Showing category results for AIAgent

Why edge AI development is still hard  AI is no longer confined to cloud experiments. Developers are increasingly expected to deliver AI inside apps, devices, and edge systems where responsiveness, privacy, resilience, and local control are essential. But building those experiences for production is still difficult.  Teams often have to solve m...

Learn how Microsoft Foundry helps developers build, deploy, and operate production-ready agents with Agent Framework, Toolboxes, hosted agents, Microsoft 365 distribution, observability, and agent optimization.

Learn how Microsoft helps developers build trustworthy AI agents with open evaluations, portable runtime controls, production observability, and security workflows that work across frameworks.

A few weeks ago, we announced the public preview refresh of hosted agents in Foundry Agent Service — a fundamentally re-imagined agent runtime built for operationalizing production-grade AI agents in enterprise systems. Today at Microsoft Build, we are excited to share several updates that make hosted agents easier to deploy, more capable across mo...

When we launched Microsoft Agent Framework last October, we made a promise: building production-grade AI agents should feel as natural and structured as building any other software. Today, we’re delivering on that promise — with the v1.0 release of Microsoft Agent Framework and the general availability of Foundry Toolkit for Visual Studio Code (...

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 ent...

Give your agents the power to remember  Imagine your agent never asks the same question twice. Until now, most agents have been stateless. Each conversation resets to zero, forgetting what users said just minutes ago or weeks ago. Developers tried to bridge this gap with homegrown solutions — storing embeddings in databases, manually retrieving pr...

Across industries, organizations are moving from experimenting with single agents to running AI at the center of their business operations. While single agents excel at focused tasks, customers quickly discover that real enterprise work stretches across multiple steps, involves different roles, and requires strong governance. To operationalize AI i...

In today’s rapidly evolving AI landscape, developers are seeking reliable, secure, and predictable language capabilities to power the next generation of enterprise-grade agents. As agentic architecture becomes central to modern applications, teams need tools that deliver stronger privacy guarantees, deterministic behavior, and seamless integration ...

Why agents need a new foundation Over the last year, developers have been experimenting with AI agents in every imaginable form. Agents are not just chatbots or copilots — they are autonomous software components that can reason about goals, call tools and APIs, collaborate with other agents, and adapt dynamically. Whether it’s a retrieval agent fo...