Is OpenAI Agents SDK better than LangGraph for cyclic workflows?

All answers to this question.

LangGraph is essentially a state machine, which is perfect for cycles. The OpenAI Agents SDK can simulate cycles—for example, Agent A hands off to Agent B, who hands back to Agent A—but it lacks the "State" management of a graph. In the OpenAI Agents SDK, each handoff is a new turn. If you need to "branch" or "wait" for external input mid-cycle, LangGraph’s nodes and edges are far more robust. For simple retry loops, though, the SDK is much faster to implement.

   Answered 2025-10-15 by Rebecca Higgins

Does the OpenAI Agents SDK support parallel execution of agents in a cycle?

   Answered 2025-11-01 by Jason Myers

• Currently, no. The OpenAI Agents SDK is primarily designed for sequential handoffs. If you want to run three "Reviewer" agents in parallel and then aggregate their results, you'd have to manage that concurrency yourself using Python's asyncio or threading, whereas LangGraph has built-in support for parallel fan-out/fan-in operations.

     Commented 2025-11-05 by Brian Walsh

For a "Write-Test-Fix" loop, I’d just use a single agent with multiple tools. The OpenAI Agents SDK is overkill if it's just one persona.

   Answered 2025-12-12 by Deborah Long

• Good point, Deborah. Sometimes we overcomplicate things with multi-agent setups when the OpenAI Agents SDK works best with just a few clear handoffs.

     Commented 2025-12-15 by Michael Lawson