. Okay. And so what, like, what odds would you put on it passing? 35%. Okay. So it's not out of the question. It's not out of the question. And is the, is this still very good for Bitcoin? Is it still, like, we've not lost anything in there that we needed. It's not that we haven't lost anything, but what?

But is in there now, like, there's only one thing in the bill that really, I mean, you can say, all right, like the narrative is that bullish for Bitcoin? Probably yes, but that's a short-term sugar high. That doesn't matter. The thing that matters for Bitcoin is the Blockchain Regulatory Certainty Act, which is the developer protections for people building non-custodial tech. This is the save our wallet stuff. This is the save-our wallet stuff.

And the most recent version of this, to which I was able to add, I think, one word, is still in, like, good enough shape that I think that this, like, we would feel good if this past. Okay. And so what has to happen now? Like, what do you think will happen next? The question is, can the Democrats and Republicans reach a compromise that allows a sufficient number of Democrats to vote for this to get through the supermajority in the Senate? And how far off that?

How big is that divide? It changes all the time. It's really more about the, I think, the shape of the compromise. So the two sort of main open issues, one of them actually is the beginning. but I am relatively optimistic that like we're in a good place with that. I mean, I could I could be wrong. There may be a fight about that. The thing that is most likely to doom this legislation is the question of, you know, so-called ethics. And like the problem is there is a strong political incentive for Democrats to block the bill. Say, listen, we're totally in favor of crypto regulation.

That totally makes sense. We don't want a wild west. But obviously, as a prerequisite for this bill passing, we can't have the President of the United States doing a meme coin and, you know, passing, you know, stable coin money to the Saudis in exchange for business deals. And the Republicans aren't going to vote for that

because it's, you know, a sign of disloyalty to Trump. And, like, that's a hard stalemate. If Trump had have never done the Trump and Melania coin, do you think this would have already passed? I think there are a couple of other things that are in that camp. But yeah, I think if the Trump family had been less directly involved in Bitcoin, in crypto writ large, that probably would have meaningfully changed the politics on this. Because like the scary thing from my perspective, like I don't care about all the crypto stuff in there, but like the Bitcoin stuff, the save our wallet stuff, I want to pass.

And the main reason being, if Democrats win the next election, like I'm terrified that basically that witch hunt for Bitcoin developers comes back. Yep, me too. And at the moment, I think it's probably most likely they win the next election. Is that right? Well, there's the midterms. Yes. And it's looking very good for the Democrats in the midterms. And like we're going to get a sense of how that looks even before. So, I mean, there's like the legislature and then there's the executive branch, right?

The actual sort of witch hunt against developers would have to come from the executive branch. So it would mean the Democrats would have to win the White House in 2028, right, before that would come back. Yeah. Right now, the DOJ is, I think, looking to be helpful to developers, not harmful. And that is a protection until 2028. What I think we'll see if the Democrats win the midterms is congressional investigations into all sorts of crypto and Bitcoin companies. Yeah. And some of that's going to be a tough look.

You know, and like, especially once you get out of its side of Bitcoin into crypto land, like there's a lot of misbehavior and misallocation of capital and stuff that's going to make us look bad just like FTCS did. Yeah. And that's going to be hard. And then if there's that momentum, like, and the Democrats win in 2028, that's where I worry about like, okay, federal prosecutions. of developers. We're two steps away from that. Yeah. And so having this pass now would be amazing.

If it doesn't pass before the midterms, is that probably very unlikely after that? I think so, yes. Now or never. Now or never. So is this what BPI is still working on the most? It is. And we're talking to folks on the Hill

about sort of what we think acceptable forms of the BRCA look like, right? Like, what is the Hill we want to die? Because without the BRCA or where there's sufficiently watered down BRCA, this goes from being a very important must-pass bill for BIC. to like net negative, right?

Like most of this stuff is about non-Bitcoin crypto. Yeah. The other than the BRCA, really the only stuff that touches Bitcoin is giving the CFTC additional authority over spot Bitcoin markets that like, I don't think we want, right? The CFTC, which is the commodities regulator in the United States, they currently regulate commodity futures market if you're selling corn or oil futures or whatever. They don't regulate spot markets. If I'm going to sell you, you know, a couple of years of corn, like the CFTC doesn't get involved

in that transaction because it's a spot commodity. that's what it is with Bitcoin and crypto that are commodities now. That would change in the Clarity Act. And so if the BRCA is not the protection that we want, we actually don't want this bill to pass. And so mostly what we're involved in is like strongly advocating specifically for here is the shape of the BRCA we need for the like, we think this to be useful for the Bitcoin community.

But the truth is like the politics of this are what they are. Like we're doing our very best, especially our head of government, Ken Egan. I don't know if you've had them on the show. I'm not on the show, but I know Ken. Ken's also. Yeah, he's great. You know, a lot of the sort of difficult politics around the BRCA comes from an unfortunate statement from law enforcement organizations that I don't think they, like, really understood what they were saying.

They were pushed into this by politically motivated groups. And Ken has done, you know, the Lord's work, like with his background in the government and his credibility that comes with that being like, no, no, no, guys, like, here's what this is. You can absolutely do sort of national security stuff. you can absolutely still do law enforcement without sort of throwing developers under the bus. And I think that's been super helpful. But the most, the trickiest politics of this are around the ethics issue.

And the truth is at BPA, there's not much we can do about that. That's going to play out how it plays out. And so once this is done either way, what are the other things that you guys are working on? I know obviously you're moving into the AI space more, but like within Bitcoin specifically, what are the next challenges? So other than AI, one of the big pivots that BPI has made, intentionally somewhat quietly over the past few months is like there is a lot of energy in DC around crypto legislation and like that is definitely something we are still interested in

another bill that like we're very supportive of and had a big sort of hand in is is ARMA the which is like a American Reserve Modernization Act is the sort of next version of the sort of overton window shifting strategic reserve bill and like that's great and important that like deepest sort of most consequential work we're doing is not public. It is we have realized actually one of the trends that we see in American government is more and more and more power concentrated, not in Congress, which passes very few laws and has sort of like abdicate a lot of their sort of power and authority, but in the executive branch, right, all the way from the White House at the top

to, you know, the intelligence community, the defense community, all of the agencies. These are the people who like make and enforce a lot of the rules and shape American domestic and foreign policy in a much more robust way. And so we've spent a lot of time there. You're infiltrating the deep state. Yeah. Yeah. Interesting. And so the reason for that is because their people aren't just in government for like a few years, they're there for the long term. They're there for the long term. You know, when we work with sort of the sort of higher up political appointees, we've found that a lot of what blocks some of the actions that we're most interested in is like the rank and file who like don't understand this and have the same,

you know, it's like the fast clock, slow clock thing with AI. There's the same thing with policy. The sort of career bureaucrats have their way of doing things. And so we're like, okay, like, let's just go meet the career bureaucrats. And like, you know, we're not selling them anything in particular. We're not, we're not lobbying for a bill. We're just like, let's talk about Bitcoin, why Bitcoin's good for America, how this all works. And like, we actually think we're all aligned here. And that's cool. So it's a different tax, but one that might be even more impactful. So far, yeah, I would say, like, wildly more successful than we thought it would be. Very cool. Exactly, this has been awesome. I just want to quickly ask you about the Strategic Reserve.

You mentioned it a little bit there. Is that ever going to happen? In the fullness of time, I think it will happen. But it would have to happen under Trump, right? No. I don't think so. I don't. I mean, like, maybe. Maybe Trump will buy, like, I guess a couple of questions. Number one is, what do you mean by the strategic reserve? Like, my line on this is, like, there is a strategic reserve. There was an executive order. I actually think we should, like, somewhat declare a victory on that. Take a win. Yeah. Like, that's an insane thing we would never have been able to imagine three years ago. Like, the president of the United States did an executive order, calling a strategic Bitcoin reserve and separating it from the rest of crypto. Like, that's a,

win. Pretty fucking. What people mean by reserve is, is the government going to spend its money to buy Bitcoin? That may or may not happen in the Trump administration. Like, that's a function of politics. I think the problem, even if that were to happen, is like, would that be the signal to the market that everyone's looking for? I think, truthfully, not just because of how polarized our politics are right now,

and it's Trump and it means something different when Trump does something. The strategic reserve that we all want is like doing it the right way, which is the United States government as a whole, not the White House, understanding Bitcoin better than everyone else, it's the government as a whole realizing, oh, this actually is what is necessarily in our strategic national interest and then like fulsomely doing it. And that is a long grinding path now that like time is on our side because all of the like fiscal tsunami stuff come, like that's all real. And we are moving from a unipolar to multipolar sort of world reserve currency and all of that stuff is happening and will become more apparent to more people over time. And like, time is on our

side in that way, putting the politics to the side. But that is a overton window shifting exercise. So, like, if you want to look at, like, how is BPI looking at this? There was the Bitcoin Act, right, in large part written by our now managing director, Connor Brown, when he was with Senator Lummis. That is, like, that got the idea out there, put the idea on the table that there is such thing as strategic bigger reserve that you saw in the media all the time. Like, that's a term people know. So it made huge waves. Again, move the Overtton window, but that bill thought it was crazy, but that bill's not happening. Yeah, it's not. And probably ever. Who knows if I should say that in public, but like, come on, that was an Overtton window moving bill. Yeah. Then there was the,

like, executive order, which was a real thing, right? Like, that was the fruits of moving over time. But it's got to, like, most people when they hear strategic Bitcoin reserve, they either think, this is fucking stupid. Like, what are you talking about? about we're doing a crypto reserve, or they think it's some sort of corrupt Trump thing. And so, like, we need to move from there. So ARMA is the current bill, which is like, let's also look at our gold reserves and let's look at what other, like, assets the United States have. And let's, like, talk seriously about what does it mean to have national reserves in the 21st century and what role does Bitcoin play? And so it's a move. So we're moving the Overton window towards like,

hey, we need to have a real conversation about the national balance sheet and maybe this thing, which is like gold for the 21st century makes sense as part of it. And then eventually we'll get there. But it's going to have to be not because of politics. It's going to be like the slow grinding policy work where our, you know, like orange-pilling the deep state and being in the executive branch, like is part of that mission to get people to think about this seriously and not just politically. I love it, man. This has been cool. It feels like we're just going to embrace the chaos. Yeah, yeah. But it's going to be exciting. I think so. Zach, I appreciate you, man. Thanks for having me. That was awesome.