'Han' workflow runs multiple Claude agents in parallel using a spec-first approach
Han is a community-shared workflow that coordinates several Claude Code agents like a small team, each following a written specification. Instead of asking one AI to do everything, you write a plan first, then agents use it as their source of truth. It's a practical method for solo developers who want more reliable results from Claude Code.
Most people use Claude Code by chatting with a single AI and iterating. Han introduces an 'agent swarm' model: you split the work among several Claude agents that each handle a specific role — writing code, reviewing it, checking against requirements, and so on. The key starting point is writing a clear specification (a document describing exactly what you want to build) before any code is written.
The 'evidence-based' part means agents don't improvise — they refer back to the spec to make decisions and verify their output. This reduces drift and keeps a complex feature on track even when multiple agents are running. This is a user-shared workflow posted on Reddit, not an official Anthropic product, so it requires hands-on setup and adaptation to your own project.
Key points
- Write a detailed spec (requirements doc) before coding — agents use it as ground truth
- Multiple Claude agents divide roles: one writes code, another reviews, etc.
- 'Evidence-based' means agents check their work against the spec, not just intuition
- Designed for solo developers using Claude Code on non-trivial features
- Community workflow, not an official tool — expect manual setup and customization
Quick term guide
- workflow
- A repeatable set of steps for getting a task done.
- agents
- AI helpers that follow your instructions and make changes for you.
- specification
- A written document that defines exact rules a piece of software must follow
- developers
- Developers are people who build software, apps, or websites.
- iterating
- Going through repeated small rounds of editing and testing to improve something step by step.
- agent swarm
- Multiple AI agents working at the same time, each assigned a different task.
- swarm
- A group of AI agents each handling part of a task at the same time, like a team instead of one person.
- evidence-based
- Making decisions by referring to a fixed document or data rather than guessing.