What problem does it solve?
Autonomous development often fails because LLM-driven loops lack clear architectures for iteration, coordination, context persistence, and quality gates, causing duplicated work, missed failures, or stalled progress.
Core Features & Use Cases
- Loop Pattern Library: Provides practical architectures ranging from simple sequential pipelines to multi-agent RFC-driven DAG orchestration for larger changes.
- Context & State Management: Covers techniques like persistent REPL sessions and cross-iteration context bridging (e.g., shared notes) to prevent “lost progress.”
- Quality Gates & Recovery: Includes reviewer/de-sloppify passes, CI-failure recovery patterns, and merge-queue-style eviction to handle conflicts and test failures safely.
Use case example: Turn a multi-day feature into a continuous PR loop that iteratively implements changes, runs CI, auto-fixes failures, and merges when checks pass—using shared notes to preserve progress across iterations.
Quick Start
Start an autonomous PR-style loop by directing the agent to implement a feature, run CI checks after each iteration, and continue until it produces an explicit completion signal.
