If you've been watching the AI space from the sidelines and thinking, “This all looks interesting, but where does a C# developer even begin?”, you’re not alone. Most of us started there.
AI agents seem complicated until you actually build one — and then suddenly the whole idea becomes surprisingly straightforward.

This first post in the series is all about getting that initial win. You’ll build a small .NET 8 console application that talks to an AI agent using the Microsoft Agent Framework and the OpenAI .NET SDK. No ML background required. No giant architecture diagrams. Just code, clarity, and an agent that responds to your questions.

Let’s get something working.

Note : This blogpost is part of the AI Agent learning series here.

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What You'll Build Today

By the end of this post, you’ll have a functioning AI agent that:

• Reads instructions you define

• Accepts a question

• Calls an AI model

• Produces a clean, human-readable response

Visually, the flow looks like this:

You → Agent → Model → Response

And yes — you can build this in under 50 lines of code.

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Before You Begin

You’ll need:

• .NET 8 installed

• A terminal

• An OpenAI-compatible API key

• Basic C# familiarity

If you’ve built a console app before, you’re ready.

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Building Your First AI Agent

Let’s walk through the entire process step-by-step.

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1. Create the Project

dotnet new console -n AgentWorkshop
cd AgentWorkshop

2. Add the Required Packages

Install the OpenAI SDK and Microsoft Agent Framework extensions:

dotnet add package OpenAI
dotnet add package Microsoft.Agents.AI.OpenAI --prerelease

The first package is your API client.
The second transforms a model into an agent with instructions and behavior.

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3. Write the Agent Code

Below is the full Program.cs for this first post. It’s simple by design, but shows the core pattern used throughout the series.

// Program.cs — "Hello, AI Agents!"
// A straightforward introduction to the Microsoft Agent Framework in .NET 8.

using System;
using System.Threading.Tasks;
using OpenAI; // Official OpenAI SDK used by the agent extensions

internal class Program
{
    private static async Task Main(string[] args)
    {


        // 1. Add your API key.
        // For local experiments and simplicity let's define the API key here
        const string apiKey = "sk-proj-API";

        if (apiKey.Contains("YOUR_API_KEY_HERE"))
        {
            Console.WriteLine("Please insert your API key before running the application.");
            return;
        }

        // 2. Create an OpenAI client.
        // This client communicates with the model.
        var client = new OpenAIClient(apiKey);

        // 3. Wrap the model as an AI agent.
        // "gpt-4o-mini" is a compact, fast model suitable for simple tasks.
#pragma warning disable OPENAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
        var agent = client
            .GetOpenAIResponseClient("gpt-4o-mini")
            .CreateAIAgent(
                name: "HelloAgent",
                instructions:
                    "You are a clear, friendly assistant who explains AI agents " +
                    "to developers without assuming prior AI knowledge."
            );
#pragma warning restore OPENAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

        Console.WriteLine("Ask your AI agent a question (or press Enter for a default prompt):");
        Console.Write("> ");
        var question = Console.ReadLine();

        // Provide a fallback question for convenience.
        if (string.IsNullOrWhiteSpace(question))
        {
            question = "Give me a simple explanation of what an AI agent is.";
        }

        Console.WriteLine("\nProcessing your request...\n");

        // 4. Execute the agent request.
        var response = await agent.RunAsync(question);

        // 5. Display the result.
        Console.WriteLine("=== Agent Response ===");
        Console.WriteLine(response);

        Console.WriteLine("\nComplete. You've just created your first AI agent in C#.");
    }
}

Run it:

dotnet run

You’ll see a prompt, enter your question, and the agent will produce a response that follows the instructions you gave it. That “instruction layer” is one of the most powerful parts of building agents — and something we’ll explore more as the series continues.

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Try It Yourself

Once the basic agent is working, experiment a little to build intuition.

1. Adjust the agent’s behavior

Change the instructions:

instructions: "Explain everything like you're mentoring a new developer."

Run it again — notice the shift in tone.

2. Ask a deeper question

Try something more contextual:

> When should a team consider using an AI agent instead of a traditional API?

Now you have a lightweight agent shell running locally.

Source code :

You can find the entire source code here for this blogpost.

What You Learned Today

By completing this first post, you now understand:

• What an AI agent fundamentally is

• How the Microsoft Agent Framework wraps model calls into a structured “agent” pattern

• How to configure the agent’s behavior using simple instructions

• How to build and run a minimal agent in a .NET 8 console app

This foundation will make the next steps feel much more natural.

Next Up: “Zero to Agent in 30 Minutes: Your Foundry Setup”

In the next post, we’ll clean up this initial project, move configuration out of the code, and prepare your environment for a full-featured agent workflow.