Agents as a crew with roles and tasks — the most intuitive mental model and the fastest path to a working system, with the largest beginner community.
— You need fine-grained low-level control of agent state machines.
Multiple specialized agents beating one generalist is the promise; coordination is the hard part. The three serious open-source answers each encode a different philosophy of how agents should talk.
Agents as a crew with roles and tasks — the most intuitive mental model and the fastest path to a working system, with the largest beginner community.
— You need fine-grained low-level control of agent state machines.
Microsoft-backed, research-grade multi-agent conversation framework — the deepest well of patterns for agents that negotiate, critique, and delegate among themselves.
— You need a stable, minimal API for simple single-agent tasks.
Explicit graph orchestration — every hand-off is an edge you defined, which is exactly the control you want once a multi-agent system faces production traffic.
— You want a quick no-code start — expect real engineering investment.
Multi-agent systems multiply cost and failure modes with every added agent — most tasks are still better served by one good agent with good tools. Reach for a crew when the task genuinely decomposes, and cap iterations so a disagreement between agents can't run your bill in a loop.