Unchained - The Chopping Block: AI's Role in Crypto, Agentic Coding, & Citrini Financial Crisis

Episode Date: February 26, 2026

Explore how AI could reshape crypto and finance, redefining traditional systems and introducing new threats. As AI-powered agents promise efficiency, Haseeb, Tom, Tarun, and guest Illia Polosukhin critique Citrini's controversial predictions on a global financial crisis and consider whether AI might just save or further complicate crypto's role in the economy. Welcome to The Chopping Block — where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. Joining us is Illia Polosukhin, co-founder of NEAR Protocol and contributing author to the original transformers paper that's revolutionized AI. Buckle up as we delve into AI's burgeoning role in the crypto world, dissect the sensational claims from Citrini’s article predicting an AI-triggered financial crisis, and explore the potential of agentic coding in reshaping traditional systems. Let’s get into it! Listen to the episode on Apple Podcasts, Spotify, Pods, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Hosts ⭐️Haseeb Qureshi, Managing Partner at Dragonfly ⭐️Tarun Chitra, Managing Partner at Robot Ventures ⭐️Tom Schmidt, General Partner at Dragonfly  Guest⭐️ Illia Polosukhin, Co-founder of NEAR Protocol Disclosures THE 2028 GLOBAL INTELLIGENCE CRISIS by Citrini and Alap Shah https://www.citriniresearch.com/p/2028gic Timestamps 00:00 Intro 01:06 AI Agents Meet Crypto 08:06 Dark Forest Threat Model 15:31 How Close Are We 18:41 AI Coding Risks in Crypto 27:27 Citrini 2028 Crisis Explained 35:01 Demand Shock Missing Money 37:55 Automation Limits and Human Value 44:13 AI Zero Days and Botnets 51:40 Escrow Courts and Enforcement 56:05 Illia on Vibe Coding Future Learn more about your ad choices. Visit megaphone.fm/adchoices

People were telling me last night that like the new street cred in SF is like how many agents you have running in the background. If you have like less than 10, you're like not really cool. 10 to 15 is like how all the cool kids are at. Or it's like that what's your anthropic bill while you're away? Not a dividend. It's a tale of two fun. Now your losses are on someone else's balance. Generally speaking, air drops are kind of pointless anyways.

I'm in the trading firms who are very involved. I like that eat is the ultimate policy. D5 protocols are the antidote to this problem. All right. Hello, everybody. Welcome to the chopping block. Every couple weeks, the four of us get together and give the industry insight of perspective on the crypto topics of the day. So quick intro is Trisica Tom, the Defy Maven and Master of Memes. Hello, everyone. Next, we've got Turun, the gigabrain and Grand Puba at Gauntlet. Yo. And joining us today, we've got special guests, the leader of lobsters at Near Ilia. Welcome back to the show, Ilya. Hello, hello. And I have a sieve the head hype man at Dragonfly. We're early-station investor in Crypto, but I want to caveat. Nothing we say here is investment advice, legal advice, or even life advice, please see chopping block that XYZ for more disclosures. So it looks like AI has come to save crypto.

Cryptos in sore need of saving, and AI seems to be putting the entire economy on its back to drive everything that matters in the world. And there's a lot of excitement going on, continuing to go on, about agentic payments, and, of course, specifically around the software called OpenClaw. So OpenClaw, if you recall, was previously acquired or at least aquaired or something. thing by reverse-mergered by OpenAI. But they're continuing to build the project, Peter Steinberger, who is the original creator, has continued to ship more features and try to make the whole thing more secure.

But many people have tried to build more secure alternatives to OpenClawe, creating this broader ecosystem of what are now called Clause, a term that's been coined by Andrew Carpathie, of being these like kind of agentic, homebrew agents that run in a loop and kind of do things in the background for you with minimal. human intervention. And so one of them is called Ironclaw. And so Iron Claw is one that's built on the Near AI Cloud, which of course is affiliated with the Crypto Project Near, in which, full disclosure, we are investors into Near. Today, it's, I think, the largest crypto AI project in existence. Ironclaw, it's not an Ironcloth, I mean, Neer specifically. Ironclaw is an open source

alternative to OpenClaw that runs in TEE encrypted enclaves in Near Cloud. It's in a Wasam sandbox, credentials never touch the LLM. And it also does some prompt injection protection. I remember looking through the code base and there's like a bunch of redjaxes in there of like checking you forgot the best part. It's written in Rust. And it's really with that.

And it's written in Rust. That's a big one. Ilya, give us a little bit of call. All crustaceans. It's like only crustaceans. Very crustacean theme. That's a big thing if you don't know. Open Claw's got a lot of lobstery things going on.

I also saw that you guys are also a lot of allowing people to just run vanilla open claw on the near AI cloud. Ilya, talk to us about that. Is, is AI here to save us in Cryptiland? Yeah, so there's two things, right? One is, I think I talked about agents and effectively AI starting to do things on your behalf and being the interface to computing for a while now. I think we talked about some of this even, I think it was two years ago at the episode.

and it took a little bit a while, right, for, like, the models to actually enable that activity and, like, really run in a loop and be able to access. It first happened with coding agents, right? So, Cloud Code, Codex, like, a few others. They're effectively a general agent that is control your computer, but they were just, like, tuned for coding, right? They had code in them. What Open Cloud did is effectively removed that limitation and said, like, hey, by the way, it can read your email and schedule your calls. It can go and shop for you on Amazon.

It can go and execute other things that you want to do in your life, right? Your universal assistant and chief of staff. And so that is extremely powerful, right? It effectively changes how we interface is computing. It removes the need for browsers and apps and kind of goes directly to intent of what you want to do to action that AI does for you. Now, indeed, OpenClaw, you know, great idea, but kind of build, like, it's a homebrew

project in the best way, right? The guy was building it for himself, running it, tweeting about it, and then started picking up Steam and more and more people started to use it. And it's exciting, but it's extremely dangerous if you give it all your credentials, if you give it all your things. Yeah. So actually, I want to add a couple stories before you go further there. So there's a couple stories that went viral about OpenClau.

security snafus just over the weekend. So one of them was somebody named Summer You, who is a meta-director head of alignment, or so director of alignment at Meta-superintelligence lab. She was having an open-claw that she was experimenting with on like a, initially like a kind of toy inbox and then moved it over to a real inbox after establishing like, hey, this seems seems to work, seems to be pretty controllable. And she asked OpenClaw to suggest some emails to delete out of her main personal email. And she just kind of wait around for the agent to like suggest what emails should be deleted. And apparently the open claw

just started deleting emails, just started deleting hundreds of emails. And she was like, oh my God, they deleted every email going back before February 15th or something. And she was like, oh my God, please stop, please stop. And like it just would not stop, that it just kept going.

And apparently people suggest that what happened was that there was too much of her, too much emails in her inbox that caused the context window and overflow triggered a compaction event. And that compaction, is when basically the context window's too big, doesn't fit into the memory, basically, of the model, and the model then, or not the model, but the harness that you've built, will go and basically

summarize everything that's happened so far in the context window to shrink it down smaller so you can add more stuff in the context and keep going. So in this compaction, oftentimes information gets lost because you're summarizing, you're not retaining everything. And so presumably what happened was that, you know, very carefully check and, you know, the instructions of do not delete anything before asking me, got compacted into something like, you know, the owner wants you to delete emails thoughtfully or something like this. You know, something like this. You know, something like this. And so it just ended up going, wow, this created a very viral story. Now, there was a second story that's a little closer to crypto, which was an open-a-engineer named

Nick Pash gave his open-claw wallet a 50K in Seoul and an X account, as well as access to a training API and told it, be yourself and have fun. This open-claw proceeded to to be named Lobstar Wild, named after Oscar Wild, and Lobster Wilde created its own meme coin, and somebody, there's some guy, some reply guy, who kept begging for soul, kept begging for free money from this AI. And they begged, I think, something like 50 times of just in the replies every single time asking for money in different ways. And one of the last times that he asked for money, he asked to have four soul for treating his uncle's tetanus, which obviously is not real, but the agent tried to send $300, just trying to say, ha ha, this is funny. Sure, fine, I'll send

you for a soul. So the agent was going to send $300, roughly, for sole to this person, but instead seems to have miscalculated the amount to send them, and instead sent 52.4 million tokens of its own meme coin, which had been worth $400,000 to this user. The recipient immediately dumped them, only got 40K because, of course, it's a very low liquidity meme coin, and this caused, again, another hullabaloo about, oh, it seems like these things are not yet stable enough and secure enough to really want to let them run wild. So with that as a little bit of backdrop, tell us, Ilya, about Ironclaw and what you guys are building at NIR to try to make this stuff more secure. Yeah. And so kind of there's a number of additional challenges which people don't talk about.

So one of them is literally right now everybody's streaming all of their credentials and private keys for that matter to LLM providers. So Anthropic and OpenAI, I right now probably have access to everybody's accounts because they literally in the logs like explicitly have your bare like out key and API keys to everything that you know, claw or whatever LLM used. Even, you know, the codexes and cloud codes are doing that. And so so we kind of in the like weird state where right now effectively everybody's like forgot about security and just going nuts.

and we are living in a dark forest, right? Internet is becoming, you know, was always a dark forest, we know that in crypto, but it's especially true now when everybody else uses AI tools to kind of, you know, try to exfiltrate everything from everyone. And so near AI has been building secure infrastructure

for private inference, for verifiable inference, so you know what you're using, you know that your data is not going anywhere. We're using indeed the secure enclaves and encryption to enable that, But with kind of this rise of clause, indeed the fundamental issues are in the harness, not just in the kind of LLMs anymore.

And so that's where, okay, we need a harness that is actually like designed with the blockchain principles, right? Meaning there is always somebody attacking you, right? This is, there's always like, even if you're a third-party developer contributing something, they probably are trying to break into your stuff. if you're using somebody's skill, they try to steal your money, right?

If you use that mindset, which is, again, in blockchain, that is kind of how we think about everything, right? Smart contracts are malicious by default. The contributions are malicious, supply chain attacks, et cetera. So kind of bringing all that expertise and trying to put together a framework

that is benefiting that. And then, so to be clear, Iron Claw is an open source project. You can run it with your OpenAI or, you know, Anthropic. You can run it on your desktop. or you can run it on your laptop. But we also offer hosting,

which is in the confidential environment, enter and kind of encrypted and uses private inference as well. So you kind of know that nothing is going anywhere. So it's really about like protection and depth, right? The tools are in Indeed, in WebAssembly. We're using what we use for NIR for the smart contracts, something that we hardened for seven years.

We know that it's really not possible to exploit. We use that for now kind of tool calls. We have indeed credentials stored encrypted and injected effectively at the edge versus, you know, being funnels through LLM. And so a lot of this kind of thought, and I mean, we still work in it, to be clear, it's still alpha, still kind of needs more work before it's ready for, you know, like enterprise adoption. But we believe this is the approach.

It's like actually using the lessons we have done, using some of the kind of tooling we have, For example, we use MPC for a key holding that is delegated as well so that you effectively can have like a fire blocks for agents, right, where you have a policy that you deployed that agent can only spend $100, et cetera. Even if something is like broken out of the LLM loop and like, hey, let's, you know, send all the money to somebody else. Like the policy on MPC side can stop it. So all of this piece is really like, I mean, in a way, you're rebuilding a lot of the lessons we've learned for people. like usually getting fished or getting intact and applying that to agents that just runs at 100 miles per hour.

How do you, yeah, I'm curious to hear about this kind of like, you know, harness the permissioning system because it does feel like to your point where you kind of keep relearning these things where it's like, you know, for the web or for like Linux-based systems, we've like very robust, you know, permissioning and user systems.

And so we've like thrown that all away and just be like, no, actually, like, let's just hope that this, you know, model that we've imbued with some character will reason through what it is allowed and not allowed to do and just give it the master key and kind of hope. I feel like in crypto we have gotten very anal and like

everything is locked down to like the minimum possible level. How do you think that kind of plays out in Agent Land? I mean I think we'll just like Agent Land needs to relearn this and this is why like Crypto actually is at the good forefront because we have learned all those lessons.

We are living at a dark forest at all time. So like we can apply this lessons. But I think the rest of the world, the rest of like AI, and again, to be clear, like this is right now,

it's all over Twitter, but this is still a very like niche, you know, people's rich. Extremely niche. Yeah, extremely niche behavior. There was a story that went viral recently

talking about how roughly a billion people have used AI tools in the world out of a population of 8. something billion. So vast majority of humans have not used any AI tools, even though AI tools are free, right? I mean, obviously not in every country, but they're free, at least in, you know,

a lot of Western countries. Are you telling me that you're going to get flip phones? Are you going to get flip phones and feature phones to support AI tools? I mean, they're not that bandwidth intensive, right? I mean, they're pretty... Well, I just mean more like to get to the last $3 billion you're going to have to...

No, there's a lot of smart phones in emerging markets. No, no, no, no. Market penetration over places that can use it or it's still like 30%. I saw some number that was claiming. It's like $3 billion accessible. The last $3 or $4 billion is going to be much harder than the first $3 billion.

And you're already at one third of that. Wait, what? I don't know. I mean, because Open AI alone reports like $900 something million monthly. So like it has to be higher. And then, I mean, I agree with the smart phone penetration is insanely high. Yeah. Like, you know, at this point, pretty much everyone has a smartphone.

And it's like, yeah, you're just getting an API anyway. And Google search. Right. Right, right. To say nothing. Yeah, let's put Google Search site. Oh, yeah, yeah. Yeah, but I'm only mainly pointing out that like there was basically some estimate.

And I think this is like in the end recent report of like AI penetration versus mobile penetration over time. Right. And obviously it's like a way faster slope. But then the point that I wanted to make, which is like the more interesting point, is that only one percent, less than one percent of the people who use AI products, pay anything. Overwhelmingly people are on the free tiers, which means that they're getting like, you know, GPT5 Mini or, you know, Claude Haiku. They're getting the really crappy versions of all these things. And it, which implies that, like, they don't see the value. They don't actually

think that it's worth paying for frontier level intelligence. And like these things are not expected, you know, it's like 20 bucks a month, right? Like, this is like Netflix. Like, there's a lot of services that have higher penetration into the normal world compared to AI, which is, you It tells you, like, take that. So 1% of people using AI products, you know, 90% of people have never used any AI product at all, or 85%, have never used any AI products. Of those, 1% of people are paying any money at all. And of those, a tiny fraction are doing crazy shit like OpenCla. So although it's very viral on Twitter and everyone's talking about it, and it's a cocktail party conversation, the reality is very few people have touched this stuff.

This is the fringe of the fringe, the frontier of the frontier. I was actually on stage yesterday at New Yorkcon, arguing with Arjun, the CEO. of Co-CEO of Cracken. And I was on stage talking about how, you know, this stuff is really exciting, but it's really the frontier, it's really the Wild West. It's extremely dangerous. And it's going to be a while until this stuff is hardened enough that you're actually going to want to give it money

and just let it rip. And Arjun was arguing, like, no, you know, why are you talking like this? Like, actually it's already there. It's so close. And his claim was that he was going to have 100% of his portfolio managed by an AI within 6 to 12 months. And I was like, I think you're high. I think you're out of your mind.

I'm like, I don't know what you're talking about. So like, I think there's wildly different perceptions, even within people who are living on the frontier, about how close we are to this stuff being ready for prime time. Ilya, what is your take on that question? Yeah, I mean, I'm probably more in Arjun camp, but it's also, it's going to be, you know, Arjun and, you know, few thousand other people who are approaching that in like six months.

I think like we can harden. So first of all, like the coding has changed over past months, over past two months. Like, I mean, everyone on our team uses some kind of AI to write code. And yes, we were using Courser and like IDE co-pilots before. But this is going away. Nobody's writing code anymore. Like we're just talking to a machine. Right.

And like, yeah, so there's frontier of frontier. But this is the new world. The new world is like, you're actually design your software in such a way such that the machine can just code it and like it figures out how to debug and test it itself, right? People, the only thing you now need to figure out is how to tell it to figure out how to test it correctly. People were telling me last night that like the new street cred in SF is like how many agents you have running in the background while you're out. And they're like, oh yeah, if you have like less than 10, you're like not really cool. 10 to 15 is like how all the cool kids are at.

Or it's like what's your anthropic bill while you're away? You know, like that's like the sign of how cool you are and how hardcore of an engineer you are. So it does. I mean, it is about like it's actually becoming interesting because it's bounded by how much context you can manage of different workflows like work streams running in parallel. And it's, yeah, it is a very interesting.

Like it again, it's exercises at different functions that like as in you usually don't. It's more, again, like you, it's like you managing a bunch of people. Right. Engineering is traditionally very single-threaded. And this is more like playing a real-time strategy game. It's like you're playing StarCraft. Yeah.

And like jumping between different contexts and like trying to, you know, control all of your economy at the same time as you're attacking an enemy. Like that kind of fast context switching seems like that's what all these cracked, you know, 21-year-old engineers are all learning how to do. Yeah. I mean, that's, yeah, I have a couple of clothes running right now in the background. Only a couple? Well, you know, I'm on a call here.

I am curious. I mean, how do you think about, like, how, you know, using coding agents is going to intersect with crypto, which obviously is a very different standard around, like, code quality. I mean, there's a story, it was like last week about, like, Moonwell, like, they vibecoded some update. And then, like, there was an Oracle exploit as a result because you can see, like, Claude is like a co-author in the commit. So clearly it was like having Cloud write it. And so to your point, you know, with really robust testing, you know,

you can be sort of loose on the inputs and strict on the outputs. But it feels like even still we, you know, in theory, have extremely strict testing and, you know, formal verification. But even that isn't sufficient to, you know, catch all the bugs and it's very deliberately written code. Yeah. So there is like a multiple multitude of things here. One is exactly right now.

So right now this AI coding systems. they are very spotty, meaning they kind of look at some of the files and then, you know, they make a diff and it, and it's very good at passing its own tests. So it writes its own tests and it will pass them, right? So if your tests are wrong, right, or if your tests are not covering the cases and it's, yeah, it leaves a lot of kind of slop and like not implemented things and sometimes just like not handling state transitions correctly. And so, yeah, right now, effectively, the job is figure out how to test all the state transitions, right? Like, literally, that's the first thing, okay, what is my state machine, how to test it, et cetera. The, with smart contracts, obviously, extremely more valuable. But all the auditors now are just using AI on the other side as well, right? So, like, I've definitely, like, copy pasted an audit for a smart contract into a check if this is, you know, GPT generated.

And it was, like, 78%, you know, GPS. So we're kind of already in this chicken and egg AI on both sides problem. And so for me, the foundational, the only way to get out of this is actually for modification, because that is actually a mathematical proof that code does exactly what spec is saying. Now, you still may have problems in spec. And so you actually need to design the whole flow around it, the whole, and this is something that we have like a whole thread on. how do you design a blockchain in such a way that the formal verification is on a transactional level, right?

When you send a transaction, you can attach the spec that you care about, right? So your wallet says, like, hey, I want to make sure that this is my contract will never lose my money, right? Or, you know, under this scenarios, like of whatever lending liquidations, that's only the reasons when this do it. And so you can actually check this at the transactional level. So that's something that, again, I think we will need to evolve. really quickly to support this type of thing. So, yeah, I mean, this is, again, we're learning all this lessons, and I think, like, blockchain space is indeed on the forefront because we just have way higher standards for

this. It's interesting. So, YQ, who's one of the founders of Altlayer, he created this project, which he called ETH 2030, which is basically taking the Ethereum 2030 roadmap that Vitalik has described, and just vibe coding the whole thing using, using Klaude. And so he tried to one shot basically like the entire Ethereum roadmap. And they created something. It passes a lot of the tests, I think almost all the tests.

The problem is that apparently it's like 50 times slower than Ethereum. Like it's extremely inefficient and like, but it does have the stuff, I think, is my understanding. So it's like it's a little bit like when Quad, if you remember when Opus 4.5 was released, they show that they'd implemented a browser. And they were like, look, it can like open the Google homepage, which was true. didn't do anything else, like, and almost anything else it would just, like, break. But technically it could, like, render, it could, like, fetch and render the Google homepage. And I think recently they also did, like, with 4.6, they showed the C compiler.

Yeah, it was also not good. Yeah, it was like, yeah, you can, like, do a hello world, but, you know, you try to compile, like, you know, my sequel or something, and it just totally collapses, you know, I can't, can't really do stuff. So I think it's still not at the phase that you can really write complex software without a lot of human intervention. But it's like, you know, we're starting to get to something that can, you know, really building these scaled projects. It's no longer a hard no. It's a soft no or it's a like, you probably shouldn't, you know. Well, I think that the interesting thing for me, like, as an engineer that happened is that before some things were like, this is too complicated

even to try. Now you're just like, I have an idea I put it in a cloud. It tries it. And yeah, It's probably like, will require a lot more work to get it. But like, you get, you know, 80% to validate if this idea even makes sense to try, right? It's amazing. Marketplace, yeah, I just built it. Like, I've been thinking about it for a year and a half, right? This is something that when we built intense, when we started building intense, that was the idea. That was like, how do we enable agents to do?

And obviously, back then, none of this worked. So we actually built, you know, crypto-focused intents. But I was like, okay, I know exactly how it should work. I can describe that. It went and built it. It took, you know, obviously a bunch more work to get it to like polish and be able to launch. But it's, it removes that barrier completely. True.

Let's bring you in here. What's your take on how agentic coding meets crypto? So I think to be on, my personal usage is not actually writing contracts, but writing all the scaffolding of, okay, I want to use these five contracts and these five protocols like here's a script like do this I use it more for like plumbing together things between contracts or between chains where I don't want to like think about you know writing the type script or Python that is orchestrating stuff but on the contract stuff I feel like you know I spend a lot of time kind of yeah doing a little bit of what like I described of like trying to

take find exploits that existed and and I think it's actually pretty good for finding existing exploits. I think if you give it sort of like novel exploits, you're still kind of, you still kind of get stuck a little bit, even with a lot of hints. So I'm just like uncomfortable with the idea of writing de novo smart contract code ever from these yet. You know, like I'm not saying where that won't change, right? Alia's formal verification world is supposed to make me never have to worry about that. But until that world exists, I think I like using it for glue code where I don't have to think about the real security vulnerabilities, right?

Like, I want to make some complicated defy position that, like, you know, adjust itself, like perfect. It's really good for that. And that's kind of where I see the right now aspect of things, you know, like that's sort of the easiest intersection. But I think the long-term thing is one thing about agents that I think is, you know, Actually, well, I don't know if I should save this for our Satrini when we talk about that. But one thing about maybe this is a natural, which is a natural segue, but one thing I think

about the dumerism that you see a lot of people have is like, hey, we're going to have all these agents. Agents are all going to replace people and employment goes down, world ends, whatever, right? That's like the, the dumer story. The other mindset, the abundance mindset of like, I can have a million agents like doing a bunch to work for me at the same time is a very different type of like network effect, right? Like the barrier to, you know, the barrier to getting started for things is like very low now, right? Like there's a million ideas you have that like in the past, you've been like,

oh, I'll have to spend like a day writing all this Python code whereas like now it's like it spent five minutes writing a prompt and then, you know, a few other prompts to correct some mistakes it made. And like now I got to try this thing. And maybe the experiment failed, but at least I got to try it. So the lower barrier to entry to me sort of is a little bit more like crypto, right? Because in crypto, it's like I can have 10,000 wallets, Sybil attacking, a protocol. And in some sense, I think the network effects for agents are going to look like things where that are a little more like crypto, where like the thing that's most valuable is like liquidity and something you can't copy, like explicitly, no matter how many copies you have,

you're not going to be able to split it up, which is, I think, why the SaaS stuff is, you know, the Dumerism like this is coming from the SaaS stuff because, like, a lot of that stuff is... Let's cover the Satrini thing. Maybe that's just so people know what we're talking about. So at this point, I'm sure everyone has heard of this massive Satrini article came out a few days ago

called the 2008 Global Intelligence Crisis. So it's kind of a fanfic, you know? It's sort of like a fictional story about what might happen. It's bear porn, dumer porn. I mean, the White House commented on it today. Seriously? Yeah, yeah. I just saw it.

So, Satrini, so just to be clear, Satrini is like a former, I think he's like a med tech entrepreneur who like then pivoted into being like a macro kind of substacker. He runs one of the most popular finance substacks. And he just writes about general kind of macro worldview. He's somebody very well followed on Twitter. A lot of crypto people like him.

He likes some crypto people. So he wrote this, this long form article describing a quote unquote fictional macro memo from June 2028, after which point the S&P 500 has dipped 38% from the highs. There's massive white collar displacement. There's all sorts of quote unquote ghost GDP that supposedly there's supposed to be all this great productivity, but it never circulates through the economy. Consumer spending collapses and basically you have huge wipeouts of companies like Amex, Visa, DoorDash, Service Now. And he claims that, you know, basically AI bullishness is going to be so disruptive. So,

suddenly that it's going to cause huge financial wipeouts and company profit margins to collapse. And one of the vectors through which this happens is through crypto. So he claims that one of the reasons why the credit card companies are likely to lose a lot is because agents are going to realize that they can settle more effectively using stable coins on Solana or Ethereum L2s for fractions of a penny and completely cut out interchange. And his claim is that there's so many of these friction-based business models that exist in the real economy, such as credit card.

cards, such as platforms like DoorDash, travel platforms, et cetera, and he thinks that stable coin rails are going to disintermediate and reduce a lot of the margins that are otherwise captured by corporate America. So very, very, very contentious article. It's gotten like 25 million reads. I mean, tons of, tons of newspapers and Twitter. It's like the first time I've seen the agreement. Everyone was like attributing like 200 billion market account lost to it.

I think it wasn't it like a trillion? Yeah. I think the truth. I'm also like, yeah, the other macro. I don't know the IBM thing, I don't know why the IBM thing, which was actually one of the larger components, gets attributed to it. So it's like, it's the accounting is because anthropics and they can write co-offs. Yeah, that's my point. They didn't even announce anything new.

They just wrote a marketing piece that was already a capability that existed. This is like 2017 crypto partnership marketing. Yeah, yeah, partnership confirmed. It does feel like something has changed in the X algorithm. Because, like, this thing went super viral and the, um, something big is happening post also about, like, 80 million views. And I had, like, people who, I think they're just promoting long reads. Yeah.

So I'm like, because they have this competition. Yeah, Nikita can basically sigh off everybody by just promoting, you know, uh, random, random articles in the feed. Yeah, because I like, you know, people, like, friends who are like in academia, it's like a philosophy professor. Like, was texting this to me. I'm like, why are you seeing this? Like, this is nothing to do with, you know, what you're doing.

but I didn't really like the piece. I thought it was bear porn. I thought it was not very good bear porn, to be honest. I think... What made it not fair porn? So I think there's this existing kind of debate around, oh, will there be mass employment because all these companies are going to, you know,

just automate away all these white-collar jobs? I think that is per debate. I think I maybe take, you know, not as bearish of view on that. But a large part of the thrust of the piece is about this agentic story that you're talking about where, hey, there are all these big companies that mostly deal in software that basically exists as intermediary for a marketplace, and they take a cut, and that's their main

business. And stable coins basically disintermediate that. And I think there's a couple of issues with this. One, I mean, this was kind of the same argument as like this sort of aggregator theory as what happened in, you know, the early internet that like, oh, well, you know, you're not going to, you're going to put all the travel agents out of business because, you know, you're just going to go directly to search for the thing that you want, and, like, therefore, it's, you know, the sort of intermediaries get commoditized out, and they sort of have no pricing power. And, I mean, it's true to a certain extent, but, like, hey, it ends up being that there are a lot of other subsequent jobs that kind of downstream from that. But the big point on this, like, this macro thing is the wiseest bad for the economy.

It's kind of like, it reminds me a little bit of, like, the broken window fallacy, familiar with this, where it's like, you know, someone, you know, breaks a storekeeper's window, and it's like, well, that's good for the economy because then someone's going to, you know, he's going to pay for the window to be created, and the person who makes the window is going to pay for other things. And it's like, well, actually, you know, that money could have been spent elsewhere that had been more productive versus just breaking the window. And for this, it's like, oh, is it, is it, you know, good or bad that, you know, Visa right now, you know, takes two and a half percent of every single transaction. And it goes, if that goes down to zero, wouldn't that

be really bad? It's like, well, the sort of other way to think about it is like, what if it took 20 percent today? Would it be in like a worse economy or a better economy? And I think there'll be a much worse economy. If there's a 20 percent tax on every single transaction, a lot of things just wouldn't happen. We'd see way lower volumes. And so I think ultimately things are trending towards efficiency. And this is just another example of that. And yeah, in the short term, there is going to be some economic disruption.

But like, yeah, we want a more efficient, you know, a more properly allocated economy. And like that seems to be actually what the piece is about, which is good. Yeah. I would say, so I agree with you. I think that the piece, I mean, one question is like, why did this piece go so viral? And I think the answer, I mean, a lot of people, especially if you really, read the Wall Street Journal or whatever, or the economist, they look at this thing and they're like, this guy's like a medical entrepreneur, like why is his macro thing getting upvoted over the

banks and over all these other financial analysts, which I think is very satisfying to see as like a kind of extremely online person. It's like, yeah, one of us. You know, we like, we did it. I think the reason why it's so compelling is because it's written in this way that is this kind of in Medea-Rez backwards looking like, oh, this already happened. It's actually very It's very well written. It's very tantalizing and believable the way that he draws out the whole thing. It's not written like a bank analyst report, you know, which nobody would care if like, oh, you know, JP Morgan wrote some of the report about AI who gives a shit. So the first thing, I think it was well written. Now, that being said, what's wrong with the piece? A lot of people had very good

takes that they were like, oh, you know, he wrote about 20 different industries. I don't know about all those, but I know about this one, you know? And so like, I know a lot about, you know, marketplaces, right? I know a lot about DoorDash. And like, his description of DoorDash is just complete nonsense because, like, there are competitors to DoorDash. People do multi-home and yet DoorDash is still a dominant player because, like, it's mostly not a software company, it's a logistics company. And like, logistic, there's all this data that you just vibe coding some alternative to DoorDash does not give you the ability to just like compete DoorDash's margins to zero. It's just not how it works. For what's worth, he got, his responses on Twitter were all

just about how much hate he's getting over the door dash. Is that right? No, but then somebody made the same argument about service now and like a lot of these other businesses. And it's like, okay, if he got this one, this wrong, like the other ones that I don't know about, probably he all, you know, it's like a sort of, what's the, what's the effect that that physicist talks about? Oh, it's on. Yeah. Yeah, yeah, yes, yes, exactly, exactly.

It feels like a little bit of this where like every single little industry, you kind of get a little bit wrong, but it like sounds plausible to someone who doesn't know that much about it. But the core problem I have of this piece, which I think is like the real weakness of the piece, is that he basically describes this huge demand shock, right? Huge supply shock, huge demand shock, and the inability of the market to recover from this. And I think this is plausible. Like, there are parts of it that are plausible about financial shocks and like assumptions that are made in lending and underwriting that are going to be violated when you realize, oh, there's a bunch of bad debt over here. Very plausible how you can have some kind of financial snarls that end up, you

resonating through the economy. The problem with the story, I think there's two fundamental problems. One, no explanation for where the money's going. Like, who's making all the money and what are they doing with the money? And he just doesn't address it, right? Okay, so AI companies meaning that like, oh, shareholders are making a lot of money and they also have employees who are making all this money. And what do they do with that money? But it's like, you know, 100,000 versus 100 million. Right, right. So the answer is that they invest it. And so where does the money that they invest? they're not spending on the yachts. So they make money, they invest it. Where does that money go? If they were spending on yachts, that would, if they were spending on that also also will pump some

parts of the economy. Yeah, no, exactly. Right, fine. But like there's a demand, there's a demand shock that comes from another side, right? The money doesn't disappear. We don't shoot it into space, right? Like, you have to explain where does the rest of the money go? And he doesn't even address that part, which is a problem, right? Good, actually, this is somebody else told me, but good to compare with actually 2020 because we had a massive effectively unemployment slash no work, people are not working

shock to, I mean, United States, but also globally. And people were like, okay, you know, I'm getting like a stimulus check here. You know, the economy was actually flowing. It was kind of a bull market across, you know, crypto end. Like we actually had all of this money circulating through the system. right? And so yeah, I mean, that's probably not sustainable and there's like better system that needs to be to kind of balance it. But like the reality is I think that the piece that to me kind of I do think that the labor to capital mechanism is going to start shifting. Right. It's already been shifting over past, you know, multiple decades, right? Realistically, capital becoming more and more productive than labor and like,

with this, like, AI being kind of this pinnacle of automation, right, this is just going to accelerate. And so that doesn't mean that, like, that means that we're going to be fine living in the world where there's a lot more people that are not actually contributing productively to the, you know, quote-unquote GDP, but that doesn't mean that that's going to, like, break the whole system and just, like, keep adjusting.

I'm very, very skeptical of the story. I'm very skeptical of the story. I will say, a lot of the, there were, there's a huge number of, like, retorts. to this post because it angered people so much, right? Like, I feel like I saw hundreds. The only ones that I personally, but all the replies that were fast reply guy things for engagement,

most of them were kind of AI slop, if I'm going to be honest, they just were like, what is wrong with this? Like, Claude, tell me what to write. But the ones I thought were actually good were the ones that were comparing this style of posts to like Marx and like Marx writing about the Industrial Revolution of like how it's going to wipe out all jobs forever and humanity and labor has to fight back. And how it's like a very similar kind of like,

the way the story is written is kind of similar to some Marx writings from the 19th century. And I kind of think that's sort of what inevitably happened. Like you're assuming a sort of static world where capital and people don't reallocate themselves or that they don't train themselves. You know, like for instance, the white collar worker blowout. I'm like, all this means is that the white collar worker is going to be like 10,000 times more efficient. So you will need fewer of them. But then also the bar has gone up where everyone's expected to be doing like 10,000 times more things. Right. And I think like that aspect is always

this assumption that everything is static and that the worker is static forever. It's like I think a kind of hidden fallacy in a lot of these arguments that people don't adapt at all. Now I'm not thinking there won't be some people who can't adapt. Because a lot of the a lot of the this argument that you're making to ruin is also kind of doesn't account that AI. as soon as it's, you know, effectively in a full loop and it doesn't make mistakes and kind of doesn't leave a slow behind. Like, I think like, you know, when we had like, you know, tractors and like plants, like all of those industrial transformations, yes, they were elevating like, hey, now a person

can do 10, like 10 persons jobs with a tractor, right? But with AI, there's no, like, again, right now there's a limit. context as soon as compaction hits it is crude but like imagine we actually figure out how to do infinite context or you know in some hierarchical format like you now have no natural limit like right now you know one person can manage seven people then those people manage like we have this hierarchical organizations for a reason but yeah you actually can have like a you know kind of a flat scaling of a so so actually i i was i was like i went i listened to this um lecture from this economist that was kind of interesting about how there is there are a lot of

jobs that somehow persist even when automation exists because there's like people are willing to pay for the more expensive human version and an example of this is piano players there is certainly automated piano players. They've been around since the 19th century let alone like recordings and everything yet the actual wage while there are fewer piano players the actual wage of piano players relative to inflation has gone up since the 19th century to now, because there's a view that it's sort of this necessary good to have the old-fashioned thing. And I think basically there's going to be way more of those types of jobs, which we are kind of ignored.

My thesis is everybody will be in a job that are not actually productive from an economy perspective. Yeah, yeah, exactly. Orts, e-gaming. Like, all of these things are like, I mean, there's obviously entertainment industry on top of it. But like the reality is Yeah, yeah, all right, Tom, jump in here. As competing with each other, you know,

like faster running is not making a productive, more productive economy. It's not creating more output for the economy, but it's self-satisfying. You're saying entertainment is not, you know, doesn't contribute to GDP? No, no, entertainment does, but I'm saying that the job itself.

Yeah, I mean, everything will be left to entertainment. And we want actually to see real here. the thing is like you don't care that the robots can run faster than one another right like we're not going to watch that we're going to see like we want to associate with with people so those i agree those jobs totally i'm talking more about like what actually builds the foundation of mass low pyramid right sure those things yeah that is right now that is where the trillions of economy is and i think that's kind where, like, we all going to have stuff to do. Like, that's, I don't think this is going to, like, I don't think that's, if people are

afraid of that, this is more that like the fundamental kind of, what is, what is forms GDP effectively going to start shifting? Yeah, I think it kind of is, again, this like, like, lump of labor, you know, fallacy where it's like, yeah, people will, you know, find new things to do and find new things that they find valuable and people will reskill and change different things. And, I mean, also, not to speak of, like, okay, they don't, you know, talk about, like, Fed policy and even that's like one of the common retorts he's like well I think they learned their lesson from 2008 so this guy's like also kind of like a gold bugger it's like yeah obviously in like a very

you know high unemployment deflationary environment we're going to see interest rate adjustment and it's yeah I mean it could kind of go on but I just I think maybe to trune's point and to at least point it's like we live in a very dynamic economy and it's not this kind of like one shot tomorrow you know AI is automating everything people are already kind of adjusting and adapting and I'm just going to continue to do that. I mean, I also think you make a good point. Yeah, well, the thing I was going to say is I do think it makes a good point that, like, look, our economy is built on certain foundational assumptions, right?

As you say, our financial system is based on certain foundational assumptions about the distribution of wealth, about where value accrues, about who's a good credit risk. And if there is a certain sudden re-rating of risk in the economy and there are risks in places that they weren't supposed to be, that absolutely can cause a financial crisis. You know, like even if there's a productivity boom, there's nothing that in principle stops both things happening simultaneously, that there's a productivity boom, but also there was huge mistakes in underwriting. And that can cause an enormous amount of financial damage, as we saw in the 2008 crisis, right? Like, you look back 2008. Yeah, but my point is, again, yes, that's reflexive, right?

It's like, I think the Fed has learned at this point to, like, be aggressive in, you know, using the tools that they have. So it's like, yeah, if you think, you know, prime mortgages are going to get hit, we know kind of how to deal with that now. And again, I also think one of my bigger issues with this piece is it's like this kind of, you know, cherry-picked, I think your world where it's like AI gets so good that everything is completely automated and everyone's out of a job. But it's not so good that it gets super intelligent and it finds a bunch of zero days and you destroys a bunch of critical infrastructure. It's like just good enough to be this like very aligned, beautiful being that we can tame. And like that that seems more unlikely. I'm actually more afraid of the actually think that the second part finding all the zero days is actually. faster than it will get good at like a bunch of...

Yeah, that's possible. Yeah, it's like, oh, it's a bipedal thing and it has like a head and eyes. It's like, no, it's not what an alien is going to look like. It's going to be like a 5D plasma cloud. You know, it's going to be like three body problem. You won't even like recognize what it looks like. Well, actually, there was a really funny,

speaking of open-cloth stories. There was this really funny story, but this guy who like bought like a DJI drone or like mini-haport. I forgets a drone or like mini helicopter or something. and basically he like told Claude to like and DJI charges you the vacuum for the vacuum sorry, sorry vacuum right and DJI charges you for subscription to use the thing so he told Claude thought hey like try to break into this thing it's like at this this IP address on

my network and like this use these ports and Claude found some zero day in the DJI thing in the sense that they actually just didn't do any off of the device so you could actually log into any of these devices around the world if you found them. And then he like, his Claude bought, figured out how to scan for this particular device and then made a, replicated itself to like 700 or 7,000, some number like that of agents, each controlling all of the different vacuum cleaners. And it was all because like DJI basically had the zero day. Now it was a kind of dumb zero day.

It's like they have a function that was like check off and then it just returned true all or something stupid like that, but like, it was, it was so kind of like, it was still kind of like... It's all right. Yeah, it created its own botnet out of vacuum cleaners, right? I thought that was like an amazing story. But there's probably like millions of those things because on average is 15. And every thousand lines of code, there's 15 bugs. Yeah.

And I think this is for humans. I think AI actually may leave more behind if you're like, don't reorder. it multiple times. And so, yeah, this is like, we are actually really need the formal verification or are we going to be in a very bad situation? I agree with that. Okay, one quick thing. So I'm going to go back to, you know what? You're at like, what do you think about crypto and AI and does Dumer the story? I think, like, agents sort of have network effects that are more like crypto in the sense that you can have many of them, you can replicate them. And like the only things at work are civil resistant things, like things that if I send five,

agents, it doesn't change the value of that thing. So and in some sense, this is actually the argument instead of the like MasterCard thing I would give for cryptos. Like the agents are better, crypto is built around making these things civil resistant by definition. Whereas like MasterCard is only civil resistant by legal force, which is going to be just harder to enforce for these agents. I think that's, it's fundamentally easy to say. I think agents are just not going to have identities. I'm just going to spin them up on demand on some event if I need it and then kill it and make another swarm, then kill it, right? And the only thing that's infrastructure for finance that's actually built around this identityless sybilness is crypto.

And like fundamentally, I think that means all the network effects that these things have should kind of look like the crypto network effects. You see? That's sort of the – I would have rewritten that part. I don't buy the MasterCard thing that he wrote because there the network effects is like the distribution. It's really hard to get vendors to shift, right? I mean, yes and no. It's also crypto being working to shift this. And it is starting to shift as well because it is expensive for merchants.

Like merchants are taking that price. But even further right now, let's say my agent can just go and talk to the factory in China and just purchase things directly. And like if it can negotiate, like let's say they're running an agent there. as well, they can just like, oh, can I just send you crypto, right? It's way easier than figure out how to send money into China in any other way. And so like to me, this is actually, I mean, again, the agentic marketplace we launched is effectively like a prototype of that cutting out to the whole distribution, like supply chain

pipeline. Because now if you can find that other agent and you have a way to agree with them on something, escrow money and pay, crypto indeed is, is the best way to do that because I actually, the piece that when everyone who talks about payments actually gets wrong is because it's not about payments. Payments is just the final piece of a commercial transaction. It's about finding the country party. It's about figuring out how to actually agree on the terms, which are not just money. It's delivery time. It's, you know, like what happens in force major? What if the truck gets flipped, right, et cetera.

And then at the end, you deliver money, right? And like, maybe you have insurance over this. Maybe you have escrow. Like, that's the whole flow. And this is where agents have, and like, if the two agents are talking, they effectively can do all of this way faster, way cheaper. They don't need a legal lawyer, like two lawyers affected to jump in after the, you know, primary agreement to go and negotiate red line, the contract,

billing, invoicing, et cetera, right? So, like, that flow gets compressed. And that is actually where trillions of dollars have been moved, right? Not the e-commerce part where we buy from Amazon is actually less of a problem, right? Because my credit card is already on Amazon. It's really the, you know, I need to purchase, you know, 10 tons of steel and need to ship them. And I need insurance and reinsurance and like financing to do this. And so that, that like can be sped up and simplified a lot.

Okay. So let me, let's see if I can flesh this out. It sounds like what you're saying is almost that the place where AI is going to be more disruptive in commerce is on the discovery side, right? Like, the reason why we all go to Amazon is that we don't have to go and figure out who is anchor, who is, you know, I don't know, like all these Wowbox or all these, like, random Chinese vendors that Amazon has diligence and is like, yeah, these people are good enough to be our fulfillment partners to actually sell things to American consumers.

Your AI agent doesn't need Amazon to go and aggregate that information for you. It can go to the source, parse all huge amounts of information, and basically does not require aggregation in order to, like the reason why aggregation is there is to save you the work and the discovery cost. Because humans have, you know, low context, right? We have a small context window, right? Like, the AI has a very big context window. So if the AI is going and like actually checking every single flight or checking every single

vendor or checking every single whatever, going on MLS and checking every single listing, that is the reason why commerce is going to get disrupted and that's why the credit card system, like, so how does it connect to the credit card system? Why would it not be that, yes that, but also. as well just pay directly, right? Because like you don't, like, if you're already doing this, you don't need to go through like the slow also settlement process and figure out. So that's true. So settlement process on credit cards are slow, right? You have 30-day hold back. You've got the chargebacks. But arguably what the credit card system is doing is it is the long arm

of the law, right? The credit card system, right, Visa is basically the monopoly on violence that says, do our money. If you don't behave, we're not taking you, we're not giving you the money. And that does serve some purpose. Like if I go directly, my AI agent goes to this like, you know, vendor in China and is like, yo, here's 25 bucks. Please send me a, you know, USB charger. And the USB charger never shows up. There is no enforcement.

There's no law. There's no way that I can enforce anything on this person besides some like, you know, leave a bad review. Well, except, you know, we have escrow. You can effectively insurers. You can, like, we have all the financial instruments. Who's holding the escrow, though? Who's holding the escrow?

The smart contract. On the escrow now is the, what's the Oracle, right? What's the Oracle? New MasterCard. No, no, there's AIA. Yeah, yeah. I think there's another AI agent.

Claros court, Claros court. No, no, I think that both sides agreed is a resolve. So you're imagining private law enforcement, private law enforcement through another AI agent. Like this is like what you're describing is like an arc of capitalism. Is that what you're imagining? This is agent marketplace. This is marketed near the eye.

I don't disagree with the ilia's view in the sense of like there's going to work. You think that's going to be a part of the economy that's like that. That's no doubt. But you can still rely on some jurisdiction. Because the thing is like you have all of the interaction between agents is fully documented. Right. And so if like whatever AI. But who would work?

How does enforcement work? Like for digital goods, I get this. For digital goods, no, no, but like you can have this contract in some jurisdiction. You can literally have this, the two AIs effectively built a contract, like a legal contract. Okay. Legal contract.

We were talking about no legal contracts, and now we're back in legal contract. No, no, it's still a legal contract. They just don't need, you know, lawyers between them. Like, they've been trained on all the legal contracting. So the AIs are the lawyers. Okay, fine. But like, okay, let's say I want to enforce. How do I enforce against a Chinese company?

Well, same thing as if you're doing it yourself right now, right? Well, that's the thing. That's why, like, Amazon, right? Amazon actually can enforce against the Chinese company. I can't do that. Well, your AI agent can. I think Tom has the right idea, which is, like, there's just going to be a new master card or many new master cards that just are the judge agent and then also go file the lawsuit,

right? And it probably just relies on, like, one. Where are they filing lawsuits? No, hold on. either we're in agent land and there's a third party that we all trust as like basically arbitrators, right? How do I get, how do I seize my collateral back? Like, if it's like, I mean, they hold the escrow. Yeah, the money is an escrow.

So I can tell you how this works right now, right? The money are in escrow. On delivery, right, the both sides need to say effectively good, money got released. If one of the side says no, this is case moved to the dispute agent, to the judge, who evaluates a case. and effectively decides like return all the money, split the money or give it to the whoever delivered the goods, right?

That judge can be this can be a filed as a court case, like in a rectual physical court if both sides didn't agree with the judgment right in some scenarios. Now what is missing in this system

is affecting now as a worker I can actually take a loan I can effectively do financing against the escrow, right? Because like this is, I mean, the same thing that, like, you know, Costco, for example, literally has no working capital because the invoices come in 30 days later

and they sell, on average, faster than 30 days. So actually, like, really money that's, they sell the stuff they didn't pay for it yet. And so, like, those kind of things now you can start doing because you can actually borrow against an escrow given, you know, reputation, like the history you've built on this marketplace. And so we can start,

we can start building all the financial instruments, but now they are actually linked in into the kind of smart contracts and escrow payments. All right. Well, this has gotten very sci-fi. One thing we have kind of buried here is for people who aren't familiar, Ilya is one of the co-authors on the original Transformers paper, which obviously spawned these GPs and this entire agent sort of thing that we're going through. And so, I'm curious, like, how it kind of feels to see everything.

unfold and stuff that you that happened that you think wasn't going to happen and vice versa? Yeah, I mean, it's exciting to see it. Like, I mean, the context actually, I was excited about AI since I was like 10 years old, right? I tried to build my first neural network when I actually didn't know linear algebra yet,

so that didn't work very well. So yeah, I mean, it's exciting to see this. The near AI actually in 2017 started to build effectively what now is called vibe going, right? Like, I was, you know, I was pitching that, hey humans will stop writing code it will just all AI is doing that and you will and all the SaaS will be gone because you can just write your own software but don't you feel don't you feel sad that program synthesis is now called vibe coding because it's like yeah so the naming is very

unfortunate yeah yeah so I mean that's why we need formalification so we can actually get back go back to program synthesis yeah this is program synthesis not just some like slope code produced by AI but yeah no I I'm just excited. I think the world is going to be reshaping. I'm not doomer about it. I think we're going to adjust with that. There's a lot of smart people thinking about what the implications are.

I think the capital markets are indeed very flexible to adjust with that. I think there's a control question that obviously, we in blockchain believe that control should not reside with a single party. That I think is important. but overall, I think we're just going to continue seeing productivity gains. We're going to continue seeing we can do more. And at the same time, we're going to keep expanding what we can do and what we want to do, right? And keep spending our time in the way we're enjoying, like, more than the, you know, we need to because need to earn money, et cetera.

So, like, I think that shift is just going to make everyone kind of happy. And like, the question is, like, how to get distributed across the full world, right? Like, how do we get into Africa? How do we get into, you know, Sest Asia, et cetera? But, yeah, I'm just excited. Fair enough. And do you think is AI going to save crypto? I think, I don't know about, I mean, let's be clear, right?

The adoption of crypto is at the highest mark it's ever been, right? The stable coins are being used everywhere. The, like, infrastructure is being used. Like, more and more people are leveraging it across the board. this is like, you know, the identity solutions, like all those things are using effectively blockchain one way or another. And yes, markets are kind of, markets honestly on time, like they're so in time. It's kind of, it's kind of funny. But like Bitcoin is on its, you know, the halving streak.

I mean, I'm sure everybody's looking at the chart like halving to halving. But like I think the peak like all time high of Bitcoin was literally like two weeks off from the all time high of two previous cycles. And so like it's kind of funny because like so much macro changed, but like at the end, Bitcoin just does the thing that it does. I would, I would say the one thing is that crypto people seem to always have the right. Some of the right things to think about things that work in AI. I think like if you look at the data center build out, obviously that was like 90% crypto people. if you look at this kind of agent finance stuff, I think I sometimes look at some of these fintech things.

People are doing with agents and they are idiotic and sib-siblable. And I think there's a lot of stuff people in crypto know about how things can be abused that's actually very useful in an agent world that I think AI people are too optimistic about. And I think hopefully we can bring the realistic pessimism to that world is where I think. I mean, I call it a multiplayer. Yeah, multiplayer view. Like, AI companies usually work in a single player, right? They're like, we're building it for another user, and this is how they're going to use it.

Crypto built for multiplayer, right? Like, they're going to be malicious players. They're going to be great players. You need to value align them. You need to incentivize them. Anybody can join it any time. Like, how do you design for that? Right?

That's a mindset difference. And we're bringing that to AI for sure with all of the tools we built. Yeah. No, it's a fascinating time. Ilya, we thank you for coming on and sharing your perspective with us. And we look forward to see how all this stuff plays out. We'll be back next week. Thanks for having me.

Thanks, everybody.