I’m a cloud engineer. I’d never shipped a mobile app, never written React Native, never used Astro, never used Remotion. Two months later, I have all of those running in production for a privacy-first period tracker called Veil - a privacy-first period & cycle tracker where your health data stays on your device (no accounts, no cloud). I built it because too many people hand their most intimate health log to apps and companies by default - when today’s phones can process that data locally, privately, on the device. iOS is live; Android is in progress. Nine languages.
The leverage came from how I used Claude Code, not just from prompting. Worth sharing because most “I built X with AI” posts skip the workflow.
What I actually did
BMAD method for planning
Breakthrough Method of Agile AI-Driven Development. Structured workflow for proper PRDs, sprint planning, story creation, and retrospectives. Way less “please generate an app” and way more “let’s actually think about what we’re building.” Also, a game-changer for avoiding spaghetti code.
Outputs in _bmad-output/: product brief, PRD, architecture doc, epics, story files. Each new session starts from those.
CLAUDE.md + repo docs as durable memory
CLAUDE.md is the always-on layer. Single file in the repo root; every new session loads it. Mine is ~1500 lines and grew organically - each section started as something I had to re-explain twice.
How it’s structured (not a dump of the codebase - a contract for future sessions):
- Project overview + stack so cold starts don’t hallucinate Expo/RN versions
- Architecture (data flow, stores, prediction pipeline) with “import from here, never duplicate” rules
- Conventions that bite if ignored: Zustand selectors,
useTheme()colors, 9-locale i18n, ISO dates + DST-safeaddDays - Push back when the user is wrong - explicit instruction to argue once before implementing a bad idea, then do what I pick
- Medical correctness: research before coding - full workflow: primary sources first (ACOG/FIGO/WHO/DSM-5-TR), cite in code docblocks, log in
HEALTH_FEATURES_PLAN.md, flag disagreements before picking a threshold, never invent plausible numbers - Pointers to deeper docs so Claude reads the right file before touching load-bearing code
- Checklists wired into “Adding a New Feature” (export, restore, PDF, gating doc, website)
CLAUDE.mdis the index. Threedocs/files hold the detail that would bloat it or go stale if duplicated: docs/algorithm-decisions.md- Why prediction/destructive logic works the way it does: surfaces affected, rejected alternatives, “don’t break this if you…” Not a changelog. Example entry: buffered prediction window edge vs true predicted period start (easy to “fix” back into a user-visible bug).docs/feature-gating.md- Living Free vs Plus matrix across every screen. Update on every ship so specs and<PlusGate>stay aligned.docs/feature-shipping-checklist.md- Blast-radius playbook (~70 touch points per feature): design-phase medical research, schema migrations, every UX surface, backup/CSV, i18n, marketing, store assets. The checklist learns - when something bites us, we add a lesson so the next feature doesn’t repeat it. Workflow for a new feature: read the shipping checklist -> design doc indocs/superpowers/specs/-> implement -> update gating doc + algorithm log if applicable. Clinical thresholds get inline citations insrc/utils/and an algorithm-decisions entry when the choice is non-obvious. Repo docs = git-tracked truth. Good for “what did we decide and why.” Bad for “what did we try in Tuesday’s session.” claude-mem plugin for cross-session memory On top of the repo docs I run the claude-mem plugin (session memory - compresses observations from reads/edits/bash, injects relevant past context on later sessions). Local SQLite under~/.claude-mem; not a substitute forCLAUDE.md. How I use it vs the files above:- claude-mem - “last week we tried X for the cycle ring and rolled it back,” “jetsam on 6 GB devices needed Y load opts,” session-specific debugging threads. Fuzzy recall across tens of sessions. Skills + sub-agents for specialized tasks Skills library: bmad, mobile-ios-design, react-native-architecture, react-native-best-practices, react-native-design, remotion, social-content, marketing-ideas, marketing-psychology, desloppify, superpowers, etc. Sub-agents dispatched in parallel for independent tasks. What I shipped
- React Native + Expo iOS app, 9 languages, on-device Gemma 3/4 1B/2B/4B LLM via llama.rn, full Health Report PDF generator, app lock with biometric/PIN, encrypted backups and more
- Astro 5 + Tailwind 4 marketing site at https://veiltrack.app/
- Remotion compositions for App Store Screenshots, Promo Videos and App Preview clips
- ElevenLabs voiceover for the videos submitted by /u/altinukshini
Originally posted by u/altinukshini on r/ClaudeCode