How to Create a Simple Project Using AI Coding Tools in Under 2 Hours

If you’ve ever stared at a blank screen, wondering how to start your next project, you’re not alone. As indie hackers and solo founders, we often find ourselves overwhelmed by the complexity of coding. Luckily, AI coding tools have made it easier than ever to whip up a project quickly. In this guide, I’ll walk you through creating a simple web application using AI coding tools in less than two hours.

Prerequisites: What You’ll Need

• A laptop or desktop computer: Should be able to run a web browser.
• Basic understanding of HTML/CSS/JavaScript: You don’t need to be an expert, but some familiarity helps.
• Accounts for AI coding tools: Sign up for a couple of the tools we’ll discuss below.
• Time: Set aside about 2 hours to complete the project.

Step-by-Step Guide to Building Your Project

Step 1: Define Your Project

Before diving into the code, decide what you want to build. For this tutorial, let’s create a simple to-do list application. It’s interactive, and it allows you to see the functionality of your code in action.

Step 2: Choose Your AI Coding Tools

Here’s a list of AI coding tools that can help you build your project quickly. Each tool has its strengths and limitations, so choose based on your specific needs.

| Tool Name | What It Does | Pricing | Best For | Limitations | Our Take | |-------------------|--------------------------------------------|------------------------|----------------------------------|------------------------------------------|-----------------------------------| | GitHub Copilot | AI-powered code suggestions | $10/mo | Code completion | Limited to popular languages | We use this for quick snippets. | | Codeium | AI code completion and suggestions | Free tier + $19/mo pro | Beginners needing guidance | Less effective for complex queries | We don’t use this as much. | | Tabnine | AI assistant for code completion | Free tier + $12/mo pro | Fast coding | Can suggest incorrect code | We like it for speed. | | Replit | Online IDE with collaborative features | Free, $10/mo for pro | Rapid prototyping | Limited offline capabilities | Great for team projects. | | OpenAI Codex | Natural language to code | $0-20/mo (API usage) | Building APIs and complex logic | Requires more setup | We use it for backend tasks. | | Ponic | AI-driven code reviews | $15/mo | Code quality checks | Can miss context-specific issues | Useful for team reviews. | | Sourcery | AI code improvement suggestions | Free tier + $9/mo pro | Code refactoring | Limited to Python | We don’t use it often. | | Codeium Chat | Interactive coding assistant | Free | Asking coding questions | Less effective for advanced queries | Handy for quick help. | | Jupyter Notebooks | Interactive coding environment | Free | Data science projects | Not ideal for web apps | We use it for data-heavy projects. | | AI Dungeon | Text-based game creation using AI | Free, $10/mo for pro | Creative coding | Not suited for traditional apps | Fun for experimenting. | | DeepCode | AI code review and bug detection | Free, $25/mo for pro | Finding bugs | Limited language support | We use it for quality assurance. | | Snorkel | Data programming and labeling | Free | Machine learning projects | Requires some setup | We don’t use it often. | | ChatGPT | Conversational AI for coding assistance | Free, $20/mo for pro | General coding help | Sometimes incorrect suggestions | Our go-to for brainstorming. |

Step 3: Set Up Your Development Environment

1. Choose an IDE: Use Replit or any local IDE you prefer (like VSCode).
2. Create a new project: Set up your project structure (HTML, CSS, JS files).
3. Integrate AI Tools: Connect GitHub Copilot or your preferred tool to assist with coding.

Step 4: Build the Application

1. Create the HTML structure: Start with a simple HTML file that includes a header, input field, and a button.
2. Add CSS for styling: Use CSS to make your application visually appealing.
3. Implement JavaScript logic: Use AI tools to help write functions to add, delete, and mark tasks as completed.

Expected Outputs

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

Step 5: Testing and Debugging

Run your application to see if everything works as expected. If you encounter any issues, use AI tools like DeepCode for bug detection or consult ChatGPT for troubleshooting advice.

What Could Go Wrong

• Code errors: AI tools don’t always suggest the correct code. Review suggestions carefully.
• Integration issues: Sometimes libraries or frameworks may conflict. Ensure compatibility.
• Performance issues: If your app is slow, optimize your code and check for unnecessary loops.

What’s Next?

Once you have your to-do list application up and running, consider adding features like user authentication or a database to store tasks. You can also explore other AI tools and frameworks to expand your project.

Conclusion: Start Here

Creating a simple project using AI coding tools is not only possible but can be done in under two hours with the right approach and tools. Start by defining your project, choose the appropriate AI tools, and follow the steps outlined above.

By leveraging AI coding tools, you can focus more on logic and creativity instead of getting bogged down in syntax.

What We Actually Use

In our experience at Built This Week, we primarily use GitHub Copilot for code suggestions and Replit for rapid prototyping, which allows us to iterate quickly on our ideas.