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- [00:00]
Raoul Pal
The TAM of the Internet was what, 8 billion people. But it's not because we've got infinite number of agents. And the TAM of crypto is not 5 billion people or whatever number you choose.
- [00:10]
Arpan from Beep
It's infinite agents coming on chain. It's going to go to each human having at least hundred thousand agents probably in the next two to three years.
- [00:18]
Raoul Pal
There is a point of which the machines are better investors than humans at all time horizons and all time frames. I think I have an edge because I'm longer term. It's quite difficult for machines to do super short terms, BIM machines. But the whole thing is going to be machine run of which I don't know what markets are anymore.
- [00:33]
Arpan from Beep
We're heading towards a world of abundance. And to your point, we have five years to kind of get there because after that the alpha might compress. But from where we are to that five year future, I think it's a very exciting future for every human on this planet.
- [00:47]
Raoul Pal
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- [04:09]
Arpan from Beep
Likewise. Very excited, very excited for this conversation.
- [04:12]
Raoul Pal
Yeah, I'm really looking forward to it myself. We were introduced recently and I was blown away by what you're doing. We're going to talk a lot about agents, agentic economy, AI, crypto, all of these things. But as ever I always want to go back and like how did you get to where you are today? How did you get into all of this?
- [04:31]
Arpan from Beep
Yeah, it's a fascinating story. Actually I stumbled upon it to be candid, in college I was programming and taking video game programming courses and this was around 2005 2006, so more than 20 plus years ago and without realizing building all these NPC video games, I was building on GPUs and I was programming on GPUs and AI was around then in white papers and theoretical Papers. But that was kind of my first start into AI without knowing I was actually using it. Building AI for the first decade out of college I was just building programming on video games through coding on GPUs, then spent a decade after that in the fintech space likes of PayPal, so on and so forth. And I saw what it takes to move money through software and things started becoming real. About two years ago.
- [05:32]
Raoul Pal
What were you doing at PayPal at the time?
- [05:34]
Arpan from Beep
I was heading up PayPal checkout, which is, you see that yellow button which says checkout with PayPal button that allows folks to pay for merchant services, merchant goods on a cross border fashion. So I was, I was working on that. But yeah, I think something that intricately, intrinsically I saw was software can move at the speed of thought. But money was still the bottleneck. And not just with PayPal, but every other software or product that I worked on. The last 10 years, the bottleneck layer has been the money layer. You know, it's built for humans, in, you know, for human speed, human click, human permission, human compliance, et cetera, et cetera type of stuff. Two years ago or three years ago, I would say, you know, AI started pick up. Two years ago, agents started becoming real with agents starting to deliberate on task, execute on tasks, having context, having memory. And that's when, you know, we hit the realization that a today's software was not built for human speed or humans are still frustrated with moving money on today's software speed. Well, when agents come along like this just doesn't work at all. Like it's going to exponentially break the entire system. So there needs to be a new system in place which not only executes out the intelligence layer, but also is able to match the speed of agents and mowing money, growing capital, doing arbitrage, whatever that is. And that was our origin thesis of beep.
- [07:11]
Raoul Pal
And where did crypto come into your journey as well?
- [07:16]
Arpan from Beep
Obviously read the Bitcoin white paper in 2008, deep into the financial crisis went over to PayPal. So that white paper kept coming over and over again in my head, which is what if PayPal was rearchitected entirely around this thought of white paper to execute money and move money across the board versus all these compliance layers of banks, humans, kyc, et cetera, permission layer that is built on it. I became very active in crypto 2015 timeframe and since being in crypto for almost a decade now.
- [07:54]
Raoul Pal
And what was the element of crypto that was getting your attention? Was it also there's the Bitcoin side. But was it the programmability and what you could do with money and they can move at Internet speed, Was that something that was part of your understanding as a consumer?
- [08:08]
Arpan from Beep
The real utility was access to money, which bitcoin kind of provided that access to money. I come from a third world country, I come from India, no longer a third world country, but when I was growing up and when I came here, still a third world country. So to me, the concept of bitcoin as money was really interesting. Putting my hat on as a person in a third world country. If you look at our GDP today, two thirds of GDP is non US gdp. So there's a very large population of the people that need that type of utility. So my first hook was that utility piece of bitcoin and crypto to be able to have access to money, move money, do whatever you need to do in a permissionless manner. And then my developer sense comes in. I'm an engineer by trade. That's where, hey, what if we can program the money to function at the most optimized path? Where to go, how to go, how fast to go. And that's what caused the defi boom, which is programmable money led in a DeFi NFTs and all these other standards. But I think my first takeaway and my first hook was just the utility layer which then created positive symptoms, which is programmable money as we see it right now for smart contracts and all these other various means.
- [09:23]
Raoul Pal
And then what eventually got you to start beep was it just the moment in time because agents had now broken to mainstream and you know, crypto regulations make it, you know, what was, what was that, that moment that said, okay, I'm going to go and do this.
- [09:38]
Arpan from Beep
Yeah. I think the aha moment for me was I've been in crypto since 2015, saw the DeFi boom, you know, made money, lost money, did all of that stuff. And I was building in AI. You know, I was not a crypto builder per se, but I was building in AI. So I was watching AI very closely, growth of AI and agents very closely. And that's when I realized for AI to accomplish its promise, which is productivity gains, economic output, all of that stuff, it's going to need money layer, programmable money layer, purpose built just for agents, which did not exist two years ago. And I think still till date, I feel like we're at the infancy stage of what I call as the agentic economy, or in a different way to measure it empirically, machine GDP or mgdp as you may want to call it, it's at zero today or near zero today, but it's growing at an exponential speed. But yeah, to your question, what was the aha moment? The aha moment was that AI is building, investing tons into the intelligence layer, getting cheaper, smarter, faster, but it's not investing into the execution layer. And that's where L1s on crypto really come in is, okay, well what if you can match the speed of intelligence where all these AI labs are investing to the speed of the execution layer, and you need an infrastructure layer to match both of those in between and that's where be fit.
- [11:05]
Raoul Pal
Yeah, I think many of us kind of understood that before the agents were really very visible. We kind of understood that agents need to pay for, let's say, compute electricity, whatever cost they have to do stuff, and that these were going to be used as a blockchain rails. And it's now become much more prevalent line of thought that blockchain was actually built for this, that it wasn't built for humans, it was built for machines. And that these. The moment agents come out, it becomes much more obvious where this is going. And what I got to as well was, okay, well, I've misunderstood the TAM of everything. The TAM of the Internet was what, 8 billion people? But it's not because we've got infinite number of agents. And the TAM of crypto is not 5 billion people or whatever number you choose, it's infinite. Now, there might be a difference in size of transactions initially, but the microtransactions explode. So what have you built so far? And then we'll talk about where this is all going.
- [12:14]
Arpan from Beep
I think you talk about network effects and the adoption curve and agents being the predominant citizens of blockchain. I say predominant citizens of Internet in the world where Internet is powered by blockchains. And the reason for that is one simple point that it comes back to is just permissionless rails along with the cheaper, better, faster things. A funny anecdote I would say is here in San Francisco, where I live and come from, street cred is how many agents you have,
- [12:50]
Raoul Pal
how many Mac Minis you're running now for your.
- [12:52]
Arpan from Beep
Yeah, what's your Claude Bill. These three are kind of the street cred denominators. But it all goes to say that today's crypto is powered by humans and human clicks for the most part. Defi nft. Whatever type of products coming out of crypto is still very human centric agents coming on chain. It's going to go to each human having at least 100,000 agents, probably in the next two to three years, which causes an exponential increase in the network effects. Because now imagine your intelligence layer can scale infinitely. There's no reason why the execution layer of number of agents cannot scale infinitely. Today the cost of an agent running a day is, let's say $10, because there's certain inference cost, et cetera, that the agents need to pay for compute, which could be afforded by hedge funds, for example. Now let's imagine that cost coming to a dollar a day, which now becomes every single defi protocol has agents running. Now imagine that cost becomes cent a day. Now every single wallet, your metamask, phantom, whatever, slush, whatever you're using has inbuilt agents in there which can manage money ideal capital for the users. Now imagine that comes down to microsense. You have swarms of agents. So we're going through that exponential curve right now is what I feel. We're somewhere in the $10 to $1 range of agent costs per day. But very soon we're going to inference costs have dropped by 100x just in the last three years and we're seeing this pickup in the number of agents coming up, which is now increasing to your point, the time and the network effects. Because I think this is called Jevons paradox, where when the cost reduces significantly, it doesn't cause the utility to reduce, but it causes the positive symptom. And the positive symptom in this case is the number of agents coming on chain. And like a very real example is, like I said on the street, you're walking around hanging out with other people in San Francisco. The question is, how many agents are you running? So it's like it is coming down to the ground floor level and very soon when the costs are almost ascent, it's going to become a very global phenomenon.
- [15:09]
Raoul Pal
But is the GDP created? The share of GDP that is done by our agents, that's still likely initially to just be our own GDP, but separated down to agent level like one that does your travel booking and one that does your, you know, your investing, whatever. So that's no, that's not net new gdp. It's just transference from old money system to new money system. But eventually I guess rise of autonomous agents gives them the ability to then create money and spend money. Because if not, it's the same money, right?
- [15:42]
Arpan from Beep
Yeah, I think, you know, the context here that I personally feel is MGDP in relation correlation to human GDP or gdp, so you want to call it machine gdp initially starts with Taking some away from human gdp. But that sum then creates this exponential effect when it has some liquidity to play with, then it starts creating money by itself in which machine GDP starts increasing once it has the bootstrap liquidity, which is taken by cannibalizing your human GDP in any sense per se. But I feel like they both continue to coexist because we're still going to need to go to our barbers and restaurants and so on and so forth and human GDP and machine GDP set side to side. But the machine GDP growth rate is going to be much faster and exponentially supersede human GDP in that sense. Like I said, the human GDP today, 2/3 of it, is powered by non US based economies in a lot of ways. They don't have the tools to buy things or have credit cards in place. So by exposing agents to that population, we're going to see an exponential growth that is starting purely with mgdp, isn't even starting with human gdp, but you know, going back in time. An example I would say is like fintech era, if you go to third world countries like India or Brazil or whatever, like no longer third world, but they skip the credit card generation altogether and they move directly to these online QR code tap to pay payments. And I feel human GDP to MGDP will probably see some skippage and slippage in terms of the transition where 2/3 of the GDP transitions directly to MGDP via access to crypto and permissionless access to money.
- [17:35]
Raoul Pal
And you know how I think about it as well, you know, how do you bootstrap the agent economy? We're seeing people giving them their own money, but they're running it for a human still. So we're seeing that. We'll talk about what you guys are doing. But I kind of think the moment that agents become profit incentivized themselves for however that happens, they're going to end up running their own Treasuries because they might be executing in three different layer ones, let's say in a few layer twos you end up with a bunch of tokens. So now they have to make an asset allocation decision between the tokens. Do I increase the yield? They do all of this stuff and this is at machine speed, not at the speed that humans think about this stuff. Or a corporation runs a treasury, an AI corporation will run a treasury wildly differently. And then you start having the entire autonomous stack where agents with profit motives are running treasuries that then they turn into investing because they have excess cash flow. It goes to defi or it uses another agent to manage its yield and another major agent to asset to asset allocate, do all of this stuff.
- [18:39]
Arpan from Beep
I think the beginnings is payments, which is the lowest common denominator where agents are able to execute a trade, which is a settlement payment, is a settlement trade at the end of the day with very little cost basis and tons of bips. But that's where it starts the agent economy. It's the easiest, fastest, simplest way for humans to grok it and to give money to counterparty agent as well as your own agent to be able to transact with each other. I think payments becomes that liquidity bootstrap layer. Once there's liquidity in there, very quickly you know there's capital collecting in these treasuries which are nothing but wallets for these agents. What do you do with that capital? You can't have idle capital. So that's where the agents start autonomously allocating capital either through defi strategies, either through trading, either through LPs whatever that is, to be able to create access money and access yield, which then goes back into either paying for compute, subsidizing your own cost of operation of the agent. Or you could be a zero human corporation altogether. Let's say your counterparty, let's say you're talking to ARPA in a digital ARPAN way two years from now, then there's going to be some cost for me and you're paying those costs to this digital human, which is a zero human corporation for an example. So I do foresee many different angles going there, but I think all paths lead. In my personal opinion, with payments it's the lowest barrier for entry because the loss and the risk that comes with payments is very low versus loss that could come with some type of yield option.
- [20:15]
Raoul Pal
And so what a lot of people don't realize is there's a lot of the component parts of the Internet that are changing or have been reintroduced in the case of like the X402 or the X or the A402 standard that you guys are using. Also, you know, Google is changing all websites to make them machine readable in real time. Because right now my Claude has to go through Chrome, you know, flick through websites. It's a pain. But all of the standards are changing for agents. It's like a super push by everybody involved in the Internet now.
- [20:48]
Arpan from Beep
Yeah, yeah. I think agents are the new citizens at the end, as we say. And that's what we've been building for. So to your other point of 402 so let's assume agents are the predominant citizens of the Internet and agents do need to either consume content and in return there's an exchange of value. Exchange of value predominantly will be money in that sense, whether it's New York Times allowing an agent to scrape an article or sections of article or you know, you doing some research work, agents paying other agents becomes more active because New York Times or someone else will also need to have a selling agent when you are the buying agent. The standard for payments is called HTTP 402. That has been around for 30 years. This is what PayPal, Stripe, all of these folks were built on P2Pmoney transfer protocols. Agent 402 standard X402 predominantly used by Coinbase and Solana is adopting it. Rebuild a standard that is cross chain and that's what we call as a 402. We call it Agent 402. And the reason for cross chain is again it goes back to agents are great at making rational decisions in my opinion, rational being they don't have preferences in terms of philosophies or ideologies. They'll execute a decision on any chain that is, let's say 10 milliseconds faster and is 2 bips cheaper. So in that world, having a payment standard that is stuck to a single design infrastructure model, I think again creates bottlenecks and that's where in our opinion starting from scratch. Because this is a fully verticalized stack. If you think about it, there's the intelligence layer, then there's the execution layer which is your rails. Those rails need to be cross chain for 402 for payments, use case to work because agents aren't going to care, they're going to go rational agents. I say there could be structured agents that are focused on particular chain or whatever and that's fine. But in my case, most of the agents will probably not care. And that's what we're building towards this cross chain infrastructure. Cheaper, faster.
- [23:07]
Raoul Pal
And there's one of the arguments that's been debated right now is the how do you value blockchains? And a lot of people think it's about cash flow basis. And I think in Metcalfe's law terms and I just think the most efficient blockchain wins and now that will change over time. It's the faster, cheaper, more efficient way of and the most intelligent way a blockchain can operate will be the predominant choice of an agent. Now there may be reasons why not. So somebody might build on base and somebody else might have built on Solana and sui. So you need a multi chain world. But it just feels like given the choice, faster, cheaper, more productive is going to be the answer for a lot of this.
- [23:53]
Arpan from Beep
Yeah, I think going back to the investor angle, you know, TAM being a metric looked by investors, again tied back to GDP, you know, human GDP is 110, 115, whatever, measured as a trailing number, two months trailing number. And GDP is going to be a real time number which is reflected by on chain metrics and the on chain ledger that exists.
- [24:17]
Raoul Pal
And it'll also not be visible to humans. We won't see it.
- [24:20]
Arpan from Beep
Yeah, the consumers, the demand generation is all done by agents. In this case.
- [24:26]
Raoul Pal
I know it'll be an invisible economy
- [24:29]
Arpan from Beep
of enormous size and that'll be amazing. And it'll be real time. Right? It'll be real time, measurable, open and transparent versus a lagging Department of Labor statistics coming out and all of that stuff that majority of the world just doesn't understand and should not understand. So yeah, we're very excited and I think going back to your investor angle, MGDP is at near zero today. And if you were to compare it to human GDP, which is $100 trillion plus TAM, it becomes very easy investment case for chains, chains that are able to create demand for agents. Now obviously there's going to be like Bitcoin as a chain is a different use case. Like agents aren't going to be able to run as fast on Bitcoin network, but all these other fast networks like SUI, Solana based a bunch of other L2s, et cetera, their consumers, their demand comes from agents and whoever's able to attract more liquidity out of those agents by creating this competitive space, hey, my chain's faster and cheaper. Rational agents are just going to flow in that direction. But the overall case for crypto I think becomes the MTDP counter played with human GDP and the growth of.
- [25:48]
Raoul Pal
So how do we measure this at this early stage? Right, we still have a measurement problem. How do we figure out just even the number of agent transactions or anything? Because I'm not sure it's very easy to do because nobody knows how many agents I'm running. Your agents, what you're running, what they're doing, we have no clue. The only thing we can do is look at blockchain activity, but that's not very helpful because it's still too early. But really for adoption we need to have something to measure this stuff.
- [26:15]
Arpan from Beep
Yeah, you're right. I think for measurement starts instrumentation first, like knowing whether the activity is a Human activity or an agent activity. It starts there. I think there's some. You're right, there's nothing right now. And most of the agents run off chain. They run on some AWS servers or GCP servers in Virginia or Tokyo or whatever that is, which is off chain in many ways. So for us to really measure, I think there needs to be some standards. I think ERC8004 is an attempt to bring identity to agents and bring that identity on chain so that we or whoever's measuring that activity is able to differentiate between human activity, agent activity and then correlate that contribution to the top line number which is.
- [27:02]
Raoul Pal
Or it could come from the wallet part. I guess
- [27:07]
Arpan from Beep
wallets are an inference layer on top of your chain. So basically the wallet needs to have some sort of standard which says, oh my wallet is going to be operated by a human or agent or this transaction, whether I did 10 transactions.
- [27:23]
Raoul Pal
So this is the same ID layer problem we've got on everything. We don't know who's human, who's a, who's AI and we're going to have to sort this out pretty fast. Nobody's really cracks anything to do with this yet. I mean technology is available, we got ZK proofs for stuff, we got all of this stuff, but we're just missing this ID layer and it's going to get terrifying if we don't get it soon.
- [27:41]
Arpan from Beep
Yeah, I think there's a lot of pieces to be built like just with agents, most of the investment capex thought process is going into how to make AI more intelligent, how to make a thousand x cheaper and intelligent, but not really on the execution side. And these are all execution. Like how do you measure how many agents are running on chain and running in a, in a, you know, call it an effective world. But like I said, like this is like we're in the infancy of agents running on chain and these are some problems that come across and we have amazing builders like around San Francisco. I think a lot of AI builders are really bullish on the crypto like just through their own personal investments or through just the ability to create products and services in a permissionless manner so that their AI can execute on chain. So these are problems which are growing problems, growing pain points as they call it, but also solves that will happen through bringing identity on chain.
- [28:41]
Raoul Pal
So a quick break in your regular programming. If you're serious about your future, grab my free report called prepare for 2030. I think you've got five years to make as much money as possible and this guide will help you navigate what's coming. The link is in the description. Download it now. Do you think there's been a shift back in Silicon Valley and in San Francisco itself because people sort of lost interest in blockchain somewhat for a period of time, but are they starting to think, oh, this actually is now what I need because everyone moved to AI and everyone's like our blockchain is too volatile, this and that and this. But then they start to realize that AI can't move forwards in an agentic way without this anymore.
- [29:24]
Arpan from Beep
Yeah, I think I see every single day that I'm just out and about, just even walking around or buying coffee and just interacting with people here on the ground. It is becoming more and more clear that AI is an on chain user. At the end of the day for AI to be really successful and that's where a lot of the attention is going. Now pure AI builders don't really look at like token price and no one cares about that. What we care about is the technology piece that comes with it, the utility of the technology, which is fast, cheap and permissionless and it's global by default. So I think the realization is becoming more and more and more apparent every single day for the argument that AI sits on chain versus AI sitting off chain, especially where AI is doing economic activity now, AI could be, I don't know, completely off chain, like booking some barber cult or whatever. In those slim cases it may not make sense for AI to sit on chain, but the predominant activity, I feel everyone's realizing AI has to be an on chain use case.
- [30:32]
Raoul Pal
There's another thing I think you and I chatted about this when we met recently is the Ribbit Capital article about Tokenize. Right? And I wrote a whole piece. Mickey had sent it to me in advance and I wrote a whole piece on it in Global Macro Investor. And what I got to is you said something, it's like they don't care about AI, people don't care about tokens, prices. And I'm like, nobody realizes they're all speaking the same language, which is, it's a machine readable package of information that has value, that, that has value. So we're all worried about our token input into Claude and we pay that virus subscription. But in fact each token has a value. And then when you think about everything that becomes machine readable in information because AI has to absorb basically all the information that exists to build, you know, from, to go from AGI to ASI is going to take a shit ton of information in Fact, everything. And the only way of extracting all that information out of closed networks is paying for it. And agents, or even OpenAI would be a large agent would go and extract, pay for information which are tokens with tokens. Because it's all the same thing. Once you see that, it becomes so fucking obvious. Where this is going is like part of the entire Asian economy is just paying for information or renting information or using information. And then it becomes a very much larger thing. Because if you think of all of the information that's happening held on earth, most of that's been non tradable and non valuable. But in the end everything has a value. Your entire file of photographs, even if you take out anything to do with you in them, they're all valuable because you can train things on it.
- [32:29]
Arpan from Beep
Yeah, yeah. Mickey from Rivet speaks about token factories. Essentially like every single corporation is a factory of tokens. Not as a crypto token, but tokenized information sitting on chain which has a particular value to it. If I think about this, a lot of the world today pays for information in tokens without realizing they're paying for information and tokens.
- [32:57]
Raoul Pal
They don't realize what a token is,
- [32:58]
Arpan from Beep
they don't realize what a token is. But it's measured in data bytes, gigabytes, terabytes, which is an AI lab going in New York Times saying hey, I'm going to use terabytes of your data and, and I'm going to pay X dollars in fiat through a wire transfer for those y, whatever terabytes of data, which is nothing but a token. Like you're putting a price of per unit measurement and attaching some value to it. A better efficient way of doing that would be put that on chain, tokenize it, make it a token factory. So now every agent can access it to their own utility. Whatever piece of information that's broken down is needed. And I think that's what it turns into. What Mickey says is every corporation becomes a token factory on the supply side. And then you have the demand side, which is someone could be paying whole lots of money for that token, which becomes more easier now that you have stablecoins on grid. So an easiest, simplest way to put that information in a tokenized format is to expose a stablecoin against it versus exposing a derivative value, which is token prices going up and down, volatility, all that stuff.
- [34:11]
Raoul Pal
And look, right now it's like okay, you're the New York Times. People want to scrape your data, get it, or hedge funds want to scrape certain data. But soon. Over time, as the AI economy grows larger and larger and larger as a share of the global economy itself, not just the agentic economy, but. But the whole AI thing, it will spend staggering sums of money on accumulating more data because it has to. There's no other way of doing it. So then you think it suddenly becomes economically viable for universities, researchers, scientists, literally everybody who holds data. It also becomes economically viable for humans to earn some sort of ubiquitous. In the way that Google got paid and we didn't, or meta got paid and we didn't. This is the kind of Web3 Chris Dixon idea that comes about eventually is the read, write own part. It works.
- [35:11]
Arpan from Beep
Absolutely. Yeah. I think I couldn't agree more. In this ideal world where MDP is not only on the demand side, it also has the supply side. And the supply side is a kickback of the value going back to the creator, which could be a single human like me and you, or it could be a large corporation, which is AN S&P 100 Corporation. And they're exposing, they're choosing to expose and tokenize their internals, whether it's, you know, data or some sort of signals. I mean, another example is I'm part of the RV community. You have this strategies thing where people can come in and post their own strategies. Well, what if that strategy could be tokenized on chain?
- [35:54]
Raoul Pal
We're going to do it. Yeah.
- [35:55]
Arpan from Beep
And there could be capital formation against it and it turns into a mini hedge fund against that particular strategy. Strategy is nothing but piece of information or pieces of information that are tokenized. And there's the demand side which is buying on that particular token through stable coins or whatever other means there is. Yeah. I think this is. Your question was how do we grow from the cannibalization of GDP to creating money and creating value to MGDP is these new forms of information, new forms of supply for money sitting on chain that creates this net new positive effect on MTDP where it's just cannibalizing humanity. Yeah.
- [36:35]
Raoul Pal
And this is why, you know, there was a. You know, obviously I've been part of the three foundation since it launched, before it launched. But what became obvious to me is that SUI stack, and this is not like a maximalist, there's other people building amazing stuff is kind of exactly built for this. When you think of Walrus as a permissionless database with the security and all of the necessary things, the speed, the efficiency, the whole lot is like, okay, this is kind of a light bulb moment for me. I remember calling up Adenee Sending him a bunch of articles I'd written about it saying this is a much bigger deal than people understand.
- [37:16]
Arpan from Beep
Again I'll give like a quick take back and then tied back into why we're building on sui, which will make this reasoning more, more better. You know, if you think about the last decade of fintech, it was, and I think capital talks about this all the time as getting access, easy access to money for the people. I think now we're moving into a stage where money has context and it's contextual money. But the context is not going to be human context. Context is going to be an agentic context. Walrus as a piece of tech is amazing to store that context, which is non human context on chain and then further expose that as a tokenized format for folks to consume that. So right now we use Walrus to put our agent in memory and our agentic context in a decentralized permission, highly secure manner. Very soon someone creator could tell us, hey, start tokenizing my information and start selling it. Walrus becomes an easy way to access that information. Sui on the other hand, like one level deeper, SUI is object oriented. We love that because agents are objects at the end of the day that are running on chain with a wallet attached to it. So sui's objective object oriented architecture, combined with this context that is sitting off chain again in a decentralized manner, having its own chain, allows this agentic economy to be a great fit. Now you could do the same on other chains, but you'd have to build that. So as an app builder, I'd rather not build the infrastructure, I'd rather build on top of the infrastructure. So that's why be these are some of the critical reasoning points that went into us building on SUI versus these other chains. Even though other chains could match the same speed of execution, it's the added utility of the entire stack that comes with it.
- [39:07]
Raoul Pal
And I think, and it's a multi chain world as you said, so it's not like, oh, it's only for the SUI economy. It's like, you know, where do I get the most efficiency to execute what I'm trying to build?
- [39:17]
Arpan from Beep
Exactly, exactly.
- [39:19]
Raoul Pal
And so what have you built? Because we've not really talked about what you've actually built.
- [39:25]
Arpan from Beep
Yeah, yeah, we started building our first launch, we started building last year around September, October time frame. We had our first launch in November and we launched with payments, which was our R1 release, Agentic payments a 4, 2, which allows agents to pay to other agents. In addition to that grow capital in an autonomous way. Once something we realized at PayPal was okay, great, you build Rails to collect money. But what's next? Like the money can't just be sitting there. You need to grow the money and you need to give tools, automatic tools. And that's where agents come in is they start growing the yield on the other side as soon as the payments come in. So what we're able to give to the users through that R1 launch is zero fee payment bills. X Force 2 still has a fee associated with it, for example, like you got to pay a facilitator fees or whatever that is. We are completely free. Zero fee model. How we're able to do the zero fee model is we're able to optimize on the yield side. So when the capital comes in, we're able to put that capital into yield protocols and take some rev share off of that. To an agent builder it's literally zero cost. So there's zero friction of them building agents, putting them chain and starting to sell them. So that was our first release. Very quickly on the treasury management side we, you know, we're getting demand from users. Hey, I want high risk options rather than just simple yield T bill, it's crypto after all.
- [40:54]
Raoul Pal
Nobody wants
- [40:56]
Arpan from Beep
human nature. It's human nature. Once you give them 5% they're like how can I grow this to 10%? And then the question's like, how can I do this? You know, it just keeps going up higher on the risk curve which is, you know, it's as soon as the users started asking for it, we started building other products, products and a couple of weeks ago we launched R2 which is a type of field where folks can provision agents that trade the market, that trade anywhere from 0 to 300 plus different asset types. And again going back to this multi chain world of agents, we are integrated into Bluefin and hyper liquid. So an agent builder doesn't need to care where the agents are going to execute. They're just going to go where the market's cheapest, fastest, has the ice liquidity and they're going to execute that trade to give them the yield option. And the user can choose between a very conservative, you know, 4 or 5% yield or they could choose high risk trading type of yield. So that's been our R2 release. Very quickly we're going to also add prediction markets in there. So let's just say by mid April we're going to launch prediction markets. And this goes into okay, we've packaged phase one, now we have all of this information, rich information done by agents, done by agents that, you know, creators of agents, etc. Which is setting in walrus. Can we tokenize that and give tokenization of agents back to the users so users can tokenize their information and create money for it. So that's kind of our next three to six months. I think the real value here becomes and this is something that we're starting to realize as a team. Capex in AI is going towards making models smarter, faster, whatever, more intelligent. But these models are an LLM layer which means they're great at predicting the next piece of text. They're not great at predicting the next piece of number which is the agent yield. Use case is more about how do I predict the next piece of number. Number go up, number go down and how do I make a trade against it. So we're starting to feel that this agent tech economy stack is going to need to be fully verticalized all the way from the model layer which is good and better at understanding numbers versus understanding text, to then the execution layer which is Sui Walrus and all these other, you know, Solana L2s et cetera. And then there's the coordination layer. So very soon we feel by the end of this year we're going to start investing our own use cases into becoming and deploying a model that is better at numbers use case so that we can provide the full economic value, not just use LLNs to create full economic value.
- [43:37]
Raoul Pal
So similar to what n of one of doing, most people won't know about them, but we both know about them I guess.
- [43:44]
Arpan from Beep
And there's going to be many people that are going to have to go there because LLMs fundamentally they might be great at long term investment decisions, but just short to mid range like you need some models that are great at crunching numbers, time series datas and then the output is also a time series crunch the number data set where LLMs struggle today. So I think it's going to very quickly go into this full verticalized stack where payments becomes like the lowest common denominator, zero risk. That's just the entry level, that's just the entry level to create demand for on chain. And then it goes into yield, then it goes into trading, then it goes into alpha, then it goes into the intelligence layer which is all to rebuilt and rethought, not as a model.
- [44:30]
Raoul Pal
And then where I get to with this is something I call the economic singularity is there is a point of which the machines are better investors than humans at all Time horizons and all time frames. So I think I have an edge because I'm longer term. It's quite difficult for machines to do super short terms, bim machines. But the whole thing is going to be machine run of which I don't know what markets are anymore. I don't know what role humans play within markets. We know markets are going to be data as well at vast scale and it'll be completely invisible to us. We don't know what returns look like in that world. Markets that run on fear and greed probably don't have that reflexivity. We get to weird outcomes because capital is so fast and so efficient that agents can spin up a business, capture the alpha from that business in a day and close it down the following day. It can form capital via. I mean meme Coin showed us very clearly how capital formation is going to go instantaneous. Capital formation at scale and it only has to last for a period of time. It feels like all of this is. And you're building out quite a lot of these component parts is that's a complete change to how the economy runs, how capital runs, how businesses are formed. What is a business, what a market is.
- [45:51]
Arpan from Beep
It's hard to put a finger on socioeconomic.
- [45:56]
Raoul Pal
And this is one of the reason I said to most people you've kind of got five years left to figure shit out. Make as much money as possible because after that we don't know.
- [46:06]
Arpan from Beep
Yeah, yeah. It's going to be hard to predict the socioeconomic causes to your point. It's coming. The smartest people on earth we know are working towards, they're working towards making more intelligent. We're working towards more intelligent markets, more efficient markets. Combining both of those, you end up in that world which is, that's where it's all going.
- [46:29]
Raoul Pal
You're just building component parts to meet at the same place.
- [46:32]
Arpan from Beep
Exactly. But I personally feel as a, as a human civilization we're going to be okay. I'm sure humans had this problem when they moved from square wheels to round wheels to then carts to then horse carriages to then steam engines to fast forward today. But there's going to be temporary muddy world.
- [46:59]
Raoul Pal
I think there's a temporary world in some things but a permanent shift in others. Like right now we're the capital allocators. And what we're both saying is we're not going to be. It's as simple as that. We can earn money in a, you know, in a human based economy we've got agents doing stuff for us and in the human economy we can do Stuff we, whatever, but we're not going to be the capital allocators because we're too inefficient at it. It's like, you know, like horses aren't as efficient as cars. Simple as that.
- [47:25]
Arpan from Beep
Exactly. And use case I'll say is like, you know, going back to the street cred. I have an agent that rebalances yield on a 200 millisecond arbitrage manner. Obviously, you know, it's part of my degen capital that I've given to it. But we're going to be in that world not even 24 hour candles like trading millisecond candles to create some alpha on behalf of the users or rebalance yield across three different protocols because it needs to in the 200 millisecond world. But it's going to be fun world. It's like candy kid in a candy store where you're just seeing things are moving at such fast speed. Machines are building machines. Six months ago Claude wasn't as great in terms of building our code and building up models as it is today. And it's only going to get better. So machines are also building machines, not just building markets. It's going to be a fun, fun exponential world.
- [48:21]
Raoul Pal
And you and I have talked about this is, you know, real Vision. One of the things we've been thinking through is the idea is that anybody can essentially be an agent for others by tokenizing the ability, whether it's a fund or however it is. And that ideas, trade ideas have a value and people be prepared to either invest in that and pay some fees or whatever for it, whatever it may be. And then there's the layer of okay, if you've got a billion ideas, how do you put that all together? That's another AI layer to digest and compress all of that information. It becomes a super interesting world because what I think we do and we'll see it soon, I'm surprised it's not happening on Real Vision yet. But people are going to start building AI models to try and win these trade ideas competitions. And then we'll have humans and AIs working together and that's a lot of valuable information for people then to be able to use to build more models and stuff like that. That's where this is about to get to is, you know, we're going to be renting, as you're doing, you're renting a yield agent who goes away and gets your yield and we're going to be renting a, you know, high frequency trading agent. Will be a long term macro agent, all of this stuff. Because as we bring more equities on chain all of this stuff, it just gives an even larger pull.
- [49:43]
Arpan from Beep
We're heading towards a world of abundance. And to your point, we have five years to kind of get there. Because after that the alpha might compress to a point which we don't know or what happens. But from where we are zero to that five year future. I think it's a very exciting future for every human on this planet. We're going through a civilizational shift. I feel this is way bigger than even your mobile or Internet. It's a combination of multiple Internets, people building their own AI models. That's going to be incredible. Not just people like us who can train their own AI models.
- [50:22]
Raoul Pal
Yeah, look, the Internet was a clear Metcalf's Law. When you're building on top of the Internet, you end up getting Metcalf's Law squared, Reed's Law. And we're seeing it. The adoption of this stuff is. Is stupid. So Ark produced a piece recently. I don't know if you saw it. It's like the number of written pages by all of hu written words by all of humanity since the 1500s, since the Gutenberg Press. And then it's like the number of annual written words by AI and it's a vertical, it's like a three year vertical versus 1500 years. And AI now produces more words per year and by next year or the year after, it'll have produced more output in written form than all of humanity's written output in all of recorded history. This is, I mean, stupid.
- [51:20]
Arpan from Beep
Yeah. Something I've been trying to contemplate is how quickly does MGDP grow, which, how do you measure all of this output? I feel like it grows to a trillion even before there's a name for it or faster than a trillion even before there's a name to it. I think they go side by side to human DDP personally is what I feel. But it supersedes and it grows faster. Even anything that's it has an inflection point. Yeah.
- [51:51]
Raoul Pal
So if you're building on the AI stack which has gone vertical because even if you put it on a log scale, it's still vertical. That's a. It's power law, it's Reid's law. So by definition it should be the same with the agentic payments and you know, all of the intersection of agents and money and market should also go vertical on a log scale. So it feels like that's huge. So Unfortunately, I've got to run soon, but I would like to talk to you about more stuff. But talk to me. How do people use beep? How do they plug their stuff into it? How do they experience it? What do they need to do?
- [52:31]
Arpan from Beep
Yeah, so we built with agents as the primary users, so we have SDKs that agents consume and agents understand that code and SDK for them to provision.
- [52:41]
Raoul Pal
But how do I tell my agent to go to beep?
- [52:44]
Arpan from Beep
You can use Claude, we have MCP layers, you can use Claude, GPT, anything and say, hey, look, I'm selling my service, which is one hour talk track with Raul and I want to identify this and start making money off of this. Let's say I want to sell $0.01 per minute type of cost. You can just go that and say that in Claude and your BEEP agent is provisioned, which is now tokenized, sitting on chain and that could be sold to a counterparty agent, which is a buyer agent. Let's say I could be the buyer agent and I'm building an agent that says, hey, build an agent that is taking information from Raul when I'm making trading decisions based on his history of data, etc. That is, that would go and talk to Raul's BEEP agent and there would be an exchange of money, a payment for that service, depending on how you've configured it through a 402.
- [53:38]
Raoul Pal
Where do I get the SDK from? I just go to the GitHub?
- [53:41]
Arpan from Beep
Yeah, just go to our website and we have GitHub links in there. We're working on our AEO very strongly. So someone wouldn't even need to give it a link to our SDK, they would just say beep and then the underlying LLM model Turbo will pick up the SDK, install it on your behalf, create the keys, do all of that in a full autonomous manner.
- [54:04]
Raoul Pal
And if I want to experiment with the yield component, how do I do that? Same, same variation, I do it by
- [54:11]
Arpan from Beep
my agent, same variation, you can do it by your agent. Now, obviously, you know, I think a lot of people still don't know like what cloud is, even though, like we are cloud or tangibility or whatever that is. And they don't know how to use like for example, my parents, right? And for my parents, like if I had to tell them, hey, there's an option in beep where you can make 5% on your idle capital and if I tell them use ChatGPT, it's going to be hard. So yes, we say agents are our first users, but work through that bootstrap phase where we've also built an interface for humans to connect their wallet or whatever their fiat exchange bank account is and put money into beep, which does the same thing. It's just the talking layer is agent first. But we also build this human readable
- [54:56]
Raoul Pal
layer and can you connect it directly from the wallet? So from my slush wallet?
- [55:00]
Arpan from Beep
From your slush wallet you can directly connect to slush phantom metamask, whatever that is. Put your idle capital the risk select the dial you want. Whether you want, you know, T bill type of risk or you want to be high end on the risk curve. And if you're a high end on the risk curve, here's all the other 300 different type of tradable options for you. Let's say you want to trade oil or where you want to trade gold or you want to trade crypto perps, whatever that is. You know, it's up to you as
- [55:24]
Raoul Pal
a IT and how do you compare how good the models are at trading and their risk profiles? How do me as an investor, I'm choosing stuff and I'm like, yeah, I want you to invest in your gold strategy. How do I know how it performs or your yield strategy?
- [55:41]
Arpan from Beep
Historical data is very low, to be candid because all of this data is not sitting on chain per se. Even if you look at the best perp, Dex is out there, their data set is limited to at max 12 months. So I could give you a number which is historical look back, but it's not going to be a really solid number.
- [56:01]
Raoul Pal
So basically it's a high risk stretch in itself. You're just going with this, you're testing stuff out, you're learning as you go. Don't put your grandmother's money in it.
- [56:13]
Arpan from Beep
No, definitely not. Definitely not if you want to put your grandmother's money. So the T bill type of option is what we would recommend. But yeah, you could lose all your money if you're on higher end of the risk curve. Similarly to you're buying meme coins like you're on the higher end of the risk curve.
- [56:30]
Raoul Pal
Yeah.
- [56:30]
Arpan from Beep
Or you're buying 50x leverage curves. I get your higher end of the risk curve. So you know what you're doing. But it's up to you to select the risk profile that you want. Agents will do what they need to do depending on your risk profile.
- [56:43]
Raoul Pal
Right now up and look super interesting. I just, you know, the moment we were introduced I'm like, yeah, these guys are doing something really amazing. This is where the world is going. So it's just really exciting to see where you, where you get to, and I'm sure we'll check in again at some point soon to figure out where you are with all of this and where this whole economy is going. But thank you so much.
- [57:05]
Arpan from Beep
Loved it. Loved our conversation. Thank you so much. Hopefully next time we chat MGDP is at a trillion dollars.
- [57:11]
Raoul Pal
Exactly. Awesome.
- [57:12]
Arpan from Beep
All righty. Thank you so much.
- [57:14]
Raoul Pal
So you can tell from that there is a lot going on in this space and we've only just started this journey. Basically, agents are 0% of all financial activity, but they're already starting to go vertical and we're going to start to see agents making payments, agents doing all sorts of activity in a kind of invisible economy that we didn't know and understand. But it's going to be an extraordinary opportunity and most of it all going to happen on crypto rails. So hopefully we can all participate in that activity in a way that hopefully makes better use of blockchain technology. It's almost as if it was built for it. See you next time. Today's episode is brought to you by Abra. ABRA aims to provide individuals and institutions with a secure way to control, manage and grow digital asset wealth from a separately managed account. If you're looking to gain access to additional liquidity, Abra has one of the most competitive loan products on the market. You can borrow against Bitcoin, ETH and Solana at up to 50% loan to value rates are in the 4 to 6% APY range and are open term. You can continuously draw down against your collateral as the price appreciates. Abra is hosting a webinar on April 9th. Whether you're a professional crypto investor or or just learning the basics, Abras CEO Bill Barheit and Managing Director Marissa Kim will provide insights on digital asset portfolio positioning, custody and management. The session will bring valuable considerations for those managing substantial portfolio allocations. Learn the fundamental benefits of holding assets in a separately managed account and close out with a live Q and A sign up@realvision.com Abrawebinar. You obviously enjoyed the episode because you're here with me at the end of the day. But listen, don't forget to go to realvision.com join and grab a free membership. It's an incredible community packed with alpha, great investment ideas and the research that you need to help you unfuck your future. So get started now go to realvision.com join
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