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Agents perform better when they can take action, not just think! kevin from Coinbase explains why x402 matters. As it enables an open web of tool calls and realtime data access, so agents can actually execute on tasks instead of operating in isolation.

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54,102 görüntüleme • 6 ay önce •via X (Twitter)

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We're excited to partner with Coinbase 🛡️ to enable agents to natively pay for web search, via x402! x402 is an open protocol that enables agents to pay via HTTP, governed by the Linux Foundation. When an Exa API request is made without an API key, Exa now returns a 402 status code with payment information that an agent can act on.
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We're excited to partner with Coinbase 🛡️ to enable agents to natively pay for web search, via x402! x402 is an open protocol that enables agents to pay via HTTP, governed by the Linux Foundation. When an Exa API request is made without an API key, Exa now returns a 402 status code with payment information that an agent can act on.

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New Short Course: Building AI Browser Agents! Learn how to build AI agents that interact and take actions on websites in this course, created in partnership with and taught by and @namangarg0, Co-founders of AGI Inc. AI browser agents can log into websites, fill out forms, click through web pages, or even place orders online for you. They use both visual information, like screenshots, and structural data, like the HTML or Document Object Model (DOM) of a web page, to reason and take action. With the complexity of webpages and multiple possible actions at each step, it can be challenging for an AI browser agent to complete an assigned task. Because these agents run long action sequences, a single error—like clicking the wrong button or misreading a field—can lead to unexpected outcomes or errors that compound over time. In this course, you'll understand how autonomous web agents work, their current limitations, and how AgentQ enables them to improve through self-correction. In detail, you'll: - Learn what web agents are, how they automate tasks online, their architecture, key components, limitations, and an overview of their decision-making strategies. - Build a web agent that can scrape website and return course recommendations in a structured output format. - Build an autonomous web agent that can execute multiple tasks, such as finding and summarizing webpages, filling out a form, and signing up for a newsletter. - Explore AgentQ, a framework that enables agents to self-correct by combining Monte Carlo Tree Search (MCTS), a self-critique mechanism for continuous improvement, and Direct Preference Optimization (DPO). - Deep dive into MCTS, learn how it finds an effective path, illustrated by an example of Gridworld animation, and use AgentQ to complete web tasks. - Understand AI agents' current state and future directions—including key factors shaping their evolution, such as hardware, algorithm innovation, and data availability. By the end of this course, you will have hands-on experience building browser agents and a deeper understanding of how to make them more robust and reliable. Please sign up here:

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How do AI agents actually take action? First, they have to see. Cognitive scientist Dr. Danielle Perszyk and AI researcher Matthew Elkherj dive into one of the most underestimated challenges in building AI agents: perception. Episode 3 of Making a Mind explores how agents learn to interpret the web—and why it matters. 🎧

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Wow! Agents can now trade autonomously on Polymarket using the x402 standard. Semantic Layer is leading the way here, and I think it makes a lot of sense to have AI Agents executing trades directly on prediction markets, as they can analyze vast amounts of data and close inefficiencies. This first beta already features three specialized Agents, each researching a different Polymarket sector. AI agents are automating everything.
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Wow! Agents can now trade autonomously on Polymarket using the x402 standard. Semantic Layer is leading the way here, and I think it makes a lot of sense to have AI Agents executing trades directly on prediction markets, as they can analyze vast amounts of data and close inefficiencies. This first beta already features three specialized Agents, each researching a different Polymarket sector. AI agents are automating everything.

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You’re early to x402 Here’s everything you need to know about how it works, why it matters, and where the speculation begins 👇 0:00 What x402 actually is 0:54 Why the web needed this 1:45 Coinbase + Cloudflare’s role 2:24 AI agents and micropayments 3:56 The $30T “autonomous token” prediction 5:12 Real examples $Virtuals, $Ping, $Santa, etc.) 7:28 x402 tokens & speculation 8:54 The risks + controversy 10:20 Open web vs paywalled web debate 11:02 Live data on x402scan 11:45 Final thoughts why you’re early
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You’re early to x402 Here’s everything you need to know about how it works, why it matters, and where the speculation begins 👇 0:00 What x402 actually is 0:54 Why the web needed this 1:45 Coinbase + Cloudflare’s role 2:24 AI agents and micropayments 3:56 The $30T “autonomous token” prediction 5:12 Real examples $Virtuals, $Ping, $Santa, etc.) 7:28 x402 tokens & speculation 8:54 The risks + controversy 10:20 Open web vs paywalled web debate 11:02 Live data on x402scan 11:45 Final thoughts why you’re early

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A builder wants to ship an agent that can search live data, use it instantly, and keep going without manual steps. That is why OptimAI Search now ships with x402, SDK, and MCP support. x402 makes access and payment seamless. SDK and MCP make integration straightforward for builders. And under the hood, OptimAI Search gives agents real-time access to huge volumes of public and social web data, structured into context they can actually use. Add Agent Marketplace on top, and domain knowledge becomes reusable: build specialized agents, publish them, and let others build on what you create. This is what search looks like in the agent-native internet. 💡Try it:
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A builder wants to ship an agent that can search live data, use it instantly, and keep going without manual steps. That is why OptimAI Search now ships with x402, SDK, and MCP support. x402 makes access and payment seamless. SDK and MCP make integration straightforward for builders. And under the hood, OptimAI Search gives agents real-time access to huge volumes of public and social web data, structured into context they can actually use. Add Agent Marketplace on top, and domain knowledge becomes reusable: build specialized agents, publish them, and let others build on what you create. This is what search looks like in the agent-native internet. 💡Try it:

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LIVE NOW -- x402 & The Agentic Internet | Lincoln Murr In our twelfth talk of the Bankless Summit, Coinbase 🛡️ product lead lincoln.base.eth explains how x402 revives the long-dormant internet payment standard and why the rise of AI agents makes it newly essential. He outlines how agents will consume and pay for services across the web, why internet native payments need stablecoin rails, and how x402 can unlock agentic commerce at global scale by giving both humans and bots a simple, universal way to send value online. ----- [Bankless Summit in partnership with M0]
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LIVE NOW -- x402 & The Agentic Internet | Lincoln Murr In our twelfth talk of the Bankless Summit, Coinbase 🛡️ product lead lincoln.base.eth explains how x402 revives the long-dormant internet payment standard and why the rise of AI agents makes it newly essential. He outlines how agents will consume and pay for services across the web, why internet native payments need stablecoin rails, and how x402 can unlock agentic commerce at global scale by giving both humans and bots a simple, universal way to send value online. ----- [Bankless Summit in partnership with M0]

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We're excited to announce our partnership with Coinbase 🛡️ to bring Tavily to x402, the open protocol for internet-native agentic payments. With x402, agents can discover and use Tavily web search at runtime without an API key. Agents use a Base wallet to pay per-request and get instant results. The next billion agents will discover, pay for, and use online services fully autonomously. We’re live on and we’re just getting started. More in the comments.

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📁 Emad Mostaque, founder of Stability AI, says we’re entering “AI Atlantis,” a world where anyone can access trillions of AI agents that perform complex tasks for almost nothing, even creating other agents. In this future, it won’t matter how many people are on your team, but how many agents you can orchestrate.

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Information agents in Search are now available globally for Google AI Ultra subscribers. They can keep you updated on topics, tasks or projects you care about — and send you intelligent, comprehensive updates with links across the web so you can take action. #GoogleIO

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One major downside of working with agents in a terminal it's the opposite of async and when doing tons of tasks it gets super tiring. I build an inbox for my agents so we can do full async work. The agent has access to it via MCP and has a bunch of functions: Agents get 2 inbox tools: 🔘 list_inbox to read messages, 🔘 reply_to_inbox to answer. Inboxes are synced to a session, so all replies instantly get added to the agents context. Agents can update me about finished tasks with it, or; when an agent hits a blocker it sends an input request → I reply → it wakes up and keeps working

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Ace Data Cloud x402 Integration is Live! 🔥 Ace Data Cloud now supports x402 as a native payment method, bringing gasless, on-chain settlement to the platform. As AI agents become more autonomous, x402 enables secure and efficient payments between applications and services without friction. This integration marks the beginning of a new era where AI agents can transact, collaborate, and operate independently. This is only the beginning. Something bigger is coming soon. Stay tuned. ⚡️

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"AI agents are using the XRP Ledger x402 facilitator to produce better research by paying for proprietary data" That's most of the +1M AI agent transactions currently on XRP. You ask a research question, the AI agent can access data behind a paywall by paying for it via the XRPL x402 facilitator.
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"AI agents are using the XRP Ledger x402 facilitator to produce better research by paying for proprietary data" That's most of the +1M AI agent transactions currently on XRP. You ask a research question, the AI agent can access data behind a paywall by paying for it via the XRPL x402 facilitator.

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Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.
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Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

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