task-coordination-strategies

Task decomposition for multi-agent coordination splits complex features across layers, components, concerns, and file ownership. This creates independent work units that multiple agents can execute in parallel without conflicts.

Parallel task planning uses Independent, Sequential, Diamond, and Pipeline dependency graph patterns. These manage blockedBy and blocks relationships to minimize bottlenecks and structure agent execution flows.

A structured task description for workload balancing includes objective, owned files, requirements, interface contracts, acceptance criteria, and scope. This ensures clear ownership and even distribution across agent teams.

Diamond dependency in project planning starts with one task, branches into parallel independent tasks, and converges into a final dependent task. It balances parallelism with controlled synchronization points.

Use pipeline task decomposition when output of one stage feeds the next, requiring sequential handoffs. Independent parallel tasks suit isolated work units without cross-dependencies or strict execution order.

Workload monitoring tracks progress across agent teams to detect blockers and uneven distribution. Rebalancing guidance helps shift pending tasks to available agents to maintain continuous throughput.