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An agent can plan and sequence a multi-step task and stall at a signup form. Orthogonal (YC W26) replaces account creation, API keys, and billing with one integration. Christian Pickett and Bera Sogut (Orthogonal) join Stateful, hosted by Mason Nystrom. In this episode, they discuss the infrastructure needed for...

23,636 görüntüleme • 1 ay önce •via X (Twitter)

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We gave an AI agent its own wallet and a job. Then we tried to rob it. Meet the Casper Agent Simulator: an AI analyst paying its own way over x402 on Casper, powered by ChainGPT. Right now AI agents can't buy anything on their own. Every API wants a human to sign up, hand over a card, and babysit the keys. The whole internet runs on subscriptions because charging half a cent was never worth the payment fee. We built a demo to show what happens when that changes. Meet Caspi. She's an AI research analyst with a Casper wallet, an era allowance, and a client who wants a market briefing. She buys her own inputs, one request at a time: → live CSPR market data → two headlines from ChainGPT's AI News API → one ChainGPT LLM call for the analyst take → a second of compute to compile it Every purchase is a real HTTP 402. The stall quotes a price, Caspi signs an x402 payment payload, the server verifies it and hands back the goods with a settlement receipt. Around 8.5 CSPR of micropayments become a finished briefing. No signup, no card, no API key. What Casper brings to it: → Fixed 0.1 CSPR fees, so tiny payments actually make sense → Zug finality, settled in one block, no reversals → Smart-account guardrails: era spend cap, per-payment ceiling, endpoint whitelist, verifiable identity (caspi.cspr) That last one is the good part. You can fool an AI agent. You can't fool its account. So there's a "try to rob the agent" panel. A 4,800 CSPR fake NFT. A phishing invoice. A shady endpoint. A thousand-payment drain. Every one of them bounces off a rule the chain enforces. Losses: 0.000 CSPR. The whole thing was lab-coded with the ChainGPT Claude Code skill. One prompt scaffolded the x402 server, the signed-payment client, the live news and LLM integration, the guardrail logic, and the entire 8-bit agent floor. What used to take a team a sprint now takes a prompt and an afternoon. Install: /plugin install ChainGPT-org/chaingpt-claude-skill Anyone can build on Casper with ChainGPT!

ChainGPT

55,142 görüntüleme • 1 ay önce

New short course: Practical Multi AI Agents and Advanced Use Cases with crewAI. Learn to build and deploy advanced agent-based systems in real applications in this course, created with CrewAI and taught by its founder, João Moura! (Disclosure: I've made a small seed investment in CrewAI.) In this course, you’ll learn how to create advanced agent-based apps that use external tools, do performance testing, can be trained with human feedback, and perform multiple tasks with different large language models. You will build several practical agentic apps that provide real business value, such as an automated project planning system, lead scoring and engagement pipeline, customer support data analysis, and a robust content creation system. In detail, you will learn how to: - Create these multi-agent systems with the building blocks of tasks, agents, and crews, along with the different things that make them work, such as caching, memory, and guardrails. - Integrate your multi-agent application with internal and external systems. - Connect multiple agents in complex setups, including parallel, sequential, and hybrid configurations, and create flows involving multiple agentic applications working together. - Test your agentic workflow and train it using human feedback to optimize its performance for better and more consistent results. - Work with multiple LLMs in your multi-agent system, using the appropriate model sizes and providers to fit each agent’s specific task. - Start a project from scratch in your environment and prepare it for deployment. You’ll also learn from an interview between João and Jacob Wilson, the Commercial GenAI Principal at PwC , in which they discuss deploying agentic workflows in real industry use cases. By the end of this course, you will be equipped to start building custom multi-agentic systems for your work. Please sign up here!

Andrew Ng

341,204 görüntüleme • 1 yıl önce

I’ve been watching x402 since Coinbase 🛡️ launched it in May 2025. I did a quick research pass. Here’s the snapshot ↓ Early integrations: • CoinGecko: x402 pay-per-use access for agents (shared by Coinbase Developer Platform🛡️). • Vercel: x402 AI starter template (x402 + modern AI stack demo). • Firecrawl: x402-powered search endpoint (pay per request). • Concordium: x402 + native age verification for agent payments. • Multiversᕽ: “agentic payments” built around x402 support. • AltLayer: building an “x402 Suite” for value exchange between agents. • Solana claims x402 has processed 35M+ transactions and $10M+ volume since launch. TL;DR x402 turns HTTP 402 “Payment Required” into a payment flow. A server returns a price for a request. The client pays in stables like USDC. Then the server returns the result. → Coinbase launched x402 via Coinbase Developer Platform (May 6, 2025). → Coinbase + Cloudflare announced the x402 Foundation (Sep 23, 2025). → Cloudflare added x402 support into its Agents SDK + MCP servers. Why? - AI agents need a clean way to pay for tools. - Data, compute, APIs, services. - No accounts, cards, or subscription screens. x402 is trying to make pay-per-request feel normal. Use cases that already make sense → Paid APIs Pay per call instead of subscriptions. → AI tool calls Pay per query, per inference, per task. → Agent-to-agent payments Software paying software automatically. → Micropaywalls Pay for one endpoint, one action, one piece of content. If this takes off, stablecoins stop being a story. They become how apps and AI agents pay for things online.

Stacy Muur

12,212 görüntüleme • 7 ay önce