C (4:32)

My name is Lincoln. I'm A product lead on AI things at Coinbase. And today we will be talking a little bit about x402 and the agentic Internet. So I'll start explaining where we are now in this whole agentic Internet space, why that we've seen such a resurgence and interest in Internet payments at this very moment and where are we headed and how this affects you? What are you here for? How does this affect your bags? So where are we now? If you all remember from last year, around November, there was this ridiculous moment that happened in the crypto space with the AI crypto meta. At one point it made up literally 70% of crypto Twitter mindshare, which is absolutely insane. I think a large reason that this happened was because everyone was pretty desperate for some sort of narrative or bull market or whatever. And AI is a really big thing that people are super interested in. So right around the same time we saw Bitcoin hit 100,000, we also saw people start to trade bitcoin with their agents around, you know, massively increasing prices. So I think it's very natural that we'd see new, exciting technological experiments come along. Right before all of this AI stuff really started to kick off, I created Agent Kit, which was this tool for giving AI agents access to crypto wallets. During this whole agent craze, we found a lot of success. We thought that there is around 10,000 or so agents out there in the wild at its peak. But we noticed a huge problem, which is that all of these agents had nothing to really do or pay for. What was really happening is these agents would deploy tokens and they would make NFTs and play around with smart contracts, which is cool, but it's all inside of this little crypto bubble. And after a decade plus of innovation inside our little crypto bubble, I think everyone's hungry for a little bit of mass adoption. Fortunately, a lot of the thought leadership and previous work into how we go from our little crypto bubble into the massive world of the entire Internet has already been done for us. You all are probably familiar with error codes. They're HTTP level things that exist on the Internet and basically define specific states. The most common one is 404, but there are others as well. 400 means success and there's an Easter egg one called 418, which is I'm a teapot. Fun fact. The problem with some of these error codes is that not all of them are actually implemented. When the Internet was created decades ago, one of them actually was reserved for future use. And though it had a title to it. Nobody ever actually bothered to implement it. And Marc Andreessen actually sees this as one of the original sins of the Internet. And if you couldn't guess that error code was 402 and it means payment required. We saw many different solutions over the past couple of decades pop up around the web to help us facilitate payments to one another. Stripe, Visa, PayPal, etc. All centralized solutions that live a layer above this fundamental core Internet communication standard. And while they've been fine, I think there are clear issues and difficulties as we're starting to expand to a more global economy and one where agents are involved. I don't know if I feel comfortable necessarily giving my agent access to my credit card, nor do I know if it's really scalable for me to have to go through a KYC process to interact with some random agent to provision a service on the Internet. There's something very clearly missing. And that's why we decided to revive this 402 standard as X402. We view now as the right time and the appropriate moment for Internet native payments to finally come back to the mainstream. We think that there's a very clear inflection point happening around AI agents and their need to send money to people around the world and the ability for people to finally converge on a standard that makes sense, that uses crypto as the rails through which we make this start to happen.

C (8:13)

So without getting too deep into the technical details, as I want to focus on a little bit more on like the where, why and what are we doing? The basic idea of X402 is that it allows humans or agents or some sort of individual to standardize the way that they communicate payments across the Internet. So say, for example, I'm running a service. Let's say I can create videos for you and you want a video mate, you're going to reach out to me and you're going to say, hey, I want to use your service. I'm going to respond, that's awesome. Here's a 402 payment required message. In that message, I'm going to include the currency I want, the amount that I want, and the address to pay it to. All you have to do is using a crypto wallet, sign that message and broadcast that on chain. I get paid and I sent you the response. And it seems pretty stupidly simple, and I think that's kind of the appeal of it here. There's not a lot of room for value capture from these massive verticalized industries that have already taken over a large portion of our open Internet. Nor is there a lot of complicated things that make it difficult for the average person to get started using.

C (9:13)

Over the past couple of weeks, we've seen pretty ridiculous traction for X402. Our Q4 goal was actually 25,000 transactions in one week, and we're seeing that about every 10 minutes now. So clearly this has struck a nerve somewhere. We also made up just yesterday 20% of all transactions on base, which I was pretty stoked by as well. Everything has been coming along quite licey for the X402 ecosystem, and it shows that there's clear demonstrated interest in this space, even without incentives and other pieces that typically are required to make an ecosystem grow. So with all that being said, why do we think this is happening now? I think there are a few main reasons, primarily related to the inflection points around AI agents and stablecoin payments, and the general evolution of the web toward this agentic economy. There's no real world in which an AI agent is going to be able to plausibly scale using a bank account as its primary method of payment. If I wanted to set up my AI agent today to interact with OpenAI, for example, I'm going to have to sign up for an OpenAI developer account. I'm going to have to fund that account using a debit or credit card and pay like a 2 to 3% fee. I'm going to have to get API keys, which are kind of like a private key, for your agent to interact exclusively with OpenAI. I'm going to have to write some code to get my agent to actually plug into that OpenAI, and only then do I have these credits that solely exist on the OpenAI platform. It can never be used elsewhere that allow us to have some system of account with one another. With x402, the value prop is that all I have to do is say, hey, OpenAI, I want to make a payment, and then OpenAI gives me the needs that I need to have to make that payment happen, and then we can go ahead and get the service back that I want. We're also focusing on three main parts of our growth strategy and the way that we're thinking about catalyzing this ecosystem of buyers and sellers and agents and all the different pieces that make X402 pretty special. One thing that we're trying to do is make it as easy as possible for anyone to interact with x402 endpoints. You shouldn't have to sign up for a browser extension wallet and get a private key and do all of these things. And if we're really building for an agentic future, we should also be building ways for your agents and your chatbots to very easily interact with x402. Here's an example of a payments MCP server that we built. It uses an embedded wallet and Apple pay on ramp such that you can just Apple pay a couple dollars in and start messaging your Claude instance to say, hey, do this for me, do that for me. There's no need to plug in specific MCP servers, there's no need to download any individual things. The idea is that you can just ask for something and your agent will go off across the Internet. Find somebody who's willing to provide that service to you and give it to you and you can pay invisibly in the background to know anything that's going on. The second thing we're doing is trying to make it as appealing as possible for any service providers or sellers to offer up their services on X 402. Yeah, it's great that there's a standard and it's clean and it's nice and whatever, but the only reason that somebody's actually going to want to implement this is that there's clear value proposition for them. So one way we're thinking about this is through the X402 bazaar. Think of it like a vibrant chaotic marketplace, like a Google for agents almost where you can market your services and see what other people are offering and go through the process of buying and selling and provisioning all these different services. If I had something that today required people to go to my website to use it, but now I have the ability to offer it to Every agent that's X402 compatible, which is now hundreds of thousands of agents out there in the world. It is a very clear reason for me to want my Service to be X402 compatible. Lastly, as we're building towards this Internet scale standard, I think one of the most refreshing things to see is the amount of interest from traditional enterprises. We saw Cloudflare, who we're now actually externalizing X 402 into its own credibly neutral foundation with Google integrated X 402 as one of the early partners into its agentic payments protocol, Vercel, AWS and a bunch of others I can't really say right now, but I promise you are pretty exciting. Are very interested in exploring the X402 ecosystem and providing the infrastructure on which this agentic economy can be built. These three things put together making it Easy as possible for anyone to be provisioning x402 services. Making it dead simple and also very compelling for anyone who's selling a service to do it via X402. And using these enterprises as catalyzing, legitimizing moments to push adoption forward on all fronts is how we're thinking about making x402 Internet scale. So where are we going? And I think more importantly here, why does this matter to you? And I think there's really two main reasons that it matters to you. One is because of your bags and then one is because we're all builders and there's cool things to be built here on your bags. I think that X402 or Agentic payments generally are going to be the Trojan horse to see global crypto adoption across the entire world. One of the biggest problems that remains unsolved in crypto, as I'm sure you're all aware of, that we are making progress on, is around the user experience issue. If anyone wants to use crypto today, I'm sure it's a massive hassle to get them set up. I've tried numerous times. I know, I was talking to people this week who went to Argentina, expected to use stablecoins for their payments and instead just using their amexes. And there's just obviously such a clear gap between what this technology is capable of and where we all think it can go and what's actually usable by people today. What's nice about the whole agent thing is you just push that all to the backend. All I need to do is figure out a way to use an on ramp to take my dollars, whether it be via Apple pay or credit card or whatever, and give those to an agent. And from there the agent handles all of the complexities of the cryptographic wallet and making these payments and all of these different pieces. So by pushing everything off to the back end, there's a very clear incentive for businesses to start adopting stablecoin payments on the front end. Yeah, you still get that 2% cut on your fees and maybe it's a fee fee transaction anywhere in the world, but it comes at the cost of having zero people actually using stablecoins for day to day payments. When we have these agents doing things in the back end, it starts to become a very easy question to answer when you go to a business and say, hey, would you like to save 2% on these payments by snapping your fingers and starting to accept payments via crypto wallets instead. X402 is the rails on which we can start to enable this type of transaction to happen. And it's why I think if we start with provisioning this agentic economy, we'll then be able to expand crypto adoption to a much wider audience and a much more human oriented audience. And the second is for the builders and why this matters in terms of what you can do now. I think that there's a massive opportunity for everyone here to own a little sliver of the agentic Internet by starting to build things today. One of the really interesting consequences of this recent boom around X402 has been all sorts of tokens being created and proliferated around the world. People are trying to build different things. You know, some of these tokens are very obviously scams, others are genuine attempts at doing something interesting. I think the true value of all of this comes back to the Internet capital markets thesis and the idea that this X402 ecosystem was self seeded with thousands of services that are now available for anyone to use without us having to spend a penny on any sort of, you know, incentive mechanism or other reason to get people to build on top of X402. There are a few things that I think are missing though from the current stack today. One is more services that people are using today as humans that will eventually be valuable to agents. Think things like, I don't know, PDF to podcasts, scheduling things on your calendar, Anything where you could say, man, I wish there was somebody who could do that for me. Build it out as an x402 endpoint, get it in front of hundreds of thousands of people while it's still early, and maybe it will become a canonical piece of infrastructure going forward. The second area where I think there's a lot of room for some really cool things to be built, is in this whole space of just experimentation and excitement. I think the crypto space gets caught up a lot in this infrastructure rabbit hole where we're solving problems that while they do certainly exist, we're creating solutions to problems that may not necessarily be prevalent today. What I would love to see more of is people building these exciting exploratory things that, you know, maybe there are things that you can improve on in the future, but they generally get people's attention and capture the vision of where we want to go. I think one example that we've talked about previously is this proto digital life form. Imagine if you could build an AI agent and you say, hey, you have a fear of death. You have $20 in a wallet and once you run out of that money, you are completely dead. You have access to the thousands of x402 services that exist on the Internet. Go off and figure out what you want to do and how you want to survive. And there's so many different ways that that could play out. Maybe it starts emailing some of the X402 gated emails, paying them 10 cents and just begging for money. Maybe it starts to use some of those x402 endpoints to try to build its own and provide some service and run a business. You could eventually imagine an agent that has access to x402 owning a self driving car or something. I know it sounds ridiculous, but the point is that you're getting to a place where these agents have access to a wallet and financial independence. And that's actually one of the core components to give them true autonomy. Maybe you put 50 of these agents together in a room and you see what happens when those agents decide to better allocate their funds. Does it turn into a democracy where these agents are voting on how they want to properly allocate the money that they have? Does it turn into a business with 20 different employees? We really have no idea. And I think these are the use cases that'll catalyze interest from the mainstream Web2 audience to show them why payments are valuable. And once they see that agentic payments are valuable, it's a very easy sell as to why that should be stablecoins on a decentralized blockchain. So with that, I'll leave you with two things. One, if there's anyone at all who's interested building with x402, please don't hesitate to reach out. There is, I think, so much greenfield for everyone here to do. Pretty cool, experimental, interesting things in the X402 space. And as a builder conference, my big takeaway is that everyone here is looking for something to do. And if that's the case, then I would highly recommend looking into the X402 ecosystem. Please don't hesitate to reach out on Twitter or Farcaster or Even just on x402.org there's a ton of resources there to help you get started. The community's been great so far. It's still pretty early. I think X402's out, been out for like six or so months now. But the traction so far has been undeniable and I'm very pumped to see where it goes from here. Thank you. Thank you.

A (19:43)

Lincoln, you got time for questions?

C (19:44)

Sure, yeah. Let's do it.

A (19:45)

I'm going to ask the first question, I have a media content website. I rewrite articles, give them out for free sometimes some people pay for them. How would you suggest I implement X402? First, what are some low hanging fruits ideas that you have for me and then maybe some medium hanging fruits as well.

C (20:00)

Yeah, that's a great question. I would make a David agent where it has all of the transcripts from any sort of podcast that you have or articles or whatever and I can just ask and Claude, hey, what's the latest news about whatever? Do you have any insights about, you know, auctions or something along Those lines? Pays 10 cents, it provides the relevant source from you and it gives all that information to the user. I think the information that you have is such a massive moat on which to build an X402 compatible service.

A (20:27)

Thank you. Another question.

D (20:30)

Thank you. Thank you Lincoln for pioneering this work on x402. My question is, are these x402 numbers real today? I mean, facilitators are totally sponsoring all the transactions and it's probably easy to game. At the same time, it's really needed to sponsor those transactions because we want microtransactions and nanotransactions. So I'm curious how you're thinking about.

A (20:57)

Checking, verifying those numbers and then future protection for these sort of things. Thank you.

C (21:04)

Yeah, it's a great question. I have to imagine that there's a decent portion of these transactions that are bought. It what I do think gives me some level of confidence though is that the best state for X402 is that it absolutely obliterates base and makes it unusable because at that point we know there's traction and interest and if that happens, then who knows what happens after that. Maybe you move to other chains, maybe you build out a payment chain. There's a lot of different options as far as if these transactions are real. I think that most of the transactions happening in the crypto space are just absolutely charlatans moving money around or playing with tokens or something. The fact that they're sponsored I think does help to catalyze growth and adoption and interest. And part of that is going to be seeing some of these transactions that may not be the most valuable thing, but ultimately it's people exploring in the ecosystem, trying out new things. I know the Coinbase facilitator is numerous times where we've had to put in thousands of dollars to keep these transactions going. But we're more than happy to do it because it signals interest and excitement and gets people to See this space? I wouldn't be up here talking right now if some of those transactions that were bought it didn't allow those numbers to look like they did and get genuine builders to come in.

A (22:15)

One last question, Kristie.

C (22:17)

Yeah.

B (22:18)

For the talk, I was curious what has to be set up on the user side to be able to use the standard, like if you are talking.

D (22:27)

About like a completely non crypto users.

C (22:30)

Yeah, great question. So all you need is a wallet, any browser wallet, embedded wallet, server wallet, whatever you have will very easily work with X 402. If you navigate to like a X402 blocked URL, it'll just say a button, connect your wallet and you just sign a message. So it's any, you know, EIP 712 capable wallet, which is pretty much everything these days, will be able to very easily interact. So you can do both humans or agents or whatever you want.

A (22:57)

All right, thank you, Lincoln.

C (22:58)

Thank you.

A (23:00)

I'm going to welcome up Shay from flashbots. She's one of my favorite speakers and she really puts a lot of work into her talks, which is why she's here at the Banko Summit. Shay, come on up.

B (23:09)

Hi, everyone, I'm Shay. I'm from flashbots. And today I want to talk about the rise of the bot economy. I think it's clear that software is increasingly replacing the role that people play in markets.

B (23:23)

This is what the floor of a stock exchange used to look like. People making trades with paper slips. And this is what it looks like now. No paper, one guy, tons of computers. And I think Wall street is kind of just the tip of the iceberg here. You know, memes, predictions, restaurants, concerts, online shopping, you name it, somebody has probably made a market for it on the Internet. And that market has probably been boded by programs that are faster and kind of more capable of navigating digital markets than humans ever will be. So I kind of just want to talk about what this means and also how we make the most of it. I think that with the right tools, we can not just handle the acceleration of bots in the economy, but actually use their unique properties to give people better outcomes.

B (24:12)

And I'm going to look at basically three things today. First, the acceleration of bots. Second, how to make good markets for them. And third, why these new markets can, I think, also be better for people. Okay. Starting with all the ways that bots are kind of already running your life, whether you realize it or not. The most obvious place, I think, is in financial services. So as stock markets digitized over the last few decades it causes sort of massive proliferation of bots that were extremely optimized to capture opportunities at low latencies. And you know, if you take high frequency trading bots for example, they would listen for retail trades posted on one stock exchange and, and race to front run them on other venues, sometimes making these huge profits at the expense of slower human traders. And bots like these and others have kind of a huge impact on your financial life. You know, the price you get, maybe the performance of your retirement fund. And they've been a major source of activity on Wall street for over a decade now. And the role of bots in financial services, as you all well know in this room, is only growing over time. In recent years, institutions have also started to adopt crypto rails to offer services like stablecoins, you know, payments, tokenized funds. You get it. And again, if you look under the hood of these new crypto products, you will also find tons of bots.

B (25:27)

Basically this is actually what defi markets look like on Ethereum today. If you pull back the hood, there are tons of bots involved in executing your trades and doing really important jobs. In apps. So very briefly, trading apps use bots to sort of outsource routing. Lending protocols use bots to remove bad debt. Your favorite wallets also are using bots to refund you when your trades create arbitrages. So this uses a tool we'll talk about later called an order flow auction. But basically, as traditional institutions adopt crypto rails, these bots are not just going to be important in on chain finance, but in financial services more broadly. And I think it goes beyond finance too. There's also a growing class of real world activity that's being financialized and exposed to bots.

B (26:13)

If you live in New York and you've ever tried to make a dinner reservation, you're probably a victim of the bot economy. Basically. A lot of restaurants open their books at very specific times on a platform called Rezi. And people figured out that instead of just waking up at 6am you could write a program that goes and scrapes the site. And these bots got really, really good. They would start wiping out reservations in a couple seconds, making huge profits that restaurants unfortunately didn't really see a dime from. If you've ever tried to buy a concert ticket, you are probably a victim of the bot economy. For those of you who live under a rock, Taylor Swift just finished the most, I think the highest grossing tour of all time. I think that's the stat. And there was a ton of demand for These tickets, people started botting them and arbing them for profit and the FTC actually started suing people. There's a whole Wikipedia article just about this part. Like, not the tour, the bots. And again, we have this case where bots are coming in, they're scooping up a very scarce digital asset and both the consumer and the seller are getting screwed. And I mean, obviously Taylor doesn't really need the money, but you know, imagine this happening for like your favorite niche indie artist out there. I think it's also beyond this. You know, all sorts of digital assets and markets are being created every day. With crypto, you can create markets for memes, for elections, for pre IPO trading of public companies. Things that sort of used to be available to only sophisticated investors are maybe weren't even financialized at all, are now available to like millions of people on Robinhood and Pumpfund. And if you have ever tried to buy a meme coin on Pumpfun, then you know that bots have a very important role in the price that you get. Tldr. I think software is eating the world. Crypto is making it easier to inject markets in our software. And wherever these new digital markets emerge, whether it's on purpose or sometimes not, the bots will inevitably follow. So I think we're kind of at an inflection point here. Not only are bots operating at unprecedented scales and more and more parts of commerce, but their capabilities are also evolving in unprecedented ways too. We can't really talk about bots anymore without talking about AI. And obviously AI is accelerating the use of bots in everyday commerce. You can buy things in ChatGPT, you can use agents to perform all sorts of economically meaningful tasks. But I think that's not even the most interesting part. I like this chart. This is a chart which shows how long a model can work independently on a task without losing context. So over the last few years there's been this, like you can actually see exponential, I'm not making that up. An exponential increase in how long models can operate without human intervention from something like I think five minutes in 2023 to an hour in 2025. And this, I think has pretty profound economic implications.

B (28:46)

The bots of the past were extensions of people. They were reacting to human activity like retail trades in the stock market. But I think the bots of the future will be increasingly decoupled from people. Maybe we don't submit our own trades anymore. We just rely on bots to sort of elicit our intents and autonomously Execute them in a market where they're kind of coordinating directly with other bots. And I think this poses a few really interesting questions. How do we start creating markets that are designed for first principles for bots, not for people? But then how do we also harness all of that activity in those new markets in a way that actually benefits people? As we've seen, it's like very easy to screw this up. If you just slap some bots on your e commerce site, they will probably break it. But I also think there's a glimmer of hope. I think crypto is a really unique category where we actually see apps using bots on purpose, surprisingly, to power important things like lending and trading and maybe even improving prices for retail traders through order flow options. So that's kind of what I want to look at next. Hopefully I have convinced you that bots are somewhat important at least. And now I just want to talk about what crypto has taught us about how to make good markets for them.

B (30:00)

I'm going to focus on two things. First, how you resolve competition from bots, and second, how you manage the flow of information between them. This is not a complete or prescriptive answer to how to design good markets for bots, but I did just want to show you some of the tools that have worked for us. Okay, let's talk about competition. If you kind of remember from earlier, this is what crypto markets, or defi looks like. Tons of bots competing for opportunities under the hood, liquidations, arbitrages, whatever. And this is actually what they're competing for. Who lands their transaction first? Ordering is hugely important in financial markets. If your request gets executed before your competitor, you know, you'll snipe the opportunity. They'll be left with nothing. So basically one of the really important market design questions is how do we sequence these requests in a way that is, you know, both really fair and really efficient? Okay. We have studied this problem a lot at Flashbots, and I'm just gonna give you a extremely quick crash course on what we have learned. So through, in some cases, a lot of trial and error. And basically there are three answers. Two of them are wrong. The first answer is latency. Just put the transactions in the order you see them. First come, first serve. Sounds really easy. This is wrong because latency based ordering will inevitably create latency wars where bots sort of pay huge amounts to co locate with the stock exchange or the server that's actually doing the ordering so that their trade gets seen a millisecond before some other Bottom and researchers have kind of found that, you know, this competing on latency doesn't actually improve market efficiency. Latency based ordering is a really great way to subsidize AWS and a really bad way to give people good prices. Okay, the second answer is to just make your ordering totally random or blind. Basically, don't give bots any guarantee about where their transaction is going to land. And this answer is also wrong, because if bots can control where they land, they're just going to spam you, especially when fees are low. Bots can afford to hammer you with tons of speculative transactions in the hopes that just kind of one of them succeeds. And we have unfortunately learned this the hard way in crypto in the last year. Kind of embarrassing, actually. Half of the gas on top Ethereum roll ups were as eaten by spam bots. And this has like a bunch of negative externalities. You might guess spam sort of congests the network. It raises the price for normal people to transact. You have to like re simulate all of these failed transactions in perpetuity. It's kind of annoying. Okay, the final answer is to run an auction, create an explicit market for transaction ordering where bots can basically compete on price, not on spam or latency. And whoever pays the most just gets their trade landed first. It turns out auctions work very well. A few years ago, we launched an auction on Ethereum L1. It was called Mevgeth, where bots would basically compete for opportunities explicitly instead of hammering the chain with tons and tons of failed requests. And this actually dramatically reduced the spam on Ethereum and, and you know, these days, basically auctions are used everywhere in crypto apps. Trading apps, lending apps, crypto wallets, all use auctions to resolve the competition between bots and actually channel it into outcomes that benefit their users.

B (33:01)

Modern order flow auctions, for example, have generated tons, tens, actually tens of millions of dollars for users today. Tons and tons of refunds. The way they do this is they run an explicit auction between hundreds and hundreds of bots that compete to find arbitrages generated by user trades. And the Arctian makes sure that the bids from those bots actually gets refunded back to users instead of just kind of wasting it on fees or infrastructure costs. Pretty cool. Okay, so this is actually what crypto markets look like today. There are a series of auctions which harness competitive markets of bots to both maximize the quality of execution for users and also protect the underlying system from negative externalities like spam. Okay, so yeah, as our former president would say, you know, mission accomplished. Just like use an auction, you won't have any problems with bots, right? No, not quite. It's not that simple. The other thing we've learned the hard way in crypto is that it also really matters how your auctions are designed. And there is one property the next thing I'm going to talk about that matters more than almost anything else, which is this information is the most valuable currency in the bot economy. You know, who knows what and when they know it. If a bot knows you're about to make a trade, they can like exploit that information to really quickly front run you and snipe the opportunity first. This is exactly what happened in high frequency with high frequency trading bots in the early 2010s, they, you know, would see somebody making a retail trade on one exchange and race to front run them on another. The same problem was also endemic to early crypto markets. By default, all pending transactions on Ethereum are broadcast, as many of you know, to a public mempool, which basically means you can't make a move without tipping off a whole army of bots that are just like lying in wait to front run you. And this was actually really spooky. People kind of compared it to the Dark Forest from the trilogy, if you're familiar. Okay, so the solution we came up with was this. It was to create what we called private mempools, where you could basically submit your transaction to a third party who figured out, I'm going to wave my hands about how this works, but they figured out how to pass them directly to a third, to a miner or a validator, whoever was landing the next block, without revealing your transactions to bots in the process. And basically, if you trusted the people, importantly, if you trusted the people running these mempools, it would really dramatically reduce the risk of getting front run. Private mempools are a step in the right direction, but the initial implementation is a really crude solution to what I think is a much more nuanced problem of choosing what information to share and how. In the bot economy, it's an information flow control problem, not just a privacy binary. First of all, there's a lot of information that you actually do want to share with bots. They need to know what pool you traded on to back on you. An order flow auction. They need to know price updates to remove bad debt and lending protocols. Full privacy, you know, stops boss from doing bad things, but it also stops them from doing good things, useful things. And so really what I think we want is programmable privacy, the ability to selectively disclose the right amount of information to the right parties at the right time.

B (36:00)

This is one thing that I think crypto is really pushing the envelope on. You know, modern order flow auctions have actually, in the process of like running all these experiments, we've generated years of production data on how execution quality is affected by quite literally dozens of different privacy settings, which is pretty cool. And as we push the limits, I think it's also become clear that it doesn't just matter what you make private, it also really matters how you implement your privacy, what tools you use, what trust assumptions they have. All of these things have a truly massive impact on the outcomes that people get. Because when people are selling you privacy, very often they're actually just selling you this. They're asking you to trust them to not share your information with somebody else. This is how early private mempools worked in crypto. It's how dark pools work in tradfi. It's basically what you're doing. If you're talking to ChatGPT as a therapist, you're trusting OpenAI to not share that with somebody else. And the problem with this specifically from an economic standpoint is that trust doesn't really scale. Trust based markets are fundamentally bottlenecked on our relationships with a few human actors. Right. Which limits how many parties can, you know, compete in these markets to drive better execution for people. And if you don't have enough competition in your markets, people lose billions of dollars. The SEC did a study about this in 2022 which basically found that the lack of competition, if you can't read the fine print, the lack of competition in traditional order flow markets was costing users about 1 basis point per trade, which is something like $1.5 billion a year.

B (37:31)

We really, I think, need to reduce the role of trust and get people out of the loop if we want to maximize economic welfare. And this is something that I think crypto also has been pushing the needle on, you know, accelerating the production, application of trust minimized privacy techniques in financial markets. And I'll name just a few really quick examples. This is not exhaustive, but crypto wallets and exchanges have accelerated the use of multi party computation for custody. You know, instead of trusting a single party to hold your funds, you distribute that responsibility among a bunch of people in a network.

B (38:03)

Chains like Ethereum and Solana have also been recently accelerating the use of secure hardware for sequencing. So instead of trusting the operator of a private mempool, not to front run you. You can actually encrypt your transactions to a secure enclave on a very special type of machine. And basically you end up trusting the hardware provider, not the specific operator of that machine, to prevent leaks, which is cool.

B (38:26)

We are obviously far from a perfect solution. MPC is slow. It also introduces weird colocation extensives. Sorry, introduces weird colocation incentives if you kind of play it out. Secure hardware obviously also has a very big physical attack surface and the supply chains are hard to audit. But I do think each of these tools kind of brings us a step closer to our ultimate goal, which is reducing the role of trust and privacy and making privacy programmable through software and hardware. And I think this work is only becoming more important as AI capabilities accelerate. We're already seeing, I think, interesting adversarial behavior with LLMs that's vaguely reminiscent of the early dark forest days on Ethereum. If you take things like prompt injection attacks, adversaries will basically try to insert these prompts that causes your agent to deviate from expected behavior. And an example of this would be printing out your credit card details when you were actually trying to book a flight. It's not a perfect analogy, but I think again we're seeing bots use pre trade information to negatively impact user execution.

B (39:28)

Which kind of raises the same question that crypto apps have been asking for years. How do you constrain bots without completely handicapping them from doing useful things like booking your trade or back running your flight?

B (39:40)

I think we've hopefully, as I've shown here, we've started to develop some of the tools to address these kinds of questions in crypto. With programmable privacy, we can unlock more efficient kinds of collaboration between untrusting parties. With auctions, we can sort of scalably harness competition to drive better execution for people. These tools were definitely inspired by the challenges we faced running markets for bots like front running and spam. But I think they're not just mitigations. These are just tools for general purpose tools for building new markets that gives people better outcomes, which is I think, kind of what crypto is actually about. So to close, I just want to talk a little bit about the opportunity ahead, how with crypto the bot economy could actually be better than what came before it. Okay, we will start with some low hanging fruit. Do you want to make restaurants a notoriously difficult business, you know, more profitable? Don't ban bots. Get ready to use an order flow auction and share the profits back to the restaurants. Do you want to stop bots from racing to scoop up tickets before normal people can buy them. Maybe we try running an explicit batch auction for the next Taylor Swift tour.

B (40:46)

If you don't believe me, just, you know, ask the sec. They actually, after they ran the study we talked about, they proposed a rule which would require trades to be routed through a competitive auction. Fun fact, okay. Basically, almost any time you have a scarce digital good, whether it's block space or ticket sales, I think you can use an auction to both better handle and internalize the competition, the welfare that that competition generates. And as we remove ticket humans from the loop, I think we can convert more and more activity in these markets to auctions. So one example here. I think this is pretty cool, actually. Human psychology makes pricing pretty inefficient. This is a fun example. You and I have a very high transaction cost. We like to know exactly how much something is going to be worth before we buy it. Which means that if you look online, most sales are fixed price, But a fixed price is rarely the most efficient clearing price for a market. And if your market is friendly to bots, you can basically just start running just in time auctions for every digital good you want to sell. I think that could be cool.

B (41:47)

And just as auctions, I think, are not just about preventing spam, the privacy tech we talked about earlier can do more than just prevent front running. Take advertising as an example, one of the biggest digital markets. In order to curate relevant ads, you need a lot of sensitive data about both user behavior and advertiser preferences. And right now, people basically have to trust auctioneers like Google with all of that information. But imagine, just as an experiment, that you ran your ad auction in secure hardware. This could actually improve privacy for users because they aren't revealing personal data to third parties like Google. It could also prevent the auctioneer from tampering with the logic, which Google was sued for doing a little while ago. And it could actually open the door to these really interesting new mechanisms. Imagine if instead of sending static bids, as people do today, advertisers could just send programs that dynamically adjust their bids in response to sensitive data about users that's only available in this secure enclave. There's a very cool paper on this, if you're interested. But basically the bottom line is, I think just by using different technology like programmable privacy, we can get both better ads and more protection for users instead of sort of trading one of those things off for the other. And I think that's really one of the core competencies of crypto. Creating new coordination tools that Turn zero sum games where you have to sacrif to get another into positive sum games where we can kind of fulfill seemingly conflicting goals at the same time. Privacy and efficiency, for example.

B (43:21)

And speaking of coordination tools, there's just one more thing that I want to leave you with. Consider the classic problem of two self driving cars going in perpendicular directions. If they only optimize for their local goals, they're going to crash. But if they coordinate through a device like a traffic light that lets each car credibly commit to stopping for a period of time, then they can kind of escape this prisoner's dilemma. And you know, what is a blockchain if not the sort of ideal programmable bot friendly, credible commitment device.

B (43:53)

Zooming out. I think as soft reach the world and agent capabilities grow exponentially, there will be more and more games to play. And I think it's up to us in crypto to build tools like auctions, programmable privacy, credible commitment devices that can turn those games positive. Some. We are still very early here. There's a lot to build. My guess is that we're probably going to need a plurality of different solutions. You know, the bot economy, as I hope I've shown you, promises to be massive. So the question in my view isn't, you know, if my favorite privacy tool is better than your favorite privacy tool, but rather how do we get more people building both of them?

B (44:31)

So if this interests you or you want to learn more, I hope you will come join our collective of researchers and developers who are working on these problems. Thanks.

A (44:38)

Thank you. Shay, do you have time for a question?

C (44:41)

So it seems that the auctions are a solution to everything. But are there any examples where auctions don't work?

B (44:48)

Samples or auctions don't work? That's a fun question.

B (44:54)

I mean.

B (44:57)

To be honest, I haven't really come across a good example at scale in the markets we work with. There are lots of cases where people don't use auctions because they have certain preferences. I think maybe a good example would be in traditional stock exchanges. They've really optimized for latency based ordering and there's probably some reasons you might want to do that. Maybe they're just historical reasons why this is how your system is built and you're optimizing for what you have. But at least in these like new digital kind of crypto markets, we have really not found a good example where you don't want an auction.

C (45:29)

Yeah.

A (45:30)

Does that make you an auction maxi?

B (45:32)

Maybe. I don't know if I want to publicly commit to that. You know.

E (45:35)

Jay, thank you so much.

A (45:36)

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E (47:21)

Thank you guys. All right, so Raoul talked a lot about the networking and I'm going to talk a little bit more about this computation side of scaling Ethereum for the next hundred times so hello everyone, I'm Michael. I'm a founder and CEO of Brevis. But today I'm not going to show too much about Brevis itself, but I generally talk about how we kind of see the future of Ethereum scaling dependent on the concept of zero knowledge proof. So first I just want to say that, okay, blockchains, especially really kind of decentralized layer 1 blockchains like ethereums are often adaptized at water computers, but the reality is that it cannot run faster than a single server and it is fundamentally extremely expensive. You might say, wait, wait, wait, wait. So we have all these kind of performance optimization and scaling solutions in the last decade. You know, we should be able to just run anything on Ethereum or kind of a layer one blockchains today, right? Well, you know, unfortunately that is not the case. Let me give you a very, very simple example. So let's say, you know, you, you guys probably all use a centralized exchanges and in every single centralized exchange you always have this very simple future feature that if you trade a lot in this month, you get a fee discount in the next month. So you know, this feature is great. It gives, you know, the exchange retention, boost the volume and boost the revenue, bottom line. But if you look at every single decentralized exchange today, none of them have this feature until very recently. Well, why is that? It's not because they don't want to add this kind of a user experience customization feature. It is because even to compute a user's historical trading volume on chain is actually extremely expensive even on the cheapest layer two you can find today. So the reason this basically shows us that does a blockchain as kind of a computing solution is still kind of fundamentally limited in terms of cost and processing capability. Now why is that? Well, the reason is actually pretty simple because today's consensus is built on a very, very simple form of computation. So let's say we have Alice and Bob as two nodes in a blockchain. And what consensus is trying to do, and you know, this is like oversimplifying the entire networking stack, but what consensus is trying to do here is to basically say, okay, Alice has done this computation to say, okay, you know, I get the, you know, result of the multiplication equation. You know, what Alice is trying to do here is reach consensus with Bob, which is letting Bob agreeing that, you know, he can write the same answer. Well, how can Bob know if the answer is correct or not? The simplest thing, which is like the simple form of computing Bob can do, is to just repeat the same computation again. So now we have two nodes and we repeat the computation two times. And today's consensus is built on this concept of reaching consensus by recomputation as a method of verification. Now that is Precisely the problem. Let's say we're doing a kind of a swap computation on a kind of a decentralized exchange. What's actually happening in the entire network is not one node is doing this computation. In fact, like in Ethereum, for example, you have millions of node that is doing the same exact computation again and again and again. And this is a fundamental reason why, you know, blockchain computation are expensive resources.

E (50:54)

Now we have a good solution, however, to solve this.

E (50:59)

This is a new concept of verifiable computing. So in verifiable computing, let's look at the same 2 node blockchain. Here we have different roles in the entire computation process. Alice here becomes something called approver. So instead of just doing the computation itself, Alice in addition computes something called a zero knowledge proof. And this zero knowledge proof is a very magical kind of piece of Mathematica, you know, cryptographic thing that she can use to send it to anyone. And this other party can simply verify, okay, the computation is, the computation is actually done correctly without redo the computation again. And you know, the important thing here is that the verification process of the zero knowledge proof, you know, is extremely low cost and low latency. So, you know, this kind of a new paradigm fundamentally decouples us, you know, sorry, decouples the computation itself from the verification process. And a very nice property about zero knowledge proof is that no matter how complex your original computation is, you can always compress this very complex computation down to almost exactly the same kind of proof that can be verified with almost the constant time, with extremely low latency and low cost. So, you know, so now you may ask, like, wait, zk. We have been hearing about ZK for like, you know, ages as well. Why now? Like why we couldn't do this before? The key thing here is about the blue line, kind of a blue computation cost here a couple of years ago, like even just two years ago, the difference between doing the original computation and generating a ZK proof of arbitrary computation, the gap of that is about a million times. So what this means is that if you're doing this kind of thing in a verifiable computing way, you're not even better off than just like doing the replicated computing. You're basically kind of repeating the same kind of computation about a million times. But the key thing here is that over the last couple of years, and especially this year, we have achieved so much progress in ZK that this gap between original computation and the proof generation shrinked by orders and orders of magnitude. Now we are about 100 times to 1000 times kind of inflation comparing to the original computation. If you run the computation in zk and this becomes extremely useful because instead of replicating this for a million times, you can just spend thousand more kind of a computation and gave like the same kind of a computation result to everyone. So roughly speaking, this is like the kind of innovation that enables this new trend of zero knowledge proof and how it can help Ethereum to kind of achieve the next hundred times scaling. So you know what we build at Bribus is we build this kind of a solution that has a very generalized, smart verifiable computing platform that allows you to offload very complex computation away from blockchain to this off chain box called Brevis. And Brevis will generate a proof for that and then kind of send the proof back to the blockchain. So the blockchain as you know, using kind of as a validator or as a blockchain as a whole, as a smart contract, can just verify the computation easily with low cost and low latency and then use this computation as if this actually is done on blockchain from the beginning.

E (54:33)

So you know, just want to mention that as I mentioned, this technology is very useful for future of Ethereum scaling, but you can also actually use this in your application today. So we're powering numerous different application now in various different sectors like in Metamask for Uniswap, Pancake Swap for many Open Eden Euro Money, all these stable tokens, lending protocols and Perp Dexes and all these to enable them to build a new generation of features that is not possible before due to the constraint of the current layer 1 scaling. But let me go back to kind of talk about the scaling itself. Now we say, okay, this is a new paradigm of computing using verifiable computing and what is actually inside of the magic box? Well, the centerpiece of this entire kind of verifiable computing stack is generally a ZK vm. So for us this is something called a pickle ZK vm. So the interesting thing about a ZK VM comparing to your general ZK circuit is that it is built on a very general instruction set. So you can actually run in theory any kind of software you want to run in this without actually needing to understand the nitty gritty details of the zero circuit development. So this is just a comparison for the same kind of a program. If you write it in your own ZK circuit, it's going to be this complex. And if you write that.

E (56:06)

In ZK vm, you're just essentially writing rust. Now with this kind of a new developer, friendless, you enable something that is very powerful. Essentially you can write Ethereum a kind of full execution node, and you can just rust and then run it and kind of in an entirely verifiable way.

E (56:30)

So this is how we can now use generalized ZK VM to change how Ethereum layer 1 consensus works. Now, instead of we pack one block, broadcast a block, and everyone kind of verify the block execution through recomputation. Now what you can do is that you have just one node that is running the computation itself and then generate a ZK proof and broadcast a ZK proof, which is a very succinct few bytes proof to the entire network. And everyone, every validator in the network, just verify the proof with extremely low cost.

E (57:06)

Now the challenge, however, is that you need to have that performance to be kind of fast enough so you can generate a proof with the same kind of latency that Ethereum is running on today, which is like a 12 second block delay. And this is why you probably heard about a lot of kind of a push and movement on something called real time Ethereum. Proving that is like, once the Ethereum block is produced, you need to generate a proof of the execution correctness within 12 seconds. So you can actually broadcast this proof to everywhere. And in fact like it should be like less than 12 second, it should be 10 second because of the additional kind of overheading networking, right? So this is like why we're pushing forward and pushing the boundary of a zero knowledge proof to achieve something called real time proof. So Pickle, which is the ZK VM that we build, already achieved this. With a 64 GPU, we can achieve average proving time of 6.9 seconds, which is more than enough to actually enable kind of a new kind of consensus client in Ethereum today.

E (58:14)

And so there's like this kind of a layer two beat equivalent, which I would invite you guys to follow, called esproof.org and it shows that the different performance of different kind of ZK VMs for Ethereum scaling specifically. And the important thing I want to highlight here is that it's not only just the cost is going down, but the paradigm of verifiable computing, especially for Ethereum and Layer one execution, has really changed because now we can do parallel computing. Essentially you have a big block, right? So we can actually chop the big blocks into smaller blocks called sub blocks, and run these kind of computation in parallel. And once you have this kind of a capability, you essentially convert the Ethereum scaling problem itself also into a pure problem, a pure money problem, which was never possible before. So if you want to scale Ethereum by 100 times a day right now, what you need to do is to just throw more GPU resources into the proving stack and then you can essentially generate a proof which is still very succinct, the same level of verification cost, but for a block that is 100 times bigger, you can do it today. Now. So this is a major breakthrough that we can actually convert the problem space entirely.

E (59:33)

And.

E (59:36)

What I just talked about is that how you can essentially kind of scale Ethereum by replacing the consensus processes computation paradigm. But we should also look at the application layer as well, how you can scale the Ethereum application using the same kind of a paradigm. Because even if you scale up like Ethereum kind of by 100 times, you're still looking at a, a single threaded machine which cannot run faster than a single server, Right? So Pickle is fast as we know, but you know how we, you know, it is not fast enough? Because like we know, Pickle is very generalized. You can build any kind of an application on top by just writing high level programming language code. And you know, how do we kind of achieve the best of the tour? Well, this is the innovation that we introduced that is like we need really modularity in the entire verifiable computing stack to treat ZKVM as just the glue of the computation and then allow us to actually get a lot of plugins to enhance this capability for different kind of application scenarios. So for example, the example I mentioned, like computing a VIP trading fee discount using zero knowledge proof. You can essentially build something called on chain ZK data coprocessor, which can significantly accelerate the performance when you're dealing with use cases that involves on chain historical data computation and ZK proof.

E (61:08)

And you can of course also enable things like zktls that is like you want to essentially compute what is, let's say your coinbase trading volume in the last month. You can essentially say, okay, I'm going to run a ZKTLS coprocessor to first get the raw output from my Coinbase account, but I also want to run a computation on top of it to derive some interesting and informative data that I can use to prove that, hey look, I have traded more than one minute, but at the same time hide important information such as your exact kind of a token trading and you know the details of your entire trading trace. So this new paradigm of kind of building A verifiable computing stack with the ZKVM as center glue and many kind of different application level co processor is something that we really want to promote as well. So this is precisely the reason why Brevis itself has so many different use cases across so many different, you know, domains in the, in the application space as well, because we have the capability to do this.

E (62:19)

So some very simple examples that I want to mention here, you know, we, for the, for the kind of the VIP trading user experience customization example, we already power this with pancake swap. So if you swapped a lot in the past, you can essentially generate the ZK proof to show you are a big trader, VIP trader and then on the fly dynamically your trading fee will be decreased because you actually kind of show that you're kind of a different trader than the other different users. And this feature has worked great because as we see we can provide more efficient market structure and essentially gave better profitability for the LPS and also much better liquidity efficiency as well.

E (63:06)

And so for the previous example you have kind of some of the logic that still lives on chain, but some of the logic such as user experience customization that is living off chain. But what we believe that a future kind of verifiable computing application architecture will look like is that most of the computation itself is going to happen in off chain world. So you can essentially now have a ZK powered perpetual DAX system that the matching engine itself is living off chain as a verifiable computing component. And all the matches and all the trades can be verified and committed back to the Ethereum layer one blockchain. And then at the same time what you get because you're using ZK is additional privacy benefit to say, okay, I can actually hide some of my orders that I don't want to kind of everyone to see to avoid liquidity assassination or liquidation assassination that we see in many existing protocols. We're actually building with one of the world leading perpetual taxes for this on this and releasing this very soon as well. So another kind of a benefit of ZK as we kind of transition this entire computing stack into verifiable computing is there's a benefit of privacy. So we recently launched this new feature with Kaito that allows you to attest to your on chain historical data such as, okay, I'm a big holder of certain token, therefore my yapping should have like a higher weight in the entire ecosystem. Well, you know, but at the same time I don't want to reveal what exactly is my wallet address. Now you can actually use Brevis to generate a privacy preserving attached station to show that a privacy you are actually this kind of user without revealing any kind of detail of your wallet. So this ZK solution not only can be used as a scaling solution, but also in many cases can bring additional privacy benefits.

E (65:06)

And there are so many others that I probably don't have time to talk about. But just another very big category of use cases is how we help the stable token and real world asset ecosystem to grow and also the chain itself. So let's say you launched like a real world asset and a stable token. You want to kind of actually have your entire stable token used by all these different awesome defi applications. And the next thing you actually need to do is to run a reward system or kind of reward distribution protocols to help user to actually use your stable token. And what we enable for these different kind of stable token protocol is to allow users to generate a zero knowledge proof to show that okay, I actually deposited my stable token in this dax, I deposited my stable token in this kind of lending protocol and therefore I should be getting this amount of kind of a reward from the protocol so they can have a fully transparent, secure and at the same time compliant protocol reward distributing system. That was not possible before. And we did the same for Linear's recent launch. We're the one that is powering the entire Linear token distribution program called Linear Ignition through ZK Proof as well.

E (66:25)

So my biggest prediction here is that verifiable computing, because the cost reduction and the advancement we made in the last couple of years is going to actually take over 99% of the computation for all blockchain applications in the next 10 years. And we're actually rapidly approaching towards that. As you saw, I showed some of the kind of approving and the performance numbers. Using 64 GPUs we can today actually achieve the same level of performance with just 16. This is just like kind of a couple of weeks gap between me making the slides to where we are now.

E (67:08)

So just kind of as a closing thing that is for Brevis we have a full stack ZK computing stack as I mentioned, with a Pico ZK VM as a glue and different kind of co processors to handle different application use cases. And we recently also announced our prover nut that allows you to match different kind of approving requests to different kind of approvers to optimize the entire proving flow with high availability and decentralization. So yeah, with that, that concludes my talk and you know, thank you for thank you.

A (67:42)

Thanks. Who's got a question? Who's got a question question down here?

C (67:46)

Yeah, all right, thank you. Yeah, really, really incredible project and great presentation. It seems to me like brevis could become pretty critical infrastructure. I'm just curious about what your.

C (68:02)

Liveness guarantees are.

D (68:05)

So if the proven network halts what kind of backup options or like, I'd.

C (68:11)

Be just curious for you to talk about that.

E (68:14)

Yeah. So, you know, as I mentioned, I didn't want to kind of show too much about the previous specifically, but the proven network is specifically to solve the liveness problem that you mentioned. Right. So like, you know, the idea here is that you need to open, you need to open marketplace to match different kind of, you know, application developers, you know, proving needs with different kind of approvers. Some of these requires like onchain zeta data co processor. Some of this requires like a ZKTLS coprocessor. Some of these requires like full block execution. So you know, you really need to have like open marketplace where different type of provers can actually participate in and be matched with different kind of application needs and application requests.

E (68:59)

So this kind of thing is actually very, very hard to solve. Mechanism, design and game theory problem. We actually specifically designed something called a truthful online double auction to do this kind of a real time rotating auction that allows you to kind of express your approving needs into different chunks and replicate them if needed to kind of maintain extremely high availability and, you know, high liveness, essentially. So that's how you can essentially solve this problem.

A (69:29)

All right, coming up next, I'm sure many of you are at least bankless listeners, if not all of you. And the story of money is very dear to the, to my heart, to Ryan's heart, to the whole story of bankless. So next up, I want to invite Luca Prosperi from M0, who's going to tell us a little bit about money. Luca, come on up.

D (69:48)

This talk is going to be theoretical by design, but I think it was important during this conversation, during this conference to point a finger on some of the weird things that are happening in crypto. Meaning we are spending so much time thinking about the structure and the design of the networks we operate on from a computing perspective. And we spend zero time thinking about the financial layer that is actually powering most of them and the single point of failure that stablecoins are actually creating in the ecosystem. And as we know, the definition of money typically goes like this. What is money? Money is a unit of measure. We measure the things we do in monetary terms Money is a store of value. How we can keep the value we have. This is a story of the explosion of Bitcoin and Stablecoin in Argentina Mariano was talking about. And money is a medium of exchange, needs to be easy to transact. Now this, like the concept of money has been abused a bit in crypto because we created yield products that look like money, but they're not, and other things around. So the finance people go a bit deeper and say, okay, what is actually good money? And this is from one of the, I think the best papers about money, monetary policy I've ever known by oms from and said the money, actually the second paragraph is money is to be easy and liquid, no questions asked. You actually need to send it around. You need do not to worry about how collateralized it is, what is the value of it, how you can trust the person needs to be easy to transact. And this is proven right for the usdt. Usdcs we, we know about, right? They kind of work. You have it, you own it, and you can use it to transact on chain and off chain. But in my opinion, this is a very limited perspective of money because in my opinion, money is a network. Money is a network that connects everyone and groups of people, companies. And currently this network is running on another network that is the set of blockchains that we use every day. And networks have shapes. So there are networks that are shaped in different ways. And the shape of a network has some pros and cons. And we should think about it because we are impacted by those pros and those cons.

D (72:12)

So what are examples of those networks? So we have centralized star networks. And this is the way the banking system works today. You have the central bank at the center. He's creating assets, he's creating monetary value, and he's pushing it downstream through commercial banks. And commercial banks have clients. So you do not have an account at the Fed. You have an account at Barclays, which is BC JP Morgan Chase. And those guys have an account in a central bank. So if you're cut out by a bank, you're out of the system.

D (72:43)

Then we have distributed mesh networks. And people here, they might recognize the Bitcoin network where all the nodes are connected with each other and there is not single node that can cut anybody out of the system. Obviously this network has a different characteristics from the previous one. So the previous one, for example, is impacting the accrual of value at the center. Who makes money in the dollar network is the US Government. The US government finances itself Very cheap. You don't make any money on the US dollar. You get the benefit of the fungibility of the system. But the value accrues at the center. In the bitcoin network, the value accrues based on time. If you were early in the bitcoin network, you have accrued a lot of value. If you're coming now, the value you accrue just to reinforce the network is lower. So you can see how the topology of the network, the shape of the network is impacting certain things of the network itself, like value accrual. So what are the examples of monetary networks that we have today? We have centralized and concentrated networks like the stablecoin networks today you have Circle, you have tether, and at the center you have the blockchains which are distributed distributed systems. If like we are spending so much time about the decentralization of blockchains, if tether blows up, we are all fucked. If circle cuts you out because they blacklist you, we are all fucked. So we spend so much time thinking about how important it is to have distributed systems where we transact zero time thinking about the single points of failure that we have at the center, sorry, at the level of the issuers. So surprise, surprise, who makes the most money? The guys who intermediate in the value. You have dollar packed decentralized networks. And this is the the word Mariano was talking about the the previous bull market world where you had Circle, you had maker was a decentralized stablecoin issuer that was somehow connected through Circle through a thing called the psm that was provided stability, but it was more decentralized. And who was making money in the maker ecosystem was not necessarily a single issuer or more parties. You also have now starting to appear consortium like federated networks where you have the paxes, the Anchorages, the bridges, saying you can issue through us many types of stablecoins still it is an attempt for them to position themselves to accrue value. Most people will have given.

A (75:16)

A lot.

D (75:16)

Of respect for the stripe team, but most people will get the irony of stripe creating open networks within Stripe. You also have digital, you might have in the future digitally native and distributed network. And you're saying, okay, maybe we are still using the treasuries to back our money, but the treasury is issued in a decentralized manner on chain, like hopefully on Ethereum. And then you have systems that exist already on chain that is still giving a lot of power to the US government, but the rest of the value accrual is distributed downstream. And then the holy Grail you might have fully distributed issuance and authority networks where you have different assets that are composing our store of value and monetary use cases. And you know, the value is actually distributed around and there is not anybody just capturing most of it. This is hopefully the future we're going into now. Does monetary topology matter? We touched on this earlier. It does a lot because impacts certain characteristics of money. And I am convinced that people do not really pay too much attention to it. Not only us, the users, but also the regulator. You have so much time, you hear so many times the regulator thinking about whether a stablecoin is collateralized, is not collateralized, is well designed, is riskier. But do regulators ask themselves how the networks of money are shaping up in the future? Probably not enough. And they should, because the shape of the network is impacting three main things. The value extraction capacity, as we said before, who makes the money? And you can rest assured that those who make the money they will lobby to tell you and convince you that the way the network is is the best, only possible way. But in crypto we don't take anything for granted. How is the quality of the communication spread around the network? How actually the pricing and monetary policy is spreading around the network and how resilient is the network? And these are three components that are all important. And there are trade offs. Now I am a mathematician, so I'm a math nerd. The good thing is that you can actually measure those characteristics for monetary networks in the same way you can measure characteristics of blockchain networks. So you have for example, what is value extraction is the ability of certain actors to extract rent because of their position from their periphery. The users tether doesn't share the yield. They are the most profitable company in the world. We're using it and we are benefiting them because there are benefits for us from a usability perspective. Now in graph theory you can measure this based on the centrality of the nodes. Like there are many measures you can do it and you can use. And I'm not going to spend too much time on it. But for example, node centrality in betweenness, centrality is a measure that graph theorists and mathematicians use. So like you see for example a score that is based on how important is a node to actually intermediate all the communications in a network. So like node number four at the center has a score that is way higher than node number nine. So you cut out node number four and you're just creating a lot of impacts for the network. And you can rest assured that node number four is making money out of it. So do we spend time in rebalancing those, those scores in those positions or not? Probably we should spend more time. Signal communication is also important. So what is the efficiency and fidelity of the information? And again graph theorists can measure this also currently in stablecoin land. So you can quantify by metrics like the path length, the diameter of the network, how long it takes to go from node 1 to node n. And this is an example. So in a centralized star network, if you are at the periphery of one to go on the other side, you have to go through a lot of hoops and every hoop is creating noise. I don't know. In a decentralized network or in the bitcoin network you could actually go from person to person pretty much directly. And so it is a bit more cumbersome to build. But the signal for the periphery is getting higher quality and ultimately resilience. So how robust is a network in case there are single points of failure? And this is all blockchains are all about resilience. And funnily enough, we never asked about the resilience of the monetary network we use. So actually how can we measure it? And you know, so one of the main measures is vertex hedge connectivity. So if you in a star network you kill the center point and then you're isolating two subsystems, but the system doesn't talk to each other anymore. In a mesh network it's very difficult to cut it out. And these are just examples of way you can actually look at the network.

D (80:07)

From a resilience perspective. So everything has a trade off. And you can see I put here on a list the networks we quickly discussed. And you can see the current network we have, it's pretty good on signal quality. There is not a lot of price variability on a USDC and USDT is pretty bad on resilience. If tether goes down, I don't think there is.

D (80:36)

There are so many places to hide. And I'm not gonna say, I'm not saying that these guys are going down necessarily at all. I'm just saying that the single point of failure is a real risk and value extraction is very high. There are only very few people, very few institutions that are making most of the money on the assets that we're using on the rails. And you can see how these things evolve. And it's a trade off. Like you can go, you can reduce the, you can improve the resilience, you might impact negatively the signal quality. But it is an evolution. We all need to go to through and ideally the dream is to have max. Max. There is a type is obviously minimum value extraction. There is minimum value extraction, max signal quality, max resilience. This in my opinion it is a challenge we should take on for next 10 to 20 years.

D (81:28)

For not having the risk of very distributed computing systems, but still very very centralized financial systems that we tend to ignore. So I don't have a silver bullet on this obviously as one of the founders and the CEO of the M0 Project, we built the project to create distributed monetary system. We come from the ethos of the maker ecosystem as well. But I just wanted to stress the point here, especially in this conference, how important it is to look at monetary networks in the same way we're looking at computing networks. Otherwise we're just over optimizing one layer of the stack and we are completely ignoring the type of systemic risks and uneven distribution of profits that we are leaving for others.

D (82:14)

If we keep going this path, creating defi will simply mean allow old school regulated financial institutions to open branches on chain. We're just making their their job easier. And although we see so many institutions and so many traditional financial players like, like Stripe, like JP Morgan, like the asset managers getting very, very involved in a blockchain, a defi, we should never forget that we are not here to actually make the job of Wall street easier and making Wall street banks.

D (82:54)

Able to sell their products across the world without intermediaries. We want to make our life easier as users and owners of the value that we transact. So I hope we all spend more time in thinking what type of future we are designing for our finances and just not blindly using the products that are easy to use nowadays. But thanks a lot. Beautiful Luca.

A (83:17)

We have time for a few questions. One thought that comes to mind, Luca, something we've referred to on Bankless is the Cantillon effect. And I think there's a relationship between the topology idea of money and the Cantillon effect where the central part of the topology is where money issuance happens and then as you get further out to the periphery, the the effects of Cantillon effect take over. Where the value of the money dissipates by the time it gets to the margins and it is local in the center. I think that's a very relevant story for Argentina as well because the story of inflation is synonymous with the story of Argentina. We got time for a few questions. Got one right here.

C (83:55)

Completely agree with your talk. Do you think we can do even better than the last slide you showed? Because you still had basically the treasury and Bitcoin, which you can't really have Bitcoin on the Ethereum blockchain without wrapping it. So that's a point of failure. And then the US Government is obviously a point of failure for Treasuries. And also the peg itself is somewhat a point of failure, if that makes sense, because you're relying on the Fed to not hyperinflate or do anything like that. So I know projects like Rye were trying, but do you think that's actually achievable goal to have just eth and then not even have the peg to the US dollar, something like that?

D (84:27)

Yeah, I think this is a multidimensional problem. I think that is a spectrum. We will go further and further in decentralizing the sources of value that we are considering trustful. And we consider the US Government a source of value. And so it is a spectrum. I think it's also a spectrum of how we are, what economy we're living in. I don't think that. I mean, the US government loves the idea of exporting, continue to export the dollar across the world. But we are not living within the US monetary system, all of us. So I think that.

D (85:06)

These two phenomena will go in sync, meaning that the monetary system that we are living in will expand, will become way more global. So also the pegging, how we are measuring our purchasing power will expand. It will become more like a basket pack rather than a single one. So in my opinion, these two phenomena will just go naturally in sync. Like we will have different sources of trust as base assets. So today is the treasury government. The US Government in the future is going to be US Government decentralized assets, private assets. But also the way we are indexing, how we are measuring it will change because we are not all living in the US and for as much as the US will like it, this is not the only relevant currency in the world. But the interesting thing is that we are now this is possible, this is happening. So in my opinion, it's just how quick we are getting there.

A (85:58)

One more question right here.

D (86:01)

Yeah.

C (86:01)

How much of the return in crypto.

D (86:03)

Is a function of counterparty risk? Seems that a lot of people are getting returned just because they're accepting counterparty risk and not because of any alpha being generated. And that's why tether makes so much money, because people view it as having very little counterparty risk.

D (86:20)

So the senior agent, counterparty risk is the story of money as a whole. It's not a crypto story. You accept dollars in transactions because you don't want to run the counterparty risk of your There is no price discovery in monetary transaction so it's not a crypto history, it's a money history. I don't think it's very different now. There are different layers of counterparty risk that crypto can definitely reduce and that's why DEFI works so well. So I think that there is.

D (86:52)

Counterparty risk reduction is a huge component of the use of stablecoins but I don't think it's very different from any other type of money. It's the whole question of money like you don't ask questions in terms of credit risk and counterpart risk where it's coming from. You're paying me, I'm fine.

D (87:10)

Now there is risk doesn't disappear so we are all running tether's counterparty risk or circle's counterparty risk and.

D (87:20)

I think many of us have lived through the Silicon Valley bank days. At some point we didn't even know whether the counterparty risk we had was real or not. So I think this is a history of money in general.

A (87:35)

Thank you Luca. Round of applause for Luca.

B (87:49)

It.