task-coordination-strategies

Task decomposition breaks complex projects into parallelizable units using strategies by layer, component, concern, or file ownership. This allows distributing manageable sub-tasks across multiple agents for efficient parallel execution.

A dependency graph maps task relationships using blockedBy and blocks patterns like sequential, diamond, or fork-join. This visual mapping optimizes workflow management by identifying critical paths and preventing execution bottlenecks.

Workload balancing monitors agent progress and reassigns tasks to ensure even distribution across the team. This prevents individual agent bottlenecks and keeps the parallelized workflow running efficiently.

The best way is decomposing the objective by component, defining clear dependencies between frontend, backend, and testing tasks, and assigning them to different agents for parallel execution with specified acceptance criteria.

Yes, you can define task dependencies and write clear task descriptions with specific acceptance criteria. This ensures agent teams understand execution requirements and dependency constraints within the workflow.

You need task decomposition strategies when managing complex projects that require breaking down large objectives into smaller, parallelizable units with clear ownership and defined dependencies for multi-agent coordination.