How to Build a Simple Web App Using AI Tools in 60 Minutes

Building a web app can often feel like a daunting task, especially for indie hackers and solo founders who are juggling multiple responsibilities. However, with the rise of AI coding tools, it's possible to build a simple web app in just 60 minutes. In this guide, I'll walk you through the tools you need, the steps to take, and what to watch out for along the way.

Prerequisites: What You'll Need

Before diving in, make sure you have the following:

• A Computer: Mac, Windows, or Linux will work.
• Basic Coding Knowledge: Familiarity with HTML, CSS, and JavaScript is helpful but not mandatory.
• Accounts: Sign up for the following AI tools:
  • GitHub (for version control)
  • Vercel or Netlify (for deployment)
  • An AI coding assistant (like OpenAI's Codex or GitHub Copilot)

Step 1: Choose Your AI Coding Tool

Here are some of the AI coding tools you can use:

| Tool | What It Does | Pricing | Best For | Limitations | Our Take | |-----------------------|-----------------------------------------------------|----------------------------|---------------------------|----------------------------------|----------------------------| | GitHub Copilot | AI pair programmer that suggests code as you type | $10/mo | Quick code suggestions | Limited to supported languages | We use this for fast prototyping. | | OpenAI Codex | Generates code based on natural language prompts | $20/mo for Pro tier | Building APIs | Can struggle with complex logic | We don’t use it as much due to cost. | | Tabnine | AI code completion tool for various languages | Free tier + $12/mo Pro | Multi-language projects | Free tier is limited in features | We use it for specific projects. | | Replit | Online IDE with collaborative features | Free tier + $7/mo for Pro | Collaborative coding | Performance can lag with larger apps | We don’t use it for production but it’s great for learning. | | Codeium | AI code completion with support for many languages | Free | Quick code snippets | Lacks advanced features | We haven’t tried it yet. |

Step 2: Set Up Your Development Environment

1. Create a New Repository on GitHub.
2. Clone the Repository to your local machine.
3. Open Your IDE (like VSCode) and set up a new project folder.

Step 3: Build Your Web App

1. Create Your HTML File: Start with a simple index.html file.

   • Use AI tools to generate boilerplate HTML.
   • Example: Ask GitHub Copilot for a simple webpage template.

2. Add CSS for Styling: Create a style.css file.

   • Use AI to suggest styles or layouts.
   • Keep it simple to save time.

3. JavaScript for Interactivity: Create a script.js file.

   • Use AI to generate functionality, like a button click event.

Expected output: You should have a basic web app with a homepage that has some interactive elements.

Step 4: Test Locally

1. Open Your HTML File in a browser to see your web app in action.
2. Debug Any Issues: Use the browser console to identify errors.
   • Common issues might include missing files or syntax errors.

Troubleshooting: What Could Go Wrong

• Code Errors: If the app doesn’t work, check the console for error messages.
• AI Limitations: Sometimes, AI tools might suggest incorrect code. Always double-check.

Step 5: Deploy Your Web App

1. Select a Hosting Service: Vercel or Netlify are great options for quick deployment.
2. Connect Your GitHub Repository to the hosting service.
3. Deploy: Follow the hosting service's instructions to push your app live.

Expected output: Your web app should now be live and accessible via a URL.

What's Next?

Once your web app is live, consider the following:

• Gather Feedback: Share your app with friends or on social media for feedback.
• Iterate: Use the feedback to improve your app.
• Explore Advanced Features: Look into adding a database or additional functionalities.

Conclusion: Start Here

Building a simple web app using AI tools can be done in about 60 minutes, given you have the right tools and a basic understanding of web development. Start with GitHub Copilot for coding assistance, use Vercel for deployment, and don’t hesitate to lean on the community for feedback.

What We Actually Use

For our own projects, we primarily use GitHub Copilot for coding and Vercel for deployment. It’s a straightforward setup that saves us time, allowing us to focus on building and iterating.