PolymathOS
A learning platform that turns books and courses into a curriculum and plans every day of study.
- Context
- A personal learning platform. It turns books and courses into a curriculum of concepts and exercises, plans every day of study, tracks mastery and sends a daily push nudge. It runs as a web app you can install, and sign-in is invite-only.
- Role
- I designed and built it with AI coding agents across 69 commits from July to September 2026: 52 database models, 88 API routes, AI-generated lessons and exercises, and a curriculum of about 5,700 concepts across 28 subjects.
- Stack
- Next.js 16, React 19 and TypeScript; Prisma on PostgreSQL; Better Auth with Google sign-in; the Vercel AI SDK with Gemini, Anthropic, OpenAI and Groq; web-push and Vercel Cron.
- Visit
- polymath-os-rouge.vercel.app Sign-in is limited, so visitors see the landing page.
The hard problem
A study plan with no randomness in it
The scheduler has to fit every unstarted concept into the timeline the learner chose, split each day's slots by subject priority, fit reviews into every day, let a hyperfocus mode hand all the new-concept slots to one subject for a while, and never schedule a concept twice. I kept it deterministic, with no AI in the loop. The daily pace is the unstarted concepts over the timeline, with 15 per cent of days held back for review alone. Subjects get slots in proportion to their weight and the leftovers go round-robin from the heaviest down. Plans are built thirty days at a time with a position marker per subject, every concept already planned is excluded, and each day is written as an upsert on schedule and date, so the whole thing can safely run again. Reviews are never stored: they are worked out live from each concept's mastery, which sets an interval from one day to thirty, and ranked by an urgency score built from mastery, time overdue and error rate.