agent-team

To parallelize large code refactoring tasks, you can coordinate parallel agent workers that operate on separated file ranges. A central coordinator enforces output alignment and consolidates modifications to ensure a consistent result.

Multi-agent coordination is needed for codebase migrations when the task is too large for one pass and work must be partitioned into independent modules. This allows parallel workers to handle separated areas and reduce total time.

Conflict resolution for parallel agent workers happens at the coordination level. The coordinator detects cross-worker change conflicts, resolves them centrally, and stops the process when the isolated worker outputs converge into a unified result.

To split work for a comprehensive code review, a coordinator defines a scope split and establishes isolated worker editing boundaries. Workers then operate within these boundaries using a unified I/O data contract for mergeable results.

Workflow orchestration using parallel workers requires tasks that can be partitioned into independent modules or file ranges. Without isolated editing boundaries and a unified I/O data contract, merging results and resolving conflicts is not supported.

The best way to handle big refactors exceeding a single agent is to fan out the workload into parallel multi-worker execution. A coordinator assigns scopes, enforces output alignment, and reconciles findings into a single consistent result.