Project details

Overview

As someone who trains regularly, I wanted a fitness app that actually works the way I think. So I vibecoded my own: FitTracker, a lightweight, custom-built MVP that helps me stay consistent and track progress, without the mental overload.

The app lets me create custom training plans (like push, pull, legs), log weights and reps, and review progress over time. No more scrolling through Apple Notes or trying to remember last week’s workouts. Everything is simple, structured, and right there when I need it.

This was my first end-to-end MVP, built not for scale, but to see what’s possible when solving a personal problem with today’s tools. I used Lovable to prototype quickly and focused on clean UX and minimal cognitive load, making the app as frictionless as possible in the moments that matter.

It’s an early prototype, but I wanted to explore what’s possible with AI tools as a non-techie. It solves a real pain point in my own gym routine. After refining the prototype further, I plan to share it with my community to collect feedback and continue improving it.

Next steps

While some features are still manual, like tracking nutrition or sleep, I’m already thinking ahead. The next iteration will explore:

- Food logging via photo recognition

- Automatic syncing with Apple Health and my Oura Ring

- Personalized recommendations using LLM prompts trained on my own data

This project sparked my curiosity around how simple, self-built tools can drive behavioral change and how AI can support that in ways that feel natural, not overwhelming.