
AutoGen
Programming framework for agentic AI
The Lens
AutoGen is Microsoft's framework for orchestrating multi-agent AI conversations, where multiple agents with different roles, tools, and instructions collaborate to complete tasks. You define agents with different roles, tools, and instructions, and AutoGen manages how they talk to each other to complete tasks.
The framework handles the hard parts of multi-agent systems: conversation flow, tool calling, human-in-the-loop approvals, code execution sandboxing, and state management. It works with OpenAI, Azure OpenAI, and other LLM providers.
CC-BY-4.0 license (docs/examples; the code itself is MIT). Fully free, no paid tier.
The catch: AutoGen is in heavy flux. The v0.2 to v0.4 transition broke a lot of existing code, and the API is still evolving. The include a lot of early hype. Actual production deployments are less common than the star count suggests. CrewAI and LangGraph are competitors with arguably better developer experience for simpler agent workflows. AutoGen's strength is complex multi-agent patterns, but if you just need a single agent with tools, it's overkill.
Free vs Self-Hosted vs Paid
fully freeFully open source. The framework code is MIT, documentation/examples are CC-BY-4.0. No paid tier from Microsoft for AutoGen itself.
**Your costs are LLM API calls:** - OpenAI GPT-4o: ~$2.50/1M input tokens, $10/1M output - Azure OpenAI: similar pricing - Local models via Ollama: free but slower
Multi-agent systems multiply your API costs because agents converse with each other. A 4-agent workflow processing one task might use 5-10x the tokens of a single-agent approach. Budget accordingly.
Autogen Studio (the visual UI) is also free and included.
Free framework. Your cost is LLM API usage, which multi-agent patterns multiply significantly.
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