Building Autonomous AI Agents with Microsoft’s Agent Framework

Introduction: The Next Evolution in AI Development

In previous installments of this series, we laid the groundwork for AI in .NET. First, we covered Microsoft Extensions for AI (MEAI), which provides a unified interface for interacting with large language models. Then, we explored Microsoft.Extensions.VectorData, enabling semantic search and retrieval-augmented generation (RAG) patterns. Now, it’s time to move from passive knowledge to active autonomy. The third building block—the Microsoft Agent Framework—lets you create AI that doesn’t just answer questions but takes purposeful actions.

Building Autonomous AI Agents with Microsoft’s Agent Framework — Source: devblogs.microsoft.com

What Sets an AI Agent Apart?

At first glance, an agent might seem like just another chatbot. But the distinction is critical. A traditional chatbot follows a simple cycle: receive input, send it to a model, return the output. An AI agent, however, exhibits genuine autonomy. It reasons about a goal, selects appropriate tools, executes them, evaluates results, and iterates—all without requiring you to script every step.

Think of it like giving a colleague a to-do list versus having a conversation. With a chatbot, you’re directing every move. With an agent, you hand over the list and trust it to figure out the rest. It might search a database, run calculations, check real‑time data, or combine multiple tools to achieve the objective.

Inside the Microsoft Agent Framework

The Microsoft Agent Framework is a production‑ready SDK designed for building these intelligent agents. It reached its 1.0 release in April 2026 and is available for both .NET (C#) and Python. For .NET developers, the framework builds directly on the IChatClient interface introduced in MEAI, making the transition feel natural.

Key capabilities include:

Single‑agent and multi‑agent workflows – from a simple autonomous assistant to complex systems where agents coordinate via graph‑based orchestration.
Tool integration – agents can call functions, APIs, or external services as needed.
Context memory – maintain conversation history across interactions to make decisions aware of past actions.
Production stability – the 1.0 release ensures a reliable foundation for real‑world applications.

Creating Your First Agent

To illustrate just how easy it is to get started, let’s walk through a minimal example. The setup will feel familiar if you’ve used MEAI—after all, the Agent Framework is built on top of it.

Step 1: Install the Package

Add the NuGet package to your console application:

dotnet add package Microsoft.Agents.AI

Step 2: Write the Code

Here’s all it takes to create a simple joke‑telling agent using Azure OpenAI:

using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;

var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
    ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME")
    ?? "gpt-5.4-mini";

AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(
        instructions: "You are good at telling jokes.",
        name: "Joker");

Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

The magic happens in the .AsAIAgent() extension method. It’s the direct analog to how .AsIChatClient() bridges a provider’s SDK to the MEAI abstraction. With just a few lines, you have an agent that understands instructions and can be called with any prompt.

Looking Ahead: From Single Agent to Multi‑Agent Systems

This simple example only scratches the surface. In a production scenario, you’d equip your agent with tools—like database queries, web searches, or custom business logic. And when one agent isn’t enough, the framework’s graph‑based orchestration allows you to build teams of agents that collaborate on complex workflows.

To dive deeper, revisit Part 1 (MEAI) and Part 2 (VectorData)—they are the foundation that makes the Agent Framework possible. Stay tuned for more advanced patterns in this series.