#34 - Sean Neville

16 Jan 2026 · 57 min · 24 chapters

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In short

The Network State Podcast - Episode #34: Sean Neville

Episode Overview In this episode of *The Network State Podcast*, Balaji Srinivasan interviews Sean Neville, co-founder of Circle and founder of Catena Labs. The conversation delves into the evolution of stablecoins, the implications of machine-native money, and the intersection of AI with cryptocurrency.

Key Participants

  • Balaji Srinivasan: Host and tech entrepreneur.
  • Sean Neville: Co-founder of Circle and founder of Catena Labs.

Episode Highlights

Introduction to Sean Neville

  • Sean Neville co-founded Circle in 2013, with a focus on democratizing global finance.
  • The conversation emphasizes Sean's perspective on building stablecoins and the partnership with Coinbase.

The Circle-Coinbase Partnership

  • The creation of the Centre Consortium, a collaboration between Circle and Coinbase, was vital for the launch of USDC.
  • USDC: Circle's stablecoin, conceived to enable seamless global payments, requiring stability in value.

The Evolution of Stablecoins

  • Initial Skepticism: Early perceptions of stablecoins were dismissive, as many failed to grasp their significance.
  • Programmability and Use-Cases:
  • Stablecoins facilitate programmability and enable machine payments.
  • Predicted future use in broader applications like treasury management and payments across various sectors.

Importance of Decentralization

  • Stablecoins needed to be recognized as interoperable standards, not proprietary to one company.
  • The significance of a consortium model to enhance trust and collaboration among multiple issuers.

Differences Between USDC and Other Stablecoins

  • USDC's approach focused on one-to-one backing with USD, contrasting with others like Libra, which proposed a basket of currencies but failed to offer reliability.
  • USDC leverages partnerships with banks to ensure compliance and security.

Machine-Native Money and Catena Labs

  • Introduction to Catena Labs, focusing on machine-to-machine payments.
  • Vision for future economies where AI agents perform transactions autonomously.
  • Discussion on the reliability of AI in executing financial tasks and the need for a trust layer.

Innovating Through AI

  • Exploration of machine-native money and the potential for AI-driven economic actors.
  • The conversation about the importance of ensuring reliable and trustworthy interactions between AI agents and financial systems.

Future of the Machine-to-Machine Economy

  • Speculation on applications of machine payments, including:
  • Supply chain negotiations.
  • Dynamic pricing and bidding in computing resources (like AWS EC2).
  • Importance of building a decentralized web to prevent vendor lock-in in the emerging agentic economy.

The Concept of Network States

  • Discussion on the creation of startup societies or network states, and the potential for communities to evolve from digital engagements to physical manifestations.
  • Emphasis on hyper-personalization and trust in the context of community building.

Key Takeaways

  • Stablecoins and AI: The convergence of these technologies creates new economic possibilities, emphasizing the need for reliable frameworks.
  • Decentralization: The consortium model for stablecoins fosters trust and opens up opportunities for various participants in the ecosystem.
  • Future of Transactions: As AI becomes more integrated into financial systems, the challenge will be to maintain a balance of trust and reliability, ensuring that both machines and humans can transact without friction.

Conclusion This episode of *The Network State Podcast* with Sean Neville illustrates the transformative potential of stablecoins and AI in reshaping financial ecosystems. The dialogue captures insights into current challenges and future opportunities that emerge from combining these technologies.

For more information, listeners can visit [Catena Labs](https://katinalabs.com) or explore the initiatives discussed in this episode further.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

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The Genesis of Circle and USDC

0:45 to 3:30

Sean Neville discusses the founding of Circle and the vision behind USDC.

“decentralizing global finance and, you know, sort of had this vision for what that might look like.”

The Evolution of Stablecoins

3:30 to 6:20

A discussion on the changing landscape of stablecoins and their impact on global payments.

“We expected there to be multiple, you know, potentially multiple issuers, all of whom participated in a consortium, even though they may be competing at other layers of the stack.”

Challenges with Previous Stablecoin Models

6:20 to 9:40

Exploration of the issues faced by earlier stablecoin initiatives, including Libra.

“And we had been in ZERP for like almost 10 years, right?”

Coinbase and Circle: A Strategic Partnership

9:40 to 12:40

Insights into the partnership between Coinbase and Circle, and the decision-making process.

“I always wondered internally, did Brian have to be convinced to go this path?”

Building USDC: Technical and Strategic Aspects

12:40 to 14:00

Details on the technical challenges and strategies involved in launching USDC.

“And then there are several other people, you know, on design and so on.”

Challenges of Building Stablecoins

14:00 to 14:50

Learn about the complexities and risks of creating stablecoins.

“it wasn't so much it was hard because it wasn't a lot of code, but it had to be extremely correct because reentrancy bugs, there's all kinds of these things that can get you.”

Key Decisions in Compliance and Stability

14:50 to 17:40

Explore the critical decisions made to ensure stable and compliant stablecoin usage.

“So the simple thing of just one currency off chain, one currency on chain, that was one big piece.”

Innovations in Machine-to-Machine Payments

17:40 to 21:30

Discover how advancements are enabling machine-to-machine financial interactions.

The Future of Crypto and Trust in Machines

21:30 to 24:50

Understand the potential future where AI agents handle financial transactions.

“So you asked about Kupaina, and I keep going back to USDC because it's fun to chat with you about it.”

Application of Machine Payments in Real-World Scenarios

24:50 to 28:00

Learn about practical examples of machine-to-machine payment systems and their challenges.

“We have to be choke pointed in a certain way where we're only web rather than mobile.”
Show all 24 chapters

Machine-to-Machine Payments: Conceptual Foundations

28:00 to 28:32

Explore the potential applications of machine-to-machine payments.

Challenges in Agent-to-Agent Interactions

28:32 to 31:04

Discuss the barriers to true agent-to-agent communication and payment.

“We're seeing AI workflows pay for access to resources, content, data, paying for access to APIs.”

AI's Current Limitations and Future Potential

31:04 to 32:15

Analyze the current state of AI and its need for human oversight.

“And there's variation on them too, yeah.”

Navigating Consumer Retail with AI

32:15 to 35:00

Evaluate the complexities of using AI in consumer retail shopping.

“So it's possible we might be able to turn some of these other data structures like back end code into things that we can just visually debug by eye, you know, like a state machine or something like that, right?”

Supply Chain Negotiation with AI Agents

35:00 to 36:46

Examine how AI agents could streamline supply chain negotiations.

“which is sort of already having the content on the web in some way.”

Human-Curated Data for AI Efficiency

36:46 to 39:29

Discuss the role of human curation in improving AI data quality.

“It's that layer that requires human subject matter expert alignment in order to make the sort of upstream task much more reliable and effective.”

The Future of Financial Transactions in AI

39:29 to 42:01

Explore the implications of AI on financial transactions and agent liability.

“So the thing where we sort of move, you know, a little bit up the stack.”

Exploring Startup Societies and Network States

42:01 to 42:22

Discussing the concept of startup societies and their importance in the crypto community.

“That's like a place where you start with some sometimes small, sometimes large amounts of money so that like people have been building some intuitions on this for a while.”

Physical World Crypto and Hyper-Personalization

42:22 to 44:40

Delving into how crypto can transform physical spaces and the idea of hyper-personalized banking.

“Okay, so what I've been thinking a lot about, what I'm working on is physical world crypto, in a sense, right?”

The Evolution of Interest in Stablecoins

44:40 to 47:56

Examining the changing perceptions and rising interest in stablecoins and their applications.

“their space, a version of the society that they're already joining and already have joined online.”

Interplay of AI and Crypto Technologies

47:56 to 50:26

Analyzing the relationship between AI and crypto, and how they complement each other.

“We're right in the middle of both of those things, but it has absolutely flipped the other direction.”

Agentic Interfaces and Future Technologies

50:26 to 54:32

Discussing the future of interfaces and the role of agentic technologies in transforming interactions.

“that, you know, like what you're doing is one example of, I think, a useful synthesis of them with an AI agent that spends crypto, right?”

Computational Trust and Society

54:32 to 56:00

Exploring how computational trust can lead to a higher trust society and its implications.

“So that means they don't have an incentive to even try it.”

Exploring Katina Labs' Offerings

56:00 to 56:45

Sean Neville discusses the foundational and commercial efforts of Katina Labs.

“And if there's, I guess people can go to Katina Labs.”
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Transcript

Automatic transcript. May contain errors.

0:00All right, Sean, welcome to the New York State Podcast. Glad to have you here. Great to be here. Thanks. So we worked together several years ago on what became USDC. And I was the lead on the Coinbase side. And we set up the center consortium. And you and Jeremy were the co-founders of Circle. And I think the Circle Coinbase Center partnership has been pretty impressive for the world over the last seven, eight years. Do you want to talk about that? Just introduce people because you're a co-founder of Circle. You've done a bunch of other things. Give the quick spiel. Sean on Sean. Yeah, yeah. So Jeremy and I started Circle in 2013.

0:37So it's been, you know, 12 years, which is like 120 years in crypto or something. Yeah, exactly. Yeah. And so, you know, we were just obsessed with this idea about democratizing and sort of decentralizing global finance and, you know, sort of had this vision for what that might look like. And the vision really hasn't wavered. The way that we've tried to execute on the vision, obviously, has had a lot of different sort of crisscrossing paths. And probably should have been obvious in 2013 that we needed something like a stablecoin. But it was actually 2017 when we figured out that that's what we needed to that's what we needed in order to build everything else we were interested in.

1:17And obviously, I was going to say, obviously, you know, that part of the story is as you came into the picture and help make it happen as well. Yeah. And I think basically what's funny about that was that was I think that was true teamwork. and um what was interesting about stable coins at the time as you may remember is a lot of people poo-pooed them and said wow your great innovation is putting a dollar on chain that's a great innovation right and it was kind of like people not understanding how big a deal it was to put like for example news on online right or uh you know they they just didn't understand that for example once it's on chain you've got um programmability and you've got uh you know anybody can send anybody and you can use it in smart contracts and you can slice and dice it down to smaller amounts and uh you can have devices use it machine payments as we'll get to with your new startup with the katina and people didn't understand that stuff at the time but i think we we saw that and uh you know what were you thinking about you said the vision had changed for stables over time but what were you what was the number one thing that you guys were thinking about at the time you started work on USDC?

2:27Yeah, I mean, it was pretty simple, honestly. In order to enable global payments that didn't pause at borders and that were almost free, we needed some representation that was stable and capable of moving over internet rails. So the idea was multiple chains, not to be religious about any one particular chain or piece of infrastructure, but to rely on blockchains to deliver value. And that in itself was really a building block so that we can enable these other use cases. You know, I'd say today stable coins, you know, largely the use case has been in crypto capital markets. We haven't yet seen that unlock of payments, treasury management effects, you know, these other things, but we're right on the cusp of it now.

3:07And, you know, we certainly needed that building block technically, but also it couldn't just be a circle coin or a coin based coin, you know, that's right. That's why I said USDC, if you recall, I think we named it so that the C was circle and Coinbase and Center because the Center Consortium, and the Consortium meant it was decentralized because we were partners on it. And it also meant that others could, in theory, join. That's right. And that was the idea. We expected there to be multiple, you know, potentially multiple issuers, all of whom participated in a consortium, even though they may be competing at other layers of the stack.

3:43You know, the idea is just interoperable standards, right? So like back in the day, Microsoft had a slightly different version of HTTP, than, than Eatscape. And ultimately, that's interesting. Well, you know, there was this, there used to be, it was, it was sort of like, you know, build your service that ran an IE. You mean, you mean, do you mean like blink tags versus marquee, like HTML? That kind of thing. Exactly. Yeah, yeah, yeah, yeah, yeah, yeah. But ultimately everybody agreed. Let's just, let's just agree on a standard and let's not argue over different implementations of say SSL, because we can compete at the e-commerce layer.

4:15So long as we have this foundation of interoperable standards that no one vendor really owns. And when it comes to delivering dollars or other currencies, but stable coins today, largely people largely want dollars today is what they mean when they say stables. It can't be circle dollars or Stripe dollars. Or coinbase dollars. Yeah, exactly. Coinbase dollars, whatever it is. It's just dollars to people who are using it. And so we sort of saw a need for if dollars were going to move over internet rails and over blockchains, then it needed to move as an interoperable standard. And so that was the idea.

4:50So it's put together a consortium, not sort of Libra style of 30 people who can't agree on anything, but, you know, a small number of very like-minded, motivated participants who could agree on these fundamentals and get it going. Yeah, you know, I like the Libra guys, and I remember saying to them at the time, and And I think David Marcus and Morgan Beller and so on would agree with me now, I guess. It was totally fine. You know, they did their thing and I give them props for seeing it through, even though, you know, it didn't work. Another thing works. But I think the issue with Libra at the time was, A, they were using a basket of currencies to back their thing.

5:28And the problem with that is you had volatility without upside, right? You didn't know if it was like one Libra is what? It's 87 cents a day and it's$1.15 tomorrow, right? and so it wasn't mapped to anything that people had psychologically right no fixed price he had the other hand they had volatility without upside because it's never going to be 10x right so it's like worse to both roles in that sense and then there are other kinds of things that were like that as well where it was blockchain so traditional banks thought it was risky but it didn't have any upside so crypto people didn't want to back it and actually this was something which i think we did right with usdc so i'll explain on the coinbase end how we were thinking about somewhat similar to how you were thinking about it.

6:08So my view was because at that time, if you recall, we were in the ZERP era, right? And so we didn't know, I mean, only with a crystal ball would you know that they would jack rates to the moon in 2022, right? That was like four years out at that point. And we had been in ZERP for like almost 10 years, right? Since the 2008 financial crisis, right? And so USDC, it was not obvious that it was going to make any money anytime soon. and the way i conceptualize on the coinbase side is we thought about it similar to how you thought about it but we thought about as google login like google did not make money directly from google login but it sort of projected you know like uh projected power projected login over the whole internet and then people would come back to google except a decentralized version of google login where stable coins would be used everywhere and then people would come back and they'd trade on our venues they do things they basically be part of the crypto economy so just like google login sort of grows the internet we thought usdc will grow the crypto economy that was one kind of process the second thesis is we we put in capital behind it because we didn't think that um so had it been an ico for example there would have been pressure for a short-term return so we capitalized it you know together and uh i think that proved correct because had people gotten or wanted interest back from it.

7:32Now today, it throws off whatever billion dollars a year, it's like 5 % rates, 4 % rates to 70 billion, it's like two,$3 billion a year, not bad for seven years, right. But at the time, it literally returned like nothing for like the first four years or something like that, because interest rates were zero. So something like that is, you know, something where you can't necessarily make money on it, because rates are not, we're not within our control, or we didn't know. So we had to essentially assume that it was just a utility thing for the entire ecosystem until the returns came there. Does that comport with how you guys thought about it?

8:05Let me know your thoughts on that. Yeah, you know, the first version of it in 2017, actually predating Coinbase, we did have a, you know, it's probably still floating around out there. The first version of the white paper contemplated a token being released on the network that was called the SENT. And so there was sort of this alternative path that we quickly realized this is not the right way to deliver this but there was a little bit of a different revenue model tied to it um by virtue of you know having a token and this was yeah this was in the ICO you know sort of boom and bust um and uh you know we explored a lot of things uh to try to deliver it in that fashion before we did v2 yes and that was our collaboration and then we that's right we we had patient capital on the balance sheet.

8:53So we didn't need to, we didn't have ICO, like nothing against coins, but those investors are not patient, as you know, ICO investors are not patient. So, you know, so by having patient capital on the balance sheet, we could go for years and years without, you know, worrying about any return in the short term. And I think that that helped a lot. Okay. So now I'll tell you before, before, so, you know, we had sort of decided what Coinbase is the right partner. We were also talking to others, I mean, as you know, and assisted by people like Jim McDoll at Coinbase, trying to bring people into the central consortium.

9:31And there were very serious conversations we had before Coinbase that it didn't work out with very large players when ultimately you leaned in and others at Coinbase. I always wondered internally, did Brian have to be convinced to go this path? It's a good question. So now the story can be told, right? So it actually, so again, of course, you know everything that happened on the Circle side. I can describe what happened on the Coinbase side. So there was essentially a big conversation internally, which was build versus buy versus partner, right? And I wanted to, so buy would have been like buy an expensive stable coin or something like that.

10:14And I also felt that wasn't really in tune with crypto because crypto is about decentralization and so on and so forth. And so I wanted to, first of all, partnering would have been, you guys had, my view on what you guys had, you had an audited smart contract at a time when that was actually a relatively very scarce thing, right? Because a trail of bits and what have you had, you know, they were, they're still, I think they're still good, but they were backlogged. And, you know, there weren't that many people who knew how to do audited smart contracts at that time. So I knew that that would take us months to get to the level that I felt that we could put hundreds of millions or billions of dollars into it, right?

10:51Like an audits of our contract is no small thing, right? There's that and also, you know, the fact that you guys were reputable. You've been around for a long time. Jeremy had had an exit before with his video company. Gosh, I'm forgetting the name of it, but it was... Brightcove. Brightcove, exactly. That's right. Like streaming video company. And actually, we had met you, I don't know if you remember this, when I was a partner at Andresen, all the way at the very beginning in 2013 when you guys were starting circle uh you know so so we we had game film on you right and and obviously i think there was mutual respect um and then the so my view was a partner b um user balance sheet and essentially the question was partner versus build right and i felt that partner was the right approach because crypto is like i'm a i think i I'd like to be or we'd like to be win-win people and there's more that can be done together.

11:44And I felt that that would be an organic partnership since you guys were also crypto first and you've been in the space for a long time. And everybody who's in the class of 2013, we all have our grays. Right. But that was like the first time that a bunch of venture, you know, Eric Voorhees of Shapeshift really got his start back then. Right. I think blockchain.info really got going then. You know, Blockstream got funded around that time. And so I think quite a few companies, as you may recall, like CoinDesk and so on really got going. So I think some of the really foundational companies in the space got going at that time.

12:16And you'd been in the space for the right reasons. You weren't like a Johnny come lately. And I mean, it's all obvious stuff, but these are just explaining what our thinking was. So I felt you'd be a good long term partner for this. And so that's that was part of the reasoning on our side. And then what I did, which you guys don't care about, but we had just really three or four people on our stage. Jim McDull, who you met, Jacob Horn, who's the product manager, and then Maxim and Miha, who are the two lead engineers. And then there are several other people, you know, on design and so on. Those are, I think, the four principal people.

12:51Maybe there's somebody I'm forgetting, but I think those are the four principals. And the biggest, one of the hardest things was just clearing everything off of Maxim and Miha's schedule so they could just code 24-7. and block all the HR people and so on and so forth. So no, I just fell out of their forms. And we shipped it really fast. October 3rd, 2018. Go ahead. Yeah, yeah, I think that's right. And Jacob, by the way, also, I always felt he was a great champion for us internally. Yes, yes. And, you know, really, really enjoyed working with him. We had Joao Reganato, who was PM on our side, but our CD is really small too.

13:20It was a handful of people. I mean, the tech, obviously, it needed to be secure. It needed to be a strong, And obviously, we launched it on Ethereum. It's now on like 20 - On everything, yeah. It's on everything. But it has to be secure. And so the code mattered a lot, but there's not a whole lot of tech there. I think the partnerships and the distribution, obviously trying to clear the liquidity mode, which is still, there are only two dollar stables that have any meaningful liquidity right now because that liquidity mode is really difficult to clear. Like all of these things were at least as important as the pure engineering.

13:59That's right. And I think the reason on the engineering side, it wasn't so much it was hard because it wasn't a lot of code, but it had to be extremely correct because reentrancy bugs, there's all kinds of these things that can get you. There are two other things that I remember at the time that were really important. First was that a lot of other people had been doing stable coins back by what I call plutonium, right? A very unstable thing over here. And you didn't know what the value was because it jumped up and down all the time. And nothing against Tether. They've proven themselves. They've executed over the last X number of years.

14:36But at the time, it wasn't known that they had enough paper to back what their outstanding assets were and so on and so forth. And then there were other people, not even Tether, who were doing algorithmic stable coins, some of which, as you know, blew up later. And so one big thing for us was using the banking relationships to get$1 on chain backed by$1 off chain and do it in a dumb. But simple is hard and good, right? So the simple thing of just one currency off chain, one currency on chain, that was one big piece. The second big piece, if you may recall, is, and this is a big debate with those banks, right?

15:20was would people have to kyc to send to somebody or would it be a blacklist rather than whitelist right meaning would we maintain so we had to have some compliance type stuff and so on so for somebody misused it so we eventually agreed that freeze and um you know in in extreme circumstances freeze or reverse transactions in in the contract was better than having every single address have to pre-verify in KYC beforehand, which would defeat the whole point of it, right? So once we, I think that was another key thing is we got enough banking partners to agree, A, okay, with a warrant, you can freeze or seize or reverse transactions, just like you can with wires.

16:06And B, you can also guard the egress and ingress at the exchanges when USDC is being swapped for USD, right? And so given that, then you otherwise have fun on chain and do what you need to do, right? Yeah. And I think that actually now opened up the door for, among other things, something you and I have both thought a lot about, kind of your new company, which is Katina, right? Because by doing that, since, you know, if you had to KYC every address, you couldn't have a program generate 100 new addresses because it all have to be KYC by like the human and some photograph or something like that.

16:42It'd be too much friction on the thing. It'd be impossible. It'd be impossible, right? So that brings us to the unlock of machine-to-machine payments. So why don't you talk about your new thing, Katina? Yeah, so I'll also say something on the way that the sort of funds freeze happens. I was still never, honestly, I always felt like we could have innovated there a bit more past just address management. I mean, you and I talked at the time about things that were more sophisticated, probably would not have been executable then, but this - Like governance contracts that - Governance contracts, yeah.

17:15like risk and reputation on chain to, you know, sort of handle these, these sorts of things. And it turned out that you were right. So the simple approach was, was the one that was going to work, you know, but I still always felt like, you know, there's something there. And it's the, you know, one of the things that always nagged me about the internet is there's no real like, like really, you know, distributed identity layer where people can sort of manage their own credentials effectively and not have to lean on a Google or whatever. um and i i was sort of like the remnants of that i wanted to somehow figure out maybe how we could incorporate it but at the end of the day it was all about not even getting the regulators comfortable but our de facto regulators which are our bank partners um and uh this the simple approach was the one that was going to win there for both settlement and reserve bank partners yeah yes and and i think that basically um you know like you so i think today it's possible to innovate on that right but you know uh my my view on a lot of things like this is sort of like minimum necessary innovation right so no coin we just did off the balance sheet no plutonium we just did one-to-one backing you know usd for uscc uh no um coin governance we just had root access to the contract we had the minimum size of the consortium of the game which is two and and we just minimized all complexity and it was still not a completely trivial thing to scale and build this thing over last few years uh but but it was awesome and you know really you know it's funny you do 20 things and it's interesting as to what things actually turn out to be really big you know um it's kind of like for you know there are like 50 investments i do did in a year and then one of them is like ethereum or one of them is salon or something like that and then it's like oh okay well that went you know that goes really big right and it's interesting because a year later or two years later usdc was useful but it is it is after i think zerp ended that it really went boom like this and became as material as it is now right and it's funny so i'll tell you another discussion that not public but i think you know there was a discussion internally as to how much to out you know like resources to allocate towards usdc and unusually see most of the time you know good advice to the company is like ignore macro but in this case you couldn't ignore macro because 100 of the decision was what is the fed going to do right because it's like is it going to increase rates or is it going to keep them down or is it going to go wiggle like this or what is it going to do and like it felt actually it was much more wall street than i'm used to in tech because completely 100 % decision was your mental model of the Fed.

20:01I don't know if you have any thoughts on that. Then we can go to Katina over there. Yeah, yeah, yeah, yeah. No, that's true. I mean, I think that my recollection is that even after we had decided on most of the structural pieces in terms of governance and tech, and we had, you know, lined up the banking partners. And this was also, speaking of banking partners, this was also just barely after the era when there was only really one bank in the world that would bank coinbase or circle yeah so the banking partner piece which you mentioned was it was a huge negotiation and discussion because uh things are different now um you know we have you know bony mel and blackrock and you know you know but it was not like that then um uh a short time ago so so yeah but my recollection is that the the most um uh i would say difficult but time-consuming hardest pieces to put together were the economics It was the macro situation, a sort of analysis, but also micro.

21:01What should the economics be if we have a consortium, not of 100 people, but of a small number starting with two? What does that look like? And there's a lot of discussion that's been revised since our time focused on that. But yeah, absolutely. I think that was the big puzzle. And even then, I remember we had people talking about, you know, maybe can you do JPY stablecoin or like negative interest rates? All that is now happening. All that is now. Absolutely. Yeah. Yeah. So that's right. So you asked about Kupaina, and I keep going back to USDC because it's fun to chat with you about it. But, you know, one of the nice things about machine native money is that it's very reliable for machines to use it.

21:46so uh so when we have these orchestrated workflows call them no one can agree on what an agent is but sort of uh workflows with llm intelligence involved in making decisions um then as those workflows become economic actors they need to be able to transact they need to be able to hold money they need to be able to send money they need to be able to make you know treasury effects decisions potentially with you know all within guardrails um and uh humans in the loop where necessary. But simply tacking AI intelligence onto the edges of, say, a credit card flow is just, aside from the economics, it is not reliable.

22:22It's really difficult to make those, even just the simple tool calls very reliable. And so when you take a five to seven to nine party system and you add a couple more parties on the edges of it, then it's different than taking a stablecoin, you know, point to point transaction. And, you know, Agentech workflows are very good at signing cryptographic messages. And so, and then all of a sudden, you know, you sort of unlock the capability of transacting in fractional amounts, in like streaming payments in real time, all these things we've been talking about for 20 years, but have really never been economically possible or technically possible until we have the combination of machines becoming economic actors and stable coins.

23:05I don't know if we keep calling them stable coins, but it's a, you know, screaming money. Fiat coins. Yeah, that's right. Well, so because this is funny because, you know, 10 years ago, I also took a crack at the machine payable web and machine micropayments and 402. And the issue was that Bitcoin at the time, see Gavin Anderson, if you recall, had published a roadmap for scaling to huge numbers of transactions of big blocks and so on. And then the Bitcoin civil war happened and became small blocks and fine. But that just basically meant that you couldn't scale on Bitcoin in the way that, you know, lots of transactions.

23:41So everything had to move to other chains. And so and frankly, you know, it's funny now today in retrospect, now that we have Solana and base and we have USDC and we had to have Ethereum and we had to have Bitcoin. And we also had to like win this gigantic political battle. Right. After all of that, Now, finally, lots of the pent up innovation. And also we had to be able to get on phones, right? Because you have to win this political battle because this is something it's a really interesting thing, which, you know, and I know so many people for some years like where are the crypto apps? Why aren't they on phones?

24:19and the reason is that apple especially and to a lesser extent but real extent android would nerf all kinds of apps that use crypto on phones because there was some like apple payment you know the iap thing in-app purchases thing all this kind of stuff where they've now actually lost some cases on that you know and they're sort of being forced to do that and to be clear look apple does a lot of stuff well but they're sort of genetically anti-crypto and so there's a chicken and egg thing where you just couldn't get. And that's why crypto has actually developed as much more of a web phenomenon than a mobile phenomenon.

24:52We have to be choke pointed in a certain way where we're only web rather than mobile. And we have to be choke pointed through the banks in a certain way. And like you couldn't do equity issuance. You can only do meme coins. So I think Bankless also had a very similar observation. Like there's all this pent up spring of innovation go boing like this over the next 10 years that machine payments are a part of. Go ahead. Yeah, yeah, absolutely. I mean, my thesis is that in the future, the only actors that we will trust with our money and our assets and the only actors that will be capable of generating competitive returns will be agentic.

25:30Interesting. And and I mean, or do you mean delegates of yourself? So this is that's a good question. So right now there's a little bit of a battle, I would say, between those who believe that agents should be mapped to tasks that always get mapped to some user, could be a business or consumer or whatever. And those that believe that may be true, but we'll also see semi-autonomous or autonomous agents that actually do have their own identity and act on their own behalf, not just a planning loop, but can truly act on their own behalf. And so there's debates on both sides of those things. But I think, you know, either way, you know, in terms of being able to make good decisions rapidly enough with money, we will just not want to trust anything other than, I mean, it's hard to imagine now because people's anecdotal experiences are that, you know, Claude or Chad GPT can't give them a recipe for a brownie correctly because of the sort of hallucinations.

26:31but it but it is i still have strong conviction that it is the truth that we will see ai actors that will be the most effective economic participants the world has ever seen and then we will want to use those but we will have no need to ever execute a transaction ourselves we will always be doing it through some form of um uh you know personal or other ai interesting you don't think you'll ever need to execute a transaction yourself that's interesting that's strong form version um so where do you when that happens when that happens is a question i always find that when the hardest question for me to answer in this so i have conviction around the what does it take uh three years to touch certain domains before others or does it take two months does it take 20 years it's really difficult to say so 12 years ago actually me and actually the winklevosses and novel we are there's some panel and i remember thinking about machine payments then and my kind of example of something bitcoin could do that you know other currencies like fiat couldn't do is if you had two self-driving cars on the highway one of them could pay the other to pass for example right and now that's just kind of a made-up example but the general concept is machines could negotiate prioritization amongst themselves or what have you right in practice by the way self-driving cars might just drive fast enough that they could just you know boom snap snap onto each other and and and go right but there's probably something to that of machines being able to negotiate back and forth you know uh for example you could have um a fully you know right now waymo and and tesla robotaxis just to drop off and pick up finally we have truly fully self-driving end-to-end cars but you could have something load food into it and then unload the food on their side like sidewalk robots exist right and drive-thrus exist and you could have something where like the car pulls up it pays the robot it gets the food you know i mean right so that's an example of machine to machine i don't know if now the thing about that is that's actually in the physical real world which is always hard because there's other kinds of issues there's wi-fi drop out the bluetooth drop so i wanted to know where you thought the first two or three applications of machine payments would be for katina yeah so i'll say what we're seeing today what we're not seeing is true agent-to-agent or machine-to-machine payments.

28:54We're seeing AI workflows pay for access to resources, content, data, paying for access to APIs. There may be another agent on the other side of an API, but the interface is not truly agent-to-agent yet. And I think there are a lot of reasons for that that have nothing to do with the payment side. There's no DNS for agents that we haven't really figured out the right way to handle discovery. um uh you know if you're if you're if you're if your agent interface you could just do it all with text fields i guess but yeah not really because agents don't have persistent domains either they can't yeah i mean they kind of do but not really there are proposals for like registry concepts so google has you know proposed something for a registry concept attached to their a-to-a framework maybe maybe there isn't really like a standard for it maybe you could use ens or sns the salon to name system for doing that because that's a little more flexible than dns yeah you can buy i think we may see a little bit of fragmented approach where there'll be you know multiple things that will need to be supported but in the meantime it's sort of like you know if you and i go build a website we get a domain and we just deploy it or you know there are lots of ways for it to be discovered in the world and there aren't really there's not really that equivalent for agents working outside of their ecosystems and even when people build agents it's usually in a particular framework or in a particular ecosystem it's uh and it talks to other agents in that same ecosystem but it doesn't really span uh the ecosystem so if you build an agent that you deploy say um uh you build it and say you know a framework like lane graph um how does it make it self-discoverable outside of like a chat interface to an agent deployed in like salesforce or something so so you know there are smart contracts that are something something.eth right and so that i mean basically the smart contract and the agent are the same thing potentially and you just have an ens name or an sns name and that is that is the registry but but i like your framing of it which is smart contract registries and agent registries should be the same thing and that there should be like i think that itself is a business in its own right to just register and discover agents you know yeah i think that there's probably a um there's some form of you know verisign for agents company that wants to be built.

31:06And there's variation on them too, yeah. Because they could just take your funds and something, yeah. Exactly. And this is part of the work that we have done at Catana so far is just this foundational layer of trying to address trust and policy. The issue that people have with agentic workflows is not yet things related to price sensitivity or even largely data privacy issues. It's just reliability. How can you trust these things? Who's vouching for them? Or when they exceed their guardrails, who's liable? um you know all these sorts of guardrail policy reliability really trust issues um and so this is why yeah exactly that's the thing the ai like you know i i recognize that it's in like in some sense a trough of the gartner hype cycle now it's weird because both there's tons of money going into it but also there's less energy than there was a year or two ago in the sense of oh my god it's going to kill everybody and so on and so forth right but um my view is at least right now as a 2025 ai requires a lot of supervision to get anything non-trivial done and the smarter you are the smarter the ai is and it doesn't do it end to end doesn't middle to metal right because the prompting and the verifying have to be done by humans and so it's great generating reams and reams of text but often a lot of that is filler and i can always tell when someone's used ai to do something and even when you're using it like i think the biggest thing for me whenever we use ai internally is there's actually only relatively few kinds of tasks which can truly tolerate non-deterministic error prone output images and video can but back-end code can't like front-end code is more tolerant of those issues because we have our gpus in our eyes and we can instantly see it and verify that the widget is off but back-end code is much more subtle and it's like much harder to determine that it's off without like really going line by line you know right and uh and it's possible there's some like visualization mechanism, you know, like a Fourier transform, or like an audio spectrogram can turn something that's not visual into something visual.

33:22So it's possible we might be able to turn some of these other data structures like back end code into things that we can just visually debug by eye, you know, like a state machine or something like that, right? So it might be something along the lines, or it's in a domain with smart contracts, for example, as you know, formal verification finally became useful, because these were such compact programs and of such high value that all the compute for formal verification actually became valuable right so maybe maybe that's the answer is uh you know we we have an only generate code that we can do formal verification on or something along those lines but the reason i ask is where you know shopping seems to me to be like the simple kind of thing of get me a good plane ticket that satisfies my requirements, like from point A to point B, that doesn't cost more than X, seems to me like a good place to start because that actually does take a surprising amount of time to go and book tickets.

34:18It's like actually kind of a pain still, right? Oh, you have to put in your name, blah, blah, blah, fill in all this stuff on every new airline site. So that's like one thing, right? And I think the max budget stops it from totally screwing up too much, right? And Maybe you just assign it to get food or a book you like or something like that. I don't know. Maybe you have some thoughts on what it would buy for you first or what you would do with it first. Yeah. So my belief is that right now, I mean, things can change by the time this conversation is done. This space is going so quickly. Right.

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34:50But right now, I think consumer retail shopping experiences will be one of the hardest nuts to crack in terms of a full shopping flow. So I think, you know, I can see it replacing search. which is sort of already having the content on the web in some way. But the full flow, I think that'll be, I think we'll see B2B or even B2B2B sort of agentic payment solutions happen before we see some of the consumer use cases. But... How about EC2 then, compute auctions, right? So Amazon has auctions of compute because they've got real-time pricing as demand goes up and down, right? And you can get reserved instances versus real-time.

35:30Maybe somebody's already doing that. But that's an example of a machine bidding on a resource used by a machine for an algorithm where it's like truly a machine economy. I don't know. Maybe you do. Yeah. And use cases like supply chains are another one where a buyer agent and a seller agent can potentially negotiate. So if I have 12 approved vendors for this piece that I need to acquire, then this sort of discovery, negotiation, and also handling things like the fulfillment could be handled by agents on both. sides. And in that case, the data may be known, but in many cases, the data types themselves, the schemas may vary.

36:10And so you have this need to parse, you know, not necessarily unstructured, but not always, you know, schema compliant structured data, which LLMs can be quite good at. But to make that reliable, you know, what we found so far to make that reliable, it's not the AI that is actually executing the task or interpreting the data and beginning to handle the negotiation that requires human subject matter expert alignment, it's actually the evaluating sort of LLM's jury sort of evaluators that are other AIs, just evaluating the output of those task executors. It's that layer that requires human subject matter expert alignment in order to make the sort of upstream task much more reliable and effective.

36:55So actually, just poking on that for a little bit the only thing about supply chain is you know i actually ordered a lot of you know um i still i still we're building network school so actually i'm constantly looking at bill of materials and so on and so forth for various physical things um that is a manual in my view a fairly manual process because you're talking to the vendors you are i think an agent can help you with getting quotes maybe that can be helpful right if it's hitting a bunch of telegrams and whatsapps and and so that that actually could be quite helpful like i have a spreadsheet and i'm like agent get me get me quotes on this stuff where it's like only partially listed a little bit like otc markets you know where some stuff isn't listed that that's maybe helpful but a lot of those are like large enough and i also don't need it so fast that i wouldn't review the purchase order before i hit submit on it you know but that example would like ec2 compute is something where you might literally put that in a subroutine of get me the best price on this which people already do for reserved instances and so on you know um so like that's kind of machine resources like getting storage getting compute that feels like where it's like kind of native you know or i don't know maybe go ahead yeah i think that um uh you know as the the sort of business model of the web transforms from from you know search and advertising uh dominated into you know, sort of data curation, this sort of data curation flywheel that is beginning to emerge, which is intelligence, whether it's agents or Alolan Foundation, people providing agentic intelligence need data.

38:36That data needs to be curated ultimately by humans can be synthetic data, but it ultimately needs to be curated and sort of aligned by humans and humans need to be paid for that job. So that creates a little bit more of a data content service marketplace that has not existed. And the services that are helping to provide that data to the intelligence providers will pay humans for that job. And so the sort of task of the human begins to be, you know, curate this data content, these services, so that the intelligence ultimately is better for us. We can be more productive. And we get paid for doing that task.

39:11And then we pay for the intelligence in turn. And so whether it's machine resources for things like compute, or whether it's particular or content or data or, you know, services that can be quantified in like a data schema or something, then that becomes a place where agents are passing money, making payment decisions, but also actually executing, you know, a binary payment task. So the thing where we sort of move, you know, a little bit up the stack. So we're still missing some primitives, by the way, to make that reliable. Some of them are related to this potential certification or identity layer that's necessary for agents.

39:47There are many people who are working on different versions of that, but it's kind of a notion of agentic identity and handling authentication effectively. Even in the shopping example, if I'm shopping at Amazon and I'm not just using a chat bot, I'm not on Amazon.com, but I'm just interacting with the Amazon agent in some other way. How can I be sure it's Amazon? There isn't sort of this. Yeah, the authentication, the verification. Yeah. It's like, whose dog is this? Whose dog is this? And then, you know, what are the new security and risk factors that emerge when AI actors are the ones who are executing these kinds of transactions?

40:25Or an agent on my behalf and an Amazon agent on its behalf, what new risk factors emerge? This is why ultimately we decided to create a new financial institution from the ground up using AI is because, and we know this from Circle, you know this from, you know, building infrastructure to manage risk as well. Now, you know, classic finance and banking risk infrastructure is designed to make sure no bots can ever use it. You need to be a KYC or KYB individual. What we actually need is completely the other way around. Let's assume the only actors who will be using this system will be bots or agents.

41:00And how do we let the good ones in? How do we keep the bad actors out? How do we give them rules and policies so that they can't exceed? How do we tell them to escalate to us as needed? When they do exceed those policies, how do we have insurance or sort of liability protections for this? There's always like these problems have not been cracked. And so ultimately we decided, well. I mean, self-directed cars will be the first place where this stuff is happening now in some ways. Liability, all that kind of stuff. Who's at fault? All that stuff. Who's at fault? Exactly. And there is a path, obviously, to have sort of, you know, we're mostly at level two.

41:32I think there may be one level three self-driving in the U.S. now. But anyway, we're mostly at level two. There's sort of a path to get, you know, level three self-driving. There isn't really a similar path for agents executing financial transactions or, you know, aside from commerce, doing things like handling treasury management, a really large sums of money. And that is where we're headed. Yes. Well, I think you might want to I mean, obviously, agents and machine payments in crypto where an agent is trading on crypto bots. That's like a place where you start with some sometimes small, sometimes large amounts of money so that like people have been building some intuitions on this for a while.

42:09Right. But I think you're right that we could do a lot more. Okay, I wanted to, unless you had something else on this, I wanted to switch gears a little bit and just ask about some different topics, if that's all right. Okay. Go for it. Okay, so what I've been thinking a lot about, what I'm working on is physical world crypto, in a sense, right? Because you have, I think, after cryptocurrency, there's different directions you could take it. But I think crypto community is a big part of it because we go to all these conferences. And a conference, in my view, is actually like a it's an important subroutine for our space because we're so digital.

42:48And the conferences are where actually we all kind of come together in the physical world. And so we've got this startup society here off the coast of Singapore where you're just taking over an island. We've got thousands of people from around the world. It's actually really cool. You should come and visit. it um so i wanted to know what you know what do you think about startup societies network states um where's sean on that have you given any thought to that yeah i mean i think we're already in a case where um many of the things that even 20 years ago were done uh in a confined sort of geo space they're online now and so we we've already whether we want to formally uh sort of give a name to it or not we have informally formed our own communities in our own societies yeah and we're in multiple ones of those with different identities that we present to those at different times.

43:35It could be, you know, sort of a gamer society at one moment, and then something that is, you know, related to academia in the next moment, or, you know, family management in the next, whatever it is. We're already in these multiple online societies much more than, you know, than we participate in the physical space that we're in. So the next step beyond that is, well, if we're already in these other spaces, then transforming that to the physical space that we actually want to be? And, you know, how do we think about, you know, forming actual real world corollaries to where we're already spending our mental and, you know, time online today.

44:13And so, you know, that's the sort of transformation. I think of it largely from the view of, you know, we're creating a new kind of global hyper personalized bank that is run entirely by AIs as a level of private banking that most people would never have access to. And that is enabled by stable coins, the internet, AI, you know, all of these things sort of coming together in the middle of this Venn diagram. And that sort of bank is, that is the new hyper-personalized bank for people who are forming, like physically in their space, a version of the society that they're already joining and already have joined online.

44:52interesting yes and so let's say you what is the sean neville you know people ask what kind of company would you start and you have started a company which is you know katina and you did circle before that but i have a different question which is and actually we also start a currency which is we started usdc so we started companies who started currencies i have a i have a question on the third kind of thing which is not an internet company or an internet currency but an internet community if sean was starting a community if you're starting you know something what would that community be what would the theme of it is there something you'd like to see in the world for example latin immersion right or you know keto or something like that right keto keto kosher okay there's just examples toy examples i've got but you must have something you'd like to see in the world what would be your ideal community if you could fork sean and clone yourself and built something.

45:44Yeah. I mean, for me, it's about, uh, hyper-personalization, transparency, and trust that, uh, doesn't require relying on other human beings. Um, and it's all coded, you know, so what are the things that drew me to, um, you know, cryptocurrency in the first place and Bitcoin specifically in, you know, in 2011. And, and it was this idea that I don't really need to rely on, um, fallible humans or the governance structures that they create that are sort of enforced by courts if you can code those things uh crypto and then code those things cryptographically in software um and so you know trust enforced by software is is just it's a fundamental theme so one of the reasons i have such optimism about um although i think you're absolutely right we're in a little bit of the trough of disillusionment in terms of um you know people's views views of uh and this switched because nine months ago, people were really, at least in our worlds, were high on AI.

46:41But you couldn't mention stable coins to them because, especially in AI engineer communities, crypto is even more toxic than in other communities. It's funny. You know what it is? Actually, it's funny. Say if you were going to say, I was going to say, go ahead. I was going to give a meme, you know? Finish what you're saying. I was going to say something. Well, I was just going to say, it used to be that we would bend over backwards not to mention the fact that our agents were using stable coins because, you know, So I think of Circle in a good way is probably the most boring company in crypto because it's a dollar, it's a dollar, it's a dollar.

47:12We went into the front door. We know all these sorts of things. And yet people would be afraid to shake my hand because I was a crypto, maybe a Ponzi schemer or something. And it's completely flipped the other way now where people have a lot of interest in stablecoins, which over the last several months, because of the Genius Act and other things, have really achieved escape velocity in the mainstream. I mean, it was inconceivable six, seven years ago that Stripe would create a payment chain, you know, and the Visa would be leaning in and, you know, so on and so forth. But it has flipped over the last few months where now people have a lot of interest in hearing about various forms of usage of stable coins, not even just as a currency, but as programmable money and as sort of a platform to build on.

47:53They really don't want to hear about the AI component as much. We're right in the middle of both of those things, but it has absolutely flipped the other direction. it's like first it's ai and then crypto and now it's like stable coins and a little bit you know it's just funny you have to yeah but i it's there's um there's one thing about that you know the meme which with the guy getting you know hanged and he says like first time to their guy you know like from uh it says i will put the screen but um so i thought about that because you know right around the time when ai was really going vertical in late 2022 and ftx was happening right so many people were like ai is the real innovation the crypto stuff is all bogus blah blah so many people were saying something like that right and you know of course ai is a real innovation but what's what's interesting today and huge obviously but what's interesting today is I think in the fullness of time, we see a couple of things.

48:52First is AI is actually for many people in some contexts, equivalent to fake AI scam. Is that AI or is it real? You'll often hear people say that, right? So it actually has in some ways the same, it got pulled into some of the same issues that crypto has, where is it a crypto scam? Is it an AI scam? Is it right? So a lot of the AI guys, like lots of artists and so on are super mad about AI. and so it's okay that's one piece the other thing that's interesting is in many ways crypto is what ai can't do that's a deep point like i say because ai is probabilistic and crypto is deterministic ai can solve partial differential equations but it can't solve cryptographic equations and so because it cannot you know invert a hash function a cryptographic hash function um there's certain kinds of np hard problems obviously it can't it literally can't solve them without us changing what we know about computer science uh you know develop maybe p equals np but we don't know that um so without breakthroughs in theoretical computer science like ai cannot solve cryptographic equations and so that that means crypto is like a hard wall that can constrain and bound ai right it can say i have a dollar and the other ai or the other human can say, okay, send it to me on chain.

50:11And if it can't do that, then it's actually fake. It's just emitting words. Crypto is the actions and AI is the words in many ways. And the actions speak louder than words, right? So in a very deep sense, crypto and AI are complementary technologies that, you know, like what you're doing is one example of, I think, a useful synthesis of them with an AI agent that spends crypto, right? But I think there's others as well, when you start I think of them as sort of peanut butter and jelly, like dual technologies, dual to each other. Let me know your thoughts. Yeah, no, I think that's right on. And, you know, the exact form that it takes, no one, I, this is like a space where I think I heard somebody mention it's really difficult to play chess strategically in AI.

50:51Because, you know, you have to kind of go fast. Everything changes so fast. The thing is to just keep marching the ponds down the board right now. um and so people are trying different different versions of that but there are great companies um that are you know experimenting with um uh merging the two in ways that to solve real world problems and there are many uh companies that large and small startups and incumbents that have sort of realized yeah these these two do fit you know there is a little bit of a there's the crypto x ai piece which i think has been a little maybe a little overhyped but there's reality there in combining these two technologies uh at the same time so that's right and yeah in a sense you know this is another kind of parallel financial system which is it's the machine economy that is booting up right now yeah and sense of perspective yeah right so it's like another whole plane of where things are you know trading back and forth absolutely i mean i think ultimately um biology i think it's going to change everything i mean i i know uh you know the closest and the kind of analogies that we use are, well, there are so many, you know, people who first experienced the internet on their devices, they sort of skipped the whole laptop era.

51:58And then maybe there'll be other people who suddenly begin to experience the internet only through, you know, agentic interfaces. And I don't think that's a great analogy, because I think the change is even bigger. Are we still using web browsers to interact with the internet, if our interface is always going to be some series of agents? We're not trying to crack the UX problem here. But these are the kind of questions um you know that emerge i mean replet is genuinely replet and chat gbt and codex and cloud code are genuinely new interfaces for i mean because they can accept probabilistic input like a lot of it right as opposed to you know it's the exact opposite of how you type into a search engine a search engine you sort of invert and you find the least frequent keywords in your head and you give the fewest characters and boom you've got a search query and with an agent you just like you write a huge amount of text and you're as detailed as possible and or necessarily a huge amount but like you can write quite a lot and it'll take all of that and uh your vocabulary actually constrains the machine and it's just completely different you know interface in that sense i mean one other thought i had for you which is um we didn't discuss this too much yet but there's a lot more robots of different form factors not just humanoid robots but like robot dogs and drones and all kinds of things coming out of china that you know robot locks and so and so forth right that is another potential area for machine to machine for example smart locks like here's an example um there's public you could have uh for example in singapore there are these shipping containers that have gyms like like fitness centers they're just in a shipping container okay so you could in theory just go up to it and go zip zip like this and do a machine to machine payment and open the the smart lock and have it debited right that seems to me to be a pretty good application i mean you can do it with apple pay but it's lower cost if you do it with machine to machine and it's cool right and uh and you might be able to do things like that where you You've got a robot dog and it's sitting down, and then you go like this and it jumps up and it starts running around and doing something.

54:17I feel you might be able to do some cool demos there. Let me know if you have anything. Yeah, yeah, yeah. Yeah, that's a really cool idea. I mean, transforming this to the physical is a great space, creative space to be thinking about regardless. I do think in those kinds of examples, like you said, yes, you could do this with Apple. But I think it's going to be very important not to have vendor lock-in in the next version of this sort of agentic web. um and and you know i i think uh that's one of the obviously is one of the things that kind of the web was an amazing um sort of culmination of many many partnerships and technologies and so on but it also steered in a certain direction it was not the healthiest um and you know did not centralization and vendors exactly and like five companies that matter in terms of controlling identity uh you know for for instance and so the next version of this when we we are using agentic interfaces it ought to be much more broadly distributed um and that's the way that it becomes more prosperous for more people um and uh and sort of avoiding this you know yes you could i trust apple i don't want to have to trust that and i you know obviously respect apple i don't want to have to trust them uh to get access to that gym yeah and i think what's interesting is in some ways the society where everything is is computational trust actually then loops around and becomes a high-trust society again in some circumstances because you know that person can't defraud you if you checked it, right?

55:37So that means they don't have an incentive to even try it. You know what I mean, right? So anyway, I think there's something to that which is interesting. Like if their guy knows he can't get one over on somebody because they'll check it, they doesn't even try. There's like a superior force which is the blockchain above them that is enforcing rule of code. you know, between them, you know? Yeah. So, okay, cool. I enjoyed this. And if there's, I guess people can go to Katina Labs. Right now, it's join the team and katinalabs.com. Anything else you want to? Yeah, I would say we've been pretty open about some of the foundational sort of agent, you know, identity and policy and rules efforts that we're contributing just to open source code.

56:25We've been pretty quiet about the commercial product offering. And so we're hard at work building. We're really excited about it. We're taking a big swing. It leverages all these technologies. And so I'd say people are interested from a partnership perspective, learning more, working with us, potentially happy to have conversations. Awesome. Great. All right. Thank you very much, Sean. Thanks. Pleasure. Great.

From the publisher

Sean Neville co-founded Circle, the issuer of USDC, and is now the founder of Catena Labs. We cover the Centre Consortium joint venture between Circle and Coinbase, the rise of machine-native money, identity systems for AI agents, and the fusion of probabilistic AI with deterministic crypto. If you're interested in these ideas, you'll like Network School. Apply online at https://ns.com.

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