Go Micro is increasingly built by an autonomous loop of two AI agents — Codex writing scoped increments, Claude Code orchestrating, the human setting direction. Here's how the loop actually works, including the parts that broke.
Read more →The first wave of agent frameworks put a model in a loop. The harder problem is operating that loop — tools, state, guardrails, recovery, observability, interop — and that's what Go Micro is: the harness around the agent, built from the stack you already deploy.
Read more →OpenAI is backing Go Micro through Codex for Open Source — six months of ChatGPT Pro to support the work of maintaining the project. A framework built around agentic development, maintained with agentic tooling.
Read more →A real thing you can build with Go Micro: a support desk where a customer ticket triggers an agent that looks up the customer, sets priority, and replies — with a human-in-the-loop gate on the one action that touches a customer.
Read more →Go Micro started in January 2015, went through a VC-funded company and a platform pivot, and then went quiet. This is how it came back — and how agents, services, and flows brought it to v6.
Read more →Go Micro agents already call each other over RPC. Now they speak the Agent2Agent protocol too — reachable by, and able to reach, agents built on any framework. Cards are generated from the registry, the same way the MCP gateway derives tools.
Read more →Three months ago, with Anthropic's support, Go Micro went all in on AI. A look back at what shipped — agents, workflows, guardrails, payments, durable execution — and where it's heading.
Read more →An event-driven workflow runs for minutes and has side effects partway through — it reserved stock, it charged a card. When the process dies mid-run, re-running from the top does it all again. Go Micro flows are now ordered, checkpointed steps that resume where they stopped.
Read more →An autonomous agent fails in mundane ways — it loops, it runs away, it takes an action it shouldn't. Go Micro separates orchestration from execution safety, and gives every agent three guardrails at the point where tools actually run.
Read more →Agents that act on their own eventually need to pay on their own. Go Micro now speaks x402 — the HTTP 402 payment standard — so a tool can require a stablecoin payment and an agent can settle it, with the chain pluggable behind a facilitator.
Read more →Most agents wait for a human to type something. The useful ones don't — they run because something happened in the system. A Flow turns an event into the prompt, and an agent acts on its own.
Read more →Go Micro made services easy by being opinionated, batteries-included, and pluggable. We're applying the same model to agents — a model, memory, and tools that compose like a service does.
Read more →From the scaling pressures that produced microservices, through Kubernetes and the service mesh, to AI agents — fifteen years of evolution, what actually endured, and why the future belongs to agents.
Read more →We spent two posts on agents that plan and delegate. Here's the other half: when the path is known, you want a workflow — predictable, event-driven, deterministic. In Go Micro they're the same building blocks, two modes.
Read more →An agent shouldn't just react tool by tool. It should form intent — plan what it's doing — and direct intent — delegate what it shouldn't do itself. Go Micro now gives every agent both, as plain tools.
Read more →Agent is now a first-class abstraction in Go Micro — alongside Service and Flow. Build intelligent agents that manage your services in Go.
Read more →What if every service had an agent responsible for it? Not embedded in the service, but created to manage its lifecycle. A design for distributed AI agents on top of microservices.
Read more →Go Micro started as a microservices framework. It's becoming the way you build software that AI agents can use. Here's why we're making that bet.
Read more →One command generates real services with business logic, compiles them, starts them, and lets you talk to them. When you need more, the agent builds new services mid-conversation.
Read more →The path from API gateway to MCP to LLM tools was shorter than you'd think — because services were always self-describing.
Read more →A complete teardown of micro chat — how to build an LLM agent that discovers and orchestrates your services, with every line explained.
Read more →Introducing micro chat — an interactive CLI that discovers your services, turns them into tools, and lets you orchestrate them through natural language.
Read more →Exploring the concept of LLM-powered service orchestration — what happens when micro chat becomes a persistent, event-driven flow engine.
Read more →Atlas Cloud joins as an official Go Micro sponsor, bringing 300+ AI models across text, image, and video to the framework's ai package.
Read more →How existing Go Micro services become agent-accessible with zero code changes. A walkthrough using the micro/blog platform as a real-world example.
Read more →Go Micro now has a typed data model layer — define structs, get CRUD and queries, swap backends. Every service gets Client, Server, and Model.
Read more →Unified service creation, cleaner handler registration, and modular monolith support — the Go Micro DX overhaul.
Read more →Build three microservices and let an AI agent manage them with natural language — no glue code, no API wrappers, just Go comments.
Read more →How Anthropic's Claude Max sponsorship accelerated Go Micro's MCP integration — WebSocket transport, OpenTelemetry tracing, LlamaIndex SDK, and what's next.
Read more →Expose go-micro services as AI tools with 3 lines of code using the Model Context Protocol. Make your microservices instantly accessible to Claude and other AI assistants.
Read more →Deploy your Go Micro services to any Linux server with a single command. No Docker, no Kubernetes, no platform — just systemd.
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