How does the OpenAI Agents SDK handle multi-agent coordination?

All answers to this question.

In the OpenAI Agents SDK, coordination is handled via "Handoffs." Essentially, an agent can return another agent as a tool call. This is decentralized; there is no "manager" object unless you explicitly code one agent to act as a triage unit. It’s much more lightweight than CrewAI’s "Process" or "Crew" abstractions. If you want a swarm of specialists passing tasks back and forth, the OpenAI Agents SDK is incredibly efficient for that specific architecture.

   Answered 2025-03-05 by Heather Miller

Do you think this decentralized approach in the OpenAI Agents SDK leads to "infinite loops" between agents?

   Answered 2025-04-10 by Brandon Taylor

• Brandon, that’s a valid concern. Since the agents decide when to hand off, you have to implement your own "max_turns" logic or guardrails. The OpenAI Agents SDK gives you the primitives, but you are responsible for the loop termination logic, unlike some higher-level frameworks that have built-in safety limits for agent conversations.

     Commented 2025-04-15 by Justin Fisher

It’s basically the Swarm pattern made official. The OpenAI Agents SDK makes transferring context between a "Writer" agent and an "Editor" agent very seamless.

   Answered 2025-05-20 by Ryan Garcia

• Spot on, Ryan. The context variables in the OpenAI Agents SDK allow you to pass state without re-sending the entire history every time, which saves on tokens.

     Commented 2025-05-22 by Katherine Rivera