by adudley1978 | 2025-06-24 12:24:25+00:00
Hey HN,

We're excited to "Show HN" Mosava, an app to help you feel better at your desk, 45 seconds at a time. Think Duolingo for physical comfort and mental sharpness via quick, personalized movement breaks right from your browser. No gym, no gear, no sweat.

Our friendly mountain goat guide, Mo , is the personality behind the app's coaching, bringing warmth and motivation. Mo and I are excited to have built this.

This project, my final for Brainstation's AI certificate, stemmed from my own struggle as a former fitness pro turned desk jockey whose printed movement lists kept vanishing. Mo and I built this solution.

What's really exciting is how it was built: I developed Mosava with Cursor and Claude in ~20 days, generating 46,721 lines of code without writing a single line myself! This AI partnership transformed my communication skills into a superpower for building complex software.

Mosava's core is an ML system that learns your unique patterns to personalize exercises and optimize notification timing, reducing decision fatigue. Our ML for notification engagement uses LightGBM, adapting to your daily/weekly cycles, recent app usage, and avoiding fatigue. For movement recommendations, Implicit models are trained offline, but our real-time system uses high-performance heuristics for sub-100ms responses, guaranteeing snappy UX even in alpha. User feedback continuously refines these models.

Mo's personality and coaching come from Anthropic Claude API's claude-3-5-haiku, used for both real-time dynamic interactions (tips, reasoning) and offline content enrichment (initial library of behavioral cues). Our prompt engineering defines Mo as supportive and research-grounded (Tiny Habits, Atomic Habits, Hooked Model principles), adapting dynamically to your context. Clever fallbacks and caching ensure reliable, fast responses.

Why 45 seconds? Sitting 8+ hours increases health risks. Short "vigorous spurts" improve heart health and sharpen focus. Studies show short stretches offer significant flexibility gains, and tiny actions with instant celebration build habits faster.

Our tech stack is modern and lean:

Frontend: React 19, Next.js 15, TypeScript, Tailwind CSS. Recharts, react-confetti.

Backend: Next.js API Routes (Node.js/TypeScript) on Vercel (serverless, auto-scaling).

Database: Google Cloud Firestore (primary), in-memory cache.

Services: Firebase Auth, Stripe, Resend, Mixpanel, Web Push.

Testing: Jest, React Testing Library, Firebase Emulators.

AI-assisted development challenges: Claude initially "mocked up data" due to inaccessible environment variables. We solved this with custom user rules in Cursor (e.g., "Environment Variables Rule," "Confidence Check") as critical guardrails. Vexing UI bugs were resolved using a ChatGPT → technical description → Cursor workflow to translate visual problems. Human review, automated testing, and manual verification rigorously ensured quality.

For now, it's best experienced on desktop for push notifications. A dedicated mobile app is on our roadmap!

Mo and I are in alpha. You can "Try It Now" on the homepage for a quick demo, no signup required! For full personalized ML and progress tracking, signup is needed (ML requires a profile). Mo and I encourage a throwaway email if preferred; we're focused on feedback, not marketing.

Mo and I would love your thoughts, especially on:

Personalization effectiveness (ML/heuristics blend)?

Micro-movements: easy to follow/integrate?

Suggestions for exercises, timings, features?

UI/UX, considering AI-assisted dev origins?

Future features that would delight you?

Thanks for checking it out! Mo and I will be here in the comments.