| I've been playing chess for a few years with my ELO stuck around 1600 on Lichess. I wanted an app that combined puzzle training, interactive lessons, game analysis, and AI coaching in one place. But all the apps I used over the years either felt overwhelming, had UX that wasn't up to my expectations for a modern app or were lacking some fundamental features that I really wanted. So, I built LearnChess.ai. The technical angle I'm most excited about: it's built local-first using LiveStore (event-sourced, SQLite on-device), which means zero loading delays for user data and full offline support. Sync to the cloud happens in the background for cross-device usage. The stack is TanStack Start (web), Expo (mobile), and it runs entirely on Cloudflare. Features in the current beta: - Puzzle trainer with community submissions - Guided lessons for openings and endgames - Game import and analysis from Lichess & Chess.com - Opening explorer based on your own game history - Stockfish running on a dedicated Hetzner server (faster than in-browser WASM) - AI coaching integrated directly in the analysis board - Coordinate training, beginner track, leaderboards, ... Available on web, iOS (TestFlight), and Android (nearly ready). Would love your feedback — both on the product and the architecture choices! |
As a someone who recently built a chess app with Stockfish (WASM with a fallback to the server, see my profile if interested), just be aware that if your application becomes even moderately successful, a couple dozen users hitting your Stockfish server concurrently is very likely to be slower than running individual Stockfish WASM on the client side unless you significantly beef up your backend.