Migrating from LangChain to OpenAI Agents SDK for multi-agent systems

All answers to this question.

If your primary pain point is debugging, then yes, the SDK is a major upgrade. One of the best features in the 2026 version is that tracing is a first-class citizen; you don't need to configure an external platform like LangSmith just to see what your agent is "thinking." The handoff logic is explicit in the code rather than hidden inside a class abstraction. In my last project, we reduced our codebase by 40% just by moving our multi-agent router to the SDK. The token overhead is also lower because you aren't passing massive "system prompt templates" that LangChain often injects under the hood to manage its own internal state transitions.

   Answered 2025-06-12 by Kimberly Foster

Does the SDK handle long-term memory and session persistence as well as LangChain’s Zep or memory components?

   Answered 2025-06-25 by Justin Casey

• Justin, that’s where you have to be careful. The OpenAI Agents SDK handles conversation history within a session very well, but for cross-session "long-term" memory—like remembering a user's preference from three weeks ago—you still have to build your own persistence layer or use an external vector DB. LangChain has more "out-of-the-box" connectors for that kind of persistent memory, so you might end up writing more manual code with the SDK in that specific area.

     Commented 2025-07-02 by Lawrence Pratt

It’s definitely enough for developers who hate "magic" code. Everything in the SDK is just standard Python objects, which makes unit testing 10x easier.

   Answered 2025-08-15 by Megan Walsh

• Spot on, Megan. Bradley, if your team is tired of "archaeology" every time an error pops up in a LangChain chain, the move to the SDK will be a relief.

     Commented 2025-08-20 by Bradley Moore