Dispatching Parallel Agents

Dispatching Parallel Agents is a Superpowers skill for splitting independent problems across separate agents so investigation can happen concurrently. It is most useful when the workstreams do not depend on the same mutable state and can be solved or analyzed in isolation.

• Teams investigating several unrelated failures
• AI workflows with clearly independent research or debugging tasks
• Projects where parallel analysis can reduce elapsed time
• Agents coordinating separate workstreams without shared edits

• Investigate multiple unrelated failing tests at the same time
• Assign separate agents to independent bug domains
• Parallelize research across distinct components
• Collect separate findings before choosing implementation work

The skill first checks whether the problems are truly independent. It then gives each agent a narrow task, enough context to investigate it and a clear expected output. The coordinating agent later combines the findings and resolves any conflicts.

• Can reduce elapsed time for independent work
• Keeps each agent focused on a narrow problem
• Produces parallel evidence for a coordinator to synthesize
• Useful for broad incidents with unrelated failure clusters

• Parallel agents can conflict when tasks touch the same code or assumptions
• More agents increase coordination cost
• Independent results still need integration and validation before changes are merged