Generate Microservices Architecture Docs with AI Agents

What this is, in plain English

Big software is often built as “microservices”: dozens of small, separate programs that talk to each other. Keeping written documentation of how they all fit together is valuable but tedious, so it rarely gets done. This workflow has AI agents do it: they read each service’s code, trace how it connects to the others, and write a standard ARCHITECTURE.md file for each one. With that documentation in place, your other AI tools can spot system-wide problems (like security gaps) that a plain code checker would miss.

Be honest about the level: this is an advanced, developer-only setup. It needs a real microservices codebase, an agent framework (Antigravity) wired up with AI model keys, and access to your cloud infrastructure, and the author shares the approach rather than copy-paste commands. This page explains what it does, where it helps, and the realistic shape of running it.

What you can use it for

• Onboarding documentation. Give new engineers an accurate map of every service so they get productive faster.
• Security and audit context. Documented architecture lets AI tools (and humans) catch systemic risks across services, not just bugs in one file.
• Keeping docs alive. Re-run it so the documentation updates as the system changes, instead of rotting.
• Investor or compliance readiness. Produce a clear technical picture of your backend on demand.
• The reusable idea: pointing autonomous agents at a codebase to produce structured, standardized docs works for more than microservices.

Tools you need

• Antigravity (free): an open-source framework that coordinates (“orchestrates”) several AI agents to do the work.
• Gemini 3 Flash (free) and Claude Sonnet 4.6 (freemium): the AI models that read the code and write the docs. You give Antigravity their API keys.
• Google Cloud Platform (paid, free tier available): where the example’s services run (using Cloud Run, Cloud Storage, and Vertex AI). The agents inspect this infrastructure too.

How it actually works

You set up the agents, define the doc format, then let them loose. The realistic shape:

1. Install Antigravity. Clone its repository and install it, following the README. This is the framework that drives the agents.
2. Connect your AI models. Configure Antigravity with API keys for Gemini and Claude (the models that do the reading and writing).
3. Define a documentation standard. Decide exactly what each ARCHITECTURE.md should contain (for example service role, dependencies, security policies, lifecycle status). A clear template is what makes the output consistent.
4. Point the agents at your platform. Instruct the agent to inspect each service: read its source, trace its dependencies, and check it against your standard.
5. Let it generate the files. The agents write a structured ARCHITECTURE.md for each service and commit them into your repositories.
6. Feed the docs to your quality tools. Now your AI code-quality pipeline has architectural context, so it can reason about the whole system, not just isolated code.

Words you’ll see, explained

• Microservices: an app built as many small, separate programs that work together.
• Architecture documentation: written description of how a system’s parts fit and interact.
• AI agent: a program that uses an AI to carry out a multi-step task on its own.
• Orchestrate: coordinate several agents or steps to run in the right order (Antigravity’s job).
• ARCHITECTURE.md: a Markdown file documenting one service, the output here.
• Static analysis / linter: a tool that checks code for issues without running it; useful but blind to cross-service context.

Original source

Based on “Architecture Documentation as a First-Class Engineering Asset” by alexandertyutin on the DEV Community blog, an experiment using autonomous AI agents to document a Google Cloud microservices platform.

Notes & variations

• Do you even need this? For a single small service, writing the doc by hand (or asking one AI to) is simpler. This pays off across many services where keeping docs current is the real problem.
• Free-tier viability: Gemini 3 Flash, Claude’s free tier, and Antigravity are free; only the cloud infrastructure costs money.
• Common pitfall: agents without enough access. If they cannot read your code or cloud config, the docs come out incomplete. Check permissions first.
• Tip for better results: nail down your documentation standard before you start. A precise template gives consistent, useful output.