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Microsoft Semantic Kernel Articles, Tutorials & News
Microsoft Semantic Kernel articles, tutorials, and news from the DotNetNews archive.
107 articles Updated
Semantic Kernel tutorials is the focus of this topic page. Microsoft Semantic Kernel is a recurring focus for C# and .NET developers working in the Microsoft ecosystem. Intermediate and senior .NET developers use this hub to scan practical writing without treating every link as an endorsement.
Recurring subtopics in recent issues include Semantic Kernel, Semantic Kernel .NET, Semantic Kernel tutorials, and AI orchestration .NET. Those themes are drawn from titles and excerpts in the newest archive entries for this tag, not from a marketing outline.
Expect publisher tutorials, release notes, architecture write-ups, and field notes linked from DotNetNews issues. Start here is a short editorial shortlist for Microsoft Semantic Kernel; the archive list is chronological and larger. Secondary angles such as Semantic Kernel and Semantic Kernel .NET appear when the archive actually covered them. Nearby reading often overlaps with OpenAI for .NET Developers and ML.NET.
Each card points at the original publisher URL and the DotNetNews issue that carried it, so you can read the article in context or jump straight to the source.
Start here
Editor picks for Semantic Kernel
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Building an AI Agent Marketplace with ASP.NET Core and Semantic Kernel
c-sharpcorner.com Issue #503
Marketplace framing is broader than a simple demo, and Semantic Kernel keeps showing up as the glue layer for these apps.
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Semantic Kernel Plugins Explained: Extending AI Applications with .NET
c-sharpcorner.com Issue #503
Plugins are where Semantic Kernel gets practical, so this is a useful angle if you want agents to touch real systems.
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We Built an AI Agent Platform on .NET. Then Microsoft Shipped Agent Framework 1.0.
medium.com Issue #463
The most interesting part here is the retrospective: architecture mistakes around agent platforms are usually more valuable than polished success stories.
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A Semantic Kernel Alternative for .NET — When and Why You’d Reach for One
medium.com Issue #448
Worth reading if you're evaluating AI plumbing in .NET and want a clearer sense of when Semantic Kernel may be too much or not enough.
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AI integrations: Rely or verify? Checking Semantic Kernel
unicorn-dev.medium.com Issue #446
Worth reading if you’re wiring in AI features and want to validate Semantic Kernel behavior instead of assuming abstractions are correct.
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You’re Not Just a .NET Developer Anymore — Why Microsoft Wants You Thinking in Workflows
towardsdev.com Issue #259
“Durable Functions, Dapr, and Semantic Kernel: Microsoft’s New Stack for Orchestrated .NET Workflows” Continue reading on Towards Dev ».
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The AI Toolkit Every .NET Developer Should Know: Semantic Kernel
blog.stackademic.com Issue #257
Semantic Kernel, Refit, and the dnx preview give this issue a solid AI-and-tooling spine.
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Enhancing Analytical Queries with Semantic Kernel and In-Memory SQL Processing
devblogs.microsoft.com Issue #254
Interesting to see Semantic Kernel paired with in-memory SQL for analytical querying and LLM-assisted data access.
Archive
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Newest first
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ChatClient Middleware vs Agent Middleware in Microsoft Agent Framework: What I Learned After…
topuzas.medium.com Issue #534
I ran into Jesse Liberty’s post on ChatClient middleware versus Agent middleware a couple of weeks ago, right when I was wiring up logging…
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From dotnet run to Foundry Hosted Agent in 3 lines of C#
devblogs.microsoft.com Issue #534
A couple of weeks ago I was talking with a couple of friends who are building agents with Microsoft Agent Framework. The demos were great, the agents were smart, everyone was happy. And then one of th...
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Building your own MCP server
youtube.com Issue #533
The Model Context Protocol (MCP) is all the rage and rightly so. As the USB-C for AI, it is an incredibly powerful tool that acts as a bridge between real-world systems and LLMs. But how do you get st...
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AI Agents vs LLMs: What’s the Difference and When Should Developers Use Each?
c-sharpcorner.com Issue #533
Understand the difference between LLMs and AI agents with practical C# and .NET examples covering tool calling, memory, state, agent loops, RAG, guardrails, and enterprise AI architecture.
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State in AI Agents: What Should an AI Remember About You?
medium.com Issue #532
If an AI agent can remember your conversation, does that mean it actually knows your preferences?
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Building Intelligent .NET Applications: From AI Features to Agentic System
youtube.com Issue #526
AI is becoming a core part of modern application development, and .NET offers a practical, incremental way to get started. In this session, you'll learn how to build intelligent .NET applications by a...
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An Overview of Agent Memory for .NET
jesseliberty.com Issue #525
The ability for Microsoft Agent Framework agents to retain and utilize knowledge across interactions is critical. One solution for this is Agent Memory for .NET, a cutting-edge, mind-blowing, graph-na...
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Routing and Failover for Microsoft.Extensions.AI
devblogs.microsoft.com Issue #520
As AI adoption scales, cost, uptime, and latency become first-class constraints on application architecture. Routing between models or providers is a lever on all three at once. These new Microsoft.Ex...
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Implementing AI Memory in .NET Applications Using Semantic Kernel
c-sharpcorner.com Issue #519
Unlock AI memory in .NET with Semantic Kernel. Learn about types, stores, and best practices for context-aware applications.
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Building Multi-Agent AI Systems in C# Using Microsoft Semantic Kernel
c-sharpcorner.com Issue #517
Build modular, scalable multi-agent AI systems in C# with Microsoft Semantic Kernel for complex business workflows.
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Solving the Imbalanced Data Problem in RAG
c-sharpcorner.com Issue #516
Solve RAG imbalanced data with pure Python weighted sampling. Ensure critical edge cases are represented, boosting LLM performance without external dependencies.
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.NET AI Community Standup: MCP C# SDK 2.0: Building the Next Generation of .NET AI Agents
youtube.com Issue #516
Join Bruno, Pranav, and Tarek for the next .NET + AI Community Standup. We’ll explore version 2.0 of the official MCP C# SDK, including its stateless-first design, standardized HTTP support, Multi Rou...
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Gate2ASI AI’s AgentFactory: From Agent Memory to Governed Operational Intelligence
c-sharpcorner.com Issue #516
Gate2ASI AI's AgentFactory builds governed digital teams with persistent memory, operational intelligence, and human oversight for reliable enterprise AI.
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From Prompt Engineering to Harness Engineering: How .NET Teams Should Build Around Claude Code
topuzas.medium.com Issue #516
For a long time my mental model for getting good output from Claude Code was: write a better prompt. Add more context to the system prompt…
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Building Retrieval Pipelines with Microsoft.Extensions.VectorData in .NET
c-sharpcorner.com Issue #516
Build flexible .NET retrieval pipelines with Microsoft.Extensions.VectorData, avoiding vector database lock-in and standardizing RAG architectures.
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Vector Databases with .NET: PostgreSQL pgvector vs Azure AI Search vs Qdrant
c-sharpcorner.com Issue #516
Compare PostgreSQL pgvector, Azure AI Search, and Qdrant for .NET AI apps. Choose the best vector database for RAG, semantic search, and more.
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Building AI-Powered Build Diagnostics with the Microsoft Binlog MCP Server
c-sharpcorner.com Issue #516
AI-powered build diagnostics with Microsoft Binlog MCP Server. Analyze MSBuild .binlog files via natural language for faster debugging.
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Understanding SOLID Principles in C#
medium.com Issue #516
Most .NET developers learn SOLID early — yet many production systems still become tightly coupled, difficult to test, and painful to…
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Custom Error Hierarchies in Enterprise LangGraph Multi-Agent Systems
c-sharpcorner.com Issue #516
Build resilient enterprise AI with custom error hierarchies in LangGraph. Achieve automated self-healing and enhanced observability.
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Production-Ready AI Chat Applications in Blazor Using Semantic Kernel
c-sharpcorner.com Issue #515
Build production-ready Blazor AI chat apps with Semantic Kernel. Learn architecture, best practices, and deployment for scalable, secure LLM integration.
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Building agent teams with Agent Framework, GitHub Copilot CLI and Squad
devblogs.microsoft.com Issue #514
Microsoft Agent Framework supports creating agents that use the GitHub Copilot SDK as their backend. GitHub Copilot agents provide access to powerful coding-oriented AI capabilities, including shell c...
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How I Fixed a Silent Bug in Microsoft’s Semantic Kernel
medium.com Issue #514
My contribution to a 28k-star Microsoft OSS project: adding Think support to the Ollama connector for .NET reasoning models
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Building AI Agent Platforms with .NET Aspire, Semantic Kernel, and MCP
c-sharpcorner.com Issue #514
Build production-ready AI agent platforms with .NET Aspire, Semantic Kernel, and MCP for orchestration, AI, and tool access.
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Discover Agent Skills from MCP servers in .NET
devblogs.microsoft.com Issue #514
Your agents can now discover and load Agent Skills directly from a Model Context Protocol (MCP) server. Instead of shipping every skill inside your application or copying skill folders into each deplo...
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Enterprise AI Patterns for .NET Developers
youtube.com Issue #511
Join Bruno Capuano and Angel Hernandez for a live conversation on the latest developments in AI for .NET developers. In this episode, we'll explore practical ways to integrate AI into modern .NET appl...