I've seen both LangGraph and AutoGen mentioned for multi-agent setups. Which one is better for developers who want fine-grained control over the flow of information? I'm specifically interested in how they handle custom logic between agent handoffs in a production environment.
3 answers
The choice depends on your preference for "autonomy" vs "control." AutoGen is excellent for conversational agents where they figure out the path themselves, but it can be hard to constrain. LangGraph is built on top of LangChain and gives you explicit control over the flow via a graph. If you need to strictly define that Agent A must speak to Agent B only under certain conditions, LangGraph is the better tool. It feels more like writing code and less like prompting agents to behave, which usually leads to higher predictability in commercial software.
Is it possible to use LangGraph to manage the top-level flow while using AutoGen agents for the specific sub-tasks?
LangGraph is definitely more modular if you are already used to the LangChain ecosystem and its tools.
Agreed, the integration with LangSmith for debugging the graph transitions makes it a very strong contender for dev teams.
Technically yes, as LangGraph nodes can run any Python code. However, it might get complex managing two different agent states. It's usually cleaner to stick to one ecosystem.