Microsoft AutoGen
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An open-source framework from Microsoft Research for building multi-agent applications, where agents converse to solve tasks together.
Overview
AutoGen models AI work as a conversation between agents — a coder, a reviewer, a planner — that message each other until a task is done. It is research-grade and fast-moving, with AgentChat for high-level patterns and a lower-level Core API for custom orchestration. For enterprise teams it is a credible way to prototype multi-agent designs, but the usual warning applies hard here: conversational multi-agent systems are difficult to evaluate, can loop, and burn tokens unpredictably. Treat AutoGen builds as experiments until you have evals and cost controls around them. AutoGen is now in maintenance mode per its README: it will not receive new features, and Microsoft points new projects to Microsoft Agent Framework, its successor.
Pros & Cons
Pros
- Mature multi-agent conversation patterns
- Backed by Microsoft Research
- Flexible high-level and low-level APIs
- Strong fit for experimentation
Cons
- Multi-agent conversations are hard to evaluate and debug
- Token costs can escalate without guardrails
- APIs have changed significantly between versions
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