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URL: https://devblogs.microsoft.com/dotnet/category/ai/

⇱ AI - Category | .NET Blog


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Diagnose MSBuild build failures and performance issues with AI using the new Microsoft Binlog MCP Server - 15 specialized tools that let your AI assistant investigate binary logs.

Jeffrey Fritz

Announcing the .NET Day of Agentic Modernization Livestream

Daniel Roth

Catch up on all the .NET sessions from Microsoft Build 2026 covering .NET 11, union types in C#, AI building blocks, the agentic web, .NET MAUI, and more!

Wendy Breiding (SHE/HER)

Want to get more out of your GitHub Copilot experience? Here are some easy ways to get started.

Jack Batzner

Announcing a Public Preview .NET package that adds policy enforcement, startup tool scanning, fallback governance, and response sanitization to MCP servers with a single builder extension.

Richard Lander

The `unsafe` keyword is being redesigned to mark caller-facing contracts rather than just syntax. Safety obligations between callers and callees become visible and reviewable. The model is motivated by the rise of AI-assisted code generation and arrives as a preview in .NET 11.

Shyju Krishnankutty

Build durable AI agent workflows with the Microsoft Agent Framework. Start with in-process console apps, add durability with the Durable Task runtime, scale with parallel AI agents, and host on Azure Functions for serverless execution.

Jeremy Likness

Build intelligent AI agents in .NET with the Microsoft Agent Framework. Learn how to create agents with tools, multi-turn conversations, memory, and graph-based workflows that bring together the building blocks from Parts 1 and 2.

Luis Quintanilla

Learn how we built ConferencePulse, an AI-powered conference assistant, using .NET's composable AI stack including Microsoft.Extensions.AI, DataIngestion, VectorData, Model Context Protocol, and Microsoft Agent Framework.

Jack Batzner

Learn how to govern MCP tool calls in .NET with the Agent Governance Toolkitβ€”policy-based access control, security scanning, and response sanitization to reduce risk in AI agent systems.

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