Stop Picking AI Frameworks Before You Answer This One Question
If you're building AI agents on Azure, you've been here: a kickoff meeting where someone asks "what framework should we use?" and the next 90 minutes becomes a debate between Semantic Kernel, AutoGen, Copilot Studio, Foundry, and Logic Apps — before anyone has agreed on what the agent actually needs to do.
That is the wrong sequence. And it's why so many Azure AI projects start with the most sophisticated-sounding option and spend the next three months fighting the wrong abstraction.
The Microsoft ecosystem gives you more agent architecture flexibility than any other cloud provider. Conversational or headless. Low-code or pro-code. M365-native or Azure-native. That flexibility is a genuine advantage — but only if you read the decision tree in the right order.
This post walks through that tree. By the end you'll have a repeatable framework for choosing the right architecture the first time, plus a list of SDK retirement dates you need to know before you commit.








