Private Repository
Lingua
Trip-focused Spanish learning across web, mobile, API, audio, and shared contracts.
Turborepo
Next.js
Expo
NestJS
Clerk
Prisma
Project Overview
Lingua is a Spanish-learning app designed around a real trip outcome rather than generic daily practice. Users track destination, departure date, current level, weekly progress, and competency gaps.
The repository sets up a web-first alpha with shared contracts, mock and Prisma-backed API paths, mobile read parity, and provider boundaries for LLM and audio features.
The product architecture supports gradual hardening: start with typed mocks, preserve the same contracts for production persistence, and keep AI/audio providers swappable.
Built Around
Trip countdown and level targets mapped to concrete travel situations.
Shared contracts across Next.js web, Expo mobile, and NestJS API layers.
LLM and audio provider boundaries so coaching and speech work can evolve independently.
PostHog and Sentry hooks planned into the product baseline.
Product Capabilities
Trip-Ready Learning
Lessons tied to travel scenarios and competency gaps.
- - Destination and departure timeline
- - Level progression tracking
- - Scenario-based missions
- - Competency coverage by topic
Web and Mobile Parity
Shared product contracts reduce drift across clients.
- - Next.js App Router web flows
- - Expo SDK 52 mobile baseline
- - Typed API contracts
- - Mobile read parity scaffolding
Provider Boundaries
AI and audio can be changed without rewriting core UX.
- - LLM abstraction
- - Audio provider abstraction
- - Mock and production data paths
- - Smoke test scaffolding
Technical Architecture
Monorepo Foundation
- - Turborepo with pnpm
- - Next.js 15 App Router
- - Expo SDK 52
- - Shared TypeScript contracts
Services and Data
- - NestJS REST API
- - Clerk authentication
- - PostgreSQL with Prisma
- - PostHog and Sentry integration points
Project Signals
Web
Primary Alpha
End-to-end flow
Mobile
Read Parity
Expo baseline
Typed
Contracts
Shared across apps
Private
Repository
Product in progress
Interested in Learning More?
This private project reflects hands-on product, engineering, and AI workflow development across the full stack.