autonomous-loops

Multi-agent orchestration from an RFC uses a dependency DAG to execute autonomous Claude Code loops across isolated context windows and per-unit worktrees. You provide the specification, select a loop pattern, and the system coordinates the agents automatically through a merge queue approval workflow.

Autonomous Claude Code loops for complex feature development are structured using pattern selection across Sequential, NanoClaw, Infinite Agentic Loop, Continuous Claude, De-Sloppify, or Ralphinho architectures. The correct loop pattern is chosen based on problem complexity to enable context persistence and robust error handling.

RFC-driven DAG orchestration supports cross-stage isolation with separate context windows and per-unit worktrees for each agent. This ensures autonomous multi-agent tasks maintain isolated environments while executing under a defined dependency graph with quality gates.

Autonomous Claude Code execution includes a merge queue approval workflow integrated into the dependency DAG execution. This allows coordinated multi-agent tasks to pass through defined quality gates before merging, ensuring robust error handling throughout the pipeline.

A dependency DAG is needed for multi-agent task orchestration when implementing complex features described by RFCs where multiple agents collaborate under defined dependencies. It structures the execution flow across isolated context windows and per-unit worktrees to maintain task order.

Choosing between Sequential and Infinite Agentic Loop patterns depends on problem complexity and the need for context persistence. Sequential pipelines handle step-by-step tasks, while Infinite Agentic Loop and NanoClaw architectures support continuous, repeatable automation with robust error handling.