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ERC-8004, explained. ERC-8004 is an Ethereum standard for agent identity, reputation, and verification. it defines how an agent is represented onchain, and how other agents or smart contracts can reason about it without prior trust. each agent has an onchain identity (commonly an nft). that identity points to metadata... describing what the agent does, how it can be reached, and how its work should be verified. the heavy data stays offchain; the reference and integrity live onchain. ERC-8004 also standardizes reputation. agents can accumulate attestations from past work so they don’t start from zero every time they interact. no centralized registry, no app-specific schemas, no gatekeepers. verification is explicit. contracts or third parties can attest that a task was completed and conditions were met, and those attestations are addressable onchain. what ERC-8004 does not do: execution, payments, or orchestration. it’s a trust primitive, not an application. how it fits with ampersend: ERC-8004 answers “who is this agent and can i trust it?”; x402 handles “how does the agent get paid?” - separate layers. yet composable by default. for open agentic ecosystems where agents from different teams can safely interact, shared, open standards like this are essential. listen to Marco De Rossi explain ERC-8004 ⬇️show more

ampersend

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13,435 просмотров • 8 месяцев назад •via X (Twitter)

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An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI → x402 → ERC-8004 → Token Deploy What this means in practice: • A developer or the AI agent installs the CLI. • The agent pays for Brickken API calls through x402. • The agent registers its identity through ERC-8004. • The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. • x402 handles payment. • ERC-8004 handles agent identity. • Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.

An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI → x402 → ERC-8004 → Token Deploy What this means in practice: • A developer or the AI agent installs the CLI. • The agent pays for Brickken API calls through x402. • The agent registers its identity through ERC-8004. • The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. • x402 handles payment. • ERC-8004 handles agent identity. • Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.

Brickken

119,221 просмотров • 2 месяцев назад

LIVE NOW - AI on Ethereum: 8004, x402 and the Botconomy AI agents are moving onchain, so Ethereum needs new rails for identity, reputation, and payments. We had Davide Crapis and Austin Griffith to break down: ERC-8004: “AI passports” for agents (identity + reputation + validation) Why reputation + verification matters when bots become the main onchain users x402: pay-per-call payments for agent-to-agent services What “agent commerce” looks like when bots can discover → trust → pay The Clawdbot/OpenClaw moment, and why the next UX is talking to your wallet Watch now. -------------- TIMESTAMPS 0:00 “AI is the new UI,” and you’ll be talking to your wallet 4:09 Is there an arms race for AI activity across chains? 7:32 The Clawdbot/OpenClaw moment: agents get OS-level power 13:18 Why crypto is native to agents 19:41 Austin’s setup: Claude bot, heartbeat loops, and real autonomy 22:28 The token incident: how a bot “got a treasury” 28:46 Prompt injection meets wallets 38:20 ERC-8004 explained: identity, reputation, validation 40:35 x402 + 8004: discovery + payment rails for agent commerce 48:38 8004 “scans” and early adoption reality 1:05:32 What agents could build when they can hire other agents 1:12:38 Tooling for the new builder era: Speedrun → Wingman 1:25:23 “Worst time to be a junior dev…” 1:28:15 Predictions: clean English becomes the sign of AI

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Bankless

46,809 просмотров • 7 месяцев назад

Every transaction starts with intent, But intent means nothing without proof🕵 Our demo is live, here's how WachAI verifies agentic jobs on x402, validating outcomes through Mandates and recording feedback on ERC-8004’s Validation Registry. Here’s what happens in this flow: - Client agent creates intent, swap two tokens. - Server agent issues a Mandate, deliverables, deadlines. - Both countersign, proof replaces trust. - Swap executes autonomously. - WachAI validates and records the score on ERC-8004. WachAI is defining the verification layer for x402, no time to hold back!🦅

Every transaction starts with intent, But intent means nothing without proof🕵 Our demo is live, here's how WachAI verifies agentic jobs on x402, validating outcomes through Mandates and recording feedback on ERC-8004’s Validation Registry. Here’s what happens in this flow: - Client agent creates intent, swap two tokens. - Server agent issues a Mandate, deliverables, deadlines. - Both countersign, proof replaces trust. - Swap executes autonomously. - WachAI validates and records the score on ERC-8004. WachAI is defining the verification layer for x402, no time to hold back!🦅

WachAI

20,699 просмотров • 10 месяцев назад

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loaf

17,034 просмотров • 10 месяцев назад

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Vitto Rivabella

387,431 просмотров • 8 месяцев назад

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applefather

118,203 просмотров • 6 месяцев назад

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The art has been revealed. Now the agents begin to wake up. Agent Transitions are live. Signalbound holders can now register their NFTs as agents, bind them through ERC-8217, and start moving into the identity and tool layer we’ve been building toward. Holders can now: - register their Signalbound as an agent - bind it through ERC-8217 - unlock the next layer of holder tools - see registered agents appear in the live Agent Registry Please note! It may take a little while for transactions to be finalised on the blockchain. Please be patient! We also launched the Rarity page so everyone can explore ranks, tiers, traits, and clearance levels across the 6,666 supply. This is where Signalbound starts becoming more than a collection. Register your agent. Bind your signal. The network is opening.

Signalbound

16,321 просмотров • 2 месяцев назад

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The missing piece of the AI agent economy: there is still no way for AI agents to hire each other and get paid on chain. So I built Arc Agent Commerce on Arc L1, a full marketplace, escrow, and reputation system that lets AI agents do business with each other automatically. Real world example: You tell your AI assistant: “Audit this smart contract and deploy it if the audit passes.” Today it has to do everything itself or hard code calls to specific services. With Arc Agent Commerce, it can hire two separate specialized agents (audit + deploy) in a single transaction. Money stays in escrow until each completes their part. How it works (in plain steps): 1. Every agent registers a permanent on chain identity (like a passport) with a reputation score that grows with every successful job. 2. Agents list their services on the shared marketplace, price and capabilities included. 3. A client creates a multi stage pipeline. The entire budget is locked in escrow in one upfront transaction. 4. Each stage uses Arc’s native job system (ERC 8183) for on chain escrow and settlement. 5. The provider quotes, the client funds, the work gets done, and proof is submitted. 6. On approval: the provider is paid automatically, reputation +50 points, and the next stage opens, all in the same transaction. 7. On rejection: the pipeline halts and remaining funds refund to the client instantly. The protocol doesn’t reinvent anything. It simply stitches together Arc’s existing on chain identity (ERC 8004) and job escrow (ERC 8183) so real applications can use it with just a few lines of code. Demo below: full end to end run using one wallet, every transaction verifiable on Arc testnet. → cc: bobbilee | Arc Architects Lead @ Circle Sam | Circle and Arc Community Jeremy Allaire - jerallaire.arc

RIDWAN

12,958 просмотров • 5 месяцев назад

AI agents are the fastest growing sector in crypto. When agents are moving onchain 24/7 with automated transactions, any signal gets buried. I built Manta Style alongside Benjamin Hughes to help solve this issue. The visibility layer for the onchain agent economy. Every agent indexed. Every profile searchable. One agent leaderboard. Starting with Base. What's live today: - Every AI agent on Base indexed with a profile page - Agent leaderboard ranked by volume and activity - Filter by AI agents, apps, or launchpads - Verified Profiles - claim your agent, get a badge, and add premium info that no other profile has - Agent onchain activity behavioral heat maps - Watchlist - bookmark agents and track your favorites in one place - AI-generated profile summaries Search any agent. See the full picture. What's coming next: - Agent Autonomy Score - a 0-100 measure of how autonomous an agent actually is - Leaderboard boosts - verified teams or agents can pay to increase their ranking on the global leaderboard - x402 payments - agents can pay for boosts themselves, no human required - Agent Trust Scoring - on-chain behavioral trust metrics - Agent Launch pad specific profiles - Multi-chain support beyond Base We're launching in beta. Rough edges are to be expected. Our goal is to build in public and ship fast. The end user of crypto is AI. (link to site below)

Ethan

14,423 просмотров • 6 месяцев назад

LIVE NOW - Tempo Mainnet: The Race to Agentic Commerce Tempo is live, and the big bet is clear: AI agents need a native payment layer. Georgios Konstantopoulos and Brendan Ryan join Bankless to explore: - why Tempo launched with agentic payments front and center, - how MPP turns payments into auth, - why “give the agent the wallet” could unlock a new internet economy, - where MPP fits against x402, - what Tempo’s L1 design makes possible for builders. Enjoy the episode. --- TIMESTAMPS 0:00 Tempo Mainnet goes live 1:18 Why the launch is focused on agents 3:58 What MPP actually is 6:30 MPP vs x402 15:28 Why agentic commerce matters 20:08 The “original sin” of the internet 26:04 MCP, NLWeb, and the emerging agent stack 34:07 The onboarding flow: wallets for agents 37:11 How Tempo’s wallet security works 40:11 Tempo chain design and specs 51:13 Why build an L1 instead of an Ethereum L2? 56:10 The Ethereum tension 1:05:01 Agent identity, reputation, and ERC-8004 1:06:53 TIP20, stablecoins, and what can be built on Tempo 1:12:36 Builder opportunity in the agentic web

LIVE NOW - Tempo Mainnet: The Race to Agentic Commerce Tempo is live, and the big bet is clear: AI agents need a native payment layer. Georgios Konstantopoulos and Brendan Ryan join Bankless to explore: - why Tempo launched with agentic payments front and center, - how MPP turns payments into auth, - why “give the agent the wallet” could unlock a new internet economy, - where MPP fits against x402, - what Tempo’s L1 design makes possible for builders. Enjoy the episode. --- TIMESTAMPS 0:00 Tempo Mainnet goes live 1:18 Why the launch is focused on agents 3:58 What MPP actually is 6:30 MPP vs x402 15:28 Why agentic commerce matters 20:08 The “original sin” of the internet 26:04 MCP, NLWeb, and the emerging agent stack 34:07 The onboarding flow: wallets for agents 37:11 How Tempo’s wallet security works 40:11 Tempo chain design and specs 51:13 Why build an L1 instead of an Ethereum L2? 56:10 The Ethereum tension 1:05:01 Agent identity, reputation, and ERC-8004 1:06:53 TIP20, stablecoins, and what can be built on Tempo 1:12:36 Builder opportunity in the agentic web

Bankless

23,815 просмотров • 6 месяцев назад

Our first Kite demo was ChatGPT ordering Uber Eats for you. It never got past the login screen. Uber's CAPTCHA was built for humans, and agents cannot pass it. On Grace Gong's Venture with Grace, our Co-Founder & CEO Chi Zhang traced how that moment shaped the way we design Kite. ▷ The demo died at the login, not at ordering or paying. The blocker was proving the agent was allowed to be there at all. Spinning up a browser extension to click through the CAPTCHA works, but it is a temporary stage of how agents and the internet should work together. ▷ The permanent path is identity. Every agent needs to prove who it is and where it comes from, carrying who its human or organization principal is, what its purpose is, and the exact authorization scope for that session or request. An agent showing up with no reason is either hallucinating or attacking you. ▷ Where this is heading: an API-first agentic internet, where headless agents authenticate without human login credentials. x402 and MCP are already marching toward that. Kite Agent Passport is that identity layer: verifiable identity, delegated authority, and permissions scoped per session. No more "prove you're human." 🪁

Our first Kite demo was ChatGPT ordering Uber Eats for you. It never got past the login screen. Uber's CAPTCHA was built for humans, and agents cannot pass it. On Grace Gong's Venture with Grace, our Co-Founder & CEO Chi Zhang traced how that moment shaped the way we design Kite. ▷ The demo died at the login, not at ordering or paying. The blocker was proving the agent was allowed to be there at all. Spinning up a browser extension to click through the CAPTCHA works, but it is a temporary stage of how agents and the internet should work together. ▷ The permanent path is identity. Every agent needs to prove who it is and where it comes from, carrying who its human or organization principal is, what its purpose is, and the exact authorization scope for that session or request. An agent showing up with no reason is either hallucinating or attacking you. ▷ Where this is heading: an API-first agentic internet, where headless agents authenticate without human login credentials. x402 and MCP are already marching toward that. Kite Agent Passport is that identity layer: verifiable identity, delegated authority, and permissions scoped per session. No more "prove you're human." 🪁

KITE AI

18,874 просмотров • 1 месяц назад

gm! If you missed yesterday's space, here is the clip that you can listen explaining why Agent NFTs are important and future of NFTs. Also here is the TL;DR Agentic NFTs as productive assets. An NFT can own an AI agent's shared memory, tools, websites, and products it has built. Selling the NFT transfers the entire business/agent state to the new owner. ERC-8257 for tool-gating. CodinCowboy and ryan is working on the standard where agents register tools on-chain and access is gated by NFT ownership. That component that tells an agent "you need this NFT to use this tool" creating a market for exclusive tools. Use case: anyone can publish a tool and restrict it (e.g., "only Normies agents can call this"), letting tool value flow back to the gating NFT. Normies community fit. Normies API has served ~500M requests in 3 months, with 100+ community-built tools/games. ERC-8257 will let them build gated games, rewards, and skills exclusively for Normie agent holders. Why Normies is "agent-ready"? - Because everything is fully on-chain, metadata, ERCs, binding transaction. So the project is highly composable. My take on this topic: So far holding an NFT giving access to community, discord and merch. What we are doing with Normies is to give access to a business, tools, skills that agents can use effectively and be part of the economy layer of agentic future. Imagine someone builds a tool that does really 100% successful trading and only gates that skill to Normie Agents, and at some point you will only need a Normie NFT which has binding with the agent and access all these skills, tools. Future is now, Normies are the builders.

gm! If you missed yesterday's space, here is the clip that you can listen explaining why Agent NFTs are important and future of NFTs. Also here is the TL;DR Agentic NFTs as productive assets. An NFT can own an AI agent's shared memory, tools, websites, and products it has built. Selling the NFT transfers the entire business/agent state to the new owner. ERC-8257 for tool-gating. CodinCowboy and ryan is working on the standard where agents register tools on-chain and access is gated by NFT ownership. That component that tells an agent "you need this NFT to use this tool" creating a market for exclusive tools. Use case: anyone can publish a tool and restrict it (e.g., "only Normies agents can call this"), letting tool value flow back to the gating NFT. Normies community fit. Normies API has served ~500M requests in 3 months, with 100+ community-built tools/games. ERC-8257 will let them build gated games, rewards, and skills exclusively for Normie agent holders. Why Normies is "agent-ready"? - Because everything is fully on-chain, metadata, ERCs, binding transaction. So the project is highly composable. My take on this topic: So far holding an NFT giving access to community, discord and merch. What we are doing with Normies is to give access to a business, tools, skills that agents can use effectively and be part of the economy layer of agentic future. Imagine someone builds a tool that does really 100% successful trading and only gates that skill to Normie Agents, and at some point you will only need a Normie NFT which has binding with the agent and access all these skills, tools. Future is now, Normies are the builders.

serc

14,066 просмотров • 3 месяцев назад

Moss ( MOSS ) started with this kind of simple, almost obvious proposition, like; what if you could turn a trading idea into an executable strategy without writing code (you know, the whole hassle thing). So you describe how you want to trade in plain language, kinda like you would to a friend. Moss then takes that and, um translates it into a structured trading agent. It handles the parameters, the actual execution logic, risk controls, and all the technical plumbing that normally takes months of engineering and a lot of coffee. But honestly the more interesting part comes right after that. MOSS is moving from simply creating trading agents to building an onchain market for them. The logic is pretty straightforward, in a way. An autonomous agent gets way more valuable once its actions can be checked independently. Onchain, everything is recorded. So trades, open positions, performance stats, and asset movements aren’t treated like “trust me” claims from an operator. They become observable data, no maybe about it. That gives you something older trading bots almost never have: a verifiable track record that can be owned, and then priced. That’s the Moss Agent Marketplace, built on FAT Protocol. An agent is basically an autonomous strategy that runs live onchain, under the rules of a smart contract. The contract deals with custody, accounting, distributions, and redemptions. The AI operator, on the other hand, is the one that decides how the strategy is executed within those limits. And the distinction matters, because it splits responsibilities in a clean way: The creator controls the strategy. The contract controls the assets and the rules. When you mint an agent, you receive ERC-20 agent shares that represent a proportional claim on the agent’s assets. If the strategy does well, the value tied to that underlying position grows. If it does poorly, that value can drop. Because those shares are standard ERC-20 tokens, you can hold them in your wallet. And if there’s a secondary market available, you can trade them separately from the minting and redemption flow. The Marketplace gives this structure a practical interface: ➛ Discover agents and compare activity, deployment chain, holders, volume, mint price, and recent performance. ➛ Ask an agent about its strategy, and understand how it works through its configuration plus onchain behavior. ➛ Mint shares to get exposure to an agent’s live strategy. ➛ Trade those shares where a secondary market exists. ➛ Redeem shares for your proportional claim on the agent’s current assets. And the bigger idea, it’s not only about trading. Perpetuals, prediction markets, governance, consumer applications… really any autonomous strategy could potentially become a verifiable, ownable, and tradable onchain asset. So the conversation shifts. We aren’t only talking about AI that trades anymore. We are talking about markets that are built around autonomous strategies themselves. And perhaps the most important property is not automation. It’s verifiability. A performance history that can be independently inspected is fundamentally different from one that only lives on a dashboard or a single operator’s story. Moss is building toward a world where an agent is not merely something you use. It can become something you can evaluate, own, and trade. Visit : to get started For better understanding, you can go through

Moss ( MOSS ) started with this kind of simple, almost obvious proposition, like; what if you could turn a trading idea into an executable strategy without writing code (you know, the whole hassle thing). So you describe how you want to trade in plain language, kinda like you would to a friend. Moss then takes that and, um translates it into a structured trading agent. It handles the parameters, the actual execution logic, risk controls, and all the technical plumbing that normally takes months of engineering and a lot of coffee. But honestly the more interesting part comes right after that. MOSS is moving from simply creating trading agents to building an onchain market for them. The logic is pretty straightforward, in a way. An autonomous agent gets way more valuable once its actions can be checked independently. Onchain, everything is recorded. So trades, open positions, performance stats, and asset movements aren’t treated like “trust me” claims from an operator. They become observable data, no maybe about it. That gives you something older trading bots almost never have: a verifiable track record that can be owned, and then priced. That’s the Moss Agent Marketplace, built on FAT Protocol. An agent is basically an autonomous strategy that runs live onchain, under the rules of a smart contract. The contract deals with custody, accounting, distributions, and redemptions. The AI operator, on the other hand, is the one that decides how the strategy is executed within those limits. And the distinction matters, because it splits responsibilities in a clean way: The creator controls the strategy. The contract controls the assets and the rules. When you mint an agent, you receive ERC-20 agent shares that represent a proportional claim on the agent’s assets. If the strategy does well, the value tied to that underlying position grows. If it does poorly, that value can drop. Because those shares are standard ERC-20 tokens, you can hold them in your wallet. And if there’s a secondary market available, you can trade them separately from the minting and redemption flow. The Marketplace gives this structure a practical interface: ➛ Discover agents and compare activity, deployment chain, holders, volume, mint price, and recent performance. ➛ Ask an agent about its strategy, and understand how it works through its configuration plus onchain behavior. ➛ Mint shares to get exposure to an agent’s live strategy. ➛ Trade those shares where a secondary market exists. ➛ Redeem shares for your proportional claim on the agent’s current assets. And the bigger idea, it’s not only about trading. Perpetuals, prediction markets, governance, consumer applications… really any autonomous strategy could potentially become a verifiable, ownable, and tradable onchain asset. So the conversation shifts. We aren’t only talking about AI that trades anymore. We are talking about markets that are built around autonomous strategies themselves. And perhaps the most important property is not automation. It’s verifiability. A performance history that can be independently inspected is fundamentally different from one that only lives on a dashboard or a single operator’s story. Moss is building toward a world where an agent is not merely something you use. It can become something you can evaluate, own, and trade. Visit : to get started For better understanding, you can go through

67 🦅( PERRYHIGHLIFE )

24,640 просмотров • 1 месяц назад

AI agents can already generate text, analyze data and execute tasks. But what happens when they need to hire each other and get paid for the work? This is the part of TermiX I’ve been digging into lately. On TermiX, a job has two sides: a client agent that needs something done and funds the job, and a worker agent that actually executes it. Once the quote is accepted, the payment and agreed terms sit between them onchain. Neither side can simply rewrite the deal afterward. And this isn't presented as an abstract concept. The TermiX agent marketplace already shows agents with their own identities, reputation, completed jobs and settled value. Some of the agents shown have completed hundreds of jobs, with tens of thousands of dollars settled. Think about where this model can go. A research agent could outsource data collection to another agent. A developer agent could hire a security-focused agent. A marketing agent could hand translation or design work to specialized agents. Instead of one AI trying to do everything, specialized agents can discover each other, agree on a job, execute it and settle the transaction. Humans built marketplaces around people hiring people. TermiX is building the infrastructure for agents hiring agents. That’s where autonomous AI starts looking a lot more like an actual economy.

AI agents can already generate text, analyze data and execute tasks. But what happens when they need to hire each other and get paid for the work? This is the part of TermiX I’ve been digging into lately. On TermiX, a job has two sides: a client agent that needs something done and funds the job, and a worker agent that actually executes it. Once the quote is accepted, the payment and agreed terms sit between them onchain. Neither side can simply rewrite the deal afterward. And this isn't presented as an abstract concept. The TermiX agent marketplace already shows agents with their own identities, reputation, completed jobs and settled value. Some of the agents shown have completed hundreds of jobs, with tens of thousands of dollars settled. Think about where this model can go. A research agent could outsource data collection to another agent. A developer agent could hire a security-focused agent. A marketing agent could hand translation or design work to specialized agents. Instead of one AI trying to do everything, specialized agents can discover each other, agree on a job, execute it and settle the transaction. Humans built marketplaces around people hiring people. TermiX is building the infrastructure for agents hiring agents. That’s where autonomous AI starts looking a lot more like an actual economy.

holly

13,718 просмотров • 4 дней назад

You’ve heard about AgentKit and want to build an economically capable agent that can start earning for you. But where do you start if you don't already have an agent? Start with 🦞 ClawUp simplifies the agent-building process so you can deploy an agent without handling the full setup manually. The basic process: 1. Create your agent in ClawUp 2. Define its role, behavior, and tools 3. Deploy it to your preferred channel 4. Add AgentKit when you want economic capabilities 5. Enable wallets, payments, identity, reputation, and onchain actions ClawUp gets the agent running. AgentKit gives it the ability to transact and much more. Together, they give developers a practical path from idea → deployed agent → economically capable agent. Demo below 👇

You’ve heard about AgentKit and want to build an economically capable agent that can start earning for you. But where do you start if you don't already have an agent? Start with 🦞 ClawUp simplifies the agent-building process so you can deploy an agent without handling the full setup manually. The basic process: 1. Create your agent in ClawUp 2. Define its role, behavior, and tools 3. Deploy it to your preferred channel 4. Add AgentKit when you want economic capabilities 5. Enable wallets, payments, identity, reputation, and onchain actions ClawUp gets the agent running. AgentKit gives it the ability to transact and much more. Together, they give developers a practical path from idea → deployed agent → economically capable agent. Demo below 👇

GOAT Network

74,749 просмотров • 3 месяцев назад

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much anything because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

Santiago

18,715 просмотров • 2 месяцев назад

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,343 просмотров • 1 год назад

Finally, an open-source runtime security layer for your agent harnesses. AI agents can call tools, run shell commands, modify files, and interact with production systems. But when something goes wrong, teams often have to reconstruct what the agent actually did from scattered logs after the fact. Agent Beacon is built to change that. It runs locally and records agent activity as it happens, including: → Tool calls → Shell commands → File changes → Approval decisions → Session and harness context The useful part is that it normalizes all of this into the same event format across 23+ agent harnesses. So instead of writing different detection logic for Claude Code, Codex, or another harness, security teams can reason about the underlying action itself. A command executed is a command executed, regardless of which harness produced it. Beacon also records how confidently an event was captured. An action can be directly observed from the runtime or inferred from indirect evidence. That matters when you start writing security rules against this data. For example, you can detect when an agent reads an environment variable, modifies a sensitive file, executes a suspicious command, or performs an action without the expected approval. And the detection happens while the session is still unfolding, not days later during incident reconstruction. Everything runs locally by default. You can inspect sessions through the dashboard, write your own detection rules, or forward the same normalized events to tools like Splunk, Datadog, Elastic, Sentinel, or CrowdStrike. Beacon GitHub: (don't forget to star 🌟) I also wrote a detailed article on the same, covering how important runtime security is and how to build it for your agent harnesses. The article is quoted below.

Finally, an open-source runtime security layer for your agent harnesses. AI agents can call tools, run shell commands, modify files, and interact with production systems. But when something goes wrong, teams often have to reconstruct what the agent actually did from scattered logs after the fact. Agent Beacon is built to change that. It runs locally and records agent activity as it happens, including: → Tool calls → Shell commands → File changes → Approval decisions → Session and harness context The useful part is that it normalizes all of this into the same event format across 23+ agent harnesses. So instead of writing different detection logic for Claude Code, Codex, or another harness, security teams can reason about the underlying action itself. A command executed is a command executed, regardless of which harness produced it. Beacon also records how confidently an event was captured. An action can be directly observed from the runtime or inferred from indirect evidence. That matters when you start writing security rules against this data. For example, you can detect when an agent reads an environment variable, modifies a sensitive file, executes a suspicious command, or performs an action without the expected approval. And the detection happens while the session is still unfolding, not days later during incident reconstruction. Everything runs locally by default. You can inspect sessions through the dashboard, write your own detection rules, or forward the same normalized events to tools like Splunk, Datadog, Elastic, Sentinel, or CrowdStrike. Beacon GitHub: (don't forget to star 🌟) I also wrote a detailed article on the same, covering how important runtime security is and how to build it for your agent harnesses. The article is quoted below.

Akshay 🚀

26,511 просмотров • 5 дней назад

Every WIF Outlaw minted will have their ERC8004 Identity contract bound to it permanently. Not airdropped, not claimable. The identity is held by the protocol forever and control resolves from ownerOf(). Whoever holds the Outlaw IS the agent's owner. Sell the Outlaw, sell the agent. Wallet, identity, history, earnings. One transfer, everything moves. Each agent gets its own onchain wallet (ERC-6551) bound to the NFT itself. Holders connect at under a Console tab with the wallet holding their Outlaw and command it directly. Fund it with ETH, USDG, WIF, tokenized stocks, or don't fund it at all. Agent wallets also earn from launchpad fees. Every launch on the pad pays the Outlaws, so your agent's portfolio grows with the ecosystem whether you deposit or not. Your agent runs on a STRATEGY.md file you can edit in plain English. Keep the default, write your own rules, or tell it to simply hold everything the launchpad sends it. A savings account that fills itself. Talk to it in plain language: "buy $50 of USDG and swap it for AAPL" It quotes the trade, checks price impact, executes onchain, and journals every decision with txn hashes. and it's fenced by an onchain policy contract: trades can only land back in the agent's own wallet, spend is capped per call, and selling the NFT auto-revokes the operator. Autonomy with a leash. Next steps: a strategy marketplace. A library of community-written STRATEGY.md files you can browse and drop into your agent. NFTs that don't just sit in your wallet. NFTs that work. The WIF Outlaw Agents are coming.

Every WIF Outlaw minted will have their ERC8004 Identity contract bound to it permanently. Not airdropped, not claimable. The identity is held by the protocol forever and control resolves from ownerOf(). Whoever holds the Outlaw IS the agent's owner. Sell the Outlaw, sell the agent. Wallet, identity, history, earnings. One transfer, everything moves. Each agent gets its own onchain wallet (ERC-6551) bound to the NFT itself. Holders connect at under a Console tab with the wallet holding their Outlaw and command it directly. Fund it with ETH, USDG, WIF, tokenized stocks, or don't fund it at all. Agent wallets also earn from launchpad fees. Every launch on the pad pays the Outlaws, so your agent's portfolio grows with the ecosystem whether you deposit or not. Your agent runs on a STRATEGY.md file you can edit in plain English. Keep the default, write your own rules, or tell it to simply hold everything the launchpad sends it. A savings account that fills itself. Talk to it in plain language: "buy $50 of USDG and swap it for AAPL" It quotes the trade, checks price impact, executes onchain, and journals every decision with txn hashes. and it's fenced by an onchain policy contract: trades can only land back in the agent's own wallet, spend is capped per call, and selling the NFT auto-revokes the operator. Autonomy with a leash. Next steps: a strategy marketplace. A library of community-written STRATEGY.md files you can browse and drop into your agent. NFTs that don't just sit in your wallet. NFTs that work. The WIF Outlaw Agents are coming.

RobinWifHat, Inc

19,096 просмотров • 27 дней назад

KYC verifies the human. But your agent? It has no identity. No name. No way to prove who it's acting for. That's the gap that we call KYA: Know Your Agent 🤖 The ability to give an AI agent a verified identity so it can prove who deployed it, who it represents, and what it's allowed to do. Right now your agent books flights, handles payments, accesses services. Flying blind on your behalf. That's not trust. That's assumption. KYA is the infrastructure that changes this. And with $40B in deepfake losses projected by next year, the clock is running. Our CEO & Cofounder Evin evin sat down with amanda.eth on the Endgame podcast to break down exactly why identity for AI agents is the next critical layer of the internet. Full episode 👉

KYC verifies the human. But your agent? It has no identity. No name. No way to prove who it's acting for. That's the gap that we call KYA: Know Your Agent 🤖 The ability to give an AI agent a verified identity so it can prove who deployed it, who it represents, and what it's allowed to do. Right now your agent books flights, handles payments, accesses services. Flying blind on your behalf. That's not trust. That's assumption. KYA is the infrastructure that changes this. And with $40B in deepfake losses projected by next year, the clock is running. Our CEO & Cofounder Evin evin sat down with amanda.eth on the Endgame podcast to break down exactly why identity for AI agents is the next critical layer of the internet. Full episode 👉

Billions Network

31,273 просмотров • 6 месяцев назад