
AutoGen
Programming framework for agentic AI
The Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Aug 2026
AutoGen is Microsoft's framework for building multi-agent AI systems, where several agents with different roles and tools work together, or alongside a person, to finish a task. You define the agents and AutoGen handles how they talk, call tools, run code in a sandbox, and pause for your approval. The code is MIT, the docs and examples are CC-BY-4.0, and all of it is free.
Here is the part that matters before you build on it: AutoGen is in maintenance mode. Microsoft named microsoft/agent-framework as the successor and steers new users there. AutoGen still runs and the v0.7 line is stable, but its Python packages have not shipped a release since September 2025 while the successor ships roughly every week. Contributions are limited to bug fixes, security patches, and docs.
Already running it in production? You are fine for now, but put a migration to microsoft/agent-framework on the roadmap instead of treating this as permanent. Picking a framework today: start with the successor, or look at crewAIInc/crewAI and langchain-ai/langgraph, which most people find easier for simpler workflows. Solo and small teams: still a good way to learn the patterns, you are just learning a frozen API.
The catch is that, plainly: Microsoft stopped developing this. The pile of existing tutorials makes it look like the safe default, and maintenance mode means no fixes for new model behaviors and no new capabilities. Building something long-lived on a frozen framework is a decision, not a default.
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.
What to do by team size
- Solo
- free; fine for learning multi-agent patterns, just know the API is frozen
- Small team
- free, but start new work on microsoft/agent-framework instead
- Medium team
- free; if you already run it, budget a migration rather than a rewrite later
- Large team
- free; a frozen framework is a supply chain decision, get the migration on the roadmap
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