Microsoft Foundry Blog
Your source for learning and building with our models, agents, and tools.
Latest posts
Foundry Agent Service is GA: private networking, Voice Live, and enterprise-grade evaluations
The next-gen Foundry Agent Service is generally available today with end-to-end private networking, Voice Live integration, expanded MCP authentication, GA evaluations with continuous monitoring, and hosted agent deployments in six new Azure regions.
What’s new in Microsoft Foundry | February 2026
February brings Anthropic's Claude Opus 4.6 and Sonnet 4.6 with 1M-token context, GPT-Realtime-1.5 and GPT-Audio-1.5, Grok 4.0 GA, the Microsoft Agent Framework reaching Release Candidate, and the Foundry REST API quietly going GA — laying the foundation for imminent SDK GA announcements across Python, .NET, JS/TS, and Java.
Microsoft Agent Framework Reaches Release Candidate
We're happy to announce that Microsoft Agent Framework is now in Release Candidate status for both .NET and Python. Release Candidate is an important milestone on the road to General Availability — it means the API surface is stable, and all features that we intend to release with version 1.0 are complete. Whether you're building a single helpful assistant or orchestrating a team of specialized agents, Agent Framework gives you a consistent, multi-language foundation to do it. Microsoft Agent Framework is the easy and most powerful way to build agents and agent systems using Microsoft Foundry or any model or AI s...
What’s new in Microsoft Foundry | Dec 2025 & Jan 2026
Catch up on all the new models, audio updates, fine-tuning expansions, and SDK updates from Microsoft Foundry spanning December 2025 and January 2026 — including GPT-5.2, Codex Max, DeepSeek V3.2, FLUX.2, and the azure-ai-projects v2 beta consolidation.
DPO Fine-Tuning Using Microsoft Foundry SDK
In the rapidly evolving landscape of large language models (LLMs), achieving precise control over model behavior while maintaining quality has become a critical challenge. While models like GPT-4 demonstrate impressive capabilities, ensuring their outputs align with human preferences—whether for safety, helpfulness, or style—requires sophisticated fine-tuning techniques. Direct Preference Optimization (DPO) represents a breakthrough approach that simplifies this alignment process while delivering exceptional results. This comprehensive guide explores DPO fine-tuning, explaining what it is, how it works, when t...
Beyond the Prompt – Why and How to Fine-tune Your Own Models
Large Language Models (LLMs) have reached a point where general intelligence is no longer the bottleneck. The real challenge in enterprise AI systems behavioral alignment ensuring models that produce consistent, reliable, policy-compliant outputs on a scale. Prompt engineering and Retrieval-Augmented Generation (RAG) are powerful but they do not change model behavior. Fine-tuning will solve this by customizing a pretrained AI model with additional training on a specific task or dataset to improve performance, add new skills, or enhance accuracy. This post explores what Microsoft Foundry fine-tuning is, when us...
Building an AI Skills Executor in .NET: Bringing Anthropic’s Agent Pattern to the Microsoft Ecosystem
We welcome guest author, Matt Kruczek, to share how to build a complete Skills Executor in .NET, combining Azure OpenAI with the Model Context Protocol (MCP) C# SDK to bring the same agentic patterns to the Microsoft ecosystem. You’ll see how to define reusable skills, connect local and external tools, and orchestrate intelligent agent loops—so enterprise teams can standardize AI behavior without hardcoding business logic.
What’s new in Microsoft Foundry | October and November 2025
Azure AI Foundry is now Microsoft Foundry. Read the latest announcements about agents, models, tools and more.
Foundry IQ in Microsoft Agent Framework
Build enterprise-grade RAG agents with Foundry IQ Knowledge Bases in ~20 lines of Python. Learn how the Azure AI Search Context Provider brings intelligent, multi-hop retrieval to the Microsoft Agent Framework—no fragmented pipelines, just plug in the knowledge your agent needs.