Deterministic health state comes first
Targets, logs and plan state remain ordinary application rules; AI assists planning and explanation without becoming the record of truth.
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Product and backend / 2026
Nutriflux
A nutrition companion must remain useful through connectivity and provider failure, support local food context, and use generative assistance without allowing a model to become the authority over targets, logs or sensitive guidance.
Implemented the React Native/Expo mobile application, Express API and shared schemas from supplied designs. Deterministic calorie and macro targets remain separate from structured, budgeted AI planning; selected mutations use optimistic updates and an offline outbox, while sensitive content remains behind review and release gates.
- Role
- Application engineer / Product design supplied by another team
- For
- DZND LTD
- Stage
- Pre-launch
My part
What I built
- Implemented authentication, onboarding, targets, meal planning, tracking, cookbook, recovery, social, challenge, notification and settings journeys from supplied designs.
- Built API services and shared validation contracts used by mobile and backend workspaces.
- Implemented structured AI outputs, provider timeouts, feature flags, cost budgets, fallbacks and safety release gates.
- Added offline outboxes, optimistic state, rate limits, observability and PII-redacted logging.
Decisions
The choices that shaped it
Offline writes are product state
Supported actions return a visible offline state and remain queued for later processing rather than pretending the request failed permanently.
Safety uses release gates
Sensitive content is not assumed approved because a model produced valid JSON; review and feature state control exposure.
What has been shown to work
- The main journeys are covered by automated tests across the mobile app, the API and the contracts they share.
- Sign-in is rate limited and locks out after repeated failures.
- Calorie and macro targets are calculated on the server and stay correct when the AI provider is unavailable.
Current stage and limits
- Nutriflux is built but not launched. Store release is waiting on Apple developer account approval.
- The screens shown are the ones already public on nutriflux.org. No usage or adoption figures are claimed.
- Clinical review of sensitive guidance has to be completed before that content is switched on.
Screens
From the product
Phone screens
At phone size
Technical detailOpen the system view
SYSTEM ARCHITECTURE
Deterministic health state with bounded AI assistance
The mobile client and API share validated nutrition contracts; deterministic targets and tracking remain authoritative while structured AI planning, offline outboxes and review gates operate as bounded enhancements.Onboarding, meals, water, progress and recovery
Optimistic state and offline outbox
Zod schemas, types and nutrition calculations
Auth, plan, social, reminders and rate limits
Timeouts, budgets, cache and fallbacks
Postgres, RLS and durable records
Clinical review, feature flags and observability
- 01Userdaily actionExpo mobile
- 02Expo mobilevalidated mutationShared contracts
- 03Shared contractstyped contractExpress API
- 04Express APIbounded planning requestStructured AI
- 05Express APIdeterministic recordSupabase state
- 06Structured AIvalidated structured outputSupabase state
- 07Supabase statecontent / telemetryRelease gates
Security and privacy
- This public case study excludes private routes, schemas, credentials, prompts, customer records, provider configuration and operating runbooks.
- System scope and validation are described without implying unverified users, revenue, conversion, uptime, latency or commercial outcomes.
Built with
Links
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