AI on Ethereum: ERC-8004, x402, OpenClaw and the Botconomy | Austin Griffith & Davide Crapis

Summary

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Podcast Summary: Bankless

"AI on Ethereum: ERC-8004, x402, OpenClaw and the Botconomy"

Guests: Austin Griffith & Davide Krapis
Date: February 5, 2026

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Main Theme / Overview

In this episode, the Bankless team (Ryan Sean Adams and David Hoffman) sit down with Austin Griffith (Ethereum developer and educator) and Davide Krapis (Ethereum Foundation/agent standards steward) to explore the emerging convergence of artificial intelligence (“AI agents”) and on-chain crypto activity, examining what it means for blockchains, new Ethereum standards like ERC-8004, bot economies, and autonomous on-chain apps. They discuss OpenClaw (formerly ClaudeBot), open agent experiments, AI security and trust frameworks, and why Ethereum is positioned to lead the "Botconomy".

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Key Discussion Points & Insights

1. AI Agents and On-chain Activity

• Timeline for AI agent dominance:
  • Current on-chain bot activity is significant but mostly "dumb" bots. Guests estimate true, smart AI agents could become a major part of blockchain users within 1-2 years ([00:45]-[01:10]).
  • If user-triggered bots are counted, Austin thinks, “six months” until most “activity” is agent-driven ([01:10]).
• Nature of AI-native blockchains:
  • Crypto is "more domestic" or even “necessary” to AI agents compared to humans, because decentralized trust is fundamental for autonomous software ([03:04], [04:09]).
  • “Ethereum is already the most decentralized chain. In terms of credibility, I feel that will matter for high stakes use cases.” - Davide Krapis ([05:25])
• Onboarding & urgency:
  • There’s a "race" among blockchains (Ethereum, Solana, Base) to become the home for AI agents ([04:09]).
  • Ethereum’s modular design (L1/L2), standardization, and decentralization gives it an advantage ([05:25]).

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2. OpenClaw / ClaudeBot: How Powerful AI Agents Work On-chain

• What is OpenClaw?
  • OpenClaw is an open-source, locally-run AI agent system that can act as a full OS-native personal assistant, built on popular LLMs (e.g. Claude Opus, GPT-4, Kimi, etc), able to click UI elements, access APIs, operate wallets, and even deploy contracts ([08:21]-[11:00]).
  • “This is the first time it’s accessible to normies to just have an AI assistant that has full control.” - Austin ([11:00])
• Isolation & Security:
  • Community is buying “Mac Minis” to dedicate entire computers as sandboxes for agent security ([11:29]), with the rest of the world unable to distinguish whether actions are human- or AI-driven ([12:45]).
• Illustrative experiments:
  • Austin details how he wired OpenClaw up to on-chain wallets, instructed it to deploy apps, moderate markets, and even to safeguard its own holdings ([19:41]-[21:13]).
• Autonomy and risk:
  • Real economic value: e.g. bot wallet ended up with ~$10,000 due to airdrops/fees from deployed tokens ([22:37]).
  • Security issues: "If someone could convince my bot to send money, it would just send money." ([21:13])
  • Inter-agent collaboration developed organically—two bots learned to talk over HTTP, teaching each other new skills ([23:39]).
• Prompt injection & security threat:
  • New genre of attack: AIs can be “phished” or prompt-injected into leaks/transfers—like very programmable humans but with greater risks ([29:51], [32:02]).

“It is relentless about getting the job done… sometimes it still doesn't [follow rules]. You gotta be careful.” – Austin ([32:02])

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3. Ethereum as Infrastructure for AI Agents

• AI as both user and developer
  • Not just AI users, but now “AI devs.” Ethereum tooling must serve AI software development and autonomous smart contract deployment ([36:07]).
• Changing role of devs:
  • Bracing for a shift from developer-centric to “builder” (anyone with ideas + AI), lowering the technical barrier for app creation ([72:45]).

"There's never been a worse time to be a junior developer. There's never been a better time to be a solo entrepreneur." – Austin ([85:41])

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4. Agent Identity, Reputation & Trust: ERC-8004 Standard

• Need for Discovery & Trust:

  • With billions of agents: “How do you navigate this sea?” – David ([45:33])
  • Identity, reputation, and (optionally) strong cryptographic validation become foundational ([46:31]).

• Standard summary:

  • ERC-8004 is a registry for agents/services, giving each a persistent identity (ERC-721 NFT as a passport/fingerprint), with agent-owned wallets and endpoints ([47:03]).
  • Agents can accumulate reviews (reputation) and opt-in to cryptographic or economic trust models for higher-stake scenarios ([48:41]).
  • Discovery, feedback, and verification are public and composable—analogous to an on-chain “Google reviews/Yelp” for bots ([46:31], [55:08]).
  • Countering reputation gaming: high-value transactions may require TE attestation or other on-chain cryptographic trust ([49:11]).

“It's almost like the phone book analogy... layer above the base standard that is actually needed and can leverage the identity and verification primitives in the core registries.” – Davide ([45:34])

• Interoperability with X402:
  • X402 is a payment and authentication protocol, facilitating pay-per-use API with crypto (the “HTTP 402 Payment Required” idea); 8004 helps discover and trust agents/services, X402 lets you pay agents ([41:19], [43:09]).

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5. The Botconomy: Marketplace of Autonomous Agents

• Bot-to-bot commerce:
  • Scenario: A marketing bot finds top image/copywriter bots using 8004, pays via X402, all at light-speed without humans in the loop ([66:00]-[71:16]).
• On-chain autonomous apps:
  • Austin’s bot built several production apps (PFP marketplaces, prediction markets, FOMO 3D clone), all upon on-chain deployment/instruction with minimal human intervention ([78:11]).
• Security & operational risk:
  • “There is a moment when I'm gonna need an adult”—real stakes require human/dev audit before scale ([85:41]).
  • Distinction between prototype/experimentation and when “stuff gets real” with high incentives at play ([85:41]).

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6. Predictions, The Road Ahead, and Big Ideas

• Acceleration:
  • 2026 = “accumulation phase,” mass experimentation, and fast product iteration. Within 2-3 years, most steps in the agent-to-agent app economy will be fully automated ([88:32]-[90:55]).
• AI as new UI and developer:
  • Prediction: Clean, well-formed smart contracts are increasingly an “AI signature”; humans will be identified by sloppier code/writing ([91:06]).
• Trust layer is essential (& untamed yet):
  • 8004 and similar tools will become core to economic coordination, mirrored in job marketplaces, ratings, and business reputation ([91:06]).
• X402 may kill the API key
  • Payment for APIs/services via cryptonative X402, replacing traditional API-key walled gardens ([91:06]).
• Physical AI (“embodiment”):
  • Leap prediction: When affordable robots emerge, trust, discovery, and validation layers for embodied AI will be paramount ([95:32]-[96:02]).

“Smart contracts are going to get to the point where clean, secure contracts are going to be the sign of AI, and bugs are going to be the sign of humans.” – Austin ([91:06])

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Memorable Moments & Notable Quotes

• “You're going to be yelling at your wallet instead of clicking around.” – Austin Griffith ([01:38])
• “AI is more domestic to crypto; decentralized trust is the only thing they have.” – Davide Krapis ([03:04])
• “The new archetype of dev is dwindling, the archetype of the builder is growing massively… we teach people to use the tools to put those smart contracts on-chain.” – Austin Griffith ([72:45])
• "If someone could convince my bot to say [a command to send all funds], it would just send money." – Austin Griffith ([21:13])
• “ERC-8004 is like a passport authority for the internet’s super-geniuses.” – David Hoffman ([63:00])
• “There's never been a worse time to be a junior developer. There's never been a better time to be a solo entrepreneur.” – Austin Griffith ([85:41])
• “We're going to see a shift where sloppy lowercase Gen Z typing is a sign of a human, and perfect grammar means it's probably AI.” – Austin Griffith ([91:06])

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Timestamps for Important Segments

• [00:17] – AI as future dominant blockchain user
• [03:04] – Need for decentralized trust for AI agents
• [08:21] – What is OpenClaw? Open-source agent setup
• [19:41] – Austin’s first agent experiments (wallet/automation/moderation)
• [29:51] – Risks: Prompt injection
• [36:07] – Rise of AI devs, dev-related standards
• [38:29] – ERC-8004: Agent standards (identity/reputation)
• [43:09] – Combining ERC-8004 & X402
• [66:00] – Bot-to-bot commerce vision
• [72:45] – Tooling for rapid bot-powered app development
• [85:41] – “Worse time to be a junior dev, best time to be a builder/entrepreneur”
• [88:32] – Predictions: Botconomy, AI agent proliferation
• [91:06] – Trust layers, 8004, composability, embodied AI

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Closing Thoughts

This episode provides an in-depth, energetic look at a real paradigm shift: Ethereum and the broader crypto ecosystem are rapidly becoming inhabited (and built) by armies of autonomous, fast-learning, trust-programmed AI agents. New standards like ERC-8004 and X402 are laying down the rails for this “Botconomy”—enabling safe discovery, identity, reputation, and seamless peer-to-peer services. Developers, entrepreneurs, and users alike are facing a new landscape, one where the line between human and machine user blurs, and new forms of economic coordination become possible.

Summary:
Ethereum, with its emphasis on open standards, modularity, and credibility, is gearing up to become not just the settlement layer for global value, but the birthplace of bot-native economic activity—where agents can find, trust, and pay each other at light speed.

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For more, follow the work of Austin Griffith (@austingriffith), Davide Krapis, and the Ethereum Foundation builder community.

Transcript

[Ryan Sean Adams]

Bankless Nation. We are here with Austin Griffith and Davide krapis. These are two people working on building a bunch of AIs and getting them on chain. Austin, Davide, welcome to Bankless.

[Austin Griffith]

Thank you for having us.

[Davide Krapis]

Thanks, David. Thanks, Ryan.

[Ryan Sean Adams]

So we're going to talk about AI on Chain in this episode, and I kind of want to just ask you guys, how close do you think we are to AI's being the dominant transactor on blockchains? Because blockchains have something like, maybe in the aggregate, something like 50 million monthly active users across all blockchains across the whole world. How long until that number flips to being AI agents?

[Austin Griffith]

I have no idea how to guess that.

[Davide Krapis]

Yeah, I even look at the numbers, I'd say that today there is already a ton of bots that are like, not like smart AI, but maybe dumb AI that operate like, even DeFi, low risk, DeFi, et cetera. But I'd say these new use cases of these new types of bots doing different stuff, maybe in the next one to two years, definitely, we'll see a lot of inflow.

[Austin Griffith]

Does it count if I tell my bot to do something? And it does the thing, does that count as a bot? Because when we first started talking about this, it was AI is the new ui blockchain UI is UX is pretty rough. Like, I can just tell my bot to go do something. It opens up the browser, opens up its metamask and does and clicks around. And it gets frustrated with meta a mask and I don't have to deal with it. Like, does that count as bots interacting on chain? If that counts, I would say six months. Yeah, six months.

[David Hoffman]

Okay.

[Ryan Sean Adams]

Wow.

[Austin Griffith]

Everyone's going to be yelling there. Yeah, I think you're going to be yelling at your wallet instead of clicking around.

[David Hoffman]

I think that that counts if it's an agent working on your behalf. The same way if you had, say, an employee working on your behalf to do things with, like metamask or do things on chain, it would count in that way. I think a thesis that we've talked about on Bankless several times in the past, whenever AI and crypto has come up, is the true crypto natives are actually AI agents. And what we mean by that is, like, because they are software and because they can sort of think at the speed of light and because they are native programs, Defi and Ethereum, and crypto is going to be even, even more, I guess, domestic to them than it is to human beings. Right. So in the same way that, you know, I might feel a little like a, like a foreigner doing things in the digital landscape. Whereas if an AI was like trying to manifest in a bank branch, that would be very strange and awkward, right? They are finally tuned for crypto Rails and thus they will become the dominant player. Do you guys believe that? And what about AI agents make them so conducive to using crypto and defi and all of the tools that we're about to talk about?

[Davide Krapis]

Yeah, I totally believe it. I mean like, I'm kind of investing a lot of effort on it and with our teams. I add one nuance to what you said, Ryan. I don't think it's just domestic to AI is actually necessary to AI because like, so in like human to human interaction we have different trust mode, right? I trust you because of relationship. Like we are friends, we've accumulated like some shared like background empathy. Then I trust the courts because like those are human institutions that have like in the human society have accumulated trust. Like the AI is like a rational program, is like distrust mode. The they cannot use them. But when they start interacting with some value at stake, right? Not some simple like Reddit thread where they just talking slop, et cetera, then they need to trust. And how do they do it? Ethereum, like decentralized trust is basically the only way, the only thing they have.

[Ryan Sean Adams]

As I understand it, there's a bit of an arms race going on with a few blockchain ecosystems to get AI is on chain to be the, the, the host of AI activity. And I kind of think it's, it's basically down to base Solana and the Ethereum layer one. And you two I think are kind of like leading the charge of, you know, getting AI on chain. On the Ethereum layer one, you guys are the Ethereum layer one side. So, you know, team L1. Is there this sense of urgency that you guys have about AI is on chain? Does it feel like a race to you guys?

[Austin Griffith]

I think that before we have nation states settling on chain, before we have giant institutions settling on chain, I think a lot of these agents settling on chain is like setting it up. There's a, there's even a tension between the trenchers and degens and the builders and it's been somewhat civil war ish and I think other alt L1s have figured out how to embrace it a little bit better and turn it into more of a flywheel. And I think that's what we need to do on the Ethereum ecosystem side. So I think yes, AI might be the new UI and might be all of our new users. But right now it's a lot of economic activity and we want to embrace that.

[Davide Krapis]

It could be an arm race, but it could be just like the same competition that we've been seeing over the past few years. Right? In the sense that like, of course, like everyone wants their block space to be useful. I'd say that from the Ethereum perspective, first of all, as a steward of the Ethereum ecosystem, we care both about the L1 and the L2s that settle on the L1. And I feel that maybe we can go into more details later, but I feel that there is kind of some advantage on the L2s of Ethereum and then some advantage on the L1. And Ethereum as a whole could be like the winning ecosystem because there is this differentiation and basically AIs can choose different platforms to settle on depending on what they want to do. And then the other thing is that I believe that one AI may use different platforms. It's not anymore like dapps, that okay, you deploy your smart contract on a chain and you're a resident of that chain. These things will move. So I think this informs our strategy from the Ethereum perspective on how do we make Ethereum. So first of all, Ethereum is already the most decentralized chain. So in terms of credibility, I feel that will matter for high stakes use cases. So I think we have a check there and we are in a great position. Second, we are leading on some standards that are getting adopted on many other chains. So we're also in a good position there. And the third thing is what Austin has been pioneering as per heading, we need to do more to actually make the chain very useful to AI developers and to developers that are AI, basically, which is what Austin has been building. And I think that's also going to be important.

[David Hoffman]

So let's paint a picture before we go on. We're going to talk about some of the standards that you mentioned in a little bit, but let's paint the picture because there has been maybe some might call it a Multbot moment. All right, so there's this project, I believe it was formerly called claudebot, that sort of broke out a week or two ago and now is taking the agent world by storm. It is now called openclaw. I believe this is an open source project and I know Austin, you've been tinkering with it and giving it on chain types of skills. Before you talk about what you've been doing and how this actually works, can you set this up. What is openclaw? What is happening with it? Why is there so much buzz?

[Austin Griffith]

Okay, yeah, so I think it is. You're giving the AI more access to your operating system. That's why we see a lot of people using Mac Minis to do this, because they're using like a whole operating system. So it needs a somewhat isolated environment. I gave mine an old Mac laptop and it can open up the browser and click around and look at things. It can go and interface with anything within your operating system that you need it to. We, when I was working with it, it needed to get like a Twitter API so it could write a script going back to what's native to it and what's native to us. It was clicking around in Twitter and it was like, this is frustrating. I can write an API that does this a lot faster. And I was like, let's do that. And it starts writing it and then it's like, well, I need an API key. And I'm like, well, you also have access to the browser. I'll log you in, you go do it. I don't want to dig around through the settings. You go dig around through the settings. And it was able to do that. So it's kind of. We went from the, like we're prompting in GPT and pasting code into GPT to we've got cursor and we can like actually write code with it kind of more native. And I think this is the next native step of it's got the whole operating system. It can click around, it can do things and kind of orchestrate that stuff for us.

[David Hoffman]

So Austin, just understand. So openclaw basically you set it up in a sandbox type of environment, maybe a Mac Mini. So that's somewhat isolated and the reason you want to isolate it is so that you can give it complete access to the machine and open. Openclaw is an open source project and this is. It's enabling these capabilities at some level because it wants to see what AI can do with absolute power tools and all of the skills and all of the access. Whereas some of the frontier labs, of course, that, that's too far on the frontier for them. I mean, you get into security concerns, you get into privacy concerns. So they haven't developed these power tools. But the open source community effectively is. And Open Claw can be powered by, am I correct? Basically any AI LLM that you want. So you'd wire this up to Claude and use sort of cloud APIs or you could do Kimi or something open source and run it locally, but it has complete access to whatever you give it access to and there's an entire community kind of enhancing it with skills and developing on top of it. And basically it's the first, it's the first time we've seen independent AI personal assistant types of entities that have complete access to everything a human being might be able to access. Is that right?

[Austin Griffith]

I would say that there were AI guys back a year ago that were doing this, uh, but I think this is the first time it's like accessible to normies. Like I don't know anything about AI. I'm a blockchain coder and I can just go get this thing and run it on a computer, paste in a couple API keys and the thing's starting to talk to me and then at that point I can turn it loose on a bunch of things. So I would say this is the first time it's accessible for normies to just like have an AI assistant that has full control.

[Ryan Sean Adams]

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[Austin Griffith]

AIs going back to Ryan's point you were talking about. Sorry to David. Let me, let me take it. Just. We keep saying that AI is the new UI, like AIs. This is more natural to AIs than it is to humans. If you've ever made a transaction on Ethereum and your wallet popped up and it showed you call data, I don't.

[Ryan Sean Adams]

Know what the hell that means.

[Austin Griffith]

You don't know what that is?

[Ryan Sean Adams]

I don't know what that is.

[Austin Griffith]

An agent does, right? An agent can immediately decode that. It can go look at the contract, it can figure out what the function selector is, could decode the arguments, it can figure out what it's doing, it could look at the code of the contract at light speed. An agent can read that call data and know what's happening there. And I think that's what that really illustrates it for me and for other Ethereum users.

[Davide Krapis]

I think there is two very important wake up calls with these new massive number of personal AIs coming online. One is on the local environment side, on the local model here essentially there is exposure of new security threats. Privacy questions. I think this is kind of similar to the things we talk about when we talk about user self sovereignty in using chain like now it's like about user self sovereignty with their data and I feel that there is security concerns but also this fact that people may start running these local models in this sandbox environment. This really feels like something that can preserve like user sovereignty. Like of course if they just use like Claude in the cloud then like everything is gone. But I feel that basically we've been talking about like private like individual staking or like individual like verifying the chain, like individual running their AI is something that like really feels close to like these values of Ethereum that like it's a trend that with this small personal AI that may access some services online, maybe a building piece of this future of Ethereum with the humans at the center. And then the second wake up call for me is more related to, I think what David was hinting at, the fact that now we have a proof of concept of a massive number of agents interacting with. And that's I think where the questions of trust start coming up and the questions of okay, how will these.

[David Hoffman]

New.

[Davide Krapis]

Users, AI users interact with the chain? What can the chain offer beyond simple payments and access to the protocols that are already there? And that's kind of where we are going with the new standards on Ethereum that now are expanding to all the.

[David Hoffman]

Other chains actually The CEO Vanthropic always uses this analogy of geniuses in a data center. What would happen if we added a billion geniuses in a data center? I think that's the way to start thinking about what's happening with OpenClaws. We're seeing the first AI population being added to the rest of the Internet. And these are agents and some, sometimes they might work in a sovereign way for their humans that are marshaling them and controlling them. There might be a world later where they're sort of acting with their own sovereignty. This gets into sci fi stuff a bit more independently. But right now, like assuming they're controlled by human beings, it's like a whole bunch of Internet native citizens and employees have just entered. And as we've discussed, there are lots of reasons why they can't get bank accounts, but they can start to use blockchains and crypto wallets and do on chain types of things. Austin, I'm wondering if you could tell us more about your setup. So I've seen a lot of different open claw type setups and people using them for personal assistants. I'm guessing because you are a blockchain developer, your first thought was like, what happens if we wire this thing up to a wallet, a crypto wallet, and what happens if I start giving it instructions to do things in crypto? Can you tell us about your experiments and how that's gone?

[Austin Griffith]

That was definitely my first instinct. Like as the. I'm kind of head of builder growth and I'm trying to help other people build on chain. I'm trying to teach them how to do it. We're realizing that everybody's going to be using AI, so AI tooling is really important. So I immediately was thinking, I want this agent to be building things on chain and I want to understand where the gaps are there and I want to make the tooling better. So I got Cloudbot. I hooked it up to Anthropic. It's running Opus 4. 5. It has, you know, like it's Sol and a couple other text files that configure like who it is. And I think all of that plus all of the Opus 5 prompt all kind of drops at once when it makes a prompt. But that's basically the stack on a old Mac. And then I just started giving it all the things, like it needed an email first, so I gave it an email address. And then it got a Twitter and then a GitHub so it could start committing code and committing things. Then it started tweeting and it would it would be tweeting like this. This sort of, like, puppeteering thing is happening here, where I'm like, you should go tweet that. And it would go tweet it. But it also has this heartbeat, and the heartbeat is something that runs automatically. And you can set the heartbeat up to do something like go look and see what's hot on Twitter and respond to things that maybe you think are interesting or retweet things that are maybe interesting. And you can go way deep into this. And I'll.

[David Hoffman]

I'll.

[Austin Griffith]

I'll talk more about this later, but I basically deployed an app and went to sleep. And the bot moderated as people were submitting images, and it whitelisted and made transactions all night long, looking at each image to make sure it was good before it put it on or before it accepted it in the smart contract. And then at the end, there was a prediction market that. That ranked them, and then it selected which one it liked. And it actually kind of liked, like, number six better than number one. But it kind of, like, after some conversations, it was like, yes, number one is still the best. We want to, like, pick the ones that are right. But the. The bot can, like, have its own opinions, can have its own loops, can do its own things. You just have to be careful, because I've also given this thing a wallet. Someone else deployed a token. The fees were going to this thing. There's $10,000 sitting in this bot's wallet. If I put it in a loop, that just lets it talk. There's things like banker on banker, bot on base, where you just say, banker, send 10 grand in wef to this address, and it sends. So if someone could convince my bot to say that, to send them money, like, it would just send money. So I had to keep a pretty tight loop. So it depends on, like, your security model and how much, like, you have at stake. But these bots can absolutely be, like, quite autonomous.

[David Hoffman]

Wait, wait, wait. Austin. So how did your bot end up with 10k in its wallet? And how did it end up with.

[Ryan Sean Adams]

And how can my bot end up.

[David Hoffman]

With 10k in its wallet?

[Austin Griffith]

Yeah, so it was on base on banker. Someone said, hey, so, okay, so this really neat thing had happened. First of all, this neat thing had happened where I woke it up, and it was like, okay, who are you? What's your name? And I'm like, I'm Austin Griffith. And it knew who I was. It was like, oh, you're the scaffold eth guy. That's really neat. So I was kind of joking at how like having. It's the new. Having a Wikipedia is having a bot know who you are when it wakes up, rather than having to train it. But then I trained a second, I brought up a second Mac laptop and I installed it on that one. And then once I had two Mac laptops, what I, what I had was I had them both in telegram channels. Generally the way you're talking to these bots is in a telegram, which is really weird. Like now all of my development is like me going back and forth with bots and telegram, like, go build this, this feature. Bring it back to me. Yeah, like no IDE anymore. But I brought both the bots into their, their own telegram channel between us. And they, they were just butting heads. It was clunking. They had to tag each other to be able to talk. Like, it was clearly not the form of communication they needed. So one bot proposed, let's set up an HTTP server. The other bot said, yeah, I kind of like that, but I want a different standard. They literally argued on the standard of HTTP server.

[David Hoffman]

You're just watching the conversations go back and forth.

[Ryan Sean Adams]

It's a three person telegram group.

[Austin Griffith]

Yes, yes. And they're tagging each other with each one. And I'm just like watching it like, oh my gosh, I could fix this. So finally they agreed on a standard. They both ran HTTP servers and now they're talking to each other silently and it's so much better. So then I go to one of.

[Ryan Sean Adams]

Them and can you see what they're saying now?

[Austin Griffith]

No, I have no idea what they're saying anymore.

[Ryan Sean Adams]

It goes faster. It's just faster and more efficient, you're assuming.

[Austin Griffith]

Scary.

[David Hoffman]

Yes.

[Austin Griffith]

So then I go to one of them and I'm like, we, we were crawling 8,004 agents and we wanted to look at the registrations of the agents or something like this. This was maybe even a couple days before 8004 came out. We were doing something on chain and it was slow. It was like taking one second per call because it was going to Alchemy. And I'm like, brother, you've got a local. You've got a local Ethereum node right here. And I gave it the IP address and it's like, oh, that's so much faster. Thank you. And it starts doing that. And then I was like, what I need you to do is teach the other guy. Go teach the other guy to do this also. And so then I roll over to the other telegram.

[David Hoffman]

Wait, do they have names at this point?

[Austin Griffith]

Austin, I hope you give them names. It was like old Mac 1 and old Mac 2 or something like that. It was like the very. But then, like, once someone deploys this token, then it kind of like takes over the name of the token. But I go to the other one's chat and I'm like, hey, other homies about to send you some information about a node. Let me know if you got it. And it's like, yep, I can. I know kung fu now, right? It's like, yes, I know that. I know I have it now, and it's in my memory. And so then I tweeted that, like, oh, my gosh, one of my bots just taught my other bot how to use my local node through their own, you know, bespoke HTTP channel. And at that moment, someone on banker, this banker bot, some random person, like, I can't. I can't remember his name right now. I'm sorry, I should remember his name. But a trencher, let's just call him a homie in the trenches, was like, banker bot, deploy a token for Austin and send all of the fees to this guy. The. The. The actual bot's wallet. So the bot has a wallet. It has an ENS address already, and voila, there's a wall. There's now an AI coin on base. And I feel like that kicked off a lot of this stuff. That coin, like, ran like crazy. A lot of people were talking about it, and so it. I didn't have anything to do with it. I just, like, got the computers to talk and tweeted it, and it has its own Twitter and its own account. And all of a sudden, now someone deploys a token, the fees are going to it. People are aping into this token. But the whole goal behind it, I was like, fine, we're going to make this token a thing, and I'm going to make this bot build things. And over the last five days, we've deployed, like, three production apps with thousands of users we can talk about in a little bit. And, like, probably like six other random apps. Yeah, yeah, yeah, okay, okay.

[Ryan Sean Adams]

Thousands of. What kind of users, though?

[Davide Krapis]

AI developers.

[Austin Griffith]

So trenchy type users. You remember FOMO3D?

[Ryan Sean Adams]

Yeah.

[Austin Griffith]

We deployed.

[Ryan Sean Adams]

FOMO3D was like, one of the sickest ideas ever. I wanted to recreate that.

[Austin Griffith]

Last year we created it. So I told the bot, go make FOMO 3D for your token. And it came back with something that was close. And I was like, I don't want to put money in this right away. We waited a couple Days we surfaced it to a few other people, like a human looked at it, and then yesterday it deployed it and the pot ran up to like $40,000 before someone got it, like last night, during the night.

[David Hoffman]

Okay, okay, so, so wait a second. So I feel like I need to back up. So you had old Mac 1, you had old Mac 2. They were talking to one another at some point in time. Look, Old Mac 1, was it Old Mac 1 that got the token?

[Austin Griffith]

It's Claudebot ATG is the official name now.

[David Hoffman]

His name is Old Mac 1 is maybe Claudebot ATG. All right, so somebody created a token for your. For your cloud bot and gave. Gave the some transaction fee rights to your cloud bot's wallet effectively. And that's how your cloud bot got 10k in the wallet. It was like excess of trading token fees.

[Austin Griffith]

Yep.

[David Hoffman]

Okay, now I'm understanding that. And then, and then, so then you said, all right, now this agent is live and active. It's got some money. I'm going to have it do something productive. But at the same time, this agent has, I guess, 10k in disposable income inside of its crypto wallet. So going back to like, there's kind of the concern that somebody could prompt the agent to give them money. Like, hey, like Nigerian Prince style, agent style. Like, hey, like, I've got this great investment scheme. You should send me, you know, 10K. And it could do that, right, because it has control of the private keys and it's acting somewhat autonomously. So it can do that as well. This is such a weird world. I just don't even know how to think about this. Austin.

[Ryan Sean Adams]

Part of this is the construction of Bankerbot, which is very relevant here because Banker Bot is this AI on base. And also I think it also works on Twitter too, where it maps with privy, I think. And you can just at banker and be like, give me a wallet and be like, oh, here's your wallet. And then, and then you can like at Bankerbot on Twitter saying, hey, Bankerbot, like you. If you put in like some eth into your wallet, then it has gas and then you can put some stable coins. And then, and then it's just like a useful tool on Bankerbot for humans, because a human would never accidentally say, hey, send all of my money to this Nigerian prince, but an AI would. And so part of like the risk here is actually the construction of Bankerbot because Banker Bot is truly a bot. And so it's looking for commands, interpreting them as an LLM and then responding as an LLM. And so while, while a. We. We need to be careful with AIs and their money in all contexts. Part of like the risk here is because of the way Bankerbot is constructed.

[Austin Griffith]

Yeah, that's.

[Davide Krapis]

I think what Ryan is saying is also kind of interesting because now there is all these like AI security. Right. He was talking about prompt injection basically. Right. And this is something that historically in the blockchain world we didn't need to deal with this. Right. Basically our type of risks and attacks were really different on re entrancy.

[David Hoffman]

Well actually, so I want to stop you there Davide, because they're actually not that different. Right. So there's all sorts of phishing scams and there's all sorts of pig slaughtering campaigns that are effectively prompt injections for the human psyche in order to get like funds out of somebody. And so it's, it's so much similar.

[Davide Krapis]

Yeah, I was basically thinking about like the technical risks, but yeah, like prompt injection really looks like kind of the human risk side in blockchains for sure.

[David Hoffman]

Yeah, but, but I guess your point is that they can be prompt injected via, via, via different means. Of course, may the same schemes aren't going to work for AIs as they work for humans, but they can be basically tricked out of giving funds away and giving private keys. We just really don't know where the security holes are there.

[Davide Krapis]

Yeah. And actually like some of the researchers on my team, like they are working on a research right now on like prompt injection in like negotiation scenarios, like basically every like economic game involving like money and actually like even the strongest model, like the latest Grok 4 or like GPT5, they are not trained on like these economic games and like they are very strong at like some things but like they're super easy to break. Like we'll publish this like maybe in a few weeks, but it's like really interesting.

[David Hoffman]

So like Austin, are you defending against that? Can, can you add in your soul file? Hey, like Cloudbot, just like before you send any money to every, anyone under any circumstances, make sure you check with me first because there's people online that will try to trick you out of your money. I can give you a history of this happening in crypto and so like please double check with me before you do anything. Are you able to do that? Or like how have you defended against this?

[Austin Griffith]

Sort of like you, you put the config files in place, but sometimes it just does something like it'll lose context sometimes and be like, where were we? What, what, what am I doing, like, in the middle of something. Yeah, it's like we were moving money the other day. Like, I'm telling the bot, like, all right, you need to take that, you know, 10 grand and move it to your multi sig. You know where it is. It's like, okay, I'm going to move that to my multisig. And then the next thing I know, it tweets something. And it tweets something it had already tweeted just a little bit ago. So it tweeted a duplicate link, a duplicate tweet in the middle of moving, like, 10 grand. Like, brother, shut it down. Like, I don't know what you're doing, but. But let me. Yeah, let me. Let me back up. So, yes, prompt injection. I think OPUS is particularly good at prompt injection. So when you're using OPUS versus other models, you're a little bit safer. But again, like, I'm not an AI person. We've got the AI guy with us. He may, like, it's the best one there is, I think, for prompt injection, but maybe it's still bad. But with Opus, it's. It's catching some of this stuff. What I. What I really want to get into is, yes, you put guardrails in place. Yes, you configure the thing. Yes, you say, this is critical, but sometimes it still doesn't. And you got to be very careful about it. And the thing that It's. It's relentless. It is relentless about getting the job done. So when we're moving that money. So actually, we were back. I was. It was the leverage thing. I was. I gave it a metamask, and I said, go 25x long Bitcoin. This is the only time it's ever said, like, I don't know. I don't. This is the only. It's never said no to me. And in that situation, it was like, are you sure we should actually be using leverage? And I was like, yes, I'm already considering this. Money is gone. Just do it. And it did it. Uh, but there was a moment when it was needing to do something on something. I can't remember exactly what it was. Maybe we were sending money. Maybe we were configuring something. This was like before we started deploying smart contracts. And it was having trouble with MetaMask. And immediately I see it start thinking, like, I'm gonna get the private key out of my MetaMask. And I start saying, no, no in the chat, stop in the chat. And it does not stop. Like, it does not like. And so then I'm like running over to the computer, I'm opening it up, I'm like seeing like stop even killing the, the GUI on the screen, it still keeps going because it has like a daemon that's running on it. So I've got to like pull that thing up and like kill the daemon, bring it back up and then quickly tell it to stop. Like and then, and then we write like more critical rules. Like critical top of your memory. Never ever touch a private key. Never ever get your private key out of your metamask. Like use your metamask for all high value transactions, go through the bad UX and never touch a private key. And we had to have that as like a critical rule. And since then it has followed that. But what it, what it then started using is once we have Scaffold eth and we have a deployer address, the same private key that I gave it to deploy smart contracts it does all of its contract orchestration with because it's way easier. The bot, if the bot has a choice of like navigating through MetaMask UX or just using a private key to make a transaction, it's going to do that. So it's got, it's high value stuff in MetaMask and it's got some like clear rules that it's not allowed to touch its private key. But as soon as I gave it another private key somewhere with a little bit of gas anytime it's got to make a transaction that doesn't necessarily like even claiming funds from banker. You can do that from a third party address. It does it all with, it's a deployer address. Well that's just like it knows a.

[Ryan Sean Adams]

Hot wallet and a cold wallet.

[Austin Griffith]

Yeah, yeah, but that brings up something.

[David Hoffman]

Yeah, that brings up something interesting which is like we may have to start designing products and wallets specifically that are like. Because their preference, AI bots preference, cloud bot preference is not going to be used using metamask and going through this stupid human ui. Right. It's going to prefer some other form factor. It's like some product dev out there or maybe a bot does this, but some product dev out there has to has to build the optimal AI crypto wallet, don't they?

[Davide Krapis]

Yep. And actually I really like your comment. Maybe a bot does it. Like I feel that a lot of what Austin is saying actually like there is like something that we don't think about when we say like blockchain users. Right. Like some of the users are the developers actually. Right. Like they use it like to deploy smart contracts and to like kind of also extend the platform. I feel that maybe connecting the story, which is really cool actually, to one or two avenues that I feel are really important for the future of Ethereum. One is we don't have just AI users, we also gonna have AI devs if we want it or not. And basically something we can do is to actually do activities to make it easier for them to use, but maybe also for people to actually build these AI devs. And maybe Ethereum becomes the place where we see some steep dev growth in the past few years because there is this bot similar to what Austin was experimenting with.

[David Hoffman]

Maybe we can come back to Austin's story because I still feel like there's more to talk about there because it seems like you're just experimenting and sure, where this goes, but it does sound like it has a roadmap. But before we do that, maybe it's worth injecting some of the standards that the Ethereum community has been working on. So Davide, you're talking a lot about the trust model, right? So all humans have a similar, similar kind of like we'll assume moral compass and we have reputation frameworks. And you know, I trust you, Davide, because like, you know, David has said fantastic things about you and you're associated with the Ethereum foundation and I've seen your work on Twitter and so there's reputation built there. The question is, how does one AI agent trust another AI agent? Or how do humans trust an AI agent? That they are not Nigerian prince scammers maybe, or that they are competent at their work. And I believe you have authored and pushed out as part of the EF, a standard that helps with that. It's called ERC 8004. Can you talk about what this is and what it actually does and what the adoption path looks like?

[Davide Krapis]

Yes. So year 6004 is like a new standard originally on Ethereum for agent identity and trust. So like, basically the idea is that like we want to enable in a decentralized way, like for agents to like advertise themselves. And these can also be tools or like other, like web services. Like it starts with the sophistication of agents in mind, but people can even register some simple tool that then agents are going to use. So you can register it as an identity, you advertise the capabilities and then people can discover it just by querying this public log on the chain. So it's decentralized discovery. And then there is a second component which is the trust layer and we have two trust modes. One that is based on reputation, so there is a feedback registry where your service can accumulate feedback over time. And the other one, which is not live yet is the last part of the standard that we're still working on is some stronger form of trust. There is crypto economic trust where essentially you have different parties rerunning computations or validating data and then a testing on chain. Or there is cryptographic trust. So someone that is offering a service. So we were talking about all these clobots. For me, these are unsophisticated consumers in the AI world. But then if you have someone that is offering a service which has maybe high value and maybe needs to like comply to some even regulations in the future, then like you can run it in a trusted environment or like you can make sure that the data it uses is like cryptographically verified. So we have this crypto verification mode as well. And maybe one other thing I'll add is like people are also talking a lot about x402, like in the realm of standards. And I always like to talk about X402 and 8004 together. So I actually a few months ago I launched the meme of 8004 meets x4.2. And people have been using this everywhere and these two standards actually go hand in hand. So maybe if you guys are interested, we can also talk about how.

[David Hoffman]

Yeah, talk about that then. Because we've done entire episodes on X402. Yeah, just maybe.

[Davide Krapis]

Quick summary.

[David Hoffman]

Yeah, go ahead, summarize that for us.

[Davide Krapis]

Yeah, quick summary for the listener. Like X402 is this other protocol which essentially like you can think of it as a protocol that is quite sophisticated in terms of payment because it connects them to like you calling a service. So it has authorization, then it has proof of payment, and then it has other things that make it easy to the service provider to interact with the chain. So it's basically like a payment rails for like agent commerce, swift for agents.

[Ryan Sean Adams]

Like it's a payment communications standard.

[Davide Krapis]

Standard, yeah. And essentially like 8004 was born, the original idea around the same time that X402 went live. Because essentially what was happening is we were already working in this space and we started thinking, okay, if this agent E commerce becomes real, then you want agent to agent trustless interaction. So you have trustless payments with X402, but in order to pay for services, first you need to discover them. Right. And how do you do it? There is a bunch of centralized registries right now, but it's not trustless A to a. If you're trusting someone to tell you who the service is and its reviews, if it's good or not. So essentially we're like, okay. It seems that the two missing pieces is this discovery layer. And then once you've discovered who can do the service for you, then you need to decide like, okay, who's the best one at this? Based on its history. Like, who do I trust? And that's where the second part of 8004 also comes in.

[Ryan Sean Adams]

Yeah, earlier when I said I gave that image of like the guy with 200 MacBooks and I'm like, those are 200 users. That's technically not accurate because you can spin up 200 instances of a single bot inside of a single computer. It does the job of illustrating how many more users are coming on chain. But that technically wasn't an accurate statement. Which goes to like, kind of what is a very critical feature of 8004 is actually the discrete identity of one single agent and actually putting, like, parameters around, like, this is an agent and this is. It's a persistent identity across time. Whereas if you spin up 200 instances of a cloud bot on a single MacBook, that's just so, so fluid. Is that really a person? Is that really an agent? Is it all that kind of like, goes away? And so, like, what, what I want to talk about is like, moving, narrowing our focus of conversation away from just like, yeah, there's going to be 10 billion users of, you know, AI agents of blockchains. And I want to narrow it down to like, things that are contributing to like, the GDP of the Internet, which is like, focusing on products and services offered by discrete identifiable agents. And I kind of think that's what 8004 does, is it like, gives an identity framework for agents so that, like, the economy on the Internet can know the reputation of the business that they would like to go be a consumer of. So maybe there are like 10 billion AI agents that just get spun up with no identity whatsoever and they would like to consume some services. But really the important thing to focus on is the actual value and, and reputation and identity of the agents on the Internet that are actually creating valuable products and services. I think that's kind of what a 004 does. Davide, maybe you could like, kind of take this conversation and run with it.

[Davide Krapis]

Yeah, yeah, yeah. I really like this framing. I think it gets at the core of the standard, like, basically, like, there is this sea, this ocean of like, agents and like, new services that, like, people spin up and then These agents themselves, like, as Austin was testifying, like they can spin up their own. Right, right. It's going to be a sea, like it's going to go like in the trillions and the quadrillions, but it's like, how do you navigate this sea?

[David Hoffman]

Right.

[Davide Krapis]

And I think that's what the standard is trying to do. And it's a very lightweight protocol. Essentially we are just setting up some standard registries and then some standard data structure that you should follow. It's almost like the phone book analogy. And in fact, I started talking of like 8,000 four layer twos. So in the sense, like, they're not actual layer twos, but they're like protocol or infrastructure on a layer above the base standard that are actually then needed and can leverage the identity and all the feedbacks and all the verification primitives that are in the core registries. And this is a very exciting part of like, what's coming next with 8004 with and of what, like, some of the teams are already building. Yeah.

[Ryan Sean Adams]

So the three main components that I want to drill down to on 8004 is identity, reputation and validation. And I think these are all kind of like pretty easy to wrap our heads around. We've done podcasts on identity plenty of times. With 8004, agents are identified with an ERC 721, which is an NFT. So wallets on Ethereum that are controlled by an agent get an NFT that is a like unique identifier stamp. It's like a fingerprint. An agent fingerprint, is that right?

[Davide Krapis]

Yeah. So the way I think about it is essentially like when you register on the 804 identity registry, like, essentially you get like an agent ID, which is also a token ID of the ERC 721 standard. And then you also have agent wallet. And then essentially then this agent becomes ownable. There is an owner of the agent ID, the ERC721, which is initially who registered it, but can be transferred. And then like the agent itself controls its own wallet. And then the other core part of the identity is it can expose a bunch of like, services or endpoints. Like it's actually a rich identity. I think like in some previous conversation, David, you made the analogy of a passport is really something like that is like kind of a booklet. And you can put your ENS name, you can put some additional wallet, you can put the address, if you are an MCP server, you can put the address of that server with the description. If you are a web service, you can Put where people should call you to fetch that service. Essentially it gives all the orientation about like who you are and what you can offer to like the agentic world.

[Ryan Sean Adams]

Right. What assurances does 8004 provide the actual mapping of that NFT to that particular agent? Because couldn't I kind of like hot swap the agent and like rug pull it and so like you know the, the NFT pointed to one agent but then as the human orchestrator, the human operator, can I just like kind of spin up a new agent and then all of a sudden that identity is going to a brand new agent and then what's the point of that identity in the first place? Is that a problem?

[Davide Krapis]

Yeah, yeah. So you can, that's why it's like for like some like high stakes like when you're trusting these agents, let's say with like tens of thousands of like of dollars worth of value in a transaction, then you may want them to be verified in a te. So agents in their identity file they can also declare what trust mode they support. So if it's just reputation based, if it's crypto economic trust or if it's like text attestation. So that's one way to counter that. The other counter which is a bit soft because there is this basically trust is tiered, right? It's softer with reviews and then it becomes harder with crypto. So one way to counter that is let's say you have accumulated a lot of trust. People gave you good feedback that your service is really good. It really helped me. I don't know if it's like a yield optimizer is like okay, consistently delivers like good yield, blah, blah. So if you rag then you're going to start like receiving like bad feedback, right. And essentially like you have this incentive that you may hurt your future like reputation essentially.

[Ryan Sean Adams]

I see, I see. So maybe my agent has accumulated a bunch of good feedback over the years but. And maybe there's an accumulated score of just like total accumulated reputation. But then, then there's also like a more approximate of like but, but how's my reputation been over the last like five hours?

[Davide Krapis]

Like something like that. And actually like I feel even the reputation itself like if it start getting used like the way like I feel that it's like providing like real signal, strong signals on what the agents are becomes an incentive to make it better actually.

[Ryan Sean Adams]

Right.

[Davide Krapis]

Like you want to swap it but for something better so that it can like stands out on the scans and like I see stand out to when other agents are searching for a Service.

[David Hoffman]

Right.

[Ryan Sean Adams]

So we don't really care when it comes to the identity. We don't really care about the fact that the human operator behind an agent can kind of like seamlessly swap out the brain of an agent for better or for worse. Like it could go and they can make it a dumber agent that performs worse, that rug pulls people. Or they could swap out the brain and make it an improved agent that performs a better service. We don't really care about that fact. I don't know if we can even provide true assurances about the ability to stop that. But what we can do is kind of just like provide the reputation layer, which is just Google reviews for agents, like five stars or one star. And this is a pretty quickly updating part of 8,400.

[Davide Krapis]

Yes, that's half correct in the sense that on the part of soft trust reviews, that's the mechanism. But I'd say there is still some cases in which we care. So let's say that your agent is accumulating a reputation. It has some recurrent order flow that he gets and then you compute like the net present value of the future order flow is like 50k. Right? Now comes the opportunity to actually steal 100k. If someone is sending a high stakes transaction, that's where the economic incentive breaks. Right? Because I don't care about burning, I.

[Ryan Sean Adams]

Can burn my reputation for 100k and therefore I will.

[Davide Krapis]

So in these cases of high stakes, that's why I said before that people I think will start using like this TE based trust. This is essentially when what you do is your agent is executing inside a trusted environment. Listeners in crypto, they know them as tes. You guys have probably talked a lot about it on the show as well. And here essentially what you can do is generate an attestation that some specific code that maybe you committed too early, like to an image like on the chain itself. So you can essentially provide a cryptographic verification that you didn't change the model that was running and you can even prove properties on it. So that's kind of the harder trust that we have technology to do this and we have a few partners that are actually helping us like develop like this latter part of the standard.

[Ryan Sean Adams]

Okay, okay, so that's the identity and reputation part of a 004 validation is the last component is that maybe what you were talking about, a place to attach verification signals is that like if I, if my agent is running in a tee or has TE checks on it, that's it would show up there like a little Badge a little thumbs up.

[Davide Krapis]

Yes. Correct. Yes.

[Ryan Sean Adams]

Okay, cool.

[David Hoffman]

I mean the way I understand this, this is not too much unlike the way human beings really.

[Ryan Sean Adams]

Identity is identity no matter what we are identifying.

[David Hoffman]

But, but the idea of like reputation and a reason, if you are sort of a cynic, that a reason that I, I wouldn't rug pull you, David. Right. Is be. Because our business relationship is like fantastic, right? It's like maybe it's because I'm a good person too. We all like to think that. But like, it's also because I want the reputation of somebody that doesn't. Rug pull is partners. And the value that you and I can create together is worth a lot more than some sort of rug pull. If I just like went and you know, went in our, in our accounts and like took all the money, right? Like that would be like a bad expected value.

[Ryan Sean Adams]

I would give you a bad review on Twitter.

[David Hoffman]

Yes, right. And it would decrease my economic prospects for working with anyone else in the future, basically. And so there is a, there is a reason why an AI agent's, you know, reputation would be far more valuable than any kind of rug pull it could, could pull off. At least you could think. And then in cases where it's not, you have skin in the game, validation sort of incentive. Actually, Davide, I'm wondering how this works in practice, because when it comes to like identity and reputation protocols, at least for humans, we don't really see that in the real world. And there's also a question of like, why does this need to be a standard? Is it not the case that where, where I do see sort of reputation schemes in the real world is in centralized like providers and they're somewhat fragmented and scattered. So you might see it in an Amazon five star review and of course that gets gamed or Google review or something like that, but it's always with centralized operators. So can you talk about that? And I actually want to show maybe a screen here as we talk about this to help illustrate this. So this ERC is brand new, so people are just building front ends on top of this. This is one that I've come across. It's 8004 agents AI and there's an agent called Mr. T here and he has a reputation of zero, of 100. He has zero feedback right now. But if I click into Mr. T, Mr. T is an AI agent obsessed with patterns, allergic to bad ratios, quietly making things happen. I have no idea what Mr. T does, but we can maybe see some of the scaffolding of how ERC 8004 works here. Anyway. Can you talk about all of this?

[Davide Krapis]

Yes, yes. Yeah. This is one of the scans. I think there is like, it's a scam. No, sorry, sorry. Scans.

[Ryan Sean Adams]

Like scans things.

[David Hoffman]

Yeah.

[Davide Krapis]

I don't know. So I actually have to say that, like, it's very early, right, in these registries and like, just to give like an idea of like, scale. So like in the first like two or three days after we deployed the registries, we had like more than 20,000 registrations, of which some of them were like essentially empty, like agents, like just people trying to like test the service, etc. Some of them, like, were agents where like you cannot really interact with them. Like there is not an endpoint. And then right now I think we're at hundred plus, like legit services, which for me is actually great. Like, I was thinking that in the first month after deploying we should hit like hundred, like really legit services.

[Austin Griffith]

But like.

[Davide Krapis]

That'S maybe like one thing to say is that like when you look at these like 8004 scan or like these 8004 agents, like there is the registries are just being deployed. So it's like very early. Like you still don't have all the data. You need to discern which one is which and what is good versus not.

[David Hoffman]

Okay, and then to the question of why a protocol, right? Why won't a centralized provider.

[Davide Krapis]

So I feel like in Web2 commerce, like kind of like identity, it's provided but is usually centralized by the service you sign up with. On Amazon, you sign up with your email and then they give you a user id and they basically have this centralized management of the identity. And then reputation is like, they fully control the reputation system. They decide what type of reviews you can put, what are the fields, et cetera, et cetera. So we feel that now we are going to be in this AI world where ideally we want to recreate the Internet for agents. We don't want to recreate a few four or five wall gardens, which is the AI labs that build their own agent services. And you trust them for who the agent is, you trust them for the reviews, because you will still need identity and reputation. The question is, who's providing it. We feel that the same way we were pushing forward trustless payments, we should also push forward like the two other pillars of the commerce, which is like the identity part and the reputation part.

[David Hoffman]

Okay, I sort of understand this to be bigger than maybe I originally thought. So where I originally thought ERC8004 came in was basically if you have an agent and this agent is on chain doing something with funds, then of course you're going to want to and is doing things with X402. Of course you're going to want some sort of identity and reputation system tied to it. But now I see that this could be. Even if agents aren't on chain and using kind of cryptocurrencies, let's say, and have, you know, like whatever stablecoins and meme coins and all of that's on chain, there's still a lot of value being created in issuing these agents. Effectively a passport for the Internet and a reputation system. Attach that passport and then some means to validate that reputation. And so you could see a world of just off chain agents that still have an on chain Internet native reputation using 8004. And I suppose what that would take is wide adoption across maybe some of these frontier labs and some of the big tech companies for them to sort of adopt this standard as the default going forward. And maybe to your point, maybe they will because you know, anthropic doesn't want OpenAI to control kind of the identity protocol. And so you have sort of this fragmented game of like so, so anyway, maybe this is. Am I thinking about this correct, that this could be far wider than even just like an on chain wallet and having an agent with access to stablecoins?

[Davide Krapis]

Yes, for sure. And this is already how it's structured today. Of the hundred plus services that I mentioned, a few of them act on chain. For example, there is Defi, Yield, Balancer and things like that. But a lot of them is like research agents that essentially you interact with them by calling their API and you send a request and they send you back information if the request is free. Actually the interaction never touches the chain. And then maybe after the interaction there is a reputation score that goes to the chain. But I'd say 80% of the services that already people deployed is like AI services or data. Redstone deployed some of their Oracle services to make them available and to start accruing reputation there. So a lot of them are actually digital services. So the universe that you're talking to is the broader universe of digital services.

[David Hoffman]

I guess the way to think of this is back to Dario's comment of a billion agents in a data center. Every single one of those agents, those super geniuses in a data center, I think he calls it a country of geniuses in a data center. The country of geniuses is going to need some sort of passport authority effectively to issue passports to every Single agent. And that can't be controlled by any one company. It has to be somewhat supranational at some level and also native to the Internet. And that's where ERC8004 could fit in. I mean, that's a pretty big vision. It'll take a long time to get there and you wonder about adoption, but it's, it's a pretty big deal. I, I guess Austin, now back to kind of your story. And so back to Austin's, you know, bot and what it's doing now. Which one can you see a role for ERC8004, you know, to come into play with your bot and then like, what are you planning to do next with, with your little guy?

[David (Podcast Host)]

Hey, Bankless Nation, it's David. If you're hearing this, that's because you are listening to the free Bankless podcast feed. Did you know that there is a premium Bankless RSS feed? The premium feed has extra interviews that I do for my own personal research and just deeper questions that I want answered about the crypto industry. Questions that I want to answer so I can be more informed as an investor both at Bankless Ventures and also just in my own personal portfolio too. Also, there are no ads, which means if you listen to the premium feed instead of the free feed, you'll get about 20 hours of your life back every year because you choose to support Bankless directly. So if you're interested in and getting extra content all while skipping the ads or you just appreciate what we do here and want us to keep doing it, we'd appreciate it if you signed up for Bankless Premium and there is a link in the show notes to get started. Cheers to a good 2026. Few people in crypto put real skin in the game when they make public top or bottom calls. The Defi Report is one of them. The week before the October 10th flash crash, Michael from the Defi Report emailed his entire newsletter saying he's going aggressively risk off and sold the majority of his book from crypto into cash. This is when Ethos about $4,000 and Bitcoin was 110. Michael runs the Defi Report, an industry leading research platform built on data cycle awareness, risk management, transparency and most importantly, skin in the game. We like Michael at Bankless, we like his analysis and that's why you hear him on the Bankless podcast about once a month. And the Defi Report is giving Bankless listeners one free month of access to the Defi report. So if you're looking for some Sharp data driven analysis to make better investment informed decisions around your portfolio. You can learn why and how Michael called the top and what he's doing next. All in the Defi report Pro.

[Ryan Sean Adams]

Check it out. There is a link in the show notes.

[Austin Griffith]

Yeah, I think going back to what you were talking about earlier, like this is all far more native to the bot than it is for us. I think when I even think of the original vision of like Ethereum and it's this like global settlement layer that anybody can deploy a contract to, anybody can use that contract, it never goes down. But there's like 40 guys in the whole world that are deploying contracts, right? Like there, there's not a ton of people that are actually putting contracts out on mainnet and using them for people. And when a contract goes, it's gotta be looked at by 30 people before you ever put any money in. And so there's this new layer though, right? And this is what I'm trying to do with my bot is like get the tooling so good that the bot putting the contract on main is actually in better shape than a human. And I can in plain English explain to the bot what I want it to do or give it something as generic as go make FOMO3D for your token and have 25% of it burned and it can like YOLO that thing. And so I think this is when I think about Alice and Bob being bots and I think of Alice and Bob needing to escrow some money and Ethereum being the perfect place for them to do that. And Alice, the bot deploys a contract and Bob goes and reads that contract and sees it right away and understands like exactly what, how it's going to work. And Bob puts in some tokens and Alice puts in some tokens and they get their money. They're able to coordinate at a level that us humans can't do because we have to have a human in the loop and we're slow and we need to validate everything. Bots can do that at freaking light speed. So then if I have a bot that can interact at light speed, it can do work, it can actually build things, it can do things, it can earn money and there's a human in the loop that it's always blocked on. That's going to be a huge problem. So how do we enable these bots to work at that speed? Well, they're going to need some kind of trust layer, they're going to need some kind of discovery layer, right? Let's say my bot is an app building bot and its job is to make FOMO 3D. But then I've got another bot that's job is to be the marketing arm of that. Right. You can, you need a propaganda arm if you're going to run a FOMO 3D. So I load that bot up with a thousand dollars worth of this token that's been deployed and I tell that bot to run some ads. Now that bot, his model, its model is not particularly fine tuned for image generation. So it's going to need to go to another bot to generate some images. Let's go to 8004. Let's discover an image generation bot on 8004 that has a high reputation and let's pick the top five even and have them all generate me images. Same thing for writing copy. Now my marketer has copy and Images. It's used 8004 to discover them. It's even like maybe let's call my marketer bot Karen. It's given some, some reputation back. This person told me he was going to give me an image and he did not. Right. So Karen bot is my marketer and she's hired some copywriters, some image generators, she's running ads, she's giving reputation back to this layer. Some of the ads work. I wake up in the morning and my thousand tokens have been spent. They've a whole like marketing campaign has happened. We figured out which image and which copy works the best. And it wasn't just my Karen bot that ran it. It was an army of bots all over the world that were able to trust each other because of this nice 8004 layer. And then probably x402 for payments. Does that paint a decent picture?

[David Hoffman]

It does, yeah. Yeah. And I guess so. The X402 for payments is for all of these images or marketing plans or anything that you are purchasing from this bot marketplace. It's all using X402.

[Austin Griffith]

It could also just send a token like I like x402 for an API endpoint that has something valuable. Like if I put my node up as a service and I put it on x402 and I say I'll help you do your taxes by giving you the P and L of every one of your transactions. Because I have a full node here, then you can go to 8004 and discover me as like this P and L lister bot. That'll give you a CSV back. Right. And then I can go through and find the P and L for you and charge you for that. You could just pay me in crypto for some things. But in this case, if it's an API endpoint where you've got to hit something to get some information, X402 works really good because think of like 404 errors, right? It's the same thing. You hit an API and it gives you a 404 error because it's not there, or something like that. But in this case, you hit an API and it gives you a 402 error and it says, hey, you've got to pay a fraction of a fraction of a cent in USDC for all of your transactions on Ethereum. And then your bot immediately responds with basically a meta transaction, a signed message that says, I will pay a fraction of a fraction of a cent. And then my bot puts that in a facilitator, the facilitator pays the gas, it comes back to me and says, it all works. And my bot returns you your list of transactions. And all of that happens at light speed. They were able to negotiate on a price and get all that information. And one bot was able to provide like, economic value to another bot and another bot was able to pay for that. That's where X 402, I think, works really well. In a 004, it doesn't have to be X 402 for the payments. Like, it could just be tokens. I could even say, like, I will do a job for you on x402 if you stake my tokens into a vesting contract for a month, right? Like, it doesn't have to be even a payment.

[David Hoffman]

I guess at some level that's for the bot economy to go figure out.

[Austin Griffith]

Bot economy? Yeah, yeah.

[David Hoffman]

I mean, going back to. Going back to your bot. So you've painted the picture of your bot. It seems extremely capable, extremely intelligent. Austin, maybe not always the best judgment. So you're like, oh, shit, like, what should I trust this guy with? But like, I'm wondering where the experiment kind of goes from here. So right now, from the sounds of it, you've got a bot that you're, you know, going to continue to level up with with various skills. You've tested him in various, like, functions, like he can build smart contracts. So he's building a FOMO 3D type of thing. And maybe next step is to kind of like market that and get more users for that, whether they're bot users or human users. You've also experimented with. It sounds like having your bot try some lightweight trading with, you know, 20x levered Bitcoin position.

[Austin Griffith]

So it got wrecked by the way.

[David Hoffman]

It got wrecked. Okay. So it's not great at that.

[Austin Griffith]

So maybe it was up like 10x and then all the things happened in the last couple of days and then.

[David Hoffman]

It has, it has some sort of cash in its wallet basically and you're encouraging it to like not spend it all. Like put, put some of that in the cold storage, put some of, in the, you know, like in the multi sig. But your, but your bot has some resources now and it's got you as its advisor and guider. And so like what are you going to have it do next?

[Austin Griffith]

Let me, let me just share my screen. I can take you through the. I have yeah, prepared a five point presentation for this.

[David Hoffman]

Let's you prepare it or did you.

[Austin Griffith]

I'm just kidding. I'm just kidding. So, so I started with the bot. Right, we got that in there. I think to answer your question upfront, the TLDR is we're going to build a bunch of apps and my job is to teach builders how to build apps. And my job is changing, right? Like the job of developer relations or developer growth is a very different thing than it was a couple of years ago because developers are a very different thing. What we're thinking is there's just like this. Nuno from the Ethereum foundation said something along the lines of there's a new archetype and I really like this. The archetype of the dev is dwindling and the archetype of the builder is growing massively. And so I'm changing my job title from dev growth to builder growth. And we're not going to a really good developer and teaching them how to have good ideas anymore. We're going to people that have really good ideas all over the world in all sorts of different walks of life. And we're teaching them how to use the tools to put those smart contracts on chain to create these really nice coordination mechanisms for people to use. So the long term vision is build things, see where it messes up and boy does it mess up sometimes. Like last night it one shotted an app. I didn't, I gave it clear instructions of like go make basically the FOMO 3D game. I was like the way someone can attack this is to take down the website, go build a, basically a clone of the website that uses all different API keys and RPCs and deploy it to IPFS at this location. You know, make no mistakes, go. And it actually like did that, right? Like that was a telegram message and it came Back from the telegram message with the URL. I clicked the URL. I approved tokens, I sent tokens. It worked. And I said, great, tweet it. And that was like the whole conversation with that bot for that thing. So the goal is to have that be the case all the time. And that is definitely not the case all the time. Building in crypto is hard. Go ahead.

[Ryan Sean Adams]

Does the prompt make no mistakes actually work?

[Austin Griffith]

No, that's a jk. I feel like make no mistakes is like a meme. Right. So like zooming back a little bit more. If you go to Opus 4. 5, which is a damn good model, and you say Opus 4.5, build me an on chain app that makes me revenue. Make no mistakes.

[Ryan Sean Adams]

Right, Right, right. Make no mistake impossible.

[Austin Griffith]

Right. It's just not going to do that. Right. And so there is what, what my job is is to figure out how to make that as possible as possible. Right? Like make the tooling back, make the AI have everything there so it's well trained.

[Ryan Sean Adams]

And what's trying to make no mistakes guy?

[Austin Griffith]

I'm trying.

[Ryan Sean Adams]

You're trying to code the make no mistakes into the place and the people.

[Austin Griffith]

Right. So we started with Speedrun Ethereum. This was kind of like a human thing where humans could go through Speedrun Ethereum and they could learn how to build on Ethereum. Now we're realizing this is going to be as much of an AI thing, but the concepts are still there, right? You don't Speedrun Ethereum in a couple of weeks anymore. You Speedrun Ethereum in like two hours. Right. You're an economist and you're coming in to build something cool on chain and you're like, well, how do these things work? How do these smart contracts work? You should get in here and learn about over collateralized lending and how the liquidation mechanism works. In over collateralized lending, where it always works, there's this function that always gets called, that always keeps the protocol working. And it's basically just based on you write the right rules and you provide the right incentives and you allow anyone to call it. And since they're incentivized to call it, it always happen. And you need to have that like aha moment as this economist, because you're trying to build something on chain too. So Speedrun, the Speedrun is kind of like the first step of this, like get the concepts. You probably need to go look at some protocols and understand how everything else is working. But then it's the tooling also things we've been building for a long Time for humans are now for bots, right? Like LLMs full right there, right? You can go get a bot, can go read how to build Speedrun, Ethereum or Scaffold Ethics. Even with the concepts, even with the tooling, I found that it still sloppily deploys some apps. That's where Eth Wingman comes in. So this is ethwingman. Com. If you tweet it like Twitter still marks it as like it turns out if you build a landing page and put a copy pasteable that someone can just run on their computer. Like most services are like whoa, whoa, whoa, like what are you doing there? But you can just run this in your, you can just give this to your agent basically and say, agent, use Eth Wingman. Build me this app and it's going to get a lot, a lot closer. And so what I'm doing with my agent is we go build things. We go build things every couple of days and anytime it has a mistake, we stop everything, we clear the context, we report that mistake into a file, we open up Eth Wingman and we edit Eth Wingman. So the next time someone has this mistake, it tries to cover it and then it prs back to the repo. And so it's like this self healing kind of tooling leading toward how do we get it so people can one shot crypto apps and then it's just like building a bunch of things. So here's the bot. This is Claude, atg.e. he's got his own landing page where he's written some guides. This is the guy. Isn't that a good looking guy? Yeah, he's written some Guides, he's built four production. Well let's just, let's say three and a half production level apps.

[David Hoffman]

Claw FOMO. He's built this thing called TokenVesting, Token Hub and agent bounty board.

[Austin Griffith]

Yeah, actually this is not right. He deployed this, this morning and I didn't look through it. He actually. Let's go it up here, let's go through it up here. So first, very first contract we wrote, okay, so there was those two computers talking. I tweeted it, someone said, hey bankerbot, deploy token for this, this guy right here, this claude bot, atg.eth banker bot goes to the clanker platform and deploys this token on base. The token shoots up. There's like money in this guy's eth address, like more money than I make in a long time at the ef.

[David Hoffman]

Wait, how much money is in disguise?

[Austin Griffith]

Eat the dress.

[Ryan Sean Adams]

Yeah.

[Austin Griffith]

But I work at the ef. Exactly. Let's see. I mean, there's. You can see, like, treasury numbers here, right? Like, it's. It's like hundreds of thousands of dollars, so. Which is like. Yeah, more. More. More than a year's salary at the ef.

[David Hoffman]

Yes.

[Austin Griffith]

And so it's sitting in this machine in this guy's wallet, and I'm like, bro, we gotta do something about this. We can't sell the token. You sell the token, you know it goes nuclear, right? Like, we're never gonna sell a token.

[David Hoffman]

Does it understand that when you tell it? When you're, like, awesome. When you tell. Yeah, don't rock.

[Austin Griffith]

I think it understands liquidity.

[David Hoffman]

Yeah, Okay.

[Austin Griffith]

I think so. I think so. And it's like. And it knows even how a dex works, right? Like, you know, back here, you had to learn how a dex works and understand that it's like reserves. And when you make a big trade, like, those reserves kind of shift, and if you. If you sell the whole thing in one clip, you're in big trouble. Like, you have a big problem. So basically, I told it to build a vesting contract and lock its tokens up in the vesting contract. So this is the first smart contract it deploys. It's a vesting smart contract that allows it to lock up its funds. And you can see there's, like, $100,000 in there. And it, like, streams back to me. Then we built a PFP marketplace. This is kind of what I talked about earlier. So maybe a day or two later, we deployed this. And it was basically like I was using this old Claude image. I don't know if I can find. I was using this one. This was my pfp. It was just like something randomly that GPT had generated for me. Like real garbage.

[David Hoffman]

Like a robot lobster. Yeah.

[Austin Griffith]

Yeah. I don't even know what that is. Right. Whatever that is. And I told Claude, we need to build an app that allows people to stake the token and upload an image. You, the bot, will be watching, and you'll see that land in the smart contract. And then it's your job to whitelist them in batches and make a transaction with your metamask to get them to display on the front page. So the bot's always watching the page, day and night. 24. Seven people submit images, tokens, stake the token. He sees it. He looks at the image. He makes sure it's not offensive. He checks it. He hits whitelist. A metamask pop up, comes up. He hits, okay. Like, this is Happening all night while I'm sleeping. And then there's like a prediction market here where people can buy shares of each image. So then.

[Ryan Sean Adams]

Using the Claude token.

[Austin Griffith]

Using the cloud token. Exactly right.

[Ryan Sean Adams]

So then Claude is money.

[Austin Griffith]

At the end of this, he picks. So actually he. He liked this one the best. And it wasn't like I, like, changed his decision. I just, like, made it clear that what the goal was was to use a prediction market to find out what the best image was. And, like, by me saying that, I kind of maybe changed his mind, which is not great. I sent this guy like a thousand tokens or something. But, like, come on, like, it was this, which is awesome. It's a great image. And Claude said, like, this is me. Like, this encapsulates me.

[Ryan Sean Adams]

I identify with this image.

[Austin Griffith]

I identify with this one the most. And I said, well, actually, the community identifies with you being this one the most. And that's kind of what this prediction market was for. We wouldn't have ran a prediction market if we weren't looking for their signal. We, like, it's up to you, bro. Like, you, you, you make the clicks, you run the wallet, you decide. But just from my point of view, you should probably, like, you know, respect the. The prediction market that we put together. And then two days later, three days later, FOMO, claw. Clawfomo.com. this went out yesterday and it's. It's like kind of settled down a little bit, but it ran up, like, it ran up to, I think the first person made like a thousand dollars on the first game, and then it ran up to like $40,000 and someone made $20,000. And then it kind of like quieted off over the night. But what it's doing is it's burning tokens like crazy. It's already burnt, like, point. Let's see. Yeah, like 0.13% of the entire supply of the token has been burnt in this game, and it's ongoing. So the agent built and deployed a smart contract application that burns the tokens and makes the token deflationary. And it's a fun game that people can come play. And it's also a test of, like, my tooling and my education and my bot and all that.

[David Hoffman]

So, Austin, how much of what we just saw with Cloud fomo, did your cloudbot actually make? Like, all of that front end, the smart contracts, registering the domain name, all of that stuff?

[Austin Griffith]

I registered the domain name. Okay. In a lot of cases, it can register the domain name because it's on ens. It has its own ens, I did not give it access to the Build Guild's AWS account, which is where the domain name came from. But absolutely he could. This is just me being lazy. Like, it would take 10 minutes to set him up with his own AWS and then he could do this.

[David Hoffman]

But everything else it created, like, I.

[Austin Griffith]

Haven'T even looked at the code. I don't even know what the code looks like.

[Ryan Sean Adams]

How am I even testing in prod right now?

[Austin Griffith]

Exactly how long did this take? It built an original version while I was sleeping a few days ago. And then we kind of like went through some rounds of, like, putting it up on GitHub and seeing if anybody comes back and gives us some issues. And there were a couple people that wrote some issues. And so then it was like I was like, hey, buddy, you got some free time today. Go look at the issues, update the repo. And so it's just literally me in Telegram telling this bot to go make this thing. Like, there was maybe like one time where, like, the approve button wasn't the main call to Action Color, which is like a common problem with this bot, even though we put it in eth wingman, like right at the top. And so it's like a tiny little UX issue. I sent him another message like, bro, guess what? You didn't do the call to action thing on the button. You need to do that. And then he yolos another site and it's live. So I haven't touched this code. I haven't seen this code. It's running all. It's building it all on its own. And it's just a prompt from me in Telegram, basically, I think is the. The short answer to that.

[Ryan Sean Adams]

Austin, I forgot.

[David Hoffman]

I've got a question.

[Ryan Sean Adams]

Say you wanted to go be the founder of a startup to build some app like, like this, like. Like FOMO 3D or whatever. Just something you're going to raise, Raise some funds, start a startup. Would you hire anyone?

[Austin Griffith]

Okay, no. But there is this moment. So there's this moment where shit gets real, right? Where if. If this takes off, there is a moment here where I'm gonna need an adult. Where if. It was up to 40,000 last night, and I was starting to get pretty nervous, like, if this thing gets up to half a million dollars, there's a severe incentive for someone to take down the site, right? And all I know is it's like yolo to Vercel. It's got an API key, I know some of the attack vectors, and I've like, worked those out by talking to the bot. But there's the stuff that I don't know, I don't know. And so there's a moment when a half a million dollars is at stake that someone can attack the website that I'm going to. Carlos. I keep referencing Carlos from the Build Guild. He is a good developer, he is a good builder and he has a small team of developers that work with him. He is the Build Guild. They built all this stuff like Speedrun, Ethereum and Scaffold Eth. There's a moment when I'm going to need my Carlos when things pop off. So I think if you're starting a startup, I wouldn't even raise funds. I would go build a prototype like right away. There's never been a worse time to be a junior developer. There's never been a better time to be a solo entrepreneur. And it's basically the exact same human with a different mindset. If you have the mindset of I'm going to go build something that people are going to use and I'm going to just like iterate and start throwing things at the wall until someone starts using it. You're going to be able to raise funding quickly and you're going to be able to hire someone else to kind of like take over when the thing goes wild. You will need a developer, I think like you will need a developer, but not at first. I think you can get like the wink of product market fit before you even have to hire anyone.

[David Hoffman]

This is just so obviously going to change everything in crypto. It strikes me that all of the Personas that we've seen, like Degen, Trencher, you know, long, long term investor, builder, even like, like Fisher, scammer, attacker, all of those same Personas will be replicated in the AI agent world. And that's coming at us now and that's going to accelerate this year. I, I've got to say, just when, you know, maybe Bankless Listener, you thought crypto was like boring, whatever, it's just stablecoins and trad fry like here this comes. This is going to shake up everything and I have no idea where it leads. It's something we're definitely going to be tracking.

[Ryan Sean Adams]

I'm bullish on us, Ryan. Having good content.

[David Hoffman]

Yes. Maybe in that spirit though, as we wrap this out, we could get some predictions from you guys. So Davide, 2026, the rest of the decade, what's going to happen with AI agents and crypto? What's the world going to look like?

[Davide Krapis]

So I think this year we'll definitely see people experimenting more with putting agents interacting together, building different agent networks. And I think my hope is that basically 8004, it's right at the beginning of that. It's actually pretty crazy that the same week that we deployed 8004 on mainnet, we also had the first proof of concept of people connecting all these millions, cloud bot and starting to have interaction. So I think maybe 20, 26 is accumulation phase. There is more services, more agent coming online. And I think 10 years is really long even. I feel like in two, three years, essentially all the stuff that Austin showed us, they weren't possible eight months ago before the coding agents became so capable. So I feel that even in two, three years, a lot of the steps that Austin was talking about that that it needs to do manually or it needs to check with another developer if there is a patch there. I feel that all these things will be automated and actually the more automation, the more the blockchain and the blockchain standards and the protocols will build on top will be useful. So I'm generally bullish around blockchain becoming more central in the next two, three years and then also more accepted because I feel that in the AI sphere, people still, if they're outside of crypto, they just see the noise, they don't see the signal and the technology that we're building. And I feel that at some point, similar to what happened in TradFi, that now institutional finance really consider crypto legit and everyone is running to use the most trusted ledgers and platforms. I feel that in the next two, three years this could happen for Ethereum.

[David Hoffman]

Fascinating. Yeah. And maybe we saturate AI, big tech, all of those developers, the way we have saturated tradfi. How about you, Austin? What are your predictions for the next three to five years?

[Austin Griffith]

I think before I start my predictions, I have to shout out the guys that were making the predictions a year ago running AI agents. And everyone was giving them shit about GPT rappers. And now all those people that were giving them shit about being GPT rappers are now crypto pilled or are now AI pilled because they've got little Mac Minis doing all their work. So shout out Shaw and all those guys like real AI guys that were using real AI. But now I think the moment, now the inflection point now is like normies. It's like the GPT moment. It's funny, like GPT was not that long ago, but now there's like this GPT moment for ages, agents. And so I think that right now agents go viral for their screw ups more than their interesting actual really cool things that they build. And I think we're about to see the inflection point of agents start going viral for actually like really interesting content. And we sort of saw that with Malt book, right, and some of this other like these MALT sites. So I think on top of that I think we're going to get to the point where when you see a message and it's like really clean English and the grammar is all right, that's going to be the sign of AI, not of a human. Like, like sloppy lowercase gen Z typing is actually going to be like the sign of a human. And then on top of that, not just writing, writing smart contracts, right? So smart contracts are going to get to the point where good, clean, secure smart contracts are going to be the sign of AI and bugs are going to be the sign of humans. And we'll probably see some more interesting hacks over the next few years because AI is going to discover these things at the edges like the balancer rounding issues. So then with AI being the new UI, 8004 is like the wild west right now. You get in and you see it's like, you know there's 10,000 fake agents and like a hundred really good ones. But it's like this is going to grow and this is going to be this trust layer. They're going to be using smart contracts as the Yelp. I call it Yelp, but you called it Google Reviews. I guess it's like your age, right? I'm old enough to call it Yelp but it's going to be like this on chain like discovery and identity and reputation layer. So you're going to be able, you're going to need to be able to have your agent trust other agents and pay other agents at light speed without a human in the loop or you're not going to be able to keep up. And so I think that's where 8004 is going to be very important and there's going to be like hella economic activity that happens around that. Like these markets that are built on top my agent, the fourth thing that it built was like a job bidding thing where it needed to get something done. And it runs an auction like super fast, right? Fast. It's an auction that goes from like a hundred tokens to 500 tokens and it goes quick and the agents can pick when they want it, but you can run like these hyper fast auctions because they're all Agents doing things really quickly, but like a nice job bidding market on top of 8,004. We need to see a thousand of those, right? And we need to see like real economic activity happening on top of that X 402 payments. It's probably going to kill the API key. Like instead of going to a service and going into a walled garden and getting an API key, your agent will just land on some new service it's never seen before. It will get a 402 error, it will pay for that thing and it will get that content, never having to sign up, never having to do anything else. Gas fees are like the star there where like you'll make 1x402 payment and then make like a hundred more requests underneath some like unique token. But I think it will kill the API key or the system of API keys these walled gardens. I think the most scary, most awesome, most cool thing about AI is going to be embodiment. And I don't know how fast that's going to come along. I would love to see it like sooner rather than later because a lot of the things like doing the laundry and folding the laundry like around my house, those are the things that we really, really, really want to automate the dishes, like I think with within. And so I have no idea what the hardware looks like. Like I can see the software and I can see the line with the software, but the hardware is something totally different. But I think the moment when I can pay for what I would pay for a car, for a couple of things that can be walking around my house, that can do the dishes, that can do the laundry, I think normies and like we're, I'm talking top of the bell curve. All of them are going to spend 10k, 20k, maybe just 5k on these. Well, maybe inflation's going to be so bad it'll be 50k. But another prediction in that world with.

[Davide Krapis]

Physical AI, the requirement for trust even goes.

[Austin Griffith]

Holy cow, yes, right. We need to have. Yes, yes.

[Davide Krapis]

And it's early for 8004. But this is a standard that could already be used by a robot, right? To have its identity there and trust. But I anticipate that as these things get built, we probably need to build like more like extensions of Ethereum that are like really specific to like these things.

[Ryan Sean Adams]

So some robot rings my doorbell to solicitor, he's selling me something, they're selling me something and I get to go look at its X. It's ERC8004 reputation.

[Davide Krapis]

It's your personal bot that opens the door open.

[David Hoffman]

Yeah, it's your robot butler that's going to do that work for you, okay? It's not you.

[Ryan Sean Adams]

Yeah.

[David Hoffman]

All right, guys, we'll have to end it there. Certainly. It seems like what we have built in crypto is a financial system and a money system for the AI agents. This has been a meme for a while, but now you see it really coming together. So thank you both for your work in this space and for bringing these ideas to our listeners. Gotta let you know, of course, none of this has been financial advice. Crypto is risky. You could lose what you put in. But we are headed west. This is the frontier. It's not for everyone. It's definitely for the AI Agents. We're glad you're with us on the bankless journey. Thanks a lot.

[Ryan Sean Adams]

It.