How I Created a .NET Application Using AI with Cursor

Artificial intelligence (AI) is revolutionizing software development, making processes faster and more efficient. Recently, I decided to explore Cursor, an AI-powered development environment, to see how it could optimize my workflow when creating a .NET application.

In this article, I share a technical and practical step-by-step guide based on my experience.

Step 1: Setting Up the Development Environment

Before writing any code, I needed to ensure my environment was properly set up. Here’s what I used:

• .NET SDK (latest version) Download here
• Visual Studio or Visual Studio Code
• Cursor (extension available for VS Code) Download here
• OpenAI API Key (for GPT integration)

With everything in place, I moved on to the next step.

Step 2: Creating a New .NET Project

In the terminal, I created a new console project to test the integration:

mkdir MyAIApp

cd MyAIApp

dotnet new console

Then, I opened the project in VS Code with Cursor enabled:

code .

Cursor helped by suggesting code and completing snippets automatically, significantly speeding up the writing process.

Step 3: Integrating AI into the .NET Application

To bring AI-based functionalities to the application, I used the OpenAI API. First, I installed the required package:

dotnet add package OpenAI-DotNet

Then, I implemented a simple code to interact with AI:

using System;

using OpenAI_API;

class Program

{

????static void Main(string[] args)

????{

????????Console.WriteLine("Enter your question for the AI:");

????????string prompt = Console.ReadLine();

????????

????????var openAI = new OpenAIAPI("YOUR_OPENAI_API_KEY");

????????var response = openAI.Completions.CreateCompletionAsync(prompt).Result;

????????

????????Console.WriteLine("AI Response: " + response.Completions[0].Text);

????}

}

With this code, I can send prompts and receive responses directly from AI. Simple and functional.

Step 4: Using Cursor to Improve the Code

During development, I realized that Cursor could help refactor and optimize the code. Some of the improvements I implemented based on its suggestions include:

• Better error handling: I added proper handling to prevent unexpected failures.
• Parallelism: I modified the API call to be asynchronous, improving performance.
• Response caching: I avoided repetitive API calls by storing previously obtained responses.

Cursor was essential in identifying these improvements and suggesting more efficient implementations.

Conclusion

Creating a .NET application using AI with Cursor was an extremely productive experience. Cursor acted as an intelligent assistant, suggesting enhancements and optimizing my code, while the OpenAI API brought advanced functionalities to the application.

If you haven't tried these tools in your workflow yet, I highly recommend it. They can make a significant difference in your productivity and code quality. ??