dispatching-parallel-agents

Parallel agent coordination requires tasks to be completely unrelated and non-interacting, meaning they can proceed without shared state. If your tasks require shared state or interact with each other, you should tackle them sequentially instead of using parallel execution.

The best way to handle independent failures is dispatching specialized agents to work on separate problems concurrently. This ensures focused context for each task, accelerating resolution and improving coverage compared to sequential troubleshooting.

To avoid cross-talk when running multiple AI agents in parallel, assign each problem to a dedicated agent with isolated context. This structured coordination uses explicit prompts and boundaries to ensure predictable, reproducible outputs without interference.

Parallel execution coordination is designed for 3 or more unrelated failures or tasks that do not require shared state. If your tasks are related or need to interact, this approach is not suitable and sequential processing is recommended.