What does Microsoft Agent Framework add?
It separates an agent’s interactive behavior from the workflow that coordinates longer-running work. Developers can add tools, state, middleware, and checkpoints without hand-writing each part of the runtime. The useful distinction is between model-led agent behavior and explicit workflow control. That gives a team a place to model human-in-the-loop review and resumable steps.
The framework builds on lessons from AutoGen and Semantic Kernel. Microsoft Learn documents migration paths for both, which makes it a current framework fact rather than a general rule about all agent systems.
When is it a sensible choice?
It fits teams with Python, .NET, or Go codebases that need a supported route into Microsoft agent tooling, especially where workflows, middleware, and hosting need to work together. Go is in public preview, so its current feature coverage needs a separate check. Microsoft’s Agent Framework documentation lists self-hosting alongside Azure integration, so Azure is an option, not the definition of the framework.
Choose it for its execution model and operational fit, not because every Microsoft product needs it. Compare its state and debugging model with a general AI agent framework before committing a costly workflow.