Featured project
Glyph
AI adaptive learning that fits the learner and the subject.

Background
One-size-fits-all study tools don't adapt to the learner or the subject.
Concept
A learner enters a topic (or uploads a PDF), and Glyph generates a concept map, a curriculum, and an interactive learning "expedition" — cinema-style visual explainers, tutor annotations, and, for STEM topics, derivation walks, sandboxes, simulations, and challenge arenas. A domain classifier gates features so a narrative topic and a calculus topic each get the right components, and assessment adapts difficulty from learner profiles and weak-area detection.
Build story
A deep app — 30+ Supabase edge functions for AI generation, ElevenLabs text-to-speech, and PDF extraction. Teacher classrooms — join codes, assignments, differentiation, and performance analytics — sit alongside anonymous and authenticated student flows. Ben led agent-driven fixes that hardened the create-curriculum path end-to-end for both.
Outcomes
Live, with the full generate-learn-assess loop working for both anonymous and signed-in learners.
Tech / stack
- React/TS, Tailwind
- Supabase (30+ edge functions)
- Stripe
- ElevenLabs
Live
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