autonomous-loops

You can orchestrate multi-agent workflows by applying modular loop patterns with context separation per stage and guardrails for retries, cost control, and failure recovery. This automates sequential pipelines, parallel generation, and continuous PR loops.

Parallel generation in multi-agent orchestration spawns multiple agent variants concurrently to explore diverse approaches and converge on a best solution. This avoids manual coordination drift between iterations.

A continuous PR loop is an automated iteration pattern that creates and merges pull requests, fixes issues, and repeats for continuous improvement. It operates autonomously within multi-agent workflow orchestration.

Spec-driven DAG orchestration decomposes complex specs into a dependency DAG with isolated worktrees and stage-specific contexts. This ensures structured execution and context separation across complex autonomous loops.

Yes, a sequential pipeline pattern executes steps in order with a fresh context, where each step's exit code governs the next action. This provides structured, sequential execution in automated workflows.

Autonomous loop orchestration imposes modular loop patterns with built-in guardrails for retries, cost control, and failure recovery. These mechanisms prevent drift and manage resources across complex multi-agent tasks.