GitHub Copilot Agent for .NET Projects

public class Product
{
    public int Id { get; set; }

    public string Name { get; set; } = string.Empty;

    public decimal Price { get; set; }
}

Rather than writing each property manually, Copilot Agent can generate the class based on your requirements.

Refactoring Existing Code

Many enterprise applications contain legacy code that is difficult to maintain.

Consider this example:

public decimal Calculate(decimal price, decimal tax)
{
    return price + tax;
}

You could ask the agent to improve readability, rename variables, or follow your team's coding standards.

It can also:

• Extract methods

• Remove duplicate code

• Improve naming

• Simplify conditional statements

• Suggest modern C# syntax

Always review the proposed changes before accepting them.

Generating Unit Tests

Writing unit tests can be repetitive, especially for CRUD operations.

Given this service:

public class Calculator
{
    public int Add(int x, int y)
    {
        return x + y;
    }
}

The agent can generate corresponding unit tests.

Example:

[TestMethod]
public void Add_ReturnsCorrectResult()
{
    var calculator = new Calculator();

    var result = calculator.Add(5, 3);

    Assert.AreEqual(8, result);
}

This saves time while encouraging better test coverage.

Explaining Existing Code

Joining an unfamiliar project often means spending hours understanding the codebase.

GitHub Copilot Agent can explain:

• Class responsibilities

• Method behavior

• Dependency injection

• Design patterns

• API flow

• Business logic

This helps new team members become productive more quickly.

Assisting with Debugging

When errors occur, the agent can analyze code and suggest possible fixes.

For example, if an ASP.NET Core API returns a NullReferenceException, the agent may identify:

• Missing dependency registration

• Incorrect null handling

• Invalid object initialization

• Potential edge cases

While AI-generated suggestions are helpful, developers should always verify the root cause before applying fixes.

Improving Code Quality

The agent can also recommend improvements such as:

• Better naming conventions

• Removing unused variables

• Simplifying LINQ queries

• Using modern C# features

• Improving asynchronous code

• Reducing code duplication

These recommendations help maintain cleaner and more maintainable projects.

Best Practices

To get the best results from GitHub Copilot Agent:

• Write clear and specific prompts.

• Review all generated code before committing.

• Follow your team's coding standards.

• Avoid accepting suggestions without understanding them.

• Use source control to review AI-generated changes.

• Continue writing unit tests for critical business logic.

• Treat the agent as a development assistant rather than a replacement for code reviews.

These practices help ensure high-quality and reliable software.

Limitations

Although GitHub Copilot Agent is powerful, it has some limitations.

Keep in mind that it:

• May generate code that requires refinement.

• Can misunderstand business-specific requirements.

• Does not replace architectural decision-making.

• Should not be relied upon for security-critical code without careful review.

• May produce different solutions for the same prompt.

Human oversight remains essential when building production applications.

Conclusion

GitHub Copilot Agent represents the next step in AI-assisted software development. By understanding project context and helping with feature implementation, refactoring, debugging, testing, and documentation, it enables .NET developers to work more efficiently and focus on solving business problems rather than repetitive coding tasks.

While it is a powerful productivity tool, its suggestions should always be reviewed and validated. Used responsibly, GitHub Copilot Agent can become an invaluable companion for building modern .NET applications with greater speed, consistency, and confidence.