agent-team-orchestration

Multi-agent orchestration coordinates multiple AI agents across shared tasks using role definition, task routing, and asynchronous communication. It ensures work moves cleanly from planning to execution to review with clear ownership at every step.

You manage task handoffs by specifying what was done, where artifacts live, how to verify results, and what comes next for the receiving agent. This protocol keeps collaboration reliable across inbox-to-done lifecycles.

Yes, you can define orchestrator, builder, reviewer, and ops responsibilities so each agent has a single primary purpose. Role design ensures clear ownership and reliable task routing across the team.

The best way to track task lifecycles is using explicit state transitions: inbox, assigned, in progress, review, done, and failed. This tracking prevents work from stalling and ensures reliable asynchronous communication.

You handle escalations and reviews using shared files, task comments, escalation paths, and review rotation. These communication workflows keep collaboration reliable and ensure outputs meet quality standards.

Yes, shared artifact paths are required for asynchronous communication and handoffs. They allow receiving agents to verify results and access the exact outputs produced by the previous agent in the workflow.