
A production-grade, multi-tenant SaaS platform designed, architected, and built almost entirely through AI-assisted development as a solo developer.
Next Gym is the most technically ambitious project I have built: a full-stack SaaS platform spanning four deployed sub-applications and a shared Turborepo monorepo. It was developed primarily using Claude and Cursor as AI coding assistants, which dramatically accelerated the scope and quality of what I was able to ship alone.
The platform covers the complete lifecycle of running a gym business: member management, class scheduling and QR check-in, multi-product billing via Stripe, document compliance and digital signing, multi-location support, personal training management, and a React Native mobile app with biometric authentication. Each of the four sub-applications shares a tRPC v11 API layer, a Drizzle ORM schema over Supabase PostgreSQL, and a cross-platform @gym/shared package.
AI-driven development was not just a productivity tool. It was the core methodology. AI tools designed the database schema, scaffolded all 27 tRPC routers with end-to-end type safety, implemented complex multi-tenancy and RBAC patterns, wrote React Email templates, and maintained consistency across a large codebase.



Staff-facing dashboard: member management, class scheduling, QR check-in, multi-product billing, document compliance, audit logs, and full RBAC.
Next.js 15 · tRPC · Drizzle ORM
Member-facing web app: class booking, product shop, Stripe checkout, digital document signing, notifications, and profile management.
Next.js 15 · tRPC · Stripe
Public-facing marketing site for the platform with feature showcases and onboarding flows for gym operator acquisition.
Next.js 15 · Tailwind CSS v4
Native iOS/Android app: class booking, QR check-in, product shop, biometric login, dark mode, and custom tab navigation.
Expo SDK 54 · React Native · NativeWind
This project was built almost entirely through AI-assisted development. Claude and Cursor were used as primary development partners, not just for autocomplete, but for architectural decisions, full feature implementations, database schema design, API layer scaffolding, and code review. Cowork handled file management, cross-referencing documentation, and multi-step workflow automation.
Architecture decisions, database schema design, all 27 tRPC routers, email templates, RLS policy review, CLAUDE.md conventions, and multi-step workflow automation across the monorepo
Real-time pair programming, inline edits, multi-file refactors, and rapid feature scaffolding, used for the majority of day-to-day implementation
Treating AI as a senior engineer: precise context windows, explicit constraints in CLAUDE.md/AGENTS.md, task-specific agents, and iterative verification loops