autonomous-loops

You can establish a continuous PR loop that creates a branch, implements a change, waits for CI checks, performs a fix pass on failures using shared task notes, and merges when checks succeed. This loop pattern persists context across iterations to avoid restarting from scratch.

RFC-driven DAG orchestration decomposes an RFC into a dependency DAG, runs tiered quality pipelines per unit, and lands changes through an agent-driven merge queue with eviction on conflicts. This multi-agent workflow manages large feature development across autonomous Claude Code instances.

Build a sequential pipeline architecture by breaking work into isolated Claude Code steps that execute in order. This pattern is ideal for daily feature work and verification passes, applying cross-iteration context persistence to maintain state between sequential steps.

Yes, autonomous development loops transform specs and RFCs into working changes with minimal human intervention. They apply loop pattern selection, cross-iteration context persistence, and tiered quality pipelines to handle conflict and failure recovery automatically.

Cross-iteration context persistence maintains shared notes across autonomous loop cycles, allowing the agent to reference previous states and failures. This prevents the workflow from restarting from scratch and enables reliable continuous PR iteration with CI gates.

The loop applies merge and retry behavior with conflict and failure recovery. In multi-agent DAG orchestration, the agent-driven merge queue uses eviction on conflicts, while continuous PR loops perform automated fix passes based on shared cross-iteration context notes.