dispatching-parallel-agents

Dispatch parallel agents by assigning one agent per independent problem domain with a focused objective and isolated context. This ensures each domain is addressed without cross-contaminating context, speeding up debugging and coordination when multiple unrelated failures arise.

Parallel task coordination dispatches multiple agents to tackle independent problem domains simultaneously. Each agent operates with isolated context and constraints to avoid shared state, producing structured outputs that summarize findings and actionable fixes for integration.

Aggregate outputs by requiring each parallel agent to produce concise summaries and actionable fixes. This structured output format allows you to synthesize concurrent investigation results from different modules into an integrated set of findings and fixes.

Yes, you can use parallel agents for testing across modules. Dispatch separate agents to collect diverse insights or test independent subsystems simultaneously, ensuring each agent has constraints to avoid shared state and isolated context for focused execution.

Avoid dispatching parallel agents when tasks are not independent or require shared state. The approach requires clear agent prompts and isolated contexts, making it unsuitable for problems needing cross-contaminated context or sequential dependency resolution across subsystems.