Quickly prepare for SQL and Python interview code tests
A lightweight Next.js + Supabase app built to explore modern web architecture, structured learning flows, and AI-assisted development.
Modern stack
Next.js, TypeScript, Supabase, and Vercel deployment.
Structured practice
Crash course → warmups → timed tests.
AI-assisted workflow
Used AI to accelerate build, debugging, and iteration.
What’s included
- Crash Courses for core SQL and Python concepts
- Warmup tests for low-pressure practice
- Timed tests to simulate interviews
- Authentication + session tracking
- Supabase-backed persistence
What I learned
This project was built to gain hands-on experience with modern frontend tools: structuring a Next.js app, integrating Supabase for auth and data, deploying through Vercel, and using AI tools to accelerate development.
Why I stopped here
After building the MVP, I evaluated the market and found strong existing platforms that already serve this space well. Rather than expand the product, I’m sharing it as a portfolio project that demonstrates implementation, iteration, and technical decision-making.
Building this project
I built Quick Code Test Prep to gain hands-on experience with a modern web stack, and to better understand how AI can accelerate real-world product development. I wanted a project that required more than static content: routing, authentication, persistence, deployment, and a functional end-to-end user flow.
The application uses Next.js, TypeScript, Supabase, and Vercel. Building it gave me practical experience with App Router structure, protected routes, production deployment, and the small implementation details that determine whether an app feels usable or fragile. It also gave me a chance to work in the kind of tight build-feedback loop that modern deployment platforms make possible.
AI tools helped me move faster, especially when scaffolding components, debugging issues, and exploring unfamiliar patterns. But they did not replace human judgment. I still had to decide how the app should be structured, and how the demo user experience should work. AI was a facilitator, but the product decisions were all mine.
After building the MVP, I evaluated the market and concluded that established platforms already served this space well. Rather than continue developing the app, I decided to use it as a portfolio project that demonstrates technical communication, implementation, and product thinking.