Ai Coding Tools

How to Build a Simple Web Application with AI Coding Tools in 2 Hours

By BTW Team4 min read

How to Build a Simple Web Application with AI Coding Tools in 2026

Building a web application can feel like a daunting task, especially if you're a solo founder or indie hacker with limited coding experience. The good news? AI coding tools have come a long way and can help you whip up a simple web app in as little as two hours. In this guide, I'll walk you through the process, share the tools I recommend, and give you an honest look at what works and what doesn't.

Time Estimate: 2 Hours

You can finish this project in about two hours if you have everything set up in advance.

Prerequisites

Before we dive in, here’s what you’ll need:

  • A computer with internet access
  • Basic understanding of web applications
  • Accounts for the tools listed below

Step-by-Step Guide to Building Your Web Application

Step 1: Choose Your AI Coding Tool

There are several AI coding tools that can help you generate code quickly. Here’s a comparison of a few popular options:

| Tool Name | Pricing | Best For | Limitations | Our Take | |------------------|-------------------------------|------------------------------|-------------------------------------|-----------------------------------| | GitHub Copilot | $10/mo (free trial available) | Code completion and suggestions | Limited to supported languages | We use this for quick code snippets. | | Replit | Free tier + $20/mo for Pro | Collaborative coding | Performance issues on larger projects | We don’t use this for heavy lifting. | | Tabnine | Free tier + $12/mo for Pro | AI-assisted coding | Less effective for complex logic | We occasionally use it for quick fixes. | | Codeium | Free | General code generation | Limited integration with IDEs | We don’t use this because of integration issues. | | OpenAI Codex | $20/mo | Natural language to code | Requires more setup | We use this for prototyping. | | Ponicode | $29/mo, no free tier | Testing and documentation | Not ideal for full app development | We don’t use it for main builds. |

Step 2: Define Your Web Application

Decide on the functionality of your web application. For this example, let’s build a simple task management app. It will have features to add, view, and delete tasks.

Step 3: Generate Your Code

Using your chosen AI coding tool, start generating the code for your application. For instance, if you choose GitHub Copilot, you can create a new repository in GitHub and use Copilot to generate the necessary HTML, CSS, and JavaScript files.

  1. Create the HTML structure: Use Copilot to generate a basic layout.
  2. Style with CSS: Ask Copilot to help with styling.
  3. Add interactivity with JavaScript: Let Copilot assist in writing the logic for adding and deleting tasks.

Step 4: Test Your Application

After generating the code, run it locally. You can use tools like Live Server (a VS Code extension) to see your app in action. If you encounter any issues, here are some common problems and solutions:

  • Problem: The tasks don’t appear.

    • Solution: Check your JavaScript console for errors and make sure you’re appending tasks correctly.
  • Problem: Styles aren’t applying.

    • Solution: Ensure your CSS file is linked correctly in the HTML.

Step 5: Deploy Your Application

Once your app is working locally, it’s time to deploy it. Here are a few options:

  • Vercel: Free for personal projects, simple deployment process.
  • Netlify: Also free tier, great for static sites.
  • Heroku: Free tier available for small apps, but gets expensive quickly.

Step 6: Iterate Based on Feedback

Once deployed, gather feedback from users. This will help you identify what works and what needs improvement. Use analytics tools to track user engagement.

Conclusion: Start Here

Building a web application using AI coding tools can be a smooth process if you choose the right tools and follow a clear plan. Start by selecting an AI coding tool that fits your needs, and don't be afraid to iterate based on user feedback.

What We Actually Use

For our projects, we primarily use GitHub Copilot for code generation, combined with Vercel for deployment. This stack allows us to move quickly without sacrificing quality.

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