dispatching-parallel-agents

Coordinate parallel tasks across AI agents by distributing independent investigations to specialized agents with isolated contexts. This approach prevents cross-context leakage and speeds up diagnosis when handling unrelated subsystem failures.

Dispatch parallel agents when you have 3+ failing tests or subsystems that can be diagnosed without shared state. This ensures isolated analysis of independent issues, preventing cross-contamination of context between concurrent investigations.

Ensure AI agents work independently by providing each agent with a self-contained prompt that has exact goals and constraints. This isolation prevents cross-context leakage during parallel dispatch of independent investigations.

Consolidate results from parallel AI agents by collecting their summaries and integrating changes through a single review pass. This audit workflow ensures combined results are verified efficiently after parallel dispatch.

Yes, parallel dispatch is designed for diagnosing 3+ unrelated test file failures. By grouping failures into independent domains, you can dispatch focused agents concurrently to analyze them without shared state interference.