How to delegate work between Microsoft Agent Framework agents by exposing focused agents as function tools, and when this is better than manual routing or a workflow engine.
Why CancellationToken matters more in .NET AI systems, and how to pass it through LLM calls, streaming responses, embeddings, retrieval, and tool execution.
How to route requests between specialized Microsoft Agent Framework agents with a cheap intent agent, structured output, and a normal C# switch statement.
How to extend Microsoft Agent Framework agents with MCP tools and Agent Skills, when to use each model, and what trust boundaries to keep around external servers, local files, and scripts.
Use structured output in Microsoft Agent Framework to turn LLM responses into typed C# objects that can be validated, tested, and used safely in application code.
How to expose small C# methods as Microsoft Agent Framework tools, pass application services through dependency injection, and protect side-effecting actions.
How to build RAG retrieval in .NET by storing embeddings in PostgreSQL with pgvector and querying them through EF Core.
How to use AIContextProvider in Microsoft Agent Framework to inject dynamic memory, reduce tool-token overhead, add guardrails, and extend agent context at runtime.
How to control token growth in Microsoft Agent Framework with message-count and summarizing chat reducers, including setup, tradeoffs, and when each approach fits.
How to manage short-term and persistent conversation state in Microsoft Agent Framework using AgentSession, StateBag, and a custom ChatHistoryProvider.