AI build guide
Build a fitness tracker with AI and privacy by design
Health-adjacent data deserves careful boundaries. Collect only what the feature needs, explain its purpose, and avoid unsupported medical conclusions.
01
Choose the useful signal
Define the behaviour, unit, cadence, and goal the product helps a user understand.
02
Design consent and control
Make collection, export, correction, and deletion understandable and enforce access beyond the interface.
03
Test imperfect input
Handle missing days, duplicate imports, unit changes, time zones, and device sync failures.
04
A public Xroga example
Athlyra in the Xroga Showcase is an Android-first Expo and React Native product concept with readiness, hydration, workout, progress, and goal interactions. Demo activity persists in the browser; no APK, medical result, or store release is claimed.
05
A production-shaped prompt
Build a consent-aware fitness tracker with goals, workout logging, unit and time-zone handling, export and deletion controls, accessible progress views, and explicit non-medical language. Test duplicate imports and offline recovery.
06
Before calling it production-ready
Review permissions, data handling, error states, accessibility, mobile behaviour, tests, environment configuration, observability, and rollback. The exact checklist must follow the project rather than a fixed framework template.