multi-agent

Multi-agent workflows coordinate parallel software development by routing tasks through specialized roles like Scouts for discovery, Workers for execution, and Soldiers for review. This lifecycle-driven coordination manages role-based delegation, dependency awareness, and conflict handling across teams.

Dynamic task decomposition in multi-agent orchestration breaks complex software tasks into smaller parallel units allocated to autonomous agents. It uses pheromone-like metadata signals to guide prioritization and applies adaptive concurrency controls to dynamically scale agents based on current workload.

Yes, multi-agent orchestration supports team-centric collaboration by mapping agents to architect, developer, QA, and reviewer roles. This enables end-to-end workflows with clear responsibilities and structured handoffs between agents to conclude tasks efficiently.

To start a multi-agent orchestration task, initialize the task environment and spawn Scout, Worker, and Soldier agents. This triggers parallel execution where Scouts handle discovery, Workers execute coding, and Soldiers conduct reviews before a Lead aggregates the final results.

Multi-agent orchestration handles conflict resolution during task delegation through pheromone-like metadata signals that guide prioritization and adaptive concurrency controls. These mechanisms ensure clear responsibilities and manage dependency awareness to resolve conflicts across parallel agents.