AutoGen review

What it is

AutoGen is Microsoft Research's framework for building systems where multiple agents converse to solve a task. It is free, open source, and unusually flexible about the shapes those conversations can take.

Where it shines

Code execution loops. An AutoGen agent can write code, run it in a sandbox, read the traceback, and correct itself — repeatedly, until tests pass. This is the pattern that makes agents genuinely useful for data analysis and engineering tasks, and AutoGen's implementation is the most refined in the open source ecosystem.

Conversation flexibility is the other strength. Beyond simple pipelines, you can define group chats with a selection policy, nested conversations, and human-in-the-loop checkpoints where a person approves before execution continues. For research into how agents should collaborate, that expressiveness is the point.

AutoGen Studio lowers the entry barrier: a visual environment to assemble and test agent teams without writing the orchestration code first.

Where it falls short

It behaves like a research project because it is one. Production concerns — cost controls, rate limiting, graceful degradation, monitoring — are largely left to you, and the documentation assumes an experimental mindset rather than an operational one.

Major version rewrites have broken compatibility more than once, stranding tutorials and existing code. Anyone building on it should pin versions and expect migration work.

The learning curve is also steeper than role-based frameworks: the concepts are more general, which means more decisions before anything runs.

Pricing in plain English

Completely free and MIT licensed. Your only costs are the model API calls the agents make, which for conversational multi-agent systems can be substantial; paid managed hosting is available if you want the operational layer handled for you.

Who should use it

Researchers, and engineering teams that need code-executing agents and are comfortable building their own production layer. Teams wanting a supported path should look at LangChain or a commercial platform.