agent-team-orchestration

Multi-agent orchestration coordinates specialized agents by defining roles, managing task lifecycles, and establishing handoff protocols. This ensures structured task progression and quality control for complex projects like development sprints or research synthesis.

Managing task handoffs requires establishing clear communication and artifact sharing procedures between agents. Defining task states like Inbox, Assigned, In Progress, Review, and Done ensures structured progression and quality control across different roles.

Setting up a development sprint team involves assigning specialized roles like Orchestrator, Builder, and Reviewer to agents. You define task states and handoff protocols so one agent writes specs, another builds, and a third reviews before deployment.

You can implement review workflows by assigning a Reviewer role to an agent and tracking tasks through a Review state. This establishes quality gates and cross-role verification before tasks move to the Done state.

Predefined agent roles are required for effective coordination in AI teams. Clear definition of roles like Orchestrator, Builder, and Ops, along with task states and communication channels, ensures structured workflow progression.

Without structured task states like Assigned, In Progress, and Review, multi-agent orchestration lacks clear task progression and quality control. This leads to mismanaged handoffs and poor coordination between specialized agents.