This tag archive explores the application of Microsoft's Semantic Kernel technology in various .NET and Azure projects, focusing on practical considerations such as performance, architecture, and deployment. For software engineers working with AI in these ecosystems, understanding Semantic Kernel's capabilities and limitations is crucial for developing robust and scalable solutions.
3 articles since Sep 2026
Learn how to harden Model Context Protocol (MCP) servers against prompt injection and tool abuse with real‑world .NET patterns, sandboxing, and observability.
Explore a production‑grade pattern for Implementing Multi‑Agent RAG using Semantic Kernel and Azure AI Foundry, tackling latency, security, and observability in real‑time customer support.
Learn how to architect, secure, and scale Deploying Multi‑Agent RAG workflows with Semantic Kernel on Azure AI Foundry—complete with code, observability, and production‑ready checklists.