How to Write Code with AI in 2 Hours: A Step-by-Step Guide

In 2026, the landscape of coding has changed dramatically, thanks to AI tools that can help you write code faster and more efficiently. But if you’re a beginner, the sheer number of tools and options can feel overwhelming. The good news? You can start writing code with AI in just two hours. This guide is designed for indie hackers, solo founders, and side project builders who want to leverage AI for app development without getting bogged down in hype.

Prerequisites: What You Need Before You Start

Before diving in, make sure you have the following:

• A computer: Windows, macOS, or Linux will work.
• An internet connection: Most AI coding tools are cloud-based.
• Basic programming knowledge: Familiarity with concepts like variables and functions will help.
• Account setup: Sign up for a couple of AI coding tools (we'll list them below).

Step 1: Choose Your AI Coding Tool

Here are some of the best AI coding tools available in 2026:

| Tool Name | Pricing | Best For | Limitations | Our Take | |------------------|-----------------------------|------------------------------|------------------------------------|--------------------------------------| | GitHub Copilot | $10/mo, $100/yr | Code suggestions in IDE | Limited to supported languages | We use this for quick code snippets. | | Tabnine | Free tier + $12/mo pro | Autocomplete suggestions | May require training for best use | Great for beginners getting started. | | Replit | Free, $7/mo for Pro | Collaborative coding | Limited features in free version | We love the collaborative aspect. | | Codeium | Free, $19/mo for Pro | Multi-language support | Slower response times | We don’t use this due to speed issues. | | Ponic AI | $15/mo | Building web apps | Limited to web frameworks | Effective for rapid web development. | | ChatGPT (Code) | $20/mo | General coding queries | May not provide full solutions | Best for troubleshooting code issues. | | Sourcery | Free tier + $10/mo pro | Code quality improvements | Limited language support | We use this for refactoring code. | | Codex | $0-20/mo based on usage | API integrations | Costs can add up quickly | Great for integrating APIs without hassle. | | AI Code Mentor | $5/mo | Learning programming | Basic features only | Useful for beginners, but very limited. | | Build AI | $29/mo, no free tier | No-code app development | Not suited for complex apps | We don’t use it for serious projects. | | CodeSmith | $10/mo | Rapid prototyping | Limited customization | Effective for quick iterations. |

What We Actually Use

In our experience, we primarily use GitHub Copilot and Replit for their balance of functionality and ease of use. GitHub Copilot is great for generating code snippets, while Replit excels in collaborative environments.

Step 2: Set Up Your First Project

1. Select a Simple Project Idea: Start with something manageable, like a to-do list app.
2. Create a New Repository: If you're using GitHub, create a new repository for your project.
3. Open Your IDE: If you’re using an AI tool like GitHub Copilot, make sure it's integrated with your IDE (like VSCode).

Expected Output: Basic Project Setup

You should have a working directory, an initial README file, and possibly a few starter files for your project.

Step 3: Leverage AI Suggestions

With your project set up, start coding:

1. Write Comments First: Describe what you want to achieve in comments. For example, “Create a function to add a new task.”
2. Use AI to Generate Code: As you type, your AI tool will suggest code snippets. Accept the suggestions that fit your needs.
3. Refine the Code: Modify the AI-generated code as necessary, ensuring it fits your project.

Troubleshooting

What Could Go Wrong:

• The AI might suggest incorrect code. Always review suggestions critically.
• If the tool is slow, check your internet connection or consider switching tools.

Step 4: Test Your Code

Once you’ve added some functionality, it’s time to test:

1. Run Your Code: Check for syntax errors and functionality.
2. Use AI for Debugging: If you encounter issues, describe them to your AI tool to get suggestions.

Expected Output: A Functional To-Do List App

By the end of this step, you should have a basic to-do list app that allows you to add and remove tasks.

Step 5: Iterate and Improve

With a basic version working, consider improvements:

• Add Features: Use AI to suggest additional features.
• Optimize Code: Use tools like Sourcery to enhance code quality.
• Get Feedback: Share your project with friends or on platforms like GitHub for feedback.

What's Next?

Once you’re comfortable with the basics, consider exploring advanced topics like API integrations or deploying your app. You can also experiment with different AI coding tools to find the best fit for your workflow.

Conclusion: Start Here

Ready to dive into AI-assisted coding? Start by choosing one or two of the tools listed above, set up your project, and leverage AI suggestions. Remember, it’s not about finding the “best” tool but what works best for you.