Dependency Injection for AI Components
Register .NET AI clients, tools, prompts, and retrieval services with explicit lifetimes, safe request state, and clear disposal ownership.
Microsoft-Extensions-Ai
Provider Independence from Day One
A C# implementation for keeping provider coupling at explicit boundaries while making model capabilities and provider-specific behavior visible.
Embeddings in .NET
How to generate text embeddings with Microsoft.Extensions.AI and keep the model, dimensions, comparison metric, and indexing behavior compatible.
Designing an AI Service Layer
How to place model access, prompts, retrieval, tools, and application policy behind a maintainable use-case boundary in a .NET application.
Stop Letting Provider SDKs Define Your .NET AI Architecture
How Microsoft.Extensions.AI keeps provider SDKs at the edge of .NET applications through shared abstractions, dependency injection, and middleware.
Use HybridCache for expensive AI work in .NET
Use HybridCache to avoid duplicate AI model calls, with a cached summarization example and deliberate cache-key design.