The Semantic Kernel tag gathers articles comparing its performance and async behavior to Python‑based AI libraries, and exploring how it enables agentic AI on .NET and Azure. Dissecting latency trade‑offs and async patterns, these posts guide choosing the right framework for low‑latency inference and scalable agent orchestration. The material assists engineers in balancing speed, scalability, and…
7 articles since Aug 2026
Learn how to engineer advanced BPE tokenizer customization for domain‑specific corpora, integrate it into .NET LLM pipelines, and optimize performance for production workloads.
Learn how to instrument, monitor, and troubleshoot MCP server tool calls with OpenTelemetry, Azure Monitor, and Semantic Kernel for reliable, production‑grade observability.
Learn how to architect, implement, and operate a production‑grade agent harness in ASP.NET Core using Semantic Kernel, MCP, and Azure services – the five‑layer approach that scales.
Learn how to embed evaluator‑driven release gates into your .NET CI/CD flow, ensuring LLM updates meet accuracy, safety, and latency standards before they hit production.
Learn a practical decision framework for .NET teams to pick fine‑tuning, prompt engineering, or Retrieval Augmented Generation. Reduce risk, control cost, and hit latency targets.
Discover production‑ready patterns for Semantic Kernel in Python—prompt caching, context engineering, and hybrid integration with LangChain—to cut costs and boost reliability.
Explore the architectural trade‑offs, performance nuances, and .NET integration strategies of Semantic Kernel vs LangChain to make informed engineering decisions.