Multi-agent orchestration. Fancy term. Simple question underneath: how do the agents work together? The answer defines the framework, and there are really three philosophies fighting it out. The LangGraph vs CrewAI vs AutoGen triangle covers all three, which is why those names keep colliding. Picking a philosophy is the whole decision, so let me lay them out without the marketing.
First, graphs. You define nodes and edges, agents as steps in a workflow with explicit state. LangGraph is the flagship. Maximum visibility, maximum control. You feel every bit of that control in the code you write, which is either satisfying or exhausting depending on the day. Best when the workflow matters as much as the agents. Heaviest when it does not.
Second, roles. You define agents as team members with jobs, and a manager pattern coordinates them. CrewAI is the friendliest example. The abstraction matches how humans think about teams, which makes it fast to design and even faster to explain to a stakeholder. Best when the collaboration pattern is the product. I keep recommending this one to teams that need a demo by Friday.
Third, conversations. Agents talk to each other and the work emerges from the dialogue. The pattern AutoGen pioneered. Most flexible. Least predictable. That is either a feature or a bug depending on your tolerance for surprises, and I have strong opinions in both directions depending on the project. In practice, hybrids win. Real systems borrow from all three. But you still have to start somewhere.
The honest way to pick: prototype the same small task in two styles and feel the difference. An afternoon of that teaches more than a week of reading, and I say that as someone who writes the reading. Whichever philosophy you pick, plan for observability early. A mobile app to monitor AI agents is a luxury most frameworks will not hand you, but good run tracing and structured logs are the next best thing. Check before you commit, not after your first overnight run. When you see the open source multi-agent orchestration frameworks compared side by side on activity, license, and capabilities across 548 projects, the choice gets clearer fast. Compare with data at localaiagents.fyi. Or skip to working software: I build custom AI agents scoped to your actual workflow at localaiagents.fyi.