Red Queen: A Deterministic Orchestrator That Runs Claude Code as a Worker Pool

After burning $40 of tokens on AutoGPT-style experiments that produced nothing, Red Queen's author built a deterministic orchestrator that treats Claude Code as a worker pool. The key insight: routing decisions that LLMs make are just switch statements — so they moved those decisions to a state machine.

How it works

Red Queen runs a pipeline defined as a state graph, not a prompt. Each phase (spec, code, review, test) is a separate Claude Code subprocess with a focused, isolated prompt. No shared context bloat, no mega-prompt. The state machine decides which phase to run based on explicit transitions — not LLM heuristics.

Pipeline

• Jira ticket → spec → human approves → code → auto review → auto test → human approves → merged PR

Human gates are built into the state graph, not bolted on. You can't accidentally skip approval and deploy to prod.

Key features

• Zero tokens spent on scheduling — the orchestrator is purely deterministic, written in code, not prompts.
• Self-hosted — BYO Claude Code. MIT licensed.
• Isolated skills — every skill runs with a focused prompt. No shared context.

Who it's for

Developers who've hit the limits of autonomous agents and want a safer, more predictable way to integrate LLMs into CI/CD pipelines without sacrificing control.

Get started

The repo is at github.com/odyth/red-queen. Named after the AI from Resident Evil.