5 Hacks to Build Better Apps with AI
Debug faster, work smarter, and build beautiful UIs -- that actually work
Hey, I’m Colin! I help PMs and business leaders improve their technical skills through real-world case studies. For more, check out my live courses, Technical Foundations and AI Prototyping.
Six months ago, we were excited about tools like GitHub Copilot autocompleting basic code. Today, we can build entire applications using AI.
But there's a catch – most AI-generated code isn't production-ready. The demos look great, but trying to ship them to real users reveals all sorts of issues. After building 4 small production-ready apps with AI, I've developed some practical approaches to bridge this gap.
Here are my top 5 tips for turning AI prototypes into real applications:
1. Choose the Right Stack
The most common mistake I see is picking the wrong tool for the job. Each AI coding tool has specific strengths, and trying to force one to do something it wasn't designed for leads to frustration.
My number one choice for full-stack apps is Replit. Replit gives you a complete development environment with client, server, and database capabilities.
When using Replit, I typically move over to the Assistant immediately after the initial prompt to refine my product. I only use the Agent for big tasks like adding authentication. Making changes to form inputs, labels, or colors are better suited to the Assistant.
Replit’s main weakness is design – I find I just can’t replicate the same UI quality that I get from other tools. More on how to overcome that later.
Lovable + Supabase is another good option for production apps. Lovable handles the frontend while Supabase provides authentication, database, and real-time capabilities. This combination gives you everything needed for a real product.
The main downside is that you may spend significant time debugging Supabase – from access restrictions to edge functions errors, you’ll need to learn more about how Supabase works than you’d expect.
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