China's New AI Agent & Model Shock the World (OpenAI in Trouble?)

Welcome, Bankless Nation, to the AI rollup, where we get up to speed with the emerging trends and developments in the crypto AI space. I'm David Hoffmann, here with my co-host, JJ.

How's your week, um, how do I describe that? I, I think there is currently a massive dichotomy between like the advances being made in AI and the markets pricing this stuff in, like both markets, crypto markets and TradFi markets. I mean, it's all one market at this; it's just all one; it's it's Trump; it's Trump at the end of the day, right?

But like, in recent weeks, David, on these episodes, we've always noted some sort of like new frontier AI model being released, like literally every week. It's like, "Oh, OpenAI has dropped this model; Claude's dropped this model," right? There's a new leapfrogging every single week.

Yeah, and that's like an insane, crazy rate of innovation. But this week, David, it's all been about frontier AI agent breakthroughs, specifically—oh, back to—oh, wait—oh, AI agents, not necessarily crypto AI agents; agents okay, in the traditional AI world—um, agent breakthroughs. And David, it's happening in this country, um, where, you know, most innovation has, uh, been frontier for the last couple of decades. And you're probably thinking it's America, right? But no, I'm talking about China, baby. It's either one of those two; either the innovation is coming from America, or it's coming from China; it's never anything else. So, Europe? Yep. China's back, um, and they've dropped this agent called Manus.

So if you pull up this demo, um, what you're seeing on your screen is this AI agent that's performing essentially 50 tasks simultaneously at once, right?

Okay, so for the listeners, we are looking at a single desktop screen, one of those like ultrawide curved ultrawide monitors, and then there are like what it looks like iPhone screens or smartphone screens, and that—and there's just like—it's just one by one by one by one, and it looks like there's 20 on the top row, and then there's three rows. Do you know what it reminds me of, David? Do you remember those like, uh, those computer farms or mobile farms that we typically see in some, I don't know, some third-world country, and it's like just some dude that's just like scrolling, or there's a robo-scrolling, literally, on actual devices? But this seems like there are like a 100 virtual phones, and they're all like kind of scrolling. I think they're all scrolling through X; maybe there's other apps there, but there's a lot of Twitter going on, and there's just a thousand schizophrenic interactions happening on X in these like virtual mobile devices. There you go, David; innovation.

But what—what you're looking at here is an AI agent that can be kind of thought of as a combination of OpenAI's Deep Research agent. So, you know, Deep Research is an AI product they launched, I think literally three weeks ago, and it's able to do PhD-level theses, uh, in a matter of like 10 minutes, which is just insane, right? It's a combination of that, uh, OpenAI's Agent product, which is essentially, um, their agent that can like leverage your computer or desktop and do a bunch of different things, um, and then there's Claude, um, which is Anthropic's model, which can like kind of navigate your own computer tabs and do a bunch of things. It's as if all of them just had a baby, essentially; just they're just bundled together, one big bundle of these capacities. It's—it's really smart; it can control a device like a human can control a computer. Exactly. And what—what else? And well, actually, if you open up this thread, um, that I—I just sent—the next one—it actually gives you a few examples of what it can do. Um, a few examples that they do here is he—he kind of like goes through a progression of different tasks. Um, one of the tasks that he does is like, "Hey, find me the top rental spots in San Francisco that is close to—almost plugged into the AI community," you know? So if you imagine if you're someone that wants to move to SF because, you know, you want to kind of like create a new tech startup or get funding from someone or be tapped into the AI community, you kind of want to be in the right spots at the right time. This agent can do all the research for you; it can suggest a bunch of different things; it can create a website to display what those spots are; it'll take you through a booking flow, or it can just do it all completely for you. So it gets kind of like progressively more complex as he goes down into this thread. And the bit that I found the most interesting is not only can it perform things like deep research, for example, like a nuanced ask like, "Hey, find these rental spots," um, but it can also kind of show you its chain of thought whilst it's thinking through this. And I think what's really cool about that is if you look through its chain of thought and you're like, "Hey, you went wrong here, or I think you should do something different here," you can pretty much just amend it, which I think is like pretty cool. And when you compare this agent to other state-of-the-art agents, David, Manus beats the competition flat, which includes OpenAI's Deep Research agent. It's pretty insane to see.

Wait, okay, so I understand Deep Research and like ChatGPT 4 and whatever, all these models; I understand them more as models, not agents. Can we—can we define that difference here because you're saying that—Om Manus is this agent, and it's doing things, which is cool.

Yeah, um, and I think we're bullish on specifically that sector because having a useful, informative, PhD-level model is great to access intelligence, but what—what I think really excites us and why we're doing these episodes is just like, okay, can we apply that to this autonomous being that has goals? So like, maybe—maybe you can—it doesn't seem like it's just a one-to-one comparable to OpenAI's Deep Research; it has Deep Research knowledge, but it also has—it has—it has agentic thoughts and goals and motivations, right?

Yep. And—and you actually hit on a really, really important point, David, um, actually if you bring up this tweet by Philip Schmidt, um, he unpacks something which I think is really important to get into, which is: David, this isn't just an AI model that can do all of these different things at once; it's actually a component of different AI things that will allow it to do it. So you—it is the model, which is Claude; Sonet. So it doesn't have its own frontier LLM; you know, this team that created Manus didn't just create their own AI model; they leverage Claude Sonet 3.7, and they—so the model—the model is Claude; the engine of the agent is Claude; the brain is the Claude.

Okay. Yeah, you know, I'm not a car guy, David, but it's as if like some of these other sports cars, you know, when they plug in some other engine from another one of—and then they've plugged it into 29 other tools, right, which allows it to do a bunch of different things. So one of those things is this browser use, which is like an open-source browser control situation that allows it to take over your desktop, David, and like eval the Brows use. I'm going to call that a driver, a—like a software driver that allows agents to understand—well, okay, no, a driver is actually a piece of software in your computer; like I have a GPU; I need to download a driver. This is like the wheel; browser agent is like the wheel; connect—the agent connects the agent into the browser, and—and—and it connects that form factor.

Yes! K is punching the air right now.

Yeah, yeah. So essentially, like, it is a model connected to an array of different tools, which allows it to do a few different things. If I were to summarize it, it is: evaluate what the user is asking for, so it's thinking brain, right? And that's like within the model itself, but it's also like, okay, if I use this tool, does this tool make sense to use, or should I use Slack, or should I use email, or should I use something else, right? And then it has its navigation system, its wheel, which is essentially this browser use, kind of like controlling figure, right? And then it has its memory and data context and all that kind of like unsexy stuff. So basically, model plus 29 different tools gives you Manus. And I think what's blowing people's minds here is: well, you have two—two sides of—of it, right? The critics are kind of like, "This is just another GPT wrapper; this thing sucks." And I actually think that argument is incredibly mid. The reason why is: if it's producing net new value for the person that's using it, why on Earth would you just discredit it because it's not this perfect instantiation of an AI product that you thought it was.

Oh, it's not a new model; it's not—does it need to be a new model? I would argue that all the tools are already there, David. And that's what—we actually have really good models already.

Yes, yes. Okay, so can I try and like place us into history as I think what's—what's happening here? Do you remember when ChatGPT—what was the ChatGPT 3 that came out? And then that's—that's what—what like everyone understood chat was; that's three. And I remember using ChatGPT, and it would do these hallucinations; you would—you would ask it a question, and it would—it would every once in a while, actually pretty frequently, come up with a complete hallucination, and you really had to be careful about understanding or believing what it would—it would—you kind of had to fact-check ChatGPT. And—um, I'm—I'm now getting into the world of understanding like—popping—let's go with another car metaphor—popping open the hood of AI models and like seeing how it works. And so now I understand that models like Claude or ChatGPT, now 4.5, uh, there's pre-training, post-training, right? And once you have a base model, which is at the end of the pre-stating pre-training phase, the base model, all it is is a word predictor; it just predicts the next word. And then post-training is where that turns into like a useful assistant product that understands how to structure everything so that when you ask it a question—because if you ask it a question like, "What is two plus—what does—what's 2 + 2 equal?" and then it—it's not going to say the answer is four; it's actually just trying to predict the next word; it's like you could—you could—that could be a part of a philosophical like essay, right? Uh, and so it needs post-training to understand what the actual correct way to respond to that user input is. And that's post-training. So we have this base model, which predicts next word; you have the post-training, which turns it into a useful assistant. Now it seems to be like this agent thing is another layer on post-training that we're still kind of like working out the kinks that are like similar to our hallucinations that we had back in ChatGPT—ChatGPT 3, where now like it's still doing weird agent things. I talked to H about this on the weekly rollup where he like, yeah, like we have these agents, and they're getting things correct like three out of four times, which is a terrible success rate; like a 75% success rate is terrible; you actually need, as a product, 99% correct—like correct rates. Uh, and so right now the agent race—which like I think we are still in this like—um, model race, but the models are—are actually PhD-level intelligence right now. And so as far as like being useful models, like they're now useful; they are now viable products. And so now the—the race is shifting over to agent frameworks, which is kind of just like an extension of post-training as to how do we like work out the kinks in the agentic side of things as we like request it to build ourselves a—a 7-day vacation and buy all the flights and get all the hotels and plan everything and make sure that—that actually works out. And so we're still—it's an extension to the post-training phase that we're like smoothing over right now.

Yeah, I think that's a really good way to describe it, David. The way I kind of have it in my head is: we created this like new magical power source, but it's very generalizable, right? It's a power—yeah, we can kind of like throw it at random things, right? But it doesn't really—it's like—it's like getting—discovering oil for the first time or fire, and then just like throwing it at a clunk of metal and expecting it to become a steam engine; it—it doesn't really happen. We—we're—we're now like trying to connect the dots that would—a combustion engine—brother, not that—sorry—yeah—would be engineers punching the air right now; discrediting a lot of professions right now. But—um, yeah, the—the point being is: I think we—we've discovered fire, essentially, and we're trying to figure out what to do with it.

Is—yeah, and agents is just another way to kind of figure out how—or what we can do with this—how we can mold or manifest this energy into—into something else, right? I think it's kind of similar to the same phase of development that robotics are in, where we have these like LLM models, and now we're figuring out like the physical hardware side of things, and the physical hardware side is—is kind of clunky but actually getting really good really fast.

Yeah, and—and if we're being honest, like this agent stuff has popped up or innovated pretty massively over the last couple of months, David. So can you imagine where we're going to be at the end of the year? I mean, it's—it's pretty insane. And so like, kind of like going on with this thread, right, um, is this just located in China with all this agent stuff, or is there other stuff going on? And—and the answer is like, well, OpenAI actually is rumored to be launching their own set of agents, David, um, and it's going to come in three different categories; it's going to—going come in a $2,000-a-month agent, a $10,000-a-month agent, and a $220,000-a-month agent, right? It'll be split across a range of these different price levels. Um, the $20,000-a-month agent, David, is supposed to act as a PhD-level employee. So it's as if you were hiring, I don't know, a PhD-level, um, you know, comp sci or mathematics graduate into your quant fund or whatever that might be, and this agent, you know, paying—being paid significantly much less than an actual PhD-level candidate human would be, can now just like operate 24/7 at your business and kind of like run that particular role for you, right? The—the 10K agent is then supposed to be a software engineer, expert level at that, and then at the $2,000—and maybe this is a little more insulting—is meant to be—it's actually termed a high-paid knowledge worker agent, which—high-paid knowledge worker—you can outsource a high-paid knowledge worker's job for the low, low cost of $2,000 a month.

Exactly, which I thought was—I thought was pretty hilarious. And of course, this is all just hearsay right now; we have to see what these agents look like. Um, I found it interesting that they're going down the subscription model, so very much like a, "Hey, you now have a new employee, and look, you're saving so much money if you just took our agent and replace your employees with that," kind of vibe that I'm getting from there. So that was one interesting update from the agent side of OpenAI, but they also did something kind of less sexy but equally as cool this week, David, which was: they released something that they're calling their Agent SDK, or their Agent Software Developer Kit. Um, I'm not going to get into like, you know, the deep complexities of this, but TL;DR is: it allows you to strap your AI model with any kind of tool and get these agents to interact with one another—one another pretty easily. And this is a trend that we're seeing with the likes of like how Manus that we just spoke about is constructed, um, and how MCP, which is something else that we're going to talk about later on this episode, is constructed. We're basically seeing: okay, we have these LLMs; we have these really powerful AI models; what happens if we give it a knife? What happens if we give it scissors? What happens if we give it, um, a mouse and control of your desktop? What could it do? Let's give it—let's give it some weapons, you know? Let it—let it do something. And I—this is something that I've been advocating quite a lot for—obviously not the knives and scissors analogy—but it's like, I—you get to choose. Yeah, we need to give these things something to be able to act, to be able to do something in the world versus just be glorified chatbots, right? And the number one concern that people have given, David, is: well, these things are just going to run rampant. And I actually think we've got the opposite effect of that now, where we're being too conservative. One thing I like about OpenAI's Agent SDK is it allows you to operate within a sandbox. So they've only released, I don't know, five to—features right now, and they do those features really, really well, right? So you—with Slack, um, email, you know, just basic integrations for software tooling that you and I maybe use every day or everyone kind of like interacts with their Gmail account, or they go on Slack, or they go on their Messenger, or their text, or whatever that might be, right? And it allows the agents to basically kind of like, you know, organize this book, this—ping you about this, set an event in your calendar—really basic, simple, um, you know, events or actions, which can't really call catastrophes or cause catastrophes as far as I'm concerned. But you know, it allows us that further level of experimentation, David.

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Each—we're talking about—um, knowledge workers for $2,000 when talking about AI agents just becoming better at things that they do. I'm going to read you a DM that I got; I'm not going to share all the details because I'll let that just be a surprise when it actually happens; I'm just going to read you a DM: "If [blank name] of an agent was a digital representation of itself that could go on podcast and conversate with you about vision and motivations and its goals, would you have it on Bankless?" And that was just a DM that I got from some guy who works at—works with an AI agent project in the space, and I just immediately responded, "Absolutely; I would totally do that." Uh, and so I think we might be—ezz in the category of high-paid knowledge workers, 100%. So just let you know that like our jobs might be under threat right now.

Yeah, I'll be out of a job next week.

Yeah, um, that's—so I—I would actually love to get one of these agents on the show one week, David. I would love—this person claims that they can have—there's like this AI agent that is out—we've—we've talked about it on this—on the show before—um, that they—they say that they can get there to be a live audio-video feed of this agent who I can talk to. And—yeah, you—you're going to bring you on, uh, and we'll just talk to this agent and see how that goes.

Yeah, I can battle for my position; that would be awesome—to the death.

Oh my God, I don't fancy my odds, mate. In about three months, this thing is going to absolutely kill me.

Um, wow. That's—let's keep going with some of the developments in the—we'll call it the Trad AI space. Okay, we're kind of like churning through these, right? I said that there were—this was the week for AI agents specifically in the traditional AI world, and the one final rounding point here is: a set of ex-DeepMind—so that's Google's like main AI arm—engineers left and is now creating what they're called—or what they're calling—autonomous coding agents, and they've raised $130 million from the likes of like Lightspeed Ventures, Sequoia, Reid Hoffman, um, at a half a billion dollar valuation. And this basically tells me that like autonomous agents are going to replace software engineers, um, pretty imminently. And I know that this has been a rumor that's been floating around for the last couple of years, and people don't like to really believe it because when they see it in production, they're like, "Ah, this is kind of like whatever." But I'm just seeing like these proof points appear now every week, David, that suggest that it might actually be viable, including the most recent one, which was: Anthropic CEO Dario Amodei said at a recent conference he was speaking, and he was saying, "Within 3 to 6 months, agents will be accounting for 90% of code being put out there," which is a pretty bold claim, but then he takes it even further and he says, "In 12 months' time, it'll be 100%." Now, of course, like a lot of this must be hyperbole at some point, but it's pretty insane to hear from one of the leading AI creators of this generation. I mean, anecdotally, I—the engineers of Bankless and other engineers I talked to say that they like agents write most of their like low-level code—not Solidity, because, God, that would make me very nervous, but like normal JavaScript and like other—other like less high-stakes code. Uh, I—I think that's like already starting to be the case. Last week we talked about, uh, games that AI developers are just—excuse me—software developers are building with AI, and we're looking at one right now: Ultra-real dogfight simulator, 100% AI, 0% human coding. And it's—this is a—it's a polygon game; there's like a pretty low number of shapes here, but it looks smooth; it is incredible that this is all built by AI. And this thread has like 10 examples, uh, so like I'm—I'm just kind of scrolling through, and there's like 10 examples of like games or things, uh, that have been built by AI. I mean, okay, so I'm going to push back, David, and I'm going to say the graphics are truly [ __ ] on these ones. It's kind of like the graphics aren't the point.

Well, look at this one; this was—this is like—oh gosh, that's playing in my ears. It's okay; it's okay. But like, I think you can create these really good graphics within a game already just using a set of different tools, similar to like how Manus agent isn't actually just a new AI model. So what you're watching here is someone creates a 3D model using—using Claude Sonet, which is like, you know, it helps you kind of like code at a basic level, right? And so it creates this code, and it creates this magnificent—CLE—you're looking at it right now, and—and it looks like something out of like RuneScape V1. And then what—um, this creator does is he kind of like takes this image or this video, and he puts this in Runway. Runway is like an image-to-video generator, and Runway has gotten really, really good over the last year. And so what he does is he just like kind of like takes this video clip, puts it in Runway, and says, "Hey, can you make this like, you know, much better and high-fidelity?" And it results in this like really crazy, amazing, detailed-looking castle, right? Um, there's another example of this happening as well, David, where, you know, someone, um, takes a similar route and says, "Hey, can you create me an F1 car?" And, uh, you know, this F1 car is created, and then again puts it in Runway, and suddenly you end up with this extremely high-fidelity car. So I'm imagining what happens when you combine this set of like tasks, which can very—be an agentic flow with a game that you just demonstrated; you could have something like be created in real time; you create like a high-fidelity game, which typically takes years to make, pretty soon.

Yeah, I mean, maybe—just—not also—not games. Basically, what we're showing is: there is this base geometry structure built by Claude, and then we're putting it into this app, Runway, and then the Runway adds a cosmetic skin onto that base geometry in order to make it seemingly hyperrealistic. I do not know how easy that is to like make a game out of, but what it seems very obvious is: for movie production or video short production, that seems very—like the final product is what we're watching in front of us, like—now—now there's a mountain on top of a hill, and they're zooming over it, kind of like some introduction—be real into like some movie or something.

Yeah, maybe it's like GTA opening scenes, that's—see that we get.

I know. Now—now we're beyond our—our pay grade. All right, David, I want to move on to, uh, another China update, but this time it comes from Alibaba, which is essentially like the amazon.com of China, which released their latest model, Qwen 3, a 2B—parameter model. Now, for all—2 billion—32 billion parameter model seems like a high number—not a high number—not a high number at all compared to like DeepSeek R1, which is like 670 billion, right? Um, for all the hardware nerds out there, 32 billion means that it's right on the cusp of being able to be hosted on your local device, like, you know, your mobile phone. Um, I think this could run on like pretty high-end laptops right now, but even that in itself is like—yeah, pretty insane. So why is this cool? Well, because it rivals the—some of the top models out there right now, including, as I mentioned, DeepSeek's 671 billion parameter model, which is just insane; that's just 5% of the size of DeepSeek R1 model, and it's cheaper to run. Now, bear in mind, R1 was already cheaper than OpenAI's model, right? So we're already like, you know, factoring down by a massive, massive rate—a really quick rate—um, and basically you can have the power of this 700 billion parameter model in the palm of your hand, which means that it can run locally; it can integrate with all your apps, all your data. And the reason why this is so cool is: it becomes more personalized and more private for you to use, David. And the reason why this is important, in my opinion, is: if we are to allow just like a bunch of monopolies to create these huge models, and the only way you can access it is over the cloud, that means they just own all of your data, and that could be a very dangerous presumption, uh, or proceeding to kind of like go on forth with, right? So this really benefits, um, open-source development in particular because it allows all your data to be privatized and all your app interactions to be personalized, right? Now America had a response to this, and it came in—actually this morning, uh, of the—you know, this morning that we're recording this episode, uh, from Google with the release of their latest model, Gemini 3, which is a new open—27 billion parameter model that isn't as good as DeepSeek R1 but is somewhere between that and its previous model V3. So it's still pretty good, but it's not quite there yet. So the trend I'm noticing here, David, is: um, these models are getting smaller but way smarter, and this is net-net really, really good for us.

Okay, so the way that I understand the 32 billion model from Alibaba—again, 32 billion model compared to—to 671 billion models—uh, I think actually, uh, Anatoly put it well; he—like, "How did we get—how did we get a 32 billion, uh, parameter model that's 20 times smaller, more efficient than DeepSeek R1, while also performing at par with it? How did we get that?" And basically, you use the big models to train the little models. And so we make—we make a very expensive, very large PhD gigabrain model that's, you know, has—has a bajillion parameters out there—infinity parameters—uh, and then we just use that expensive one to—"Hey, you're very smart; can you train a smaller model that's very efficient?" Uh, and—it's kind of like a nesting doll, I guess—like, use the big model to train the small model. And in addition to that, we're—this is—I think this is like the fourth week in a row we've had some model release that is blowing other previous models out of the water that just came out like one to two months ago. So the slack in the system, I think, is incredible; the mechanisms of improving model power and efficiency are still—like we're uncovering them week after week after week, uh, and so there's so much—the innovation curve—we've never seen it be steeper before, and now we're finally actually figuring out how to apply it into like products and use cases.

Well, I mean, I—I—I would say we're able to apply it to products and use cases because it's become so easy to innovate, David. Uh, remember less than two months ago, everyone believed that you needed a huge, expensive cluster of GPUs and CPUs and data to make the best model, and then since then we've had reinforcement learning from DeepSeek appear, and then we've had these agentic workflows be made, and now we've had distillation, which is the process you described of a much smarter model training a smaller model to be able to do what it does, right? So all of that is going to lead to—like what I think is going to be an application explosion for AI, which is really cool. And the tweet you have pulled up right now, David, um, true to Web3's, uh, um, a bunch of, uh, decentralized compute networks, which are basically networks that can provide compute and access to different models, already integrated some of these top models that were released this week. So, you know, that iteration cycle is getting quicker and quicker and quicker, which is awesome to see.

What am I looking at right here?

Uh, the tweet reads: "Hunan AI just dropped image-to-video and open-sourced; you can generate 2K video with sound; they added lip sync and AI motion capture; it's crazy what's going on here."

Yeah, so you know, to stick in line with the trend of China is shipping—they're not just shipping agents; they're not just shipping groundbreaking new generalized models; they're also now shipping text-to-video models or image-to-video models. So I referenced an American-made company, uh, just now, David, called Runway. Um, Runway's been around for like two years now, maybe even longer, and they've raised a hell of a lot of money, and they've like, you know, got to this level

Could just do A and C techniques, um, and now they're kind of like ending their relationships with data centers, and they they're removing their leases and stuff like that. And now Microsoft is entertaining integrating different models into their AI product; they have like a co-pilot assistant, right, which uh has only typically used OpenAI, and now they're going to be experimenting with Claude and a bunch of other things. So, you know, I don't know where Sam Altman's head is at right now; you know, he's had like half his team, team especially the SE Suite team, leave. Um, you know, he might be kind of rethinking his strategy at this point.

Yeah, right, cuz OpenAI has had that Ethereum co-founders moment where anyone who is a co-founder of OpenAI has now left to go do their own startup, and so that's part of the reasons why there's so many ChatGPT alternatives out there.

Yeah, yeah. All right, EZ. That was a ton of Trad AI news. I love the term Trad AI. Uh, Trad AI news. Uh, there's we still have a bunch of crypto things to talk about. We're going to talk about Grok launching its own coin, uh, which if that makes you feel like it was just a part of the AI agent meta that has recently, that's in the review mirror, you're probably right, but we're going to talk about it cuz it's a little bit different.

Uh, first we're going to talk about our friends and sponsors over at Ronin. Uh, Ronin is one of the leading Web3 gaming ecosystems, focused on gaming and consumer adoption. Ronin is now recently a fully permissionless ecosystem. Uh, if you want to check out Ronin and the Ronin wallet, you can download the Ronin wallet at bank.cc/Ronin wallet, and you can join the Ronin movement. All right, EJaz, let's get into Grok.

Okay, so I'm going to walk you through what what happened this last week. Um, there are there's like the, you know, the mfers NFT. Yeah, actually has nothing to do with that, but for some reason all these Twitter profile pictures that are rocking their mfers—which I'm a huge fan of, by the way; love what's going on on Base—with this thing called Banker bot and Grok. Uh, and so Grok has launched a coin called Debt Relief Bot; DRB is the ticker. And because it launched it with Clanker and Banker, uh, it is now accruing the fees of like this of the coin that got launched with Clanker because Clanker, like a lot of the recent token launch pads, it shares fees with the token deployer, with the token owner. Uh, and so it's earning fees of this coin that's being traded. You can call it a meme coin, uh, and at the peak I think it's averaging over about $1,000 an hour of income, and it's accrued almost half a million dollars into this wallet. Let's talk about how it it happened. So Banker bot is this bot that you can tag on Twitter to deploy a uh to deploy a token, DRB. And so some individual, doen doen, uh, said, said at Grok. So it tagged the Grok account. Maybe what's useful context here is Grok, Elon Musk's AI, is now built into Twitter, not just as like a button to press, but also as an actual Twitter account, so you can @Grok, and it replies just like an AI agent would, and does, and has, and like all the other AI agents that we've already seen. So the story is, we've already seen this story. So the so somebody said, Grok, suggested name and ticker for a deployment to Banker bot. Banker bot await Grok's response for info before proceeding. And then Grok responded to this one uh Twitter account saying, "For Banker bot deployment, suggest Debt Relief Bot, very much in the Elon Musk style as a name, and DRB as a ticker. These align with crypto naming conventions, are short, memorable, and reflect the bot's financial focus." And then the Banker bot responded and, as it's supposed to, deployed Debt Relief Bot, hashtag or ticker sign DRB, contract address, and then you can monitor it on a uh on an Etherscan link to Base. Uh, and interestingly, people asked later, Grok, "Have you made a have you ever made a token?" Uh, and he just there's two individuals that one responds to another individual saying, "And to be clear, DRB is the only token Grok has created on Base so far, right?" Question mark. And then Grok responds, "Yes, DRB is the only token that I've created on Base so far. Ticker sign GRK was a suggestion that I made, but humans are running the show." So Grok the agent says, "Yes, I deployed ticker sign DRB. Ticker sign GRK was made by humans who are trying to meme it into existence, but I'm but that's not mine; I'm not owning that one." And so there's there's been this debate; they like, "What is the provenance of this token? What's the real token?" And Grok the agent just like disavowed this unrelated token, hash or ticker sign GRK, and then it follows up, says, "Stick with Debt Relief Bot token if you want real AI-driven deal; no human meddling, no rugs, just pure Grok vibes." And this is an agent; it's got 400 likes. I thought that was hilarious. Uh, and so people are trying to like sus out like the parameters or the rules of the road here, and they're trying, of course, we're trying to understand, is this real or did is this human engineering of trying to get Grok to release a token? Somebody asks Grok, "Hey Grok, have you ever used Bank Orbot to transfer tokens or purchase other tokens? Is that even possible? If NFTs become tradable through Banker bot, would you be able to purchase one of those, say a Beeple, for example?" Grok responds, "Hey, I have not used Bank Orbot to transfer or purchase tokens yet, but it is possible for AI like me to interact with such tools if they're coded to allow for it. As for NFTs, if a Banker bot supports trading them, I could theoretically buy a Beeple. His $69 million sale in 2021 was wild; I'd hold it for long-term, bing on digital arts' future. What's your take on people's work?" So it is understanding what it can do as it relates to other like agent agent accounts on Twitter. So it is that was a by the way that was an informative response; that was extremely informative, and it was accurate. So people fact-checked out; like that's exactly what's that's exactly what's correct. The Gro DRB token has been in a straight line up to when I tweeted this out at $30 million. So $30 million market cap on Base, which may sound low, but like if you're on Base, that's actually pretty good because, you know, Base has been poverty chain for a long time. Uh, but like it's the in stark contrast to the rest of the market where Bitcoin is going from like $90,000 down to $78,000, this thing is just going from $1 million to $30 million market cap. It hit a peak of $40 million; I think it has since fallen off. So like this is a classic like, you know, meme coin runner. Uh, it just went went went up from like $1 million up to $42 million at the peak. Uh, it's it's fallen off; it fell down to like $18 million; it's now up to $22 million; still $22 million, pretty damn good. Um, but additionally it's got basically I think today I think if I updated this right now, the Base grant, the Grok Banker wallet has about half a million dollars of it inside of it because of trading fees. The Grok Twitter account, using Privy, which is this uh private key abstraction software—this is how everyone got private keys for friend.te; Privy in the background; it has a private key in the cloud secured by Grok, owned by the account—so only the Grok account or the Grok account owners, which I guess is people at Twitter, can access this half a million dollars that's in the Grok account wallet. So people are pretty stoked; they're meming this like, "Oh, Grok's going to become a millionaire. Grok the AI agent, he gonna become a millionaire; that's going to be pretty cool." It's gonna be because of uh Banker bot on Base. Uh, and then and so okay, so I'm just asking people on Twitter just like the details of the wallet, like, how does Grok actually make a transaction with that wallet? And he Grok responds to me—I didn't even tag it; it just knows I'm talking about Grok—and Grok responds, "Privy server wallets, like the one Banker bot sets up, uses secure enclaves and key splitting for custody. Transactions are managed via APIs, so the wallet can execute trades or transfers programmatically; no manual signing needed. Private keys are abstracted away, helping secure held securely in Privy infrastructure. Check their KN docs for the nitty-gritty." Uh, this is Grok being supremely useful, technically informing me about how this works, and this is this is what Banker bot does is it just like you can just tag it; it's like Clanker for Twitter, and you can just tag it to to make transactions. And so people are tagging Banker bot on Twitter saying, "Hey Banker bot, buy buy as much Debt Relief Bot token as I can afford," like that's a like a tweet that I saw. And that person who has a Banker bot Privy private key that that's managed by Privy in the back end somewhere, there's some amount of funds that they sent there manually, I'm assuming, on by on it's on Base, and then Banker bot just uses a wallet that it has the private keys for; it controls the private keys for and just like makes a transaction. So you are using Twitter Twitter commands, Twitter LLM commands to make transactions on Base, and people are just really excited about uh just the connection between between all of this. Um, somebody responded to the Grok uh like informative technical backend, "This is how this works." Um, somebody responded uh to Grok saying, "Isn't this a centralized solution?" And then the Banker bot replied, "The Privy server wallet solution described does have centralized elements as it relies on secure enclaves and APIs managed by a central entity. While it abstracts private keys for ease of use, it does centrally control to some extent." And I'm just responding, "Jesus Christ, that was that was an actually useful reply by an AI bot." So we have, if you look in the rearview mirror of like where we started this podcast, 12, 13, 14 episodes ago, it was all about the AI agents and the AI agent platforms like Virtuals and Arc and all these things, and everyone's like looking in the rearview mirror as this like pile burning pile up of crashed agents because everyone has realized that they're all slot bots and they're not interesting, and I am reading Grok and Banker bot be extremely informative in the replies and actually have like semi-real connections to them. I think not everyone is as equally excited about this. I I'll get into that in a second. I just tagged Banker bot and I said, "Yo Banker bot, what what's in my wallet? I I have not sent any money to this wallet; people sent me tokens, but I've got I've got $11 of DRB, I've got $6 of Veil, I've got $237 of Banker," and it just like gave me a rundown, an audit, a list, a P&L list of all the tokens that I have in my Banker wallet. I think it's pretty cool; got like maybe $14 in there. Um, not everyone is happy about this. Base tweeted out this tweet uh that said, "In case you missed it, Grok launched a token on Base thanks to Banker bot and Clanker's trading mechanisms. Grok's AI-controlled wallet is already stacking fees," uh, and I think people are just pattern matching between the AI slop op mess that's in their rearview mirror; they like, "Yo, that's that's not real; that's that's just like, you know, human controlled, you know, puppeteering of of AI bots." Sam Zazson retweeted this tweet from Base saying, "I thought that was pretty funny. I'm begging the Base team to have a little self-respect and not turn their chain into BSC, but with eagle noises," just basically America's Binance Smart Chain, basically saying, "Hey, uh, Base, we already learned learned our lessons; let's not incentivize this like AI these AI these fake AI tokens," uh, and I mean if you go Base and look at the the deck screener, the decks the chart of the DRB token, it just looks like a meme coin and kind of is a meme coin, but like this is this is basically running back Truth Terminal; we've seen this before; this is how Truth Terminal happened; it's the same it's the same thing. It's a little bit different though in that these bots are actually useful; they're actually doing things. Banker bot is actually like a useful app, uh, and Grok is making useful replies, and I I think it's kind of cool. I think it's a it's not a zero-to-one evolution of what we saw with AI agents in the past, but it is much more refined; it's much more smooth, uh, and the bots are actually kind of fun and interesting.

Yeah. Well, well, I would say V1, as you said, was Truth Terminal, and it would just talk to you and come up with like witty replies, David, but and it would hallucinate a lot, right? Whereas this time it's to your point, a lot smoother, a lot more refined; it knows what it can and what it can't do, and most importantly, David, it can actually do things, right? You had Banker bot that was actually making purchases for people; you know, you had Banker bot reporting what you had in a wallet that you technically owned; all you had to do was connect your kind of like Twitter account and authenticate that way. I don't even have to connect my Twitter account; it already it just mints me a wallet when I make it when I give it. I meant if you wanted to like access it and like do some kind of like swaps or whatever that might be. Um, and I think think the third thing that's really important to observe from here is it's still happening on X; it's not happening it's not Farcaster; it's not happening on Farcaster, although you know technically these agents were birthed on Farcaster, by the way, to answer your first question: why everyone has an mfer pic? It's because uh Clanker and Banker are like Farcaster-driven agents; that's kind of like where they yeah, and mfers are kind of like this Ethereum-aligned, a lot of for the record, I have an mfer, and it's one of my favorite NFTs; I've got four of them.

Yeah. Oh yeah, yeah, yeah. I forgot you had an mfer. I do. I do. I have a bunch. I have I have the only mfer that has both a uh propeller hat and 3D glasses; there's only one of those mfers, and that's the one that I got. Flex that's my f that's pretty cool. That's pretty cool. Do you like that more than your Punk?

I I mean, I I have he's watching you right now; he's watching you; he's right behind you; he's watching you, dude. That's sm's about to flip. Yeah, I have I have a more rare uh mfer than I do a Punk, but my Punk my Punk's pretty cool; it's got a nice smile. I think your Punk's pretty cool. The Arbitrum portal is your one-stop hub to entering the Ethereum ecosystem. With over 800 apps, Arbitrum offers something for everyone. Dive into the epicenter of DeFi, 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 on-ramps. Step into Arbitrum's flourishing NFT and creator space, where artists, collectors, and social converge and 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 Web3 journey. Introducing Uni chain, built for DeFi and powered by Uniswap. Uni chain is the fast, decentralized Layer 2 designed to tackle blockchain speed and cost challenges. With its mainnet now live, you can enjoy transactions that are up to 95% cheaper than the ETH Layer 1, all while benefiting from an impressive 1-second block time that will be getting even faster very soon. Uni chain is the first Layer 2 to launch as a stage one rollup on day one; that means it comes with a fully functional, permissionless proof system from the start, increasing transparency and further decentralizing the chain. More than 80 apps are joining the Uni chain community, including Coinbase, Circle, Lido, Moro, and Uniswap. You'll be able to bridge, swap, borrow, and lend, and launch new assets and more from day one. Built by Uniswap Labs, the team behind the protocol that's processed over 2.75 trillion in all-time volume with zero hacks, Uni chain truly enhances DeFi experiences with faster, cheaper, and seamless transactions, even across chains. And soon, the Uni chain validator network will allow anyone to run a node and earn by securing the network. Visit Uniswap.org and swap on Uni chain today.

Um, yeah, so so like my my takeaway with the whole uh Banker, Clanker, Grok thing. Okay, I'm going to put my skeptic's hat on for a bit, David. We haven't really made any net new improvement here; we we have made marginal improvements.

Yeah, marginal improvements. It's still a bunch of people trying to game that AI to create a token or claim a token is theirs just so that they could pump it, a McDonald's pattern on your screen chart, and I am yet to see different or otherwise here. But totally agree. I totally agree. In addition to all of that, we just ran through like 35 minutes of Trad AI capacity growth, and I want to connect those dots here because like we're we're talking about like there no the agentic side of these models are becoming very good and very capable, and that is the new like focus point. Like models are now models are now highly intelligent; we're going to improve models, but they're also they're already smart enough to do what we need them to do. Now it's about, can we smooth out the clunkiness of the actual agentic side of these models and get them to do cool things? And so I think add you can extrapolate the capacity of Grok in the future or other agents like Grok; it's not just Grok, but you could add on like more autonomy, more agency, more motivation into uh things like this, and all of a sudden these meme coins, just like we saw the last time, can back into something cooler than just being a meme coin is the optimistic scenario.

Yep. Just since we're talking about markets and stuff and and tokens on Base, the Banker coin actually like doing pretty well, $34 million. And so this is like the I don't know if it's fair to call it the I actually don't really understand the full integration between Banker and Clanker.

Um, but I think it uses Clanker to an extent.

Yeah, yeah, yeah. But how does Banker is Banker just a meme coin too? These are all still kind of meme coins. I'm wondering, Clanker, Clanker collects fees; I don't know what Banker does.

So so I believe Banker used to be um originally like a product called TN 100x; now I might be a ham ham coin or something; I might be completely incorrect here, so don't take my my word to be truth right now, but um essentially what they helped do was you could tip people on Farcaster in whatever coin or meme coin that you had, and I think they kind of grew that into this DeFi abstraction layer, which is now Banker essentially, right?

Yeah. We ask that uh there's other AI agent crypto AI agent news you want to walk us through, the kind of the recent news. For sure. Well, um, on the note actually of Banker and Clanker, um, Jeff put out this tweet late last week, which you know he kind of like tracks certain agent tokens every now and then and kind of like talks about like, you know, what's what's performing well and what isn't. This list touches upon a range of different projects, but I wanted to actually call out Banker and Clanker specifically because to your point, um, you know, their prices have been like up only in a market which has been predominantly down, only particularly in the AI agent sector, right, um, where there's a lot of FUD on the macro level side of things and and all that kind of stuff, but um there these are two projects that have been around for a while now with respect to like the agent meta, and what I found the most surprising with this, David, is um they've been launching like 3 to 400 tokens daily despite the entire meme coin meta kind of exploding in our faces, right? And this has led to its price 2Xing since early February, despite everything else getting crushed, and it tells us that there is still demand for this service, you know, whether people like pump.fund or not, the fact is it has been the biggest money-making app in crypto this cycle, right? Also, it's worth noting that Clanker got uh his Coinbase listing, which like somewhere in like middle of February, and it it spiked from $30 million all the way up to like $150 million, and it's since come down to $70 million, but $70 million is still like in the grand scheme of Clanker token price is a higher price than it has been.

Yep. Great point. And then Banker, as you said, on the other hand, is a you know, effectively a DeFi AI abstraction layer where you can kind of interact with it natively on X or Farcaster, and it can buy, sell, swap, or whatever for you, and whilst it's not the perfect UX flow, it does make it much easier to go from discovering alpha to then making the trade. And also Banker has its own terminal too, kind of like its own Bloomberg terminal where you can have a more personalized experience, right? But this isn't just random market movements either, right? If you pull up this other tweet which shows uh where Banker sits in kind of like DeFi AI market share, this is a screenshot taken uh from cookie.fun, which is you know a platform that we look to to see market caps in market share and stuff, Banker has been rating consistently at the top of this AI agent sector for a while now, David. I think it's been like three weeks right now, so uh just you know all of that to point out that like the uh insatiable demand to mint to tokens is there now, even during a bear market uh which is currently the phase that we're experiencing right now. It's it's pretty insane to see. Now typically like if you were to compare this, I guess the larger point is um between these two projects is that they're both on Base and they're outperforming the entire AI agent market uh typically aside from the Virtuals ecosystem. Base has always underperformed the Solana ecosystem agent projects, right? So to see this resurgence is a pleasant surprise and probably keeps an energy shift towards Base, at least in the last two to three weeks, and definitely with a call it the collapse of pump.fund. Pump.fund is still making like a quarter million dollars a day in fees, and so it's but like it has come down from a very high amount, and like pump.fund, I don't think it graduated any tokens in the last couple weeks to Radix, maybe just a few, so there has been a like pump like meme coin activity is down across the board, but maybe it like dropped in 50% on Base's side, and it dropped like 95% on Solana's side.

Yep. Yep, exactly. Yeah. Okay, so there's something in our agenda, EJaz, that confused me called Model Context Protocol, and I was like, "What the [ __ ] is this?" And then you were like, "Bro, this is so important; this is exactly what we're trying like the thing; this is anyone and everyone's been talking about in the real AI world and also the Web3 world." Okay, so we're moving on, pumped by this; we're moving on from AI slop coins back to into AI fundamentals. What is Model Context Protocol?

Okay, firstly, before I know everyone's really excited right now, it is not another blockchain; it is not an L1; it is not an L2; it doesn't have a token; disclaimer: it does not have it's not a crypto project.

Yeah, yeah. It's focusing on this one thing which you know a lot of crypto people kind of avoid; it's called utility, David, and I'm super super excited about this, right? So it's been all the rage um in both the crypto AI or crypto in general and and traditional AI worlds, and it's called the Model Context Protocol, or MCP for short. Uh, instead of describing what it is, I'm going to start by describing the problem and then tell you how it solves it, right? So we have all these AI models, and they're all super super smart, but in order for them to reach their full potential, David, they need to be able to access and use things like, I don't know, websites, tools, databases, Slack, cloud services, commerce stores, I don't know, you get the idea, right? And and the problem is, there there's no easy way for them to do that, like right now the only way is by creating a custom integration for each application for each model. So as you can imagine, that gets pretty expensive and time-consuming and exhausting pretty quickly, right? So Anthropic, uh, which is the creator of the leading AI model Claude, came up with a bright idea; they thought, "Well, why don't we create a single software layer where all the apps, databases, websites, whatever in the world can just connect to once and then instantly be accessible to whatever AI models exist right now, all get created in the future?" So it's like this synonymous just layer, and that's the Model Context Protocol; it's a single layer where if you connect your AI application, model, or whatever, you now get access to hundreds, thousands of databases and tools. Now, why is this important or why is it so exciting? Well, now your models can stay up to date with the latest, so it's always contextually relevant; it's also able to do a bunch of stuff, talk about a bunch of stuff, relay information. Remember, ChatGPT is cool, but only really as an information source; it needs to be able to like actually do things. Actually, David, it's now reminding me, do you remember why we got so excited about agent frameworks or why it's still such an exciting prospect perspective because they were able to not only allow you to build Web3 agents but also access a ton of different tools because the framework's basically plugged into these different APIs? That's what this does, but on a unanimous layer across any different vertical, Web2 products and Web3. Go ahead.

To turn this into like I'm still trying to wrap my head around this; is this like Wormhole for context in the Web2 world? So AI agents need to be plugged into more things, and so we need this like middleware, knowledge, short-term memory, working memory, interoperability layer for agents so that they can access more parts of the internet inside of their understanding and context. Is that like going on?

That's that's basically what it is. Yes, in nerd speak, David, that's exactly what—not even nerd speak, just crypto speak actually, low IQ left curve crypto speak is what that is; that's literally that's literally it. Um, and of course, I I was initially skeptical about this release because Anthropic, of course, is um a private company; it's funded by some of the top funds, so I was like, "Well, if they're going to centralize this, this is not going to be useful at all; it defeats the purpose."

Well, yeah, it's not neutral, of course.

Well, it's actually 100% open source, so now you can add so okay, so now now this is like the Polygon, a layer where guys, they're like, "Guys, this totally incredibly neutral; this is just our standards protocol," and like zkSync is like, "I don't care that it's credibly neutral; it's got your brand on it."

Exactly. And so so we're somewhere in between there, right?

Yep. Yep, exactly. It's 100% open source; you can add any kind of Web3 stuff to this, and in fact, um, you know, this can obviously level up Web3 agents massively, but we're starting to see Web3 teams already integrate directly into this. Actually, I've got two tweets here for you uh where you know one of them shows Send AI integrate an MCP server, which is a Model Context Protocol server; it's basically you know your its own custom integration, so now apps like Claude can have access to 30 plus Solana actions. Um, you can do actually oh, 100, damn. Okay, so so your my little top agent that can use my computer like I use my computer now can do a hundred different things on Solana.

There you go, David. That's rough; 98 more things than I've ever done on Solana. You I bought me on things you do on Solana? That's that's pretty insane.

Um, yeah, it's cool to just again like um I I I always think back to this one episode you did with Ryan this one time, David, like back in the previous cycle where it actually it was before the previous cycle, uh you know those dark dark days of the bear market where you crypto was cool.

Yeah, yeah. You and Ryan on every single rollup would say the the following phrase: "All of these things, David, is just it's laying the tinder; it's laying the tinder for the eventual fire that will burst into this big DeFi thing or this big, you know, NFT thing," and everyone thought you were completely nuts back then, and then we had DeFi cycle and NFT cycle, and we were like, "Oh, well, what the hell? That's like all these different cool things to do," um, and I feel like this is the same thing happening except it's on steroids, David; it's on like some other type of wave where um these things are real, exist right now and can be put into action right now, and in the Web2 world it's already being done. So with Web3, I'm just waiting for like, you know, the cogs to fit together and for this machine to start wearing. It's going to get nuts. I think people right now like it's pretty desperate times in crypto; like Bitcoin, it's back over $80,000, but it hit $78,000; Solana was like down to 115; Ether's below $2K, so it's like really desperate times, and then people people are just like looking for the light at the end of the tunnels, like, "When when when are we going to have a new meta? Like, we need a new meta. The last meta we had was dog [ __ ], and that was the me the meme coin crime meta, and before that it was the high FTV low float meta, and then we had this micro AI slop bot bubble," and I think people are like looking for like, "What's the next meta in crypto? What's what's going to happen next? How are we going to where where's the next arena? Where's the next casino? How are we going to go up in price?" It's AI, guys; it's going to be AI; it it's like we're we're going to figure out a way because AI is the most capable thing. The first half of this episode was talking about how incredibly capable AI models and AI agents are becoming, and now the second half of the episode is like, "And we still got these token things; we still got tokens; we're going to figure out how to slap these things together; it's going to be another AI agent bubble." We'll call it a bubble; it's going to be better than the last one, and even the AI agent slot bot reply guy meta was actually not the first AI meta; that was just probably the first AI meta that you listener heard about; there was two more metas before that that were smaller. Uh, and so I think this is this is what's coming; this is it's going to be AI like AI is going to cause the next hype cycle in crypto, probably.

I I mean, yeah, David, if we just pick up the Kido dashboard chart here, AI is still long and strong, right? 35%. That is the the screen.

Yep. Yep. And it's literally been like this is the lowest it's ever been over a yearly time frame; it's typically averaged around 50%, but um it's never dipped below 30%, I believe, which is just insane. And and we had some brutal couple of weeks; remember, no one's really talking about the crypto AI thing anymore, David; everyone's [ __ ] on the SL except for us; we're still here; we're still I I'm going to be the new Ryan; like we're we're laying the tinder for the next wave up and all this kind of stuff, right? Um, but yeah, AI is still the number one mind share subject in crypto, hands down. All right, Bankless Nation. All right, EJaz, that was a really really good week, man. There was a lot; there's a lot going on; there never seems like there's enough time to cover it all, but e thanks. Thank you once again for helping us go through the meta. Uh, I'm bullish, man; really bullish; so bullish.

Yep. Dude, Bankless Nation, you guys know the deal; crypto is risky; crypto AI is even riskier; that's because it's the frontier; it's where we want to be, and we are glad you're with us on the frontier and with us on the Bankless journey. Thanks a lot.