Showing archive results for 2026

A Tour of the Handoff Orchestration Pattern Most multi-agent systems start out simple: a router agent receives a user request, picks the right specialist, and forwards the conversation. As long as each specialist can complete its task in one pass, that model works fine. The first time it breaks is when an agent needs more: a follow-up questio...

Once you have your Microsoft Agent Framework (MAF) agent or workflow happily running locally on your dev machine, it's time to decide how to deploy your agent to production, monitor it, evaluate it and version it. These decisions are just as important as getting the agent running. Hosted Agents in Foundry Agent Service is the easiest way to deploy ...

As organizations move from single-agent prototypes to multi-agent production systems, the ability for agents to communicate reliably across platforms and organizational boundaries becomes essential. With the release of A2A Protocol v1.0 and updated support in the Microsoft Agent Framework, you can now connect and expose your AI agents using a stabl...

When people talk about building AI agents, they usually focus on models, tools, and prompts. In practice, one of the most important architectural decisions is much simpler: where does the conversation history live? Imagine a user asks your agent a complex question, clicks “try again,” explores two different answers in parallel, and then comes ba...

Modern AI agents often aren't bottlenecked by model quality, they are bottlenecked by orchestration overhead. When an agent chains together many small tool calls, each step typically requires a new model turn, driving up latency and token usage. With CodeAct support in Agent Framework, agents can collapse those multi-step plans into a sing...

Your agents can now draw on skills authored in three different ways – as files on disk, as inline C# code, or as encapsulated classes – and combine them freely in a single provider. Add built-in script execution support and a human-approval mechanism for script calls, and you have a practical authoring model that fits real-world scenarios: skills t...

Multi-agent systems demo beautifully. Putting them in front of real users is another story. In early prototypes, a terminal or a basic chat window is enough. But once agents start handing off to each other, pausing for approvals, or asking follow-up questions, those interfaces fall apart. Which agent is active? Why is the system waitin...

Today, we're thrilled to announce that Microsoft Agent Framework has reached version 1.0 for both .NET and Python. This is the production-ready release: stable APIs, and a commitment to long-term support. Whether you're building a single assistant or orchestrating a fleet of specialized agents, Agent Framework 1.0 gives you enterprise-grade multi-a...

Handling Long-Running Operations with Background Responses AI agents powered by reasoning models can take minutes to work through complex problems — deep research, multi-step analysis, lengthy content generation. In a traditional request-response pattern, that means your client sits idle waiting for a connection that may time out, or worse, fails ...

Code-Defined Skills, Script Execution, and Approval for Agent Skills in Python When we introduced Agent Skills for Microsoft Agent Framework, you could package domain expertise as file-based skill directories and have agents discover and load them on demand. Now, the Python SDK takes skills further — you can define skills entirely in code, let age...