agent-team-orchestration

Multi-agent collaboration is coordinated by assigning distinct roles like Orchestrator, Builder, and Reviewer to specialized AI agents. This structured workflow manages task lifecycles from assignment to review, ensuring clear handoff protocols and efficient task routing across the team.

Task routing and state tracking are set up by defining structured task lifecycles, moving work through states like Inbox, Assigned, In Progress, Review, and Done. This process establishes clear communication channels for passing artifacts and managing work progress across specialized agents.

Handoff protocols work by establishing defined communication channels and conventions for passing work artifacts between agents. They ensure structured transitions between roles, allowing a Builder agent to seamlessly pass completed work to a Reviewer agent for quality control checks.

Quality gates and review workflows can be implemented by assigning a dedicated Reviewer role to an AI agent. This agent evaluates deliverables passed through the task lifecycle, ensuring work meets quality standards before moving tasks to the Done state or routing them back for revisions.

No specific dependencies are required to orchestrate workflows for an AI team. The orchestration framework operates independently, providing built-in role management, task state tracking, and artifact sharing conventions without relying on external libraries.

Multi-agent orchestration should be used for complex projects requiring specialized workflows and collaboration between distinct roles. It is necessary when task management demands structured lifecycles, dedicated quality gates, and parallel work streams that a single AI agent cannot effectively handle.