autonomous-loops

Autonomous Claude Code loops run without human intervention by coordinating multiple agents and iterations through a multi-stage, context-separated pipeline. This enforces explicit dependencies and per-stage context windows to manage complex development workflows automatically.

RFC-driven DAG orchestration structures multi-agent workflows by coordinating parallel exploration and iterations using directed acyclic graphs. It enforces a context-separated pipeline with explicit dependencies and a merge-queue system to safely land changes and handle evictions.

Context persistence across autonomous agent iterations is managed using per-stage context windows within a multi-stage pipeline. This approach separates context explicitly between stages, ensuring agents maintain relevant state without exceeding token limits during continuous loops.

Parallel exploration with Claude agents is supported in continuous loops through wave-based parallelism and multi-agent orchestration. This allows complex development workflows to execute concurrent iterations safely while a merge-queue system handles landings and evictions.

Best patterns for automating AI loops range from simple sequential pipelines to Infinite Agentic Loops, Continuous Claude PR Loops, and RFC-Driven DAG orchestration. These patterns provide context persistence, wave-based parallelism, and robust merge-queue strategies for safe change landings.

Autonomous loops should be avoided when development workflows lack explicit dependencies or require continuous human oversight. The multi-stage pipeline with automated quality gates assumes well-defined tasks; without clear stage boundaries, the merge-queue system cannot safely coordinate iterations.