How to Write Code with AI Tools in 60 Minutes

In 2026, the landscape of coding has shifted dramatically thanks to AI tools. If you're a solo founder or side project builder, you might be wondering how to leverage these tools to write code efficiently. You could spend countless hours sifting through documentation or tutorials, but what if I told you that you could start writing code in just 60 minutes? Let’s dive into the practical steps and tools that can help you get there.

Prerequisites: Get Ready to Code

Before we jump into the tools, here’s what you need to have ready:

1. A Code Editor: Install Visual Studio Code (VS Code) or any editor of your choice.
2. GitHub Account: Sign up for GitHub if you don't have one; it’s essential for collaboration and version control.
3. Basic Understanding of Programming: Familiarity with at least one programming language will help you get the most out of these tools.

Step 1: Set Up Your Environment (15 minutes)

1. Download and Install VS Code: Go to Visual Studio Code and download the latest version.
2. Install GitHub Copilot:
   • Navigate to the Extensions tab in VS Code.
   • Search for "GitHub Copilot" and click "Install."
   • Sign in with your GitHub account. Pricing is $10/month after a free trial.
3. Set Up a New Project: Create a new folder for your project and open it in VS Code.

Step 2: Start Coding with AI Assistance (30 minutes)

Using GitHub Copilot

1. Create a New File: Start a new file in your project, e.g., app.js.
2. Write a Comment: Describe what you want to code in a comment. For example, // Create a function to add two numbers.
3. Let Copilot Suggest Code: Press Tab to accept suggestions. You can refine your prompt if the suggestion isn’t quite right.
4. Iterate: Keep writing comments and accepting suggestions. This back-and-forth helps you understand how to structure your code.

Other AI Tools to Consider

| Tool | What it Does | Pricing | Best For | Limitations | Our Take | |--------------------|----------------------------------------------|-------------------------------|-----------------------------|-------------------------------|------------------------------------| | GitHub Copilot | AI-powered code suggestions in real-time | $10/mo after trial | General coding assistance | Limited language support | We use this for quick prototypes. | | Tabnine | AI code completion tool | Free tier + $12/mo pro | JavaScript and Python | Less effective for complex logic | We don’t use this; Copilot is better. | | Codeium | AI code assistant with team collaboration | Free | Collaborative projects | Limited integrations | We tried this but prefer Copilot. | | Replit | Online IDE with integrated AI suggestions | Free tier + $20/mo pro | Rapid prototyping | Performance can lag | Useful for quick tests. | | Sourcery | AI code improvement suggestions | Free + $10/mo for teams | Python code quality | Limited to Python | Great for improving existing code. | | Kodezi | AI assistant for debugging | $15/mo | Debugging and fixing bugs | Not comprehensive | We haven’t used this yet. |

Step 3: Debugging with AI Tools (10 minutes)

1. Run Your Code: Use the terminal in VS Code to run your code and check for errors.
2. Use AI Debugging Tools: If you encounter bugs, tools like Kodezi or even GitHub Copilot can help you troubleshoot.
3. Iterate Based on Feedback: Make adjustments based on the suggestions and test your code again.

Step 4: Version Control with GitHub (5 minutes)

1. Initialize Git: Open the terminal and run git init in your project folder.
2. Commit Your Work: Use git add . followed by git commit -m "Initial commit" to save your progress.
3. Push to GitHub: Create a new repository on GitHub and link it using git remote add origin <your-repo-url>, then push your code with git push -u origin master.

Troubleshooting: What Could Go Wrong

• Copilot Suggestions Aren’t Relevant: Be specific in your comments. The clearer you are, the better the suggestions.
• Environment Issues: Ensure your code editor and GitHub are properly configured. Double-check your installations.
• Git Errors: If you encounter issues with Git, refer to the Git documentation or community forums.

What’s Next?

Once you’ve gotten the hang of writing code with AI tools, consider exploring more advanced features, such as integrating APIs or using frameworks. You can also check out our podcast, Built This Week, where we discuss the latest tools and strategies for building projects efficiently.

Conclusion

You can start writing code with AI tools in just 60 minutes by following these steps. The key is to leverage the power of tools like GitHub Copilot for real-time coding assistance and to keep iterating based on AI suggestions.

What We Actually Use

In our experience, we primarily use GitHub Copilot for real-time coding suggestions, combined with Replit for quick prototyping and testing. For debugging, we occasionally turn to Sourcery for Python projects.