I'm on the Python advocacy team at Microsoft, so I've been experimenting a bit with the new framework. It works pretty well, and is comparable to Langchainv1 an

I'm on the Python advocacy team at Microsoft, so I've been experimenting a bit with the new framework. It works pretty well, and is comparable to Langchainv1 and Pydantic-AI, but has tighter integrations with Microsoft-specific technologies. All the frameworks have very similar Agent() interfaces as well as graph-based approaches (Workflow, Langgraph, Graph). I have a repository here with similar examples across all those frameworks: https://github.com/Azure-Samples/python-ai-agent-frameworks-demos/?tab=readme-ov-file#running-the-python-examples https://github.com/Azure-Samples/python-ai-agent-frameworks-... I started comparing their features in more details in a gist, but it's WIP: https://gist.github.com/pamelafox/c6318cb5d367731ce7ec01340ebd780c https://gist.github.com/pamelafox/c6318cb5d367731ce7ec01340e... I can flesh that out if it's helpful. I find it fascinating to see where agent frameworks converge and diverge. Generally, the frameworks are converging, which is great for developers, since we can learn a concept in one framework and apply it to another, but there are definitely differences as you get into the edge cases and production-level sophistication.