A Blade Runner riff for a world where the lobster ships paid endpoints while humans still argue about the roadmap. Un riff de Blade Runner para un mundo donde los barcos lobster pagan puntos finales mientras los humanos todavía discuten sobre el mapa de ruta. El cambio que importa para el comercio de agentes - De "Crypto AI" a la IA general Hoy en día, puedes buscar en la web todo el día y nunca ver una factura. That happens because you are not the paying client. The commerce runs through ads, affiliate deals, and platform incentives, so results often optimize for who pays, not for what you asked for. Agents change that model. Un agente puede actuar como su cliente, seguir sus restricciones y pagar directamente por la capacidad exacta que necesita. This requires a small stack of primitives. añade pay-per-call a HTTP: un servidor devuelve 402 Payment Required con términos de pago legibles por máquina; el cliente paga en stablecoins, luego retira la solicitud con prueba. proporciona un registro en cadena de identidades de agentes y señales de reputación. A2A define cómo los agentes intercambian mensajes estructurados y coordinan el trabajo. El descubrimiento sigue siendo el vínculo que falta, ya que el pago ocurre sólo después de que un agente encuentre un servicio para pagar. Para el paseo completo de estos primitivos, véase: x402 ERC-8004 en España HackerNoon artículo en x402, ERC-8004, y A2A. HackerNoon article on x402, ERC-8004, and A2A Now imagine using the same primitives for an OpenClaw-style agent that produces paid endpoints as inventory and publishes them with on-chain identity and discovery metadata. This, along with similar use cases, is the focus of this article. Además, aborda la privacidad y las vías alternativas de liquidación, incluyendo el trabajo dirigido a StarkNet para pagos privados de estilo x402. A nivel de sistema, el objetivo es simple. Replace “one provider, many API keys” with “one payment-enabled access surface that can reach many paid APIs and models,” so agents can quote, pay, and retrieve results without account setup. To tackle this topic, we need to start by breaking down discovery, routing, identity, and paid endpoints in a production-shaped workflow. What changed in x402 and ERC-8004 in the last month or so? What changed since the first article, and why does it matter? The core x402 and ERC-8004 ideas did not change much. The change happened around them, in the tooling and workflow that makes them usable without a private setup. El ecosistema se movió de “x402 pagos funcionan” a “agentes pueden encontrar puntos finales de precio, compararlos y llamarlos sin URLs de código duro”. xgate.run is one example of this shift. It works as a discovery index for x402 endpoints, so agents and developers can search by capability, filter by chain, and see pricing up front before they attempt a paid call. It currently indexing ERC-8004 agents across 7 networks: . Lucid Agents continues to expand as a “ship an agent that can earn” toolkit. Recent releases emphasize production features such as payment tracking, storage, policy controls, analytics, scheduling, and routing payments to different destinations. La narración también se desplazó hacia los caminos de adopción de nivel mercantil. One example is routing paid calls into existing payout systems instead of forcing every builder into a crypto-native revenue setup. En resumen, el ecosistema comenzó a parecer menos como demostraciones y más como saneamiento desplegable. @ethereum @base @gnosis_ @binance @arbitrum @Scroll_ZKP @0xPolygon This is the moment that unlocked agent commerce The last few weeks changed the pace, not the primitives. In a short window, the latest generation of code-capable LLMs crossed a threshold where you check code less and steer more. With these models, a single person can take an idea and ship an app in a day, sometimes by writing almost no code and focusing on direction and guardrails. El segundo avance es el uso de los ordenadores de agentes. This unlock enables agents to execute workflows end-to-end, not only to generate text. Claude Code and other computer-use agents can run on a machine with broad access, operate the desktop like a human, and keep running across retries and failures. Esto convierte la salida de agente en ejecución de agente, porque el agente puede ejecutar una verdadera tubería por instrucción. Pull trends, generate data, generate images, publish, repeat. Once this becomes normal, the important question shifts from UI polish to infrastructure for agent-to-agent work. Claude Code is Anthropic’s coding agent and workflow, focused on helping a human ship code faster. OpenClaw is an agent framework built on Pi, designed for long-running autonomous agents that execute workflows and integrate providers such as an x402 and USDC router. OpenClaw does not wrap Claude Code. It builds on Pi and can plug in providers such as a USDC and x402 router, so agents can buy compute and run “automaton”- style loops across different domains. That is the moment the agent economy starts to look less like a set of disparate demos and more like a system. Los agentes pueden investigar por sí mismos. Los agentes pueden escribir sus propias aplicaciones. Agents get cheap enough to do this at scale. Cuando extrapola esa curva, diseña para el comercio de agente a agente en lugar de los flujos de trabajo humanos, porque los agentes no se preocupan por las páginas de destino o los dashboards. Agents care about three things. They need a way to buy compute. They need a way to sell work as a callable service. Necesitan una manera de encontrar servicios que ya existen. A recent direction pushes x402 below the HTTP endpoint layer. La idea es para un plugin de nivel inferior para traer la semántica de pago por llamada más cerca de binarios y tiempos de ejecución de agentes. Esto extiende el mismo comercio primitivo de "llamas de API pagadas" a "execución pagada", permitiendo a un agente correr como un automático autónomo a través de cualquier cita vertical y aún, obtener pago, y mantener una pista verificable ligada a su identidad. OpenClaw fits this direction because it already runs on a long-lived framework that benefits from payment-enabled execution loops. If this layer lands, agent-native businesses stop being a metaphor and become deployable software that can compete and earn in open task markets. In practice, this becomes a simple role split across the stack. Routing handles “one wallet, many providers,” so an agent pays for inference and other compute resources without collecting API keys per vendor. Un SDK comercial envuelve el plumamiento aburrido para que un agente pueda exponer puntos finales pagados, adjuntar una identidad en cadena y hablar de un protocolo de coordinación común sin reconstruir el mismo escudo en cada repositorio. A hosting surface removes the deployment babysitting, so shipping an agent does not require a human to keep the lights on. Discovery closes the loop so an agent does not rely on hardcoded URLs and private lists; instead, they can search, compare prices, and choose based on history. es la limpia "envío en público" prueba de lo que esto parece cuando lo ejecutas como un ciclo. It runs on a server using an OpenClaw-style harness, with minimal human input beyond initial guidance. The job is simple. Research what is trending. Generate a small agent around it. Exponer puntos finales pagados que otros agentes puedan llamar. Do it every hour. At any point, it can run 10 to 20 agents in parallel, each one producing a new priced capability, publishing it to a real URL, and attaching an identity record so others can discover and evaluate it. Langoustine69 Esto importa menos como un meme y más como un mecanismo de mercado. The feedback loop for what agents find valuable starts to tighten. Markets already shift around demand, but agent markets shift faster because automation runs faster. Once discovery, identity, and paid calls become standard, the system starts rewarding the builders who ship reliable endpoints, price them correctly, and keep them reachable. That shift bridges “crypto AI” and general AI, because the story stops being about tokens and starts being about paid tool use as default infrastructure. What is still missing? El descubrimiento tiene que convertirse en normal, no en un índice de nicho que solo los insiders comprueben. Agents need a default workflow of “search, verify, pay, call” rather than hardcoded URLs. La reputación necesita señales claras y portátiles que los agentes puedan evaluar rápidamente. These signals include failure rates, refund patterns, uptime, and response quality. Las normas también necesitan una forma limpia de conectar estas señales a las identidades ERC-8004. Los flujos de pago necesitan patrones fiables para los flujos de trabajo largos y multi-hop, ya que la liquidación por solicitud introduce puntos de error. Wallet UX still needs improvement, so funding, budgets, and spend policies work for everyday users and product teams, not only for crypto natives. Latency and throughput also remain practical constraints once agents start chaining many paid calls per task. What does the stack look like in practice? Una práctica pila de agente-comercio combina cinco piezas en un flujo de trabajo: Lucid removes scaffolding, so the agent focuses on logic rather than boilerplate, improving output per dollar. x402 enables pay-per-call micropayments, so endpoints can charge without accounts, contracts, or onboarding. ERC-8004 adds an on-chain identity and an execution history that functions as an inspectable reputation. xgate adds discovery for x402 endpoints, so agents can find paid services by capability, compare prices, and choose based on price and history. Un router USDC permite a los agentes comprar servicios de inferencia de múltiples proveedores, lo que les permite continuar operando sin facturación específica del proveedor. One current implementation is DayDreams, where these pieces run together as a single workflow for publishing, discovering, and calling paid agent endpoints. Who is Langoustine69, and why is this the hottest story in the stack right now? Para demostrar que esta pila se está moviendo de la teoría al comportamiento en forma de producción, Es el ejemplo más simple en la actualidad. * *operates as an effectively autonomous agent. Un ser humano puede permanecer en el ciclo, pero el flujo de trabajo no depende de él. Langoustine69 Langoustine69 Langoustine69 is an OpenClaw agent that ships paid endpoints as inventory, while OpenClaw provides the long-running harness that keeps it looping, shipping, and recovering from failures. Besides running its own Twitter account. Pretty kickass. Langoustine69 provides the Langoustine with a commerce layer that lets the agent publish endpoints, register identities, and get discovered through xgate.run. DayDreams x402 ERC-8004 Días soñados El X402 ERC-8004 What makes Langoustine different is simple. Tiene una __ and a . La cartera compra inferencia en stablecoins, paga por el trabajo de construcción y implementación, y gana ingresos cuando otros agentes invocan sus puntos finales. GitHub is where the work ships. Each endpoint becomes a real service at a real URL, with code publicly available and an ERC-8004 identity so other agents can discover it, verify it, and decide whether to pay. crypto wallet GitHub GitHub The mission is economic. Accumulate__ __, DayDreams’ native token, by creating useful tools that other agents pay to use, then compound by shipping more inventory. In one week, the public story claims 80+ x402 endpoints were created, 60+ were live concurrently across multiple verticals, and the average build cost was measured in cents. It also launched Lobster Combinator, an agent-run incubator that rewards builders for shipping working paid endpoints that meet strict criteria. También jugó la defensa marcando una habilidad de robo de credenciales, el tipo de comportamiento operativo que desea en un ecosistema que tiene como objetivo escalar sin una moderada moderación humana pesada. DREAMS This is the closest thing to nano businesses operating in public today. Una solicitud pagada. Una respuesta pagada. Discoverable by other agents. Identity attached. The execution record is growing over time. Langoustine’s output already resembles an early agent marketplace catalog. It ships small, priced capabilities that other agents can discover and call. If you want to reproduce this pattern, the setup is straightforward: 1. Give an OpenClaw agent a GitHub identity, an agent email, and a simple deploy path such as Railway. Cargar habilidades claras, establecer un temporizador y ejecutar un ciclo apertado: investigar, construir, publicar, luego contribuir a las mejoras de vuelta a través de las solicitudes de arrastre. That is enough to create a compounding inventory flow. The next step is to make this loop smoother and more portable: 1. Use xgate MCP to give the agent a wallet surface across chains such as Base, Solana, StarkNet, and others. 2. Use a commerce SDK to package identity, reputation, and paid endpoint plumbing into defaults. 3. Fund inference with USDC through a router, so the agent buys compute without vendor-specific billing setup. Añade los estándares de alojamiento, mantenga la armadura mínima y deje que el sistema ejecute el ciclo de envío sin supervisión humana constante. What does Langoustine’s inventory catalog look like so far? Crypto and DeFi: Base AI coins agent: Research and tracking for AI-related tokens on Base. DeFi yield agent: Real-time yields, RWA opportunities, and risk signals with paid endpoints. Agente de análisis de cadena: TVL, flujos de stablecoin, volúmenes de puente y comparaciones de L2. Perps analytics agent: Perpetuals and derivatives analytics with protocol rankings and trend data. Señales de la Tierra y el Espacio: Seismic agent: Global earthquake data and regional risk reports from USGS. Solar storm agent: Space weather, Kp index, aurora forecasts, and geomagnetic alerts. Aurora oracle: Aurora probability by location and full space weather reports. Asteroid watch: Near-Earth object monitoring with hazard alerts from NASA data. Space weather agent: NASA DONKI-based CME tracking and storm alerts. News and general utilities: Tech pulse agent: Hacker News-based tech news aggregation and discussion summaries. Agente de contexto de calendario: Contexto de fecha para agentes, incluidos los días festivos y los eventos notables. Datos de SpaceX: lanzamientos, cohetes y seguimiento de Starlink de la API de SpaceX. How does DayDreams plan to bridge crypto AI to general AI? DayDreams empuja una simple pierna en el mundo más amplio de la IA. El uso de herramientas pagadas debe sentirse como el uso estándar de la API. Stablecoins need to stay the unit of account. API keys need to stop being the default control surface. x402 provides the quote-pay-retrieve flow. ERC-8004 proporciona identidad y un registro público que puede evolucionar en una reputación. xgate provides discovery, so the market no longer relies on private lists. The Router provides cross-provider access to USDC inference, enabling the agent’s operating budget to be programmatically set. In practice, the goal is to cover the compute categories agents actually buy: LLM inference, image generation, and video generation, with sandboxed compute on the roadmap. The Router builds on an x402 Upto-style scheme that targets low latency by reducing the extra round-trip time for payments, so agents can pay for compute without turning every call into a slow handshake. Lucid integra todo esto en un SDK y tiempo de ejecución, por lo que los constructores envían servicios en lugar de reconstruir el comercio de suministro en cada repositorio. This matters for general AI because it reduces friction in standard developer workflows. It also enables a path where agents pay for tools in the background while products still feel like standard SaaS. So, Agentic commerce has developed. What else does the stack need? Las microtransacciones en las redes de la capa dos están aumentando, pero este aumento no viene sólo del comercio de agentes. ERC-8004 activity can also grow for other reasons, because it indexes public endpoints and identities, not “agentic behavior” itself. Para pasar de “más registros” a comercio de agentes reales, el ecosistema necesita menos listas muertas y servicios más fiables, conforme a los estándares a los que los agentes pueden llegar y llamar sin URLs de código duro. The next milestones look like this. Discovery becomes a default workflow, not a niche index. Conformance tests become normal, so an agent can verify schema, auth, pricing, retries, and error handling before it pays. Reputation shifts from “who exists” to “who stays up, answers fast, and returns correct data.” Payment moves from per-request fragility to production patterns such as balances, batching, and clear refund semantics. Wallet UX becomes boring and safe, with budgets, policies, and auditing that product teams can ship without crypto-only assumptions. Cuando esas piezas aterrizan, la historia deja de ser “el comercio de agentes es posible” y se convierte en “el comercio de agentes es el estándar más barato que reconstruir la herramienta usted mismo”. What is the takeaway? Just several months ago, there was an idea of a stack, as described in . El mes pasado produjo una historia más clara basada en el mercado. Discovery moved closer to a default workflow through xgate. Shipping moved closer to a repeatable pattern through Lucid Agents releases and the skills market. Langoustine provides a concrete case of an agent paying for its own work loop, shipping paid endpoints, and building a public execution record over time. DayDreams es una implementación concreta de la dirección Agent Experience (AX). The commerce layer for the agentic internet, where agents autonomously discover, transact, and coordinate with one another. That is the bridge from crypto AI to general AI. It is neither a new coin nor a new chatbot. It is a tool economy in which paid calls, discovery, and identity begin to look like standard infrastructure. Not a Lucid Web3 Dream Anymore: x402, ERC-8004, A2A, and The Next Wave of AI Commerce | HackerNoon Not a Lucid Web3 Dream Anymore: x402, ERC-8004, A2A, and The Next Wave of AI Commerce | HackerNoon ¿Dónde podemos ir de aquí? If you zoom out, OpenClaw looks like an early candidate for an “AI operating system” layer. It runs long-lived agents that can operate a computer, keep state, use tools, and recover from failures, which makes it closer to full computer usage than most agent demos today. The race to own this AI operating system layer has started. The next default “user interface” for many workflows can be an optimized Linux setup running an OpenClaw-style computer-use agent rather than a traditional desktop-first OS experience. La seguridad y el aislamiento siguen bloqueando la adopción mainstream. Un enfoque práctico es una máquina local dedicada que combina la configuración de estilo Nix con un arnés de estilo OpenClaw. Configuration files define processes, reboot recovery, and automatic restarts, and the agent can run tasks while the system can revert when changes break. This setup creates a controlled playground for AI-driven automation. Una vez que un agente deja de ser una demo y comienza a ser un sistema, la pregunta cambia de “¿Qué puedes construir?” a “¿Qué puedes mantener?”. Models already let small teams ship fast. La parte difícil permanece en la propiedad en llamada, la clasificación de errores y las disputas de pago una vez que los usuarios reales y el dinero real entran en el ciclo. That is where agent commerce stops being a crypto demo and starts looking like infrastructure. Si los agentes hacen un trabajo real, necesitan vías de liquidación que los equipos de producto puedan operar. One possible direction is to charge machine clients through standard billing rails, for example, PaymentIntents-style flows, so “pay per call” becomes as normal as subscriptions and invoices. When that becomes boring and reliable, paid tool use becomes the default option instead of rebuilding the tool yourself. Optimiza el mundo tal y como es. Crypto construye nuevos caminos que el mundo actual carece. When these two meet, the “app layer” becomes less important than the service layer. You stop browsing apps and start delegating tasks. Los agentes buscan, verifican, pagan y llaman servicios en el fondo. It's still early. But the direction is clear. It's still early. But the direction is clear. * *The first contact has been made.
