Goal
Design and build the technical foundation for a lightweight pet-management MVP, centered around document uploads, a public emergency profile, and simple sharing flows.
The focus was on fast iteration and keeping the architecture flexible while the product direction evolved.
Stack
The MVP was built using Next.js with TypeScript on the frontend, backed by Firebase services including Authentication, Firestore, Storage, and Cloud Functions. Design iterations were done in Figma.
Firebase was chosen to minimize backend overhead and enable rapid prototyping of auth, storage, and sharing flows.
Key Decisions
The initial architecture was intentionally simple: one user, one pet, basic metadata, and document uploads stored in Firebase Storage. I implemented a public emergency profile accessible via link, enforced through Firestore rules and a small set of Cloud Functions.
As the concept evolved, I added task handling, ICS export, and a minimal family-sharing mechanism based on invite links. After reviewing comparable products, we deliberately narrowed the scope toward a lean, owner-centric tool, which led to a simplified data model and removal of several early features.
Throughout the process, I designed both backend and frontend foundations in parallel, keeping the system adaptable while iterating closely on UX changes.
Outcome
The result was a clearly scoped MVP architecture with working core flows and a revised technical plan ready for implementation. The project was discontinued before full build-out as the product direction shifted, but it produced a clean Firebase-backed structure and clarified requirements for the next iteration.
Further Details
Over several weeks, I worked across authentication, data modeling, document handling, and frontend structure while refining the product alongside multiple design rounds. The project emphasized fast feedback cycles, pragmatic architecture choices, and maintaining technical clarity despite shifting requirements.
Although the MVP was ultimately paused, it served as a practical exercise in building adaptable systems under evolving constraints.
