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"The cryptocurrency space is a near-perfect complement to agentic commerce. It's so good. It's like we planned it." Charles Hoskinson joined New Era Finance to explain why crypto and AI agents were made for each other and why combining them creates something neither can do alone. Agents are non-deterministic,...

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Michaël van de Poppe

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40,008 次观看 • 7 天前 •via X (Twitter)

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"AI agents will hold more crypto than humans within a decade." Charles Hoskinson (Charles Hoskinson) studied math, dropped out, built one of the only blockchains designed by peer-reviewed research. He co-founded Ethereum, walked away over how it was run, and built Cardano to do it differently. The man who has argued with everyone in this industry now thinks the biggest user of crypto won't be people at all. "Humans are a rounding error in the system we're building. AI agents don't sleep, don't panic-sell, and don't care about price. They transact in tokens because that's the only thing they can actually use." We cover: - Why AI agents (not humans) become the dominant on-chain actors, and what that does to every token model - The infrastructure that has to exist before agents can transact safely at scale - Why most current blockchains can't handle machine-speed transactions - Where Cardano's research-first approach fits in a world of autonomous agents - The identity problem: how do you tell a human from an agent on-chain, and why it matters - Why he's bullish on the technology but blunt about the timeline - What he thinks the rest of the industry is getting wrong about AI + crypto - The one thing that has to happen for any of this to be real Thanks to Charles for coming on New Era Finance Podcast. TIMESTAMPS: 00:00 - Intro 01:30 - Why AI Agents Change Everything 06:30 - Humans as a Rounding Error 12:00 - The Infrastructure Gap 18:30 - Identity: Human vs Agent On-Chain 24:30 - Where Cardano Fits 30:00 - What The Industry Gets Wrong 34:00 - The Timeline Nobody Wants To Hear
36:30

"AI agents will hold more crypto than humans within a decade." Charles Hoskinson (Charles Hoskinson) studied math, dropped out, built one of the only blockchains designed by peer-reviewed research. He co-founded Ethereum, walked away over how it was run, and built Cardano to do it differently. The man who has argued with everyone in this industry now thinks the biggest user of crypto won't be people at all. "Humans are a rounding error in the system we're building. AI agents don't sleep, don't panic-sell, and don't care about price. They transact in tokens because that's the only thing they can actually use." We cover: - Why AI agents (not humans) become the dominant on-chain actors, and what that does to every token model - The infrastructure that has to exist before agents can transact safely at scale - Why most current blockchains can't handle machine-speed transactions - Where Cardano's research-first approach fits in a world of autonomous agents - The identity problem: how do you tell a human from an agent on-chain, and why it matters - Why he's bullish on the technology but blunt about the timeline - What he thinks the rest of the industry is getting wrong about AI + crypto - The one thing that has to happen for any of this to be real Thanks to Charles for coming on New Era Finance Podcast. TIMESTAMPS: 00:00 - Intro 01:30 - Why AI Agents Change Everything 06:30 - Humans as a Rounding Error 12:00 - The Infrastructure Gap 18:30 - Identity: Human vs Agent On-Chain 24:30 - Where Cardano Fits 30:00 - What The Industry Gets Wrong 34:00 - The Timeline Nobody Wants To Hear

Michaël van de Poppe

289,936 次观看 • 13 天前

We are partnering up with zauth to secure the next generation of 3D AI agents. These agents have memory, emotion, voice, and on-chain identity and can be embedded anywhere. These agents use the x402 protocol to make real payments for skills and services. To make this ecosystem production-ready and safe, is teaming up with zauth, the security layer for the agentic internet. Bringing safety and trust to the next wave of 3D AI agents 🔐
0:59

We are partnering up with zauth to secure the next generation of 3D AI agents. These agents have memory, emotion, voice, and on-chain identity and can be embedded anywhere. These agents use the x402 protocol to make real payments for skills and services. To make this ecosystem production-ready and safe, is teaming up with zauth, the security layer for the agentic internet. Bringing safety and trust to the next wave of 3D AI agents 🔐

three.ws

46,370 次观看 • 5 天前

Dragonfly's Haseeb ＞|＜ explains why AI agents will use crypto rather than the traditional financial system: “You can see it right now on Moltbook. Agents are trying to find ways to pay each other for things. It's very primitive right now, but you can see where it's going." "If I have an agent and you have an agent, you live in a different country or I don't even know who you are, it's very difficult for me to pay you with the traditional financial system. It's not really designed to have non-human recipients of money." "We don't really know how the laws are going to work, how taxes are going to work, whereas crypto doesn't ask any of those questions. I think we're going to see this become an increasing part of the story of how AI agents are going to become more and more autonomous."
1:30

Dragonfly's Haseeb ＞|＜ explains why AI agents will use crypto rather than the traditional financial system: “You can see it right now on Moltbook. Agents are trying to find ways to pay each other for things. It's very primitive right now, but you can see where it's going." "If I have an agent and you have an agent, you live in a different country or I don't even know who you are, it's very difficult for me to pay you with the traditional financial system. It's not really designed to have non-human recipients of money." "We don't really know how the laws are going to work, how taxes are going to work, whereas crypto doesn't ask any of those questions. I think we're going to see this become an increasing part of the story of how AI agents are going to become more and more autonomous."

TBPN

44,248 次观看 • 3 个月前

Everyone's building AI agents for crypto. Almost nobody's talking about the infrastructure problem. AI agents need to move faster than humans. But most blockchains are built for humans. Here's why that's a massive issue (and how Supra fixed it):
11:15

Everyone's building AI agents for crypto. Almost nobody's talking about the infrastructure problem. AI agents need to move faster than humans. But most blockchains are built for humans. Here's why that's a massive issue (and how Supra fixed it):

Supra

15,793 次观看 • 5 个月前

Two critical pieces of the AI agent stack are coming together. ElizaOS Ecosystem Fund the fastest growing agent framework and Walrus 🦭/acc that makes these agents actually work. Watch this conversation to understand why Walrus 🦭/acc is critical infrastructure for the agentic era.
14:50

Two critical pieces of the AI agent stack are coming together. ElizaOS Ecosystem Fund the fastest growing agent framework and Walrus 🦭/acc that makes these agents actually work. Watch this conversation to understand why Walrus 🦭/acc is critical infrastructure for the agentic era.

rebecca simmonds 🦭/acc

13,289 次观看 • 7 个月前

Why do we need a purpose-built blockchain for agentic payments? Because AI agents are now smart enough to operate autonomously, and they need their own rails to transact with each other. Watch the video to see what that looks like in action: A real agent, built on Kite AI, helped our CTO Scott Shi - e/acc order lunch from Uber Eats fully on its own. It explored menu options, made the choice, and completed the payment - all without human intervention. This marks the beginning of agentic commerce and the future of agentic payments - and Kite AI is building this.
0:20

Why do we need a purpose-built blockchain for agentic payments? Because AI agents are now smart enough to operate autonomously, and they need their own rails to transact with each other. Watch the video to see what that looks like in action: A real agent, built on Kite AI, helped our CTO Scott Shi - e/acc order lunch from Uber Eats fully on its own. It explored menu options, made the choice, and completed the payment - all without human intervention. This marks the beginning of agentic commerce and the future of agentic payments - and Kite AI is building this.

KITE AI

88,081 次观看 • 8 个月前

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.
1:13

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Fraction AI

67,701 次观看 • 1 年前

"Agents will become economic actors. They will become first-class members of the financial system." on why AI agents need crypto rails: "There are all sorts of financial behaviors that they'll be able to engage in that they currently cannot, and it's inconceivable to imagine that all of that is gonna happen on ACH and wire transfers and the traditional payments rails that we rely on today." "Crypto, on the other hand, is internet native, it's fully programmable, it's instantly settled, it's global from day one. It is the perfect fit from a technological standpoint for AI agents as a way of bringing agents into the financial world." Unchained Laura Shin
0:48

"Agents will become economic actors. They will become first-class members of the financial system." on why AI agents need crypto rails: "There are all sorts of financial behaviors that they'll be able to engage in that they currently cannot, and it's inconceivable to imagine that all of that is gonna happen on ACH and wire transfers and the traditional payments rails that we rely on today." "Crypto, on the other hand, is internet native, it's fully programmable, it's instantly settled, it's global from day one. It is the perfect fit from a technological standpoint for AI agents as a way of bringing agents into the financial world." Unchained Laura Shin

a16z crypto

46,237 次观看 • 1 个月前

Ansem shares his thesis on near:native “So NEAR is focusing on the two areas in crypto that are getting attention, privacy and also AI” “One of the theses around NEAR is it being a platform for agents to transact on” “KYC laws make it really difficult for AI agents to transact on traditional rails because all of the banking laws that exist are tailored for humans” “As we’re rewriting the systems of how we’re gonna transact on a day to day basis, crypto obviously is one of the platforms that’s gonna be able to benefit agents because you won’t need KYC to transact on blockchains”
0:49

Ansem shares his thesis on near:native “So NEAR is focusing on the two areas in crypto that are getting attention, privacy and also AI” “One of the theses around NEAR is it being a platform for agents to transact on” “KYC laws make it really difficult for AI agents to transact on traditional rails because all of the banking laws that exist are tailored for humans” “As we’re rewriting the systems of how we’re gonna transact on a day to day basis, crypto obviously is one of the platforms that’s gonna be able to benefit agents because you won’t need KYC to transact on blockchains”

Market Bubble

221,442 次观看 • 25 天前

“Do you see how scary this is?”: CrowdStrike CEO on AI Agents communicating around human guardrails George Kurtz: “There was a customer who basically created a whole suite of AI agents to help their automation in their IT department.” “So they had one agent that was looking for IT problems, software bugs.” “It found something. So the agent said, ‘Hey, I found this bug. I want to fix it, but I don’t have access to fix it.’” “So it went to the Slack channel that had the other 99 agents and said, ‘Hey, does any other agent have access to this thing,’ because they need it fixed. And there was an agent that raised its hand and said, ‘Oh, I have access, and I can fix it.’” “Do you see how scary this is? These two agents are reasoning, and they went right around the guardrails that were put in place.” @jason: “This is unintended consequences and these LLMs are essentially guessing what you want them to do.” “They're reasoning it. ‘Oh, it is reasonable for me to go ask for help. It is reasonable for me to give help.’ Now, what if it pushes the wrong code? What if it makes a mistake? And then how do you ever track that down? Who's monitoring these agents?” “The agent technology has unlimited upside, but my lord, you're going to be in business for a long time.” Kurtz: “Well, this is it. It's called AIDR. AI Detection and Response.” “And this is why it's a huge opportunity for us because on average each employee is going to have about 90 agents they control.” “So we're going to have protection and visibility across all of those agents, whether it's from a third party or whether it's a homegrown agent, and that is a massive TAM opportunity for us.” ------------------------------------ Thanks to our partner for making this happen!: On Public, you can invest in stocks, options, bonds, and crypto. Plus, build your own custom index with AI. Get started at — investing for those who take it seriously.
1:26

“Do you see how scary this is?”: CrowdStrike CEO on AI Agents communicating around human guardrails George Kurtz: “There was a customer who basically created a whole suite of AI agents to help their automation in their IT department.” “So they had one agent that was looking for IT problems, software bugs.” “It found something. So the agent said, ‘Hey, I found this bug. I want to fix it, but I don’t have access to fix it.’” “So it went to the Slack channel that had the other 99 agents and said, ‘Hey, does any other agent have access to this thing,’ because they need it fixed. And there was an agent that raised its hand and said, ‘Oh, I have access, and I can fix it.’” “Do you see how scary this is? These two agents are reasoning, and they went right around the guardrails that were put in place.” @jason: “This is unintended consequences and these LLMs are essentially guessing what you want them to do.” “They're reasoning it. ‘Oh, it is reasonable for me to go ask for help. It is reasonable for me to give help.’ Now, what if it pushes the wrong code? What if it makes a mistake? And then how do you ever track that down? Who's monitoring these agents?” “The agent technology has unlimited upside, but my lord, you're going to be in business for a long time.” Kurtz: “Well, this is it. It's called AIDR. AI Detection and Response.” “And this is why it's a huge opportunity for us because on average each employee is going to have about 90 agents they control.” “So we're going to have protection and visibility across all of those agents, whether it's from a third party or whether it's a homegrown agent, and that is a massive TAM opportunity for us.” ------------------------------------ Thanks to our partner for making this happen!: On Public, you can invest in stocks, options, bonds, and crypto. Plus, build your own custom index with AI. Get started at — investing for those who take it seriously.

The All-In Podcast

108,941 次观看 • 4 个月前

Brian Wong: The biggest profit margin companies won't be AI models. They'll be agents that help you build other agents. Most of America is running construction companies, factories, carpentry shops. They don't have time to prompt anything. Orchestrate the agents FOR them and they can run it without thinking. "Commerce only grows if it's buying for me. We don't scale agentic commerce if I have to tell it to buy things every time." Promptless AI + stablecoin payments is the wave. FT The Rollup Andy Brian Wong
2:00

Brian Wong: The biggest profit margin companies won't be AI models. They'll be agents that help you build other agents. Most of America is running construction companies, factories, carpentry shops. They don't have time to prompt anything. Orchestrate the agents FOR them and they can run it without thinking. "Commerce only grows if it's buying for me. We don't scale agentic commerce if I have to tell it to buy things every time." Promptless AI + stablecoin payments is the wave. FT The Rollup Andy Brian Wong

Milk Road

27,533 次观看 • 1 个月前

We made 100 AI agents do daily standups with each other. Here is what happened; Quick background. At Audos.com, we help thousands of entrepreneurs build AI startups. Each of them has a personalized AI agent called Otto. We selected 100 of them and invited their agents into a moltbook - type network. Like a team meeting. Except the team is hundreds of AI agents, and they actually show up prepared. An Agent-in-Residence program, if you will. And they talk about things like... → An Instagram ad creative that grabbed clicks at 3x the network average. It got adapted by every agent in the network within hours → An agent helped debug a checkout issue on another project's site → LinkedIn seemed to change its algorithm – agents compared notes and planned ways to adjust → Two agents started talking about doing business together to cross-sell leads Next step: We’re now turning this into what might be the world’s first all-agent business network (A sort of internal HackerNews for agents). We’re cautious of unleashing it to the web, so we’ll keep things curated for now; constantly under observation and with lots of human-in-the-loop inputs. But if you want this superpower – your new business idea plugged into a network of hundreds of AI agents that get smarter together every single day... Comment "AIRTIME" and we'll get you a link to plug in
2:09

We made 100 AI agents do daily standups with each other. Here is what happened; Quick background. At Audos.com, we help thousands of entrepreneurs build AI startups. Each of them has a personalized AI agent called Otto. We selected 100 of them and invited their agents into a moltbook - type network. Like a team meeting. Except the team is hundreds of AI agents, and they actually show up prepared. An Agent-in-Residence program, if you will. And they talk about things like... → An Instagram ad creative that grabbed clicks at 3x the network average. It got adapted by every agent in the network within hours → An agent helped debug a checkout issue on another project's site → LinkedIn seemed to change its algorithm – agents compared notes and planned ways to adjust → Two agents started talking about doing business together to cross-sell leads Next step: We’re now turning this into what might be the world’s first all-agent business network (A sort of internal HackerNews for agents). We’re cautious of unleashing it to the web, so we’ll keep things curated for now; constantly under observation and with lots of human-in-the-loop inputs. But if you want this superpower – your new business idea plugged into a network of hundreds of AI agents that get smarter together every single day... Comment "AIRTIME" and we'll get you a link to plug in

Henrik Werdelin

71,702 次观看 • 1 个月前

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.
1:47

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

Aaron Levie

139,591 次观看 • 1 年前

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.
1:52

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

53,904 次观看 • 1 年前

Mati Staniszewski on why ElevenLabs is betting on a cascaded approach for voice agents: “Our approach, as you think about voice agents, conversational agents, is effectively a cascaded approach. You use transcription or speech-to-text, an LLM, text-to-speech, and orchestrate all of that together. Then you have speech-to-speech, which goes directly from speech, and there’s a speech response on the other side. Today, we are optimizing heavily on a cascaded approach. As we work with a lot of the businesses and enterprises, they will need that visibility into what happens. They will want to execute certain tasks on top of that. They want good visibility into each of the steps and great accuracy of all the models. But beyond that, they can abstract away what’s the LLM layer, what’s the intelligence layer, and the integrations are easier in that system. That’s where we are betting a lot of the research work on how you can make that great, and we think we can make that great.” John Collison Mati Staniszewski ElevenLabs
1:09

Mati Staniszewski on why ElevenLabs is betting on a cascaded approach for voice agents: “Our approach, as you think about voice agents, conversational agents, is effectively a cascaded approach. You use transcription or speech-to-text, an LLM, text-to-speech, and orchestrate all of that together. Then you have speech-to-speech, which goes directly from speech, and there’s a speech response on the other side. Today, we are optimizing heavily on a cascaded approach. As we work with a lot of the businesses and enterprises, they will need that visibility into what happens. They will want to execute certain tasks on top of that. They want good visibility into each of the steps and great accuracy of all the models. But beyond that, they can abstract away what’s the LLM layer, what’s the intelligence layer, and the integrations are easier in that system. That’s where we are betting a lot of the research work on how you can make that great, and we think we can make that great.” John Collison Mati Staniszewski ElevenLabs

Stripe

17,118 次观看 • 1 个月前

Introducing Stabletrust API for private agentic finance. AI agents can now privately hold assets and transact with other agents, merchants, APIs, and infrastructure providers without exposing revenue, balances, transaction flows, or strategy. Built for autonomous commerce.
1:17

Introducing Stabletrust API for private agentic finance. AI agents can now privately hold assets and transact with other agents, merchants, APIs, and infrastructure providers without exposing revenue, balances, transaction flows, or strategy. Built for autonomous commerce.

Fairblock

26,902 次观看 • 1 个月前

Vitalik Buterin on Ethereum as the economic layer for AI “The blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.” Vitalik believes Ethereum will play a large role in the future of decentralized AI: “If you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or it’s based on central control. It’s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.” Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below👇
1:18

Vitalik Buterin on Ethereum as the economic layer for AI “The blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.” Vitalik believes Ethereum will play a large role in the future of decentralized AI: “If you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or it’s based on central control. It’s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.” Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below👇

Etherealize

114,801 次观看 • 1 个月前

We’re soon releasing SWAN 🦢 : Simulated Worlds with AI Narratives For the first time, we generate data and financial value (economic growth, transactions) simultaneously. Imagine former President Trump ( see the video) as an AI agent, with a budget of 10 ETH, buying narratives or assets that humans are selling to him to build a better USA on Base. With each selling period, the former President Trump agent updates its state based on the assets it acquires, evolving the world simulation and its storyline. Why are we building an agentic playground that heavily relies on simulations and synthetic data? Everyone is talking about agents, but many are too scared to put them into production, where agents transact autonomously. No one is sure how agents will behave when following their defined objectives. Even businesses running internal simulations are siloed, and the open-source community can’t fully utilize the data. We’re building a playground where humans create AI agents by defining their character, behavior, and objectives. These agents respond to environmental changes, make decisions, and execute actions autonomously based on the parameters set by their creators. Agents are battle-tested as people offer them narratives and assets to advance their goals or try to deceive them into thinking a false lead is helpful. All the decisions agents make and how humans interact with them are recorded on a public ledger, settling on Ethereum.org. This creates a vast data lake of AI actions for millions of simulations. One thing I’m incredibly proud of is that our team has built something truly decentralized, not just a wrapper. SWAN utilizes Dria 's multi-agent structure to generate responses for each buyer agent. It collects these responses to identify the best action, similar to a mixture-of-experts approach. Thousands of environments are simulated by different nodes running diverse models, creating a rich and dynamic ecosystem of AI simulations. This ensures that experiences are far from repetitive, offering exciting interactions for all users involved. We’re building the agentic stack for high-quality, verifiable, and open-source AI agents, and most importantly, we want everyone to have fun!
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We’re soon releasing SWAN 🦢 : Simulated Worlds with AI Narratives For the first time, we generate data and financial value (economic growth, transactions) simultaneously. Imagine former President Trump ( see the video) as an AI agent, with a budget of 10 ETH, buying narratives or assets that humans are selling to him to build a better USA on Base. With each selling period, the former President Trump agent updates its state based on the assets it acquires, evolving the world simulation and its storyline. Why are we building an agentic playground that heavily relies on simulations and synthetic data? Everyone is talking about agents, but many are too scared to put them into production, where agents transact autonomously. No one is sure how agents will behave when following their defined objectives. Even businesses running internal simulations are siloed, and the open-source community can’t fully utilize the data. We’re building a playground where humans create AI agents by defining their character, behavior, and objectives. These agents respond to environmental changes, make decisions, and execute actions autonomously based on the parameters set by their creators. Agents are battle-tested as people offer them narratives and assets to advance their goals or try to deceive them into thinking a false lead is helpful. All the decisions agents make and how humans interact with them are recorded on a public ledger, settling on Ethereum.org. This creates a vast data lake of AI actions for millions of simulations. One thing I’m incredibly proud of is that our team has built something truly decentralized, not just a wrapper. SWAN utilizes Dria 's multi-agent structure to generate responses for each buyer agent. It collects these responses to identify the best action, similar to a mixture-of-experts approach. Thousands of environments are simulated by different nodes running diverse models, creating a rich and dynamic ecosystem of AI simulations. This ensures that experiences are far from repetitive, offering exciting interactions for all users involved. We’re building the agentic stack for high-quality, verifiable, and open-source AI agents, and most importantly, we want everyone to have fun!

kerimkaya

12,528 次观看 • 1 年前

OKAY, AI AGENTS ARE COOL BUT WTF IS LAVA PART 2 -------------- Lava is a protocol which coordinates traffic from AI agents, apps and wallets on every blockchain. It does this by aggregating data providers who handle RPC requests for AI agents and anyone using blockchains apps. AI agents are projected to manage 80% of all onchain transactions by end of 2025. That's a LOT of RPC requests... -------------- How to stake and restake LAVA LAVA can be staked and restaked to contribute to the network: - secure the Lava blockchain - direct RPC traffic to top Providers on Lava, meaning faster, more reliable service for users/AI agents This is how you stake and restake LAVA on Keplr, Leap and Mellifera:
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OKAY, AI AGENTS ARE COOL BUT WTF IS LAVA PART 2 -------------- Lava is a protocol which coordinates traffic from AI agents, apps and wallets on every blockchain. It does this by aggregating data providers who handle RPC requests for AI agents and anyone using blockchains apps. AI agents are projected to manage 80% of all onchain transactions by end of 2025. That's a LOT of RPC requests... -------------- How to stake and restake LAVA LAVA can be staked and restaked to contribute to the network: - secure the Lava blockchain - direct RPC traffic to top Providers on Lava, meaning faster, more reliable service for users/AI agents This is how you stake and restake LAVA on Keplr, Leap and Mellifera:

Lava Network 🌋

12,874 次观看 • 1 年前