AutoGen
Microsoft Research's open-source framework for building multi-agent AI systems using conversational agents that communicate to solve complex tasks
Free and open-source; self-hosted or bring your own LLM API keys
Overview
AutoGen is Microsoft Research's open-source framework for building multi-agent AI systems. It lets developers define multiple AI agents that communicate with each other to solve complex tasks — one agent might write code, another reviews it, a third runs tests — all coordinated automatically. It's widely used in research and production systems for orchestrating LLM-driven workflows.
Key Features
- Multi-agent orchestration where agents collaborate to complete complex tasks
- Built-in agent types: AssistantAgent, UserProxyAgent, GroupChatManager
- Human-in-the-loop support for approving agent actions at any step
- Code execution in sandboxed Docker containers for safety
- Works with any LLM including OpenAI, Anthropic, and local models
- Large ecosystem of community-contributed agent patterns and extensions
Pricing: Free and open-source (MIT license); infrastructure costs depend on LLM provider.
Pros
- Conversation-based orchestration is flexible — agents naturally collaborate through dialogue
- Backed by Microsoft Research with strong academic foundations and publications
- Built-in sandboxed code execution for safely running agent-written code
- Human-in-the-loop support for workflows requiring human review or approval
Cons
- Steeper learning curve than higher-level frameworks like CrewAI
- Conversational overhead can be slow for straightforward single-step tasks
- Major version changes (0.2 → 0.4) require migration effort for existing projects
Tags
Product Updates
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