StorageTrack.app
Overview
StorageTrack.app is a SaaS I designed and developed entirely on my own, built to help managers handle operations for boats, RVs, containers, and vehicles. The product was created from scratch as a way to test how far AI could go in helping a solo designer plan, build, and launch a real digital business.
Solo • Founder • Vibe Coding
Product Design
Frontend and Backend Development
Database Architecture and Security
Stripe Integration
The entire process blended design and engineering. Every step, from early discovery to deployment, was guided by a mix of human judgment and AI support. The goal was not to let AI build for me, but to use it as a tool to accelerate decisions, validate logic, and keep the product consistent from concept to code.
Context
The idea came after noticing how outdated and disconnected most storage systems were. Many operators still rely on spreadsheets or bloated tools built for other industries. I wanted to create something specific, fast, and modern — a real business tool built with care. Instead of just prototyping, this was an end-to-end business, from design to deployment.
I didn't work with a team. Every insight, decision, and build step was mine. But I didn’t do it alone. I used AI to accelerate planning, fix bugs, validate logic, and help me move faster without cutting corners.
Challenges
I started with field research. I spoke with marina owners, RV park managers, and independent lot operators to understand their routines. From those conversations, I created simplified user flows covering leases, bookings, unit management, and payments. Then I moved to architecture. I planned the Supabase database using AI to help test relationships and build policies. I structured roles, security rules, and access logic to match how real businesses operate, not just how apps usually work. Stripe came next. I designed the billing system to support both one-time purchases and subscriptions, fully integrated with Supabase and automated via webhooks. With AI, I was able to write and test secure flows fast, catching edge cases early. Design happened directly in code. I used Lovable to speed up layouts, combining React, Tailwind, and shadcn components. Every component was built to be scalable, accessible, and consistent — not as design files, but as real, working UI from day one. Throughout the project, AI acted like a partner. I used ChatGPT to debug TypeScript, refactor SQL, and prototype logic. Instead of waiting for reviews or feedback, I could solve problems immediately.
Solution
By launch, every screen, function, and flow had been reviewed and improved through an AI-powered process. The app looks clean, works fast, and matches how operators actually think. No fluff, no extra steps. Just smart design doing its job. StorageTrack.app is a real example of what one person can build when AI is used strategically — not to replace work, but to amplify it.
