feature-coordinate

Parallel work unit coordination is managed by building dependency graphs and launching sub-agents for independent tasks. The system tracks real-time progress and handles escalations, ensuring streamlined execution across complex multi-stage workflows.

Parallel task workflows support both 'balanced' and 'speed' execution strategies. These strategies dictate how work units are dispatched and managed across dependency graphs to optimize either resource equilibrium or overall completion time.

Dependency graph analysis for multi-stage workflows builds and displays relationships between work units. This mapping allows the system to identify independent tasks for parallel sub-agent execution and properly sequence dependent stages.

Escalation handling during parallel execution is fully supported with built-in user intervention options. When work units encounter errors or require decisions, the system manages the escalation and pauses for user input before merging cycle logs.

Workflow automation for parallel sub-agent execution is ideal for complex workflows involving multiple stages and dependencies, such as software development or research projects. It is best suited when independent tasks require robust error handling and real-time progress tracking.

To verify the final state after merging parallel work units, the system merges cycle logs from all sub-agents and performs a final state verification. This ensures all dependencies are resolved and the workflow is complete before handoff.