How to Write a Full Application with AI Coding Tools in 2 Hours

Building a full application in just two hours sounds like a pipe dream, right? But with the rise of AI coding tools, it’s more achievable than ever—if you know where to start. As indie hackers and solo founders, we often juggle multiple roles, and time is always of the essence. In this guide, I’ll walk you through the process of building an application quickly using AI tools, sharing the tools we use, and the trade-offs involved in each.

Prerequisites: What You Need to Get Started

Before diving in, here are the essentials you’ll need:

1. Basic coding knowledge: You should be comfortable with programming concepts.
2. Accounts with AI tools: Sign up for the tools listed below.
3. A clear app idea: Have a simple application in mind—like a to-do list or a weather app.
4. A code editor: Use something like VSCode or Sublime Text.

Step-by-Step Guide to Building Your Application

Step 1: Define the Application Requirements

Spend about 10 minutes outlining what your application will do. Keep it simple! For instance, if you’re building a to-do list app, define the main functionalities:

• Add a task
• Mark a task as complete
• Delete a task

Step 2: Choose Your AI Coding Tools

Here’s a list of AI coding tools that can help you build your application efficiently:

| Tool Name | Pricing | Best For | Limitations | Our Take | |------------------|--------------------------|-------------------------------|--------------------------------------------|-----------------------------------| | GitHub Copilot | $10/mo | Code suggestions | Limited to supported languages | We use it for quick code snippets. | | OpenAI Codex | $0-20/mo (tiered pricing)| Natural language to code | May not understand complex requirements | We don’t use it yet for full apps. | | Replit | Free tier + $7/mo pro | Collaborative coding | Free tier is limited in features | Great for quick prototyping. | | Tabnine | Free + $12/mo pro | Code completion | Less effective for large projects | We don’t use it because it’s not as intuitive. | | Codeium | Free | AI-powered code generation | Still in beta, may lack stability | We’re testing it out. | | Ponic AI | $29/mo, no free tier | Full-stack development | Expensive for solo founders | We’ve avoided it for now. | | Sourcery | Free tier + $19/mo pro | Code review | Limited to Python only | We don’t use it because of language constraints. | | AIDE | $0-25/mo | Android app development | Limited to Android only | We’re not Android-focused. | | Builder.ai | Custom pricing | No-code application building | Can become costly quickly | We don’t use it as it’s not code-based. | | AI Dungeon | Free tier + $10/mo pro | Text-based applications | Not focused on traditional coding | Not applicable for our needs. |

Step 3: Generate Code Using AI Tools

For this step, spend about 30 minutes. Use tools like GitHub Copilot or OpenAI Codex to generate code based on your requirements. Here’s how to do it:

1. Write comments in your code editor explaining what each function should do.
2. Let the AI suggest code based on your comments. For example, type a comment like // function to add a task and watch it generate the function.

Step 4: Integrate the Code

Now, take about 30 minutes to integrate the generated code into a functional application. Make sure to:

• Test each function as you go.
• Use tools like Replit for collaborative coding if you’re working with someone else.

Step 5: Test Your Application

Spend 20 minutes testing your app. Make sure all functionalities work as intended. Here are some common issues to watch for:

• Error handling: Ensure your app doesn’t crash with invalid input.
• User experience: Check if the app is intuitive to use.

Step 6: Deploy Your Application

Finally, allocate 30 minutes for deployment. Depending on your app type, consider platforms like Heroku or Vercel. The deployment process typically involves:

1. Creating an account on the chosen platform.
2. Connecting your code repository (like GitHub).
3. Deploying the app with a few clicks.

Troubleshooting Common Issues

Even with AI tools, things can go wrong. Here’s what to watch for:

• Code errors: Check the console for error messages and debug accordingly.
• Deployment issues: Ensure all environment variables are set up correctly.

What’s Next: Scaling Your Application

After you’ve built and deployed your app, consider these next steps:

• Gather user feedback to improve functionality.
• Optimize performance based on user data.
• Plan for future features based on user suggestions.

Conclusion: Start Here

Building a full application in just two hours is possible with the right AI coding tools and a clear plan. Start by defining your app, choose your tools wisely, and follow the outlined steps. Remember, the key is to keep it simple and iterate based on user feedback.

If you’re ready to dive deeper into building with AI tools, check out our podcast, Built This Week, where we share real experiences and tool recommendations weekly.