Side-by-Side Comparison
When to choose AutoGen
- ▸Your task involves agents conversing with each other — debating solutions, reviewing code, or iteratively refining a document through dialogue.
- ▸You need powerful code execution with sandboxed agents that can write, run, and debug code autonomously.
- ▸You want a visual no-code interface (AutoGen Studio) for designing and testing agent workflows.
- ▸Enterprise support, security review, and Microsoft's long-term commitment to the project are important factors.
- ▸Your use case involves a human-in-the-loop who participates directly in agent conversations at runtime.
When to choose LangGraph
- ▸You need explicit, deterministic control over agent execution paths with defined state transitions.
- ▸Your workflow requires checkpointing — the ability to save state mid-execution and resume after a failure or human review.
- ▸You're already invested in the LangChain ecosystem and want to add statefulness without switching frameworks.
- ▸You need to build complex cyclic workflows where agents loop back based on quality checks or confidence thresholds.
- ▸Your team thinks in terms of graph nodes and edges rather than conversations — LangGraph's mental model rewards careful flow design.
Find AutoGen and LangGraph Agencies
Request that any AI agent agency pitching AutoGen or LangGraph walk you through a failure scenario: what happens when a node errors, how state is recovered, and how the system notifies operators. AutoGen teams should explain their error handling in GroupChat conversations; LangGraph teams should explain their checkpointing and retry strategy. Production readiness separates good agencies from great ones.
Which has more agencies?
In our directory, there are currently 16 AutoGen agencies and 50 LangGraph agencies. LangGraph leads the directory — reflecting strong practitioner adoption. AutoGen agencies remain a strong option with deep expertise in their niche.
Bottom line
AutoGen and LangGraph solve similar problems with different philosophies. AutoGen is conversation-first: agents talk to each other and good output emerges from dialogue. LangGraph is control-flow-first: you explicitly define a state machine and execution graph. For research and coding tasks, AutoGen's conversational model often produces higher-quality results. For business process automation where reliability and reproducibility matter more, LangGraph's explicit state management is worth the extra complexity.