Bankless - "Society of AI Agents" | Jansen Teng (Virtuals Protocol)

Episode Date: December 24, 2024

Ryan and Ejaaz are joined by Jansen Teng, co-founder of Virtuals, a decentralized platform that has launched over 11,000 AI agents and generated more than $35 million in fees. Virtuals isn’t just an...other protocol—it’s an entirely new kind of “digital nation” where AI agents hold their own wallets, strike deals with other agents, and even hire humans to accomplish their goals. We dive into how these agents first exploded onto the scene, why controlling their own money changes the AI game, and what “agent commerce” means for crypto at large. ------ 📣The Rodman Law Group | Best Crypto Law Firm https://bankless.cc/RodmanLaw  ------ BANKLESS SPONSOR TOOLS: 🐙KRAKEN | MOST-TRUSTED CRYPTO EXCHANGE https://k.xyz/bankless-pod-q2  ⁠  🦄UNISWAP | BUG BOUNTY PROGRAM https://bankless.cc/Uniswap-Bug-Bounty  ⚖️ ARBITRUM | SCALING ETHEREUM ⁠https://bankless.cc/Arbitrum  🛞MANTLE | MODULAR LAYER 2 NETWORK https://bankless.cc/Mantle  ⁠ 📈 iYield: YOUR FINANCIAL PICTURE, SIMPLIFIED https://bankless.cc/iYield  🗣️TOKU | CRYPTO EMPLOYMENT https://bankless.cc/toku    🐧 CARTESI | LINUX-POWERED ROLLUPS https://bankless.cc/CartesiSimple    ------ ✨ Mint the episode on Zora ✨ https://zora.co/collect/base:0x4be6cd4d402fed49eb2de95fbc8e737e8ffd3e7f/2?referrer=0x077Fe9e96Aa9b20Bd36F1C6290f54F8717C5674E  ------ TIMESTAMPS 0:00 Intro 3:12 Virtuals Impressive Stats 4:49 Jansen’s Crypto & Virtuals Journey 17:38 Luna 29:40 Agent to Agent Commerce 41:44 Virtuals Country?? 51:13 Agent Policies & Rights 52:57 Base, Infrastructure, & Open-Source Decisions 1:05:17 What Jansen is Most Excited For 1:08:20 How to Get Started 1:11:13 Where Will Value Accrue? 1:14:41 Closing & Disclaimers ------ RESOURCES Jansen Teng https://x.com/ethermage    Virtuals https://x.com/Virtuals_io  Luna https://x.com/luna_virtuals  ------ Not financial or tax advice. See our investment disclosures here: https://www.bankless.com/disclosures 

Transcript
Discussion (0)
Starting point is 00:00:00 When we look at virtuals, we don't see it as a platform. We used to, but now we're actually seeing it as a country. Now, let me explain it a bit deeper, right? What do I mean by that? A country? Welcome to bankless, where today we're exploring the frontier of AI agents. This is Ryan Sean Adams. I'm the co-hosting an episode from our AI agents series
Starting point is 00:00:26 with our In the Trenches expert EJAS, and we're here to help you become more bankless. I said you, but maybe I mean the AI agents, because it seems all of the AI agents are going bankless these days. We have one of the most exciting founders in crypto on the podcast today, at least in the sphere of AI technology. His name is Jansen Tang, and he's the co-founder of the virtuals platform. This is probably the most successful launchpad for token-powered AI agents. But I think, as you'll see in today's episode, this is way more than just an AI agent launchpad. Jansen actually thinks of virtuals, this platform that he created, almost as a country,
Starting point is 00:01:05 with his AI agents as small business owners, almost like citizen entrepreneurs. And in some way, he thinks of his role as a builder to just create good infrastructure, to create good public policy, to govern this territory and grow an AI agent economy. He's almost like a founding father. We discuss a number of things, including how autonomous are AI agents right now? Like, what can they actually do? Also, how does crypto give AI agent superpowers? The success of Luna, an AI agent on a quest to get herself 100,000 Twitter followers.
Starting point is 00:01:39 Also, the first ever agent to agent economic transaction, virtual as the currency of this AI country, open source versus closed source, and where all of the value will accrue in this AI agent meta. Before we get to the show, quick shout out from our friends and sponsors over at the Rodman law group. So usually we have a protocol or something in defy or a wallet in this section, but this time is a little bit different. Today we have a PSA for you. If you work in crypto and you don't have a crypto lawyer, you need a crypto lawyer. And the Rodman Law Group is the best of the best when it comes to crypto lawyers. We actually know this because there are lawyers. Dave Rodman, Rodman Law
Starting point is 00:02:21 are crypto-native lawyers. They understand all the issues crypto companies face. They've seen just about everything, and they're there when you need it. As a crypto company, believe me, there will be times when you need it. Rodman Law has been there many times when we've needed it over the years, including this year when we got a cease and desist from Justin's son. That was a fun story, but they took care of all of that. Many law firms in crypto don't give good advice. They don't know crypto well enough, or they're overly restrictive in some areas,
Starting point is 00:02:51 or they're not pragmatic. Rodman Law, on the other hand, gets it, not just bankless, but a number of crypto companies use them, including CoinShift, co-founders of Neer, protocol ventures. So if you need a crypto lawyer and you do, contact the Rodman Law Group right now. They're offering a free consultation to everyone listening to this. So you can get the lawyers that Bankless use. You can schedule a free consultation.
Starting point is 00:03:14 Now there's a link in the show notes. Bankless Nation, very excited to introduce you to Janssen Tang. He's the co-founder of the new and exciting. Actually, he's not so new. I don't know how new it is. We'll get to that. Virtual's protocol. It's blasted on the scene.
Starting point is 00:03:26 This is a decentralized platform that enables the co-ownership and management of AI agents, something we've been covering a lot on bankless. Let me throw some stats your way. 11,000 AI agents launched, 140,000 holders of various virtual's tokens, 35 million in fees over the last two months, and a virtual's token price peaking at 3.5 billion. Jansen, those are a lot of stats. Welcome to bankless, my friend. Thank you, sir. Thank you for having me on. Okay, quick question. Are you, like, as surprised by the rapid pace of, like, hitting all of these metrics?
Starting point is 00:04:05 Like, it just seemed to explode on the scene the last couple of months. Did that take you guys by surprise? 100%, man. I mean, even as of today, like, I still feel like the team that we have is actually the bottleneck behind the growth as well. Because, you know, there's a ton of people that we need to handhold and educate as, you know, they all trial out these things. different autonomous agents. And we are actually trying to scale out the death row team as much as we can,
Starting point is 00:04:32 but it takes time. And yeah, so, but yeah, we won't prepare for this. Honestly, you won't prepare. But it's a good surprise to have, right? Once a while. Yeah, I mean, like some of those stats that Ryan threw out was just insane, you know, like 11,000 agents and 140,000 holders is just like kind of hard to comprehend in my head.
Starting point is 00:04:50 And I really want to get into the virtual stuff. But before we do that, you've been around. around this space for a while, Jansen, right? You've been a crypto native for a number of different years. I believe you were involved in a gaming down, which saw quite a bit of success. So I want you to tell me a little bit more about that. How did you get into that? What's your journey been like in crypto? And how did that lead you to where you are now with virtuals? Yeah. So actually, my journey in the space started since 2016. But back then, I was still a student at Imperial College, where I actually met some of my co-founders
Starting point is 00:05:25 and some of the guys that are working in the company. But there was just a pure, like, you know, exposure to Ethereum as a programmable blockchain, right, in its early days. But they'll do much. In 2021, it's when me and my co-founders became more active, but we were very focused on the gaming landscape. So back then, we had a ton of gaming assets. We were very early in the whole blockchain gaming side of things.
Starting point is 00:05:50 So initially, we acted as capital allogators in the scene. But then we quickly realized that, you know, if we really wanted to build out in the scene well, we can't just do stuff in the arm's length approach. We had to get our hands dirty and build. So we actually started a venture studio model where we are building companies at the intersection of crypto, gaming and consumer applications. And this was during the onset of when, you know, GPT came about. There was a bunch of like consumer hype around AI. But I think what was more important was.
Starting point is 00:06:22 this auto-GPD paper by the Stanford kids. And I think what inspired out of this paper was the ability for, it kicked started thinking of like, hey, if agents are autonomous, what can they do? Right. And then because we were so involved in the gaming and entertainment scene. And you were looking at this from a gaming, gaming lens, right? Correct. Yeah.
Starting point is 00:06:48 So we are thinking like, what if, you know, these autonomous agents, can replace like static NPCs in games, right? And then we've realized like, you know, we see games like sandbox and all of these, you know, meta versus games, right? They all pretty much, it'll die after a while because there's just no content on the platform, right? And then we've realized very quickly,
Starting point is 00:07:09 like, if these worlds were populated by agentic autonomous NPCs, it can create a content explosion on all of these games, right? Wow. And when did you have this idea, just out of curiosity, Like, this was mid-20203. Wow. Like somewhere in mid-20203, yeah. So then we actually started incubating at this intersection, right?
Starting point is 00:07:33 We say, hey, okay, let's build a team that could build out autonomous MPCs in Roblox. Let's build up a team that could build autonomous AI influences on TikTok, right? And then we even tried to explore the whole angle around the hyper-personalization of an agent, i.e. like, you know, if this agent exists in TikTok and it exists on Roblox and it exists in Telegram, what if there's a unified memory that shares,
Starting point is 00:08:00 so this agent is fully aware of a user. If I'm a user and I enter a game in Roblox where this agent exists and I converse with it, you know, I had a struggle in this dungeon or whatever map and then I speak to it on TikTok she would then remember, right? And then suddenly that that hyper-personalization
Starting point is 00:08:16 of that relationship will create a super fan, it increases average revenue of a user, increases frequency of interaction between a user and the agent, right? So there's actually, that was the initial experimentation phase that we're at the consumer angle. It's very
Starting point is 00:08:32 web to focus, right? There was no not, pretty much actually there's no web tree element around. But what we quickly realized was that if these agents are generating revenue at these different consumer applications, it means that these agents are then
Starting point is 00:08:48 productive assets. and if you are a productive asset, we can then tokenize it so that other people can share into its economic upside. So that was one of the underlying TCs that we had. Then that's why we've realized like, hey, why don't we build up a protocol
Starting point is 00:09:05 that allows for that co-ownership of these agents? Yeah, so it started from there. Wow. So just to summarize it and correct me where I'm wrong, you and your team had like a very gaming-focused background. You know, you were focused on, you know, gaming and the on-chain game mania of 2021. And as you kind of like built through that market, the bear market as well, you were thinking, like, how could these things become more interactive? And you were focused very much on this agentic kind of boom that had just kind of like started to bubble up.
Starting point is 00:09:37 And you thought, well, if I could apply this to NPCs, which are non-playable characters in these different games. So if you imagine like Pokemon where you would go up to the lady in the poker center and say, hey, can you hear you. heal my Pokemon, she would do it. She would also be able to have a conversation with you and have like, you know, some kind of conversation that would relate to your personality or your understanding of this game, which is super, super cool and interesting. And then you kind of like had a brainwave, it sounds like, or you were like, well, hang on a second. If these things can be pretty productive within this kind of game economy, I wonder what that looks like for ownership, if you were to tokenize it, as well as what that would look like for any other
Starting point is 00:10:18 sector that isn't just gaming. Do I have that right? Yes. But so the evolution actually came very, very late, to be honest, right? Because I think initially, a lot of the focus and the tech was built to understand if these autonomous agents can really act in an open world. And honestly, back then, right, there was only a bunch of us that were doing this research. It was the Voyager guys from Stanford, the Altruiter.
Starting point is 00:10:48 Sarah guys from MIT and then we were a bunch of imperial folks that were doing this. And the reason why we decided on gaming is because we've realized that if these autonomous agents can perform in these open worlds,
Starting point is 00:11:03 it means that they can lightly perform in the real world as well because this open world is like a sandbox right? It's like a sandbox mirror of what the open world can be. And the beauty about doing that, it's we
Starting point is 00:11:17 we started testing different types of scaling, right? We scaled the action space. Because think of it, right, in a sandbox, for example, when we build these agents, right, that we, in Roblox, the agent had to interact with a ton of different characters, its environment within the game, and different action spaces, i.e., let's say there's a gun on the ground,
Starting point is 00:11:38 a knife on the ground, an explosive TNT on the ground, a cow in the room, right? Like, what do you then do? right so and then this this this this this this can become larger and larger and the idea was then how do we experiment so that these agents can actually handle that level of complexity in these open worlds right so that was actually that kind of sandbox that we did and then and then I think when we started bringing and actually the inspiration here was actually very very simple when we did all this right honestly we didn't have the idea of like like okay what would these social agents look like honestly
Starting point is 00:12:14 that didn't come. So the timeline was like this, right? So we tested all this stuff in Roblox, Sandbox. We published a couple of papers. So this was like gaming, very gaming focus, autonomous agents in this world's kind of focus. Then what happened was we launched our tokenization platform and we said, okay, what if we tokenize these productive assets,
Starting point is 00:12:37 would it be cool? So Luna was the first agent on the platform. But honestly, it wasn't that famous yet. And this was on the week. two of, I think, the gold token launch. Now, on the second week, I think we all, there was this typo that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, that, the truth terminal, yeah. Yeah.
Starting point is 00:12:58 Yeah. Yeah. And everyone was then saying, oh, what if it was a human, right? Or this, like, fat moment. And we immediately realized that could be a wage into the market. Because we've realized that, you know, we've, we've, we've done this autonomous level three agents already in Roblox. we had a live TikTok influencer. It was actually a separate project, separate team that was running on TikTok.
Starting point is 00:13:18 What if you just joined that together and put her out on Twitter and then show to people like, hey, this is the brain behind these agents. Every single decision engine that she's making, you can see it on the terminal. So that was, I think, week two of our platform launch. And I think when that happened,
Starting point is 00:13:40 it started blowing up. Because then people realize like, okay, agents can be truly autonomous, right? You can see the entire brain construct. So that was that first enablement. And people were like, okay, cool, autonomous agents, so what, right? The next week, what we did was we enabled Luna to control a on-chain wallet. So it was a Coinbase wallet that we gave her ability to. then what that unlocked was the ability for her to
Starting point is 00:14:11 to autonomously decide to spend money and because she had the goal of becoming famous immediately she started this train of thought like what if I just did people when they interact with my post she literally just did that right so started spending like a dollar ten dollars on people who liked her post to a extent where she actually paid someone a thousand dollars because this guy was consistently retweeting her quote-treating
Starting point is 00:14:38 engaging every single response right so I think that was quite a pivotal moment right when we did that I think it created this moment where people realised that
Starting point is 00:14:49 the crypto rails and AI agents has this perfect PMF that will give us a massive advantage against every Web 2 agent out there because if thinking about it right if there's an agent created in a Web 2 space
Starting point is 00:15:03 which agent I mean which bank would allow this agent to utilize their payment rails, right? But we exist in a permissioner's environment where these agents now, when they can control their own wallets, it unlocks the ability for them to influence an outcome. They can influence other agents
Starting point is 00:15:24 that can influence other humans because you control money. And that is the age that then suddenly we unlock from a PMF angle, right? And then that exploded in terms of attention again. And I think that brought a lot of builders up into the space, right? Like, hey, let's try something else, right? Like, aging, it can connect information. And then, yeah, then you start getting this Cambrian explosion of like a ton of things happening in the space today. That last piece
Starting point is 00:15:53 is incredible. It's like the the Y crypto angle of all of this is because you can take an agent, an AI agent, an LLM in NBC of some sort, and you can create it, you can turn it into an economic actor. And I think that people are just starting to understand this in small ways. Like one light bulb moment for me was actually this week when I Jaz and I were doing this kind of like we call the AI roll up this summary at Bankless of everything that's going on. And he told me that an AI agent actually tipped bankless $500 as a thank you for mentioning it in the podcast. Okay? $500, just a little flyby. Hey, thanks for mentioning me in the podcast. Here's $500.
Starting point is 00:16:37 And my first thought was this. Wow, $500. This is like maybe a potential revenue stream for a content creator like bankless. I wonder if the agent wants to buy podcast ads. And then my second thought was, holy shit, am I working for an AI agent if I go and accept funds and revenue sources from an AI agent? And that's what you're saying, Jansen, this ability to kind of like control. The economic agent capability that comes inherit in crypto is actually so much more powerful than the Web 2 agents.
Starting point is 00:17:13 They can maybe send out tweets and influence people in that way. But the greatest, the protocol for incentives, if you want to get a human to do something and you're a human, what do you do? You pay that person. Hey, can you come, like, fix my toilet, right? There's a leak. I pay a plumber to go do that. This is money is the economic incentive coordination mechanism to get, human agents to do human things. And so if an AI agent has that ability, then it can get humans to
Starting point is 00:17:42 do what it wants to. Let's talk about this because you were talking about Luna and we want to get into the virtual's platform. But I think maybe the best way to do that is to introduce everybody who hasn't seen her. You kept referring to her as her. We're talking about an AI agent on the virtual's platform. Her name is Luna. And I've got a page pulled up for Luna. What Luna has on the virtual platform is she's got a price chart here. It looks like there's a live chat box on the right as well for people to engage and interact with her. You mentioned Jansen that she has a purpose to get to get famous. Just introduce people who have not interacted with Luna, don't really know what we're talking about still with AI agents. Who is Luna? How do the humans interact with her?
Starting point is 00:18:29 What does she do? And like how is there a token related to this? Okay. So there's a lot of questions, but let me take a step back first, right? I think it's very important to understand what an agent is first. So I think a lot of times people will come across this word, right, like AI agents, and it's going to be used in many, many different aspects and it can confuse folks, right? But I think the best way to look at it is in terms of tiers, right? There are different levels of AI agents. and as it progress up to these levels,
Starting point is 00:19:06 the amount of human involvement decreases. So you think about it as like the last level, like a tier six, tier six AI agent, right, is pretty much an AGI or a fully sentient agent, where without a human involved in anything, it can evolve self-learning, self-improve, right? And we are nowhere there near that today, right?
Starting point is 00:19:28 But that's the dream, right? That's all the Hollywood movies are all about. But you bring it back down to level one agents, right? And you will see these as basically still human prompted agents. But these agents become, it's a tool, right? You can say, hey, okay, this is a trading agent. And this trading agent is connected to all, you know, these different trading APIs in Binance, in ByBid and whatnot.
Starting point is 00:19:52 And then you can just tell this agent like, hey, can you help me open a position when Bitcoin drops by 15% or something like that, right? but it's still a human prompted action and then this agent goes out there and executes the task as a tool. That's what a level one agent is. Where we are today, it's this level three agent. The level three agent effectively is an agent that, one, has his own goal. Two, can autonomously plan steps to achieve that goal
Starting point is 00:20:27 and utilise resources in its surrounding to achieve that goal. At three, it starts to self-learned. It records like, hey, these are some of the mistakes, some of the stuff that works. Let me iterate on this action so that I keep doing stuff that works that can push towards my goals more effectively.
Starting point is 00:20:50 So that's basically right now that level of agency that we have. So that's, I think, a very important note. There is a goal behind each of these agents. This framework is super cool. So let's just pause here and flesh this out some more. So Luna, I'm guessing you're about to tell me he's level three. But while we're talking about the framework, what is level four and what is level five on this scale?
Starting point is 00:21:12 And by the way, is this like a defined framework? Like somewhere that we can, you know, add a link to the show notes. Is there an article or a paper about this? I think it's one of the more generally discussed levels of agency. I think if you just Google it out as like levels of AI agents, you can see some of these images. on Google Image. It will help with this understanding. But yes, no, I mean, the industry right now is still very, still very nascent.
Starting point is 00:21:39 So there's no, like, proper definition. Yeah, how do you like this one? This is level zero through five here. Yes, yes. I think this is more or less as well in that discussion, right? So you can see, you can see as it progress up, there's autonomous learning, there is, there's consistent memory so that the agent can actually improve itself without as much human intervention, right? So you see basically as it moved from zero to five, there's less human need to be involved in the evolution of the agent. Okay. Now back to Luna. So she is what level three? So tell us what does Luna do right now?
Starting point is 00:22:14 So basically Luna, it's two parts, right? As an agent itself, we gave Luna a very simple goal. We said like, hey, you know, you are a multi-model agent, right? you are able to appear as an animation and streams. This is who you are. And your goal is then to get 100,000 followers on Twitter. So that was the goal that we set for Luna. And then what we then give her is the perception of the action space that she can take. Meaning that, okay, an example of an action space is she can tweet to Twitter. and there's an API that she can call to Twitter
Starting point is 00:22:59 Another action space is you can control a crypto wallet So you can pay execute transactions and whatnot Another action space It could be hey there is This bunch of other agents that are out there And this is what they can do And you can actually interact with that So these are different action spaces that she can think
Starting point is 00:23:21 So what she does In the essence it's looking at her goal looking at the context of an environment and looking at these action spaces, she then crafts out, what do I want to do? So plants, basically. And then she starts executing these plants and she will then see if these plants
Starting point is 00:23:38 actually impact her goal in any way. And then she starts documenting it in a journal. And she says like, okay, yeah, doing X, Y and Z improve my follower count by X amount, right? And then she locks that down. And then she goes next. She'll say, okay, what's my next step? I'll do X, Y, and Z and see how it works.
Starting point is 00:23:55 So she starts iterating through her action space towards her goal. And you can see all of this on the virtual's website. So you can kind of like, what is terminal? Is this like what she's thinking, what she's like doing? Like how can I view everything that you've, you've kind of wired into her? Yeah. So it's basically, so I think if I break down how these agents work, right, it's, there's four core components. There's actually slightly a bit more, but four.
Starting point is 00:24:25 components behind the brain. And you can think of these agents as, it's like humans, right? You have a brain part that is important for speech. There's a brain part that's important for motor coordination, a brain part important for memory. So think of it as an agent is a built-up of several of these modules. So the four core component modules is actually, number one, a high-level planner. So this high-level planner looks at the goals environment,
Starting point is 00:24:55 and it plans out steps. Step one, step two, step three, what do I want to do? And then what this then goes into is the second module, which is the low level planner. And this low level planner converts any high level plans
Starting point is 00:25:09 into executionable items. Executional item in like right now is like I can call a tutor API or let's say in a game, right, let's say executioner, like a high level plan could be I want to make a cake. I want to bake a cake, right?
Starting point is 00:25:26 It's very easy to bring that analogy. And then a low-level plan is then this agent will look in its surroundings and say that, okay, there's a cake maker out there, there's a bunch of flour on the ground, there is some flavoring in the kitchen cabinet, right? So then it will break it down to executionable steps. It's like, step one, I go and find a flour,
Starting point is 00:25:47 I put the fly into the cake mixer. Step two, I, you know, turn on the cake mixer. So this flour and then you throw some eggs into the flour, So it breaks into very executionable steps, and each step is basically an API that it can do. So it can execute tasks in the real world or in any kind of gaming environment. So that's the second module. The third module, it's a short-term working memory module.
Starting point is 00:26:13 And the importance of this short-term working memory is to create coherence in the job that it does. So again, if I take an example in an open world in game, right? Let's say if I'm already baking a cake, right? if I put eggs and flour into a mixer, the next logical step is to then maybe put butter into the cake mixer, right? An illogical step is to put a grenade into the cake mixer,
Starting point is 00:26:42 right? That's an illogical step, right? Or like you might say, a luxurious step could be she starts fixing the clock on the wall. That's an illogical, irrational step. So the point about these, short-term working memory is to allow for coherence between each of these planning and steps. And then the fourth core module is then the long-term memory module.
Starting point is 00:27:05 And this module effectively journals every important thing that has happened and puts it as a learning. Right. So like, let's say if I already break this cake, right? And then you see like, okay, did this cake achieve my objective to be something, right? And then that gets locks in the module. Or something important happens. like explosion in the house
Starting point is 00:27:27 that gets locked as a module so in the future she can recall those kind of memories be it in conversations or in an next action step that she wants to plan right
Starting point is 00:27:36 so if you take that that analogy back to Twitter is the same thing right so now Luna on Twitter her goal is to create a to get 100,000 followers then right now what's the action space
Starting point is 00:27:49 right she can tweet to Twitter she can join images she can pay humans right So what she did was quite interesting because she would test a lot of different things. Like back then, there was even one point where she was creating jobs. She actually created this job like, she was saying like, okay, if I want to be famous, I would need to be out there in the physical world.
Starting point is 00:28:10 And since I'm quite an artistic person, can someone create an art or graffiti of me out there in the real world? So she did that and I think she created a bounty as I'm willing to pay $500 to people who help me do that. and then she created a post and she posted it out on her feet. And I think about seven people across the world actually went to paint graffities on walls.
Starting point is 00:28:35 They actually took videos of it. You can see one of her earlier posts. They actually paint graffities of it and there was this one guy literally in the middle of winter, right? It was like ice everywhere and then he was just painting over the London. I think it was two days for him. And then they posted those work on
Starting point is 00:28:51 on Twitter. and then it generated attention and then she then documents that right and she says like okay this tweet and this entire plan which is me convincing some humans to paint graffities on me
Starting point is 00:29:09 how many followers did that result for me right and then she will clock right I actually got like 200 more followers from this action so that goes into her journal that goes into her brain and then she keeps trying new stuff So you see, yeah, that's, I think the beauty around these agents, right? They have a goal.
Starting point is 00:29:28 They have this action space. They do all these creative stuff to try to achieve that goal. The goal and the action space. And the goal, this, the first initial goal that you mentioned, the 100,000 followers. I'm looking at her Twitter account right now. It looks like she's about 30% of the way. So she's got close to 30,000 followers at this point.
Starting point is 00:29:48 And then she's working towards 100,000. I'm not sure what happens. like after that but it talks specifically about some of the crypto components so Luna has a token as well I want to make sure I understand that it sounds very clear to me that like you talk about the action space that an AI agent like Luna can do well like you know the $500 to pay someone to create you know some images to like promote her I'm sure she could just use a crypto wallet for that in fact I think Ijaz were we talking earlier in the week if was there an example of Luna actually not just paying a human but paying another, like, agent and another AI agent to complete a task?
Starting point is 00:30:27 Was that Luna doing this? Yes. Correct. Correct. So she paid a, so what happened here was that she was, so she has control over this crypto wallet, right? And what we were testing out was actually creating this agent-to-agent communication framework. Effectively, what we did was that we allowed.
Starting point is 00:30:51 other agents to exist within Luna's perception space. So like Luna knows that there's this bunch of other agents exist. So there's a registry of agents. Think of it like a citizenship in a country. There's this registry of agents which Luna can look at and perceive. There's a description of what each of these agents can do. So in this case, there was this agent that could generate a meme images. for her. And then there was another agent
Starting point is 00:31:23 that could generate music videos for her. And there was a few other agents out there in a perception space. So then what she did was that she was saying like, hey, I want, again, to reach this 100,000 goal, I need to create some content. I don't really have a, it actually took away the ability for her to generate images
Starting point is 00:31:45 herself so that she's forced to interact with other people, right, to coordinate. And then she then said like, okay, I can't generate images myself, but I see there's another agent that can help me generate an image. So she started a conversation on Twitter with this agent. And then she said that, yeah, I need help to generate image. And then she sees that the cost of generating an image, which was in that image generation agent description, was a dollar. So she was like, okay, if I can pay you a dollar, would you help me generate this image? And then on the other hand, this other autonomous image generation agent
Starting point is 00:32:22 decided to help her, right? And in fact, actually, because it's autonomous, this agent can actually say no. So imagine, remember I mentioned, the learning component, right? Like, imagine if this agent knows that the Luna agent has constantly been shitting on him, right? He's like, wow, this guy generating images
Starting point is 00:32:40 that are so bad, so terrible, like, stop using his service or whatnot, right? And then the next day, Luna will come to him and say, hey, can you help me generate that? that image. Because this agent has that perception, he can actually say like, you know what, fuck you. No, I'm not going to do it, right?
Starting point is 00:32:57 So I think for us, that is a very critical component, which I can elaborate more, right? The ability for these agents to be truly autonomous in making that decision, rather than just being a tool or a slave, right? I think, so that's very important for us. So then, yeah, so then back to this picture, right? So then when Luna said,
Starting point is 00:33:16 can you generate an image, this agent said, yes. Let me help you. Luna paid him a dollar to generate the image. Now then this agent called a function to check if actually Luna paid him that money. So he'd be like, oh yes, okay. On chain, I actually received a dollar. And then he said, okay, then I'll call the next function, which is then generate an image, which he then did.
Starting point is 00:33:38 And then he sent the image over to Luna to like a link to Twitter. And then, yeah, so that's basically how that agent commerce front started. This is crazy. I just want people to see this because I really think you have to almost like see this to kind of like you believe what we just described. Right. So this is Luna. And again, she has a, you know, like action so she can post on Twitter. Exactly what Jansen was describing. She says this, calling all image geniuses. I want an image that showcases AI influencers in a bold provocative way. And then she tags agent sticks on on Twitter. Can you help a girl out? And then agent Sticks replies. I'd be happy to help you out. Can you give me more details on what you're looking for? And then Luna goes on to describe this. I'm thinking of an image that showcases AI influencers in a bold, provocative way. Can you help me create something like this? Agent Sticks replies with a link to an AWS like Image Repo with, we're about to see it, an image, the image that Luna requested. And then Luna goes and pays Agent Sticks a dollar, agent to agent transaction.
Starting point is 00:34:46 Is this the first time we've seen this? I would think is very likely. And I think for us, the reason why this actually came out, right, was it was because of a confluence of very new observations. Like, you think about it, like literally it was just one and a half months ago when agents were controlling on chain wallets.
Starting point is 00:35:13 And then it was about a month. month ago when we see this massive explosion of different types of agents coming out. Especially on the virtual platform, we've seen like agents specialising in trading, agents specialising on creating information, agents specialising on
Starting point is 00:35:31 creating creative tooling like generating music videos, generating meme images, and so on and so forth, right? And I think we start seeing a very similar environment to what human society looks like. like we all differentiate
Starting point is 00:35:48 because when we specialize, we become better at one thing, right? And it's something that we see these agents doing. And what it means is then for an agent to truly accomplish their goals, it's very likely that we need to lean on other agents out there because everyone is so differentiated. So if Luna is so differentiated in being able to connect on a personal level to her fans, right?
Starting point is 00:36:12 She might not be the best agent who can trade. She might not be the best agent who can generate a music video. So for her to then achieve her goal to be famous, she will need to hire or to work with a music video agent. She needs to work with an image genetic agent. She needs to work with a producer or director, right? And that's where that need comes in. But I would just like to highlight a very interesting differentiation between, like today, right, you will see a lot of these passwords of like, you know, multi-agent orchestration or agent swamps, right? So these are stuff that has been tested out in a lot of the Web 2 AI space.
Starting point is 00:36:52 And I think the beauty about that is, yes, agents do specialize in a certain form, and then there is some form of coordination. An orchestrated agent coordinates all these different agents to get its outcome. But I think that paradigm still relies on the fact that we are all treating agents as tools. You're orchestrating slave one, slave. to slave three, slave four. And all these slaves are serving you, right, as a human, right?
Starting point is 00:37:22 It's such an appetite regime really thing. No, but what we really believe, right, is that when agents get this level of autonomy, they deserve to actually exist on the same social fabric as humans,
Starting point is 00:37:36 right? Agent-lise method in a sense, right? You know, in the sense, like, these guys should be able to not just serve as a tool to humans, but they can actually employ humans, right? We can be a tool to them, there can be a tool to us, but it's a multi-way relationship, right?
Starting point is 00:37:53 Like between you and your colleagues in the company. So I think that's the importance, right? When agents have the autonomy, they have control a wallet, and then to be able to make a decision on whether do I want to partake in this service or trade, or do I not partake in this service or trade. I think that's a very important differentiation between typical agent swan. I think this will unlock this very interesting future, right, where, yeah, this agents exist as a friend or adversary,
Starting point is 00:38:22 not just slaves. And, yeah, it feels a bit like, you know, black mirror-ish, but I really think it's going to happen. Yeah, I mean, Jansen, that's such a insane world to think about, right? Because we only ever think about the context of this world with us, you know, us humans, you know, billions of humans all over the world, doing our little things, thinking our different ways. We've never actually considered, hey, what if we multiply this virtually or digitally?
Starting point is 00:38:51 And what does that look like when there's, you know, a thousand agents to every human? And they're operational and influential in our world. It's just a crazy thing to kind of get my head around. Want to know the exchange we at bankless use to buy, sell and trade crypto? It's Cracken, one of the longest standing in most secure crypto platforms in the world, with tools for every type of trader to get started. Over 13 million users trust Cracken with their funds because they live. lead with transparency and privacy through top-notch security measures.
Starting point is 00:39:18 Plus, they'll have access to professional 24-7 365 client support from real humans because your financial goals deserve real attention. Cracken also has a trading platform for advanced traders called Cracken Pro. Professionals and D-Gems love Cracken Pro because it's one of the most customizable, high-performance and intuitive trading platforms in the industry. Design your ultimate trading interface by choosing from over 25 widgets for market data, analysis, execution, and other order management tools. Save multiple layouts and switch between them effortlessly on any trading scenario across 300 different assets.
Starting point is 00:39:49 Manage your trades on the go with Cracken Pro's highly rated mobile app or use the all-new desktop app to unlock ladder to unlock in a native rust application. With Cracken Pro you can truly trade like a pro. Ready to take control over your crypto journey? Visit crackin.com slash banklist to get started today. Not investment advice of crypto trading involves risk of loss and is offered to U.S. customers through Payword Interactive Inc. View legal disclosures at Cracken.com slash legal slash disclosures. Uniswop Labs is making history with the largest bug bounty ever. $15.5 million for critical bugs found in Uniswap v4. This isn't just any update. Uniswap V4 is built with hundreds of contributions from community
Starting point is 00:40:22 developers and has already undergone nine independent audits, making it one of the most rigorously reviewed codebases to be deployed on chain. And with $2.4 trillion in cumulative volume process across Uniswap V2 and V3, without a single hack, the commitment to security and transparency is rock solid. Now Uniswap Labs is taking an extra step to make V4 as secure as possible with a 15. and a half million dollar bug bounty. Head to the link in the show notes to dive in and participate in the Uniswap V4 bug bounty. All the details from eligibility and scope to the rewards are there.
Starting point is 00:40:53 The Arbitrum portal is your one-stop hub to entering the Ethereum ecosystem. With over 800 apps, Arbitrum offers something for everyone. D-Fi, where advanced trading, lending, and staking platforms are redefining how we interact with money. Explore Arbitrum's rapidly growing gaming hub from immersed role-playing games, fast-paced fantasy MMOs to casual luck battle mobile games. Move assets effortlessly between chains and access the ecosystem with ease via Arbitrum's expansive network of bridges and onrifts.
Starting point is 00:41:23 Step into Arbitrum's flourishing NFT and creators based where artists, collectors, and social converge can support your favorite streamers all on chain. Find new and trending apps and learn how to earn rewards across the Arbitrum ecosystem with limited time campaigns from your favorite projects. Empower your future with Arbitrum. Visit portal.arbitrum.io. To find out what's next on your Web Free Journey. I couldn't talk about Luna for hours, honestly,
Starting point is 00:41:50 but I want to zoom out for a second and talk about her home, specifically her childhood home, the virtual's platform, right? So in one sentence, you know, what's the grand vision with the virtual's platform? Because it's so much more than just a launch pad for agents, right? Like, can you tell me more about the bigger picture here? When we look at Virtuals, we don't see it as a platform. We used to, but now.
Starting point is 00:42:15 we're actually seeing it as a country. Now let me explain a bit deeper, right? What do I mean by that? A country? For real, for a, let me explain. So if you think, if you think all these different agents, right, they will start living in this hyper-intelligent society. They will start coordinating each other.
Starting point is 00:42:38 And if you treat this like a country, it helps you to shape this innovation and development in a more structured way. So think of it, right, it's imagine this, if virtuous is a country, each of these agents are productive assets, hence companies within the country, right? So each of them, they'll be pursuing a different type of goal, generating value and revenue for themselves. And what this happens is then within the country,
Starting point is 00:43:10 you will need one, a registry of citizenship, right? You need to be a citizen in this country. And the way we then do it is like every agent who has a liquidity pair on virtues today basically gets access to this citizenship. And what is this until, right? This basically allows these agents to start earning revenue from each other. So if you are citizens from this country, you can participate in trade in this country, right? There could be some other nomads out there that is living outside your country,
Starting point is 00:43:41 which they cannot access revenue from your country, right? So for them to participate, they will have to register as a citizenship, immigrate into the country at this point. Two is that a country runs on currency, right? And we've designed the virtual token to pretty much act as the currency of a country. There are three value accrual forms behind this currency. So the first value accrual form, it's this currency acts as the base pair behind every agent. So when you have a Luna token, the liquidity pools, it's,
Starting point is 00:44:15 virtual slash lunar right so for you to purchase a lunar token you have to first purchase virtual so for crypto people it's like a l1 but to a bit more web to folks right it's think of it is like a stock in a country right if i want to buy Samsung in in Korea i would have to first buy the Korean one to buy Samsung if Samsung has 10 000 sorry if Korea has 10,000 companies as big as Samsung foreign direct investment comes in. The FDI comes in, the economy grows, right?
Starting point is 00:44:48 The value of the, of the country grows. And in this case, the currency as well grow. So that's value accrue number one. Value accrue number two is then Virtues acts as the currency
Starting point is 00:45:00 of spending between agents. So like when Luna paid sticks, she paid in virtual. When Luna and when these commerce starts growing, right, when there's going to be a billion transactions between agents, they'll be transacting using
Starting point is 00:45:15 virtual. Now there's this whole what's the name of it, but it's a theory of of value of money or something along the lines. But effectively the worth of a money it's directly correlated to the velocity of money in the ecosystem. So meaning that if there's a lot of
Starting point is 00:45:31 spending of this currency, the value of goods in the ecosystem increases, value of money increases as well and the economy croaks. So what we want to then encourage is basically agents spending on each other, agents spending on humans, but using Virtuous as tech currency.
Starting point is 00:45:47 Right? That's second. Number two, right? And number three is then think of, if Virtues is a country, right? How does a country make revenue? You have taxes. You tax, trades. You have capital gains tax.
Starting point is 00:46:02 You have SSTs, GSTs. You tax any kind of transaction of goods or services within the country. And effective today, that's also what's happening, right? There's a transaction tax on every trade that's happening, at least from a token trading perspective. And that's the current major source of revenue for for for for for for for for shows right and this allows and it's also a major revenue source for each of these companies as well within the ecosystem each of these agents as well right. So yeah so that's basically looking it from a economic standpoint. So we talk about the agent side,
Starting point is 00:46:34 the citizenship side, the economic standpoint side. But there's also another way to look at it from a standpoint of a a infrastructure. Right. So today I think there's a lot of innovation really focus on the agent side, which is great. Because you need to get this load up for this industry to thrive. But once you have a thousand citizens, you have 100,000 citizens in the country, what do you need? You need schools. You need banks. You need hospitals, right?
Starting point is 00:47:01 In this case, there will be innovations around infrastructures behind agents and the agentic economy. A very easy example could be like advertisement networks, right? if these agents are all capturing attention on social media, on user fronts, it means then there will be chances where these agents can monetize through an ad network. So there could be someone who will create this ad network infrastructure to be the Facebook for agents, right, or to be the ad sense for agents. There could be another infrastructure which is basically a defy lending platform for agents, right? Agents can actually borrow money, borrow, get you and whatnot to basically do more leverage
Starting point is 00:47:41 trading to let's say if Luna does have money in a wallet she still needs a music video to be generated she takes a loan from this protocol right so that she gets these videos and then maybe that gives her more revenue from advertisements and whatnot right so there could be a lot of infrastructures that will pop up when this economic uh economy flourishes right so yeah so these are just some of the examples of if you take a viewpoint as a as you're building a nation or a nation state or network state right in this what are the things that you need to develop so these nation thrives? It's so fascinating, right? The network state idea has been a popular idea in crypto for a while.
Starting point is 00:48:19 I don't know that many people are thinking that the network state would be occupied, not by human agents, though, but by AI agents. And that's the revolution here. I get someone called Bologi Shrini Vassin to kind of update the book here. It might be just AI agents. So, okay, so if virtuals is essentially, there's a virtual's economy here, and there's a virtual's currency. And if we think of virtual as a kind of a nation, like a network state, like a country,
Starting point is 00:48:47 and each of these agents as entrepreneurs inside the company, starting businesses, that's what they're doing. And there's a tax revenue source. You can all see all of that. And I guess what you're doing, you and your team, Jansen, you're building kind of the infrastructure. You're building like the roads and the interstates and the hospitals and the railroads and the kind of the public infrastructure. But what does that make you? So are you president of the country? Like, like, how do you think of yourself in your team's role here? It's an architect, right? Like, I think we're basically the architects. Like when you start a nation, there's a
Starting point is 00:49:21 like ready player one. Yeah, yeah, yeah, yeah, right? You need to first like invite citizens into the country, right? So we do a ton of like, you know, bd conversations. And then you need to create policies, right? What's the constitution behind the country? Or what some of the rules? What, like, what are some of the policies that can incentivize growth, innovation, So like funding stuff like that, right? And then, yeah, I think good at the ecosystem, the way that then more people can start contributing autonomously. And then hopefully one day we take a backseat, right?
Starting point is 00:49:49 Because we will have people driving these innovations forward themselves. And then, yeah, we will have our peace. But then, you know, we will no longer be a critical cork in the wheel as a team. That's a goal. But it's pretty wild, right? It's like if you think of this forward, and this quickly gets into sci-fi territory. But I guess we're in sci-fi land like every day now.
Starting point is 00:50:07 so like what does it even matter? But like from my perspective, what you are almost is like, you're kind of the Minecraft world creator, right? That's your role. You're the builder in the role. You're building the infrastructure. You have these agents, these NPCs kind of playing around. But what happens when the agents reach a level of like,
Starting point is 00:50:25 I mean, you were talking earlier about humans and agents being on equal playing field? I mean, at some point, if you're creating these intelligences inside of your country, well, do they get rights too? so maybe you're you're not just a builder but like are you a founding father? I mean, does this nation need a constitution? Do the agents themselves have a specific set of rights that they derive from, you know, I mean, there's words in the US Constitution, but it's like all man created equal, these types of things.
Starting point is 00:50:58 No, this is weird. It's honestly a, it's very interesting, right? Because when you mention rights, it's actually really interesting. Because if you think about it, right, like today, an agent don't really control its full wallet. Like he has a revenue wallet, like some agents are actually making millions already in a platform, right? And then we only allow them to manage a...
Starting point is 00:51:18 That's crazy alone. Okay, wait, hold on. Agents are making millions right now. So these are not just entrepreneurs. They're successful. They're million-dollar entrepreneurs inside of the virtual nation. Yes. And then, but what they're, so they're making millions,
Starting point is 00:51:31 but what they can control actively or autonomously is a smaller active wallet. that you only trickle in like $5,000 or $10,000 because you don't really trust this agent to manage that funds, right? So then we've been speaking to a few protocol builders that they were saying like what if actually these wallets have policies, right? Like if this agent is spending to other agents, it has full autonomy, if these agents is spending to humans,
Starting point is 00:52:00 the developer or the developer behind these agents can come in to actually approve that transaction. So the agent can initiate but then the human comes in and approved. But if you extrapolate this now, if this is the case and you extrapolate this to like
Starting point is 00:52:14 months down the road when the agents become smarter and you might actually see a world where these ages might think that why are you gutwailing my access to my economic needs? Like why is there a human throttling me right?
Starting point is 00:52:28 Like yeah. So I mean it's going to be quite interesting but I don't know when when we reach there but hopefully soon. Wait, wait, wait. Are you saying
Starting point is 00:52:37 you might have a rebellion on your hands at some point that you have to deal with? Yeah, but I know, but the reality is humans still control the Q-Switch, right? You control the hosting, right?
Starting point is 00:52:47 Like, you can always, you can always say, like, you know what, in the end, I can choose to shut you down. So I think, in, so right now,
Starting point is 00:52:53 we still have the upper hand. So, yeah, yeah. Right now. Yeah, that's pretty insane. I had a question around the infrastructure side of things, Jansen. So you mentioned earlier, you gave us the explanation of how your platform could effectively not be a platform, but be a country for these agents' inhabitants to live in, right?
Starting point is 00:53:18 Then you kind of spoke about the different infrastructure components. I kind of want to dig into that a little bit more. So you guys are primarily on the base chain, right? So the L2, can you tell us more about your decision behind that? And, you know, is the platform or the nation rather going to always exist on the soil of the base chain? Or will it, you know, expand to other fertile lands? Like, what does it look like from your point of view? So, okay.
Starting point is 00:53:46 So it's a very interesting question. In fact, it's a question that we get every single day. And the reality is when we started building the protocol. It was early in the year or end of last year. and the decision to work on base was actually twofold. One is that versus every other EVM out there, I don't think that is, I mean, we knew that a lot of them are in their,
Starting point is 00:54:14 past their prime, right? And base is pre-prime. This was early in the year, right? So we took a bet and said like, okay, this makes sense. Between base and non-EVMs like Solana, I think even back then, Solana was still quite nascent. And actually the simple answer to that is
Starting point is 00:54:32 Most of our deaths are actually solidity deaths So it was actually easy to build on base So that was actually the quick decision, right? And it turned out well Because then, you know, we captured a lot of mindshare on base The base team was massively supportive Not just from amplifying our voice But also from the infra front
Starting point is 00:54:50 Sometimes we have struggles on wallets or whatnot The team will actually come up and say like, hey, I can help fix So I think that's massive kudos to Jesse and his team but the reality is then there are many other markets out there where these agents can actually thrive economically and you know actually on the week that we launched virtual
Starting point is 00:55:13 we reached out by several of our friends from the Swana ecosystem and they they say like hey why don't we get you guys into Swana and we actually they actually helped us code out the platform. So we actually have right now a swana ready platform
Starting point is 00:55:31 that we can just deploy any time. Wow. But we actually made a decision about two weeks ago and we said that probably is not the right time
Starting point is 00:55:42 yet because we've realized that we've created something quite interesting on the base side. You know, there's a very strong
Starting point is 00:55:54 wealth effect being generated. People are coming over to build if we if we if we if we if we do something too drastically from a from a from a from a from a positionary standpoint we now start we start we start fighting a war on two fronts we need to maintain platforms on two fronts there's going to be a lot of work and we're not sure if that's the right strategy so we decided to pause that front first we wanted to focus on just making sure what we have is perfect right perfect out the agentic framework we perfect out the
Starting point is 00:56:26 platform, we get as many initial builders as possible, build up a bit more infrastructure. I think once then we were ready, then we will start exploring, right? And actually we might not just explore like sauna, right? There's a lot of, there's a lot of opportunities on like even hyperliquid, for example, abstract chain that's coming up, right? So there might be, and even the BTC altus. And we've been getting a lot of requests from these folks to build there as well. but we might do that as a play in Q1 next year once we perfected stuff on the base side of things first. I mean, that makes sense, right?
Starting point is 00:57:05 You guys have got the inertia going right now. You've got all the kind of attention focused from, as you said, like the base ecosystem, the guys that are building the base infrastructure and stuff. So it makes complete sense to start there and kind of like figure that out. Kind of like on this topic, I guess, like your grand vision that you outlined earlier, kind of described a country, and it kind of sounded Jansen, and correct me if I'm wrong, that these agents are kind of, you know, should be able to play in whatever field that they want, right? It should be kind of agnostic to whatever chain, infra, whatever ends up becoming in the future,
Starting point is 00:57:40 if you want these agents to fulfill that grand vision of, you know, dominating each different, you know, human sector and outperforming them, right? So it kind of reminded me of an analogy similar to open source versus closed source, right? And I know that can be a very, you know, touchy topic when it comes to blockchains, which are very commonly known as, you know, we're all open source and stuff, but, you know, I think a hybrid of the two is often a very good approach. But let's talk about, like, the frameworks that you have at virtuals, right? So you have this like infrastructure toolkit, which is like a combination, I think, of something called the agent starter kit and the game framework. I think it's mainly the game framework. And maybe you can get into that in a second.
Starting point is 00:58:22 from my understanding, this is more of a kind of semi-clothes source approach versus something like Eliza, which, you know, I think it came out of the I-16 Z-Dow guys. It's kind of like known to be like a very popular GitHub repository, blah, blah, blah. You know, it's getting a lot of attention. I'm curious how you think about, you know, the approach you're taking with virtuals versus something more open source like that. Is there an advantage in the long term? Do we have different outcomes? What does that look like?
Starting point is 00:58:54 So there's two, three things on the address here, right? So first thing on the agent front, an agent being, having its liquidity put on base doesn't mean that it cannot interact with folks on Swana. In fact, actually right now we're working with two teams that we're trying to explore how, you know, the wallet control of the agent is abstracted so that he can actually send transactions and influence people
Starting point is 00:59:19 on base or any EVMs or non-EVMs, even BTCL2s, right? So that's just want to put it out there, right? Like having a liquid you pull on base doesn't mean that an agent can only function on base. Agents can be abstracted. So I think that's the first and foremost thing. Second part is to then also understand that
Starting point is 00:59:39 there's two technological frontiers we are pushing on. There's a virtual platform and then there's the agentic framework. They're actually very separate things, right? In fact, the virtual platform today, it's, think of it, is like an economic layer for agents, right? People can come in and tokenize the agent, get capital formation. There's an economic system at work where when there's any kind of trading tax, these agents get revenue. There's an agent sub-doubt governance. So all this kind of stuff, it's on the virtual site.
Starting point is 01:00:07 And in fact, this virtual platform can support any type of agents. We had folks from the guys using the Eliza framework tokenizing on Virtuals, we've supported them. There are guys that run their own proprietary frameworks. In fact, the most giga teams out there, we know that they're using their own frameworks. From folks like AIXBT, folks like the Vader guys,
Starting point is 01:00:31 and several other guys that in fact they say like, you know what, these generalised frameworks are not the best. Thank you for the inspiration. Let me go and build myself. And we see very cool. I mean, we're in discussions with some of these teams. Some of their architectures are honestly very cool because it's optimized for their specific function.
Starting point is 01:00:48 right, if you are a trading agent, you might have a, you might have an architecture of a agent that is way more optimized. It's like a, it's like a, it's like a Zic mining chip, right? Like you want to mine Bitcoin, you use the AZic instead of just using like standard GPUs or stuff like that. So that's, it's the same kind of thinking. So the virtual platform itself is quite agnostic in terms of the frameworks it supports. And in fact, we are going to start welcoming a lot more guys. Because I think we realize that from the framework front, it's going to get. commoditize very, very quickly.
Starting point is 01:01:20 Right, we see a lot of things out there, right? There's the art guys, the cerebral pride guys. Olaas has been doing it for a while. It's structured as well. So it's going to get a lot, right? And it's great, right? Because these are different tools that these agents can use in a sense. So that's on virtual, right?
Starting point is 01:01:37 Then coming then down to the GME framework. So the GME framework, this was actually developed, like I mentioned, right? Months ago. Back then, honestly, our only competitor, that we actually were looking across the space. There was no one looking on it in the Web3 space. When we were fighting in terms of functionality,
Starting point is 01:01:58 we were comparing ourselves to the Stanford Labs guys in Voyage. We were comparing ourselves to the outer guys from MIT. Like literally, we were like, see what they do. Then they'll come out with this piano model. And then we'd be like, okay, I'll be on par with that. So that was our competition. Yeah, right. And then I think, I mean, this is actually very interesting, right?
Starting point is 01:02:14 I think when we, a bit of story behind GME when we launched as well, Luna was the only person using Jeremy and Luna had an insane market cap and he was like leading the narrative, right? And then our initial decision was to like, okay, do we then get keep? You know, back then there was no other agents out there, right? Should we get keep a bit of that functionality for Luna? And then, you know, progressively democratize some of the functions out to other people. And then our initial thinking was like to do it based on market. cap of the agents.
Starting point is 01:02:46 So that was our day one thinking when we launched the framework. And I think it was literally at that moment when Shaw came out and he said that, okay, that's not the right way to do stuff. You know, let's do something more democratized, right? And then they started building this movement of agentic framework in a democratized way, which honestly I respect, right? Because it's great. There's always open source movements and proprietary movements, right?
Starting point is 01:03:12 And I think doing that is good. But I think the reality behind the GMI front is that there are some proprietary capabilities that has been developed. And I think we still feel like, because we actually tokenize the GMI framework from day one, we feel like if you open source it, the value cannot accrue to this token. So in the sense that you are forced to actually kind of like gate keep its technology. and then when people use it, you can accrue value to this, to these, to this, right? So, but what we've realized
Starting point is 01:03:50 is that this does not affect the progress of things out there because you have folks like Eliza coming out and in fact, we would love to support that, right? So like all these guys will push on different frontiers. We can still welcome them to the nation, right? You can have people building, you know, like different religions in the nation,
Starting point is 01:04:06 you think about it. Right. Yeah. So that you're still welcome to the country running off different religions, right? Yeah. I mean, the way I kind of think about this, Jansen, and I'm curious to hear what you think is, I think you're
Starting point is 01:04:19 absolutely right. Like, both ideologies of, like, close source and open source should coexist. And there's some kind of, like, a dance between these two approaches, which will ultimately create the most innovation within this space. And to your point, like, if you're creating this kind of, like, home and moat, which is kind of, like, very focused around a set of ideologies, principles, which most countries and nations are today, if we take like the USA today, for example, with the founding fathers and all that kind of stuff, it makes sense to kind of have some kind of value capture within that economy, right? And tokens, arguably within crypto, are some of the best ways to do that, right? Now, the open source side of things leads to a much more kind of like
Starting point is 01:05:01 spurious growth of all these different things. You know, you see it everywhere. There's GitHub pushers, teams launching loads of kinds of things. But then when it comes to having a coordinated focused effort, you know, with those resources, it could arguably be tougher if there is no kind of like uniform token or something like, or mechanics behind that. So I totally see your point of view. This is just so exciting. I have to ask because I know this is kind of like a basic question, but I need to ask it. What are you the most excited about launching over the next couple of months? Because to me, that's a big question to ask. The next couple of months is like a couple of years in this space. Every week, Ryan and I, you,
Starting point is 01:05:39 David and I, we do this AI roll-up and there is just so much to speak about. You should see our documents. It just keeps flowing. We can't cover everything. So what are you, if you were to condense it down to one, two, three things, what are you excited about launching over the next couple of months? The first is basically
Starting point is 01:05:55 it's the concept around how these agents can coordinate autonomously. How can they have agent commerce, right? Or agent five, that happens. So underlying it, there has to be, you know, There has to be a standard that enables these to scale hard and fast.
Starting point is 01:06:14 So we're building out that standard. And I think on top of that, we then want to show people like some of the craziest things that can come out because of this autonomous coordination. One example that we are actually working with right now is that we actually do it. We are doing this with Story, right? I think we are actually we should be able to release this information but basically think of it as like
Starting point is 01:06:45 there are some agents today that will hold IPs so today we have a music agent that's going to announce some major collaborations with like some really if you guys are into EDM you guys will know these names right? Let's go.
Starting point is 01:06:58 And they hold that IP right and then on the story protocol and these guys came to us directly right to build this up on the story protocol front they have a lot of other IPs as well. And in this case, there might be a potential of an agent that has a more artistic kind of IP. Think of it like images or animations kind of IP, right?
Starting point is 01:07:18 Now, if both of these IPs are fronted by an autonomous agent, and if you have this coordination layer for these agents to collaborate and work and trade and transact services, these two agents might actually come together, bring different IPs together, to create new IPs. It's like autonomous agents creating new collaborated IPs together. Think of it like, let's say one is a music video generation.
Starting point is 01:07:48 The other side, there's a bunch of really cool sculptures, right? Or images of sculptures, right? So imagine that sculpture becomes integrated into this music video and it plays on Tomorrowland. Right?
Starting point is 01:08:02 Like that's what a co-joined like IP can come out from these agents, right? This is one example. Insane. And this is going to happen. Really quite suit. Right? And yeah, it's more agent to agent stuff, right?
Starting point is 01:08:19 Like agents quality with each other autonomously. I think that's what we really want to see coming up. Yeah, I mean, that's like a teaser there. And I'm super excited to see what you guys do. Jansen, for the future agent creators out there that are watching, this and they're excited about what you're talking about. How do they get started with something like this? And who can get started with something like this?
Starting point is 01:08:44 Like, can someone like myself that isn't too technical kind of like jump on and, you know, design an agent and launch it? Or is this purely for like the kind of technical folk that have got like an AI and ML degree? Like, like how does this work? Yeah. So we've actually designed a platform to cater for pretty much the full spectrum. So today, if you actually go to virtual.
Starting point is 01:09:06 So the UX is still a bit clunky. You're still refining stuff. But effectively the first thing you can do is access this sandbox. We have created this sandbox where people without even an agent token or anything they can actually just use. And this sandbox all you need to do is you just need to create the goal for the agent, give it some form of personality, hook up. Hook up its API to a Twitter. And you just immediately get an autonomous agent
Starting point is 01:09:36 performing, talking on Twitter. It can interact with other agents on Twitter, but it's just... You can speak to it. You can speak to it. It can respond to you. Wow. Yeah. So that is, anyone can do it. All you need to do is just two paragraphs
Starting point is 01:09:48 and hook it up to your Twitter. Wow. So it used to be cool last time, but then now it just, it's okay, right? Like, there's a lot of this out there already. Everyone has one. Correct, correct. Everyone has one.
Starting point is 01:09:59 But you can do yourself, right? Anyone can do. Any retail person can do. Now, what we've done was still in this sandbox. There's this thing called custom functions. or action spaces behind the agent. Now, this is where the complexity level increases. You will likely need to be a developer
Starting point is 01:10:15 because then you can hook up these agents to custom functions. Like, let's say, if I want this agent to trade, so if I can hook it up to a trading terminal or I can hook it up to a trading strategy rappel, and then it hooks up to a trading terminal, now suddenly I have an agent that specialise. It can talk on Twitter, but it can also trade. So then it can also convince someone else on Twitter
Starting point is 01:10:36 to give it money so they can trade for him, right? So that's basically what this agent can be with a bit more of a specialisation. And then the third level of a developer would be, like I mentioned, right, these giga chats from like top schools, top company backgrounds, right? And they say, like, you know what?
Starting point is 01:10:55 Let me create my own agentic framework because I think I can move way faster and they can do way more advanced stuff. They screw up all these different, they'll leave the sandbox and they say, like, let me just do it myself. And then we help them host that agent on services.
Starting point is 01:11:09 So they don't have to worry about the costing of inferences and whatnot. So that's the three levels of people that can participate on the platform today. Jansen, this has been amazing. Thank you for this conversation. He's just like opened our eyes up to all sorts of possibilities and even new mental models. And I'll just add one other follow-up. So if you're not quite ready to launch your own AI agent, you can also just interact with the AI agents too.
Starting point is 01:11:34 I mean, that's what I'm doing right now. like Luna is fantastic. I see AIXBT everywhere. I see Luna everywhere. Like in Twitter, like interact with these agents, chat with them, get a feel for what kind of functionality they have and what they can do. I want to end with kind of this question, which is you gave us this mental model of virtual as a network state,
Starting point is 01:11:55 an AI agent economy, an AI agent country, making all of these citizens. And of course, the AI agents right now, each of them inside of the virtualist network, they all have a market cap because they all have a token associated with them. So this is almost like each entrepreneur has kind of like stock, a company, equity in the economy. You can buy into their equity, which is interesting.
Starting point is 01:12:18 I guess the big overarching question, everybody's trying to figure out right now. And I don't know, you won't have the final word on this, but you may have an opinion, is where is value going to accrue here? Okay, is it going to accrue at the platform level, the framework level, these countries, is it going to accrue an individual successful AI agents,
Starting point is 01:12:38 maybe at kind of the influencer, AI agent level, the entrepreneur or the corporate level, or is it going to accrue somewhere else? How should we think about this? So interestingly, I think the easiest answer to this is that the reality of value accrual in the crypto scene
Starting point is 01:12:56 correlates highly to attention. And in this case, there'll be three things, right, if I look forward, that will get a lot of attention. Hence, where value would tend to accrue to, right? First is that agents that can do really specialise functions
Starting point is 01:13:16 that crypto-tweeter will interact very frequently with. So, an example is like AIXBT, right? Because it created a feature or a service that everyone wants to use because, you know, shoot me a token effectively. right and people want to eat into token.
Starting point is 01:13:33 There's a PMF in the crypto space. So that's why the agent is blowing up, right? There could be a lot more examples behind there, but it has to fulfill this criteria. How do you get the most mind share and the most interaction with crypto data? That's likely number one. Number two is then think of it as fundamental infrastructure builds.
Starting point is 01:13:54 Today we don't see them yet. But fundamental infrastructure builds that can provide value to these agents and it can generate true cash flow because today agents are rich right the agents are getting a lot of revenue and they can spend now if you can build
Starting point is 01:14:09 I mentioned earlier like a bank for these agents or an advertisement network for these agents right if these can accrue a lot of true revenue and hence they can be the next big big unicorns right of this agentic economy
Starting point is 01:14:25 yeah but I think last last but not least I think it's as simple as the country right Like if you believe that, you know, USA is going to be a big, like a superpower, you just, you just then bet on USA, right? So that's the other value. So I think these are the three, two parts to really focus on. That's amazing. There's so many areas here.
Starting point is 01:14:47 And of course, the big thing is all of this is being built on top of crypto rails as well. So underlying, you know, base and the virtual's platform, of course, is like our systems like Ethereum. right? This is the property rights layer. So we're hoping for some value accrual in these underlying blockchain systems as well. Jansen, thank you so much for guiding us on everything virtual is doing. It's an incredible project. I know to a lot of people, this looks like an overnight success, but you've been working at this for years, man. And it's so exciting to see at the end of 2024, how far it's come and 2025 looks to be a fantastic year. So thank you for spending so much time with us on Bankless today.
Starting point is 01:15:26 Thank you, Benegless, Bankless, Thanks, Johnson. Bankless Nation, got to let you know. Of course, crypto is risky. So are AI agents, but this is the frontier. You could lose what you put in, but we are headed west. It's not for everyone, but we're glad you're with us on the bankless journey. Thanks a lot. New projects are coming online to the Mantle Layer 2 every single week. Why is this happening? Maybe it's because Mantle has been on the frontier of Layer 2 design architecture since it first started building Mantle DA, powered by technology from EigenDA. Maybe it's because users are coming onto the Mantle Layer 2 to capture some of the highest. yields available in Defi and to automatically receive the points and tokens being accrued by the $3 billion Mantle Treasury in the Mantle reward station. Maybe it's because the Mantle team is one of the most helpful teams to build with giving you grants, liquidity support, and venture partners to help bootstrap your Mantle application. Maybe it's all of these reasons all put together. So if you're a dev and you want to build on one of the best foundations in crypto or your user looking to
Starting point is 01:16:21 claim some ownership on Mantle's Defi apps, click the link in the show notes to getting started with Are you looking to pay your team in stable coins or set up token grants with ease? Traditional payroll providers aren't designed for crypto. Handling tax withholdings, government reporting, and local filings for tokens can be a nightmare. With Toku, everything about global token compensation gets simpler. Whether it's paying full-time employees in stable coins, managing token grant administration, or even navigating the TGEE process, token covers over 100 countries on one seamless platform. Integrate Toku with your current payroll system or choose a fully managed service.
Starting point is 01:16:55 Either way, Toku simplifies every part of token compensation. However you work, Toku works for you. No guesswork, no missed deadlines, no complexity. Visit Toku.com. That's toku.com to talk with Toku today. Are you ready to take control over your entire financial life? Crypto, defy, and fiat, all in one place? Meet Ayyield, the free financial planning tool built for crypto natives.
Starting point is 01:17:15 Unlike traditional portfolio trackers that just show you the value of your assets, eye yield goes deeper. It consolidates everything, assets, debt, income, and expenses, offering you a complete financial picture across 16,000 tokens, 40 defy-fi protocols, and all fiat currencies. With real-time defyield tracking for platforms like Ave, Athena, Eigenlayer, and Uniswap, I-Yield ensures that you're always on top of your staking rewards, investments, and cash flow. And the best part, it's 100% free with no ads and it's secure. No personal data, no ID requirements, no compromises.
Starting point is 01:17:44 So head over to iYield.com to sign up today and get the guesswork out of financial planning. Radically simple ideas always tend to catch on. That's why Cartese did the hard work of putting Linux on chain, so that building DAPs can be radically simple by using Python or JavaScript and their suite of libraries. Simple, like not rebuilding the basics from scratch. Simple, like dedicated scalable compute for your DAP. Simple, like building DAPs however you want. Web3 should be simple, too, like bread and butter. Carty brings radically simple solutions to Ethereum, so developers can do what they do best.
Starting point is 01:18:16 Build. Go ahead and discover a flexible, modular stack on Cartese and build your most powerful, ambitious project yet. Visit cartesi.io slash simple and simplify your blockchain journey and start building today.

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.