News

News

Stay current with .NET + AI ecosystem releases, breaking changes, deprecation notices, and tooling updates that affect your projects.

The News pillar tracks everything that affects your .NET + AI projects: SDK releases, breaking changes, deprecation notices, and new tooling. Get the context behind each update — not just the changelog.

SDK Releases

.NET, Semantic Kernel, ML.NET updates

Breaking Changes

What broke and how to migrate

Tooling Updates

IDE extensions, CLI tools, libraries

Latest Updates

Feb 28, 2026 From Trending AI

OpenAI launched ChatGPT Agent Mode with autonomous browsing, coding, and multi-step task execution. Here's what .NET developers building agentic systems should understand.

Feb 28, 2026 From Trending AI

OpenAI's GPT-5 and reasoning models (o1, o3, o4-mini) bring improved tool use, longer context, and better structured output. Here's what matters for .NET AI applications.

Feb 28, 2026 From Trending AI

The industry can't agree on what an AI agent is. Here's a practical engineering definition, how agents differ from chatbots, and what this means for .NET developers.

Feb 28, 2026 From Trending AI

Open-source LLMs like Llama 3, DeepSeek, and Qwen make local inference viable. Here's what .NET developers need to know about running models without cloud APIs.

Feb 18, 2026 From NuGet Release

Microsoft.Extensions.AI 10.3.0 brings updated IChatClient and IEmbeddingGenerator abstractions, improved middleware pipeline support, and new OpenTelemetry integration for .NET AI applications.

Feb 11, 2026 From NuGet Release

Summary of the .NET 9.0.2 SDK release including new features, breaking changes, and migration guidance for .NET developers.

Jan 28, 2026 From NuGet Release

Azure.AI.OpenAI 2.1.0 ships as the first generally available v2 release with native IAsyncEnumerable streaming, GPT-4 Vision support, and structured output enforcement via response_format.

Jan 22, 2026 From NuGet Release

Azure.Search.Documents 11.7.0 introduces production-ready native vector search, HNSW indexing, semantic ranking integration, and hybrid retrieval — the foundation for .NET RAG applications.

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