multi-plan

Parallel multi-agent task decomposition breaks complex tasks into discrete subtasks for simultaneous execution by multiple agents. It generates a structured plan with task dependencies, agent assignments, and cost estimates to optimize workflow efficiency and reduce overall execution time.

To generate a dependency graph for parallel execution, input a complex task description. The system analyzes the task, identifies discrete work units, builds a dependency graph to ensure correct execution order, and identifies the critical path for efficient workflow management.

Yes, you can use task decomposition for large feature development tasks like implementing JWT authentication. The system generates a plan assigning different components, such as backend API or frontend UI, to specialized agents that can work simultaneously to maximize concurrency.

The best way to optimize maximum concurrency in multi-agent workflows is by creating a structured execution plan that identifies the critical path. This approach manages task dependencies effectively and assigns discrete units of work to agents for simultaneous processing.

Yes, parallel execution planning provides cost estimates for agent assignments. The structured plan decomposes the complex task into manageable subtasks, assigns them to specialized agents, and calculates cost estimates alongside task dependencies to optimize overall workflow execution.