LangGraph wins if you treat agents like infrastructure. You define the state explicitly, name your nodes, and the runtime gives you replayability, checkpointing, and a real visual trace. It pays off the day a multi-step flow breaks at step seven and you need to resume from step six.
CrewAI wins on time-to-first-working-crew. The role + task metaphor is the right abstraction for "I want a researcher agent and a writer agent and a reviewer agent" and the framework gets out of the way. The tradeoff is the metaphor itself: it bends awkwardly once your workflow stops looking like a small team.
AutoGen wins for the design space where the answer is "make the agents talk to each other and see what happens." Multi-agent group chat is a different shape from a graph or a crew and there are problems (especially research) where it is the right shape. Less of a production framework, more of a thinking tool.