Neon route
BenChanViolin Library is the proof surface: a Next.js site backed by Neon Postgres where decades of YouTube teaching can be organized into reviewed clips, canonical technique tags, learner phrases, transcript clues, and timestamped practice entry points.
The database is not just storage for videos. It is the layer that lets human review, musical taxonomy, transcript language, and future YY Method practice threads meet without turning the archive into a black-box chatbot.
The sibling BenChanViolin app already models videos, segments, tag groups, tags, aliases, and segment-tag relationships in Postgres. Public pages search reviewed technique clips by validated concepts and the words a player would actually type.
Queries combine exact labels, slugs, learner aliases, trigram fuzzy matches, full-text search, and contextual transcript clues. A search for bow bounce or tense bow hand can land on a tag, a reviewed segment, or the original YouTube timestamp.
Segments carry titles, summaries, use-when guidance, suggested experiments, reflection prompts, review status, source files, and quality scores. AI can propose candidates, but public retrieval is separated from review and publication.
The same structure can feed Capture, Why, Why-Not, Commit, and Timestamp. A musician arrives with an observation; the system retrieves relevant human teaching, keeps competing explanations alive, and returns a bounded next experiment.
Postgres fits the work because the product needs relational truth and retrieval flexibility at the same time: durable source records, public/private flags, review workflows, searchable text, aliases, timestamps, and future event history.
Many serious musicians have large libraries: lessons, masterclasses, rehearsals, essays, streams, and annotations. The reusable offer is a branded expert-learning layer that turns each library into searchable practice guidance without erasing the artist's voice.
The schema can generalize from violin to other instruments by swapping taxonomy, source collections, reviewed segments, learner phrases, and practice prompts while preserving the same review, retrieval, and method loop.
The system should not claim authority because text was retrieved. It should show the source, explain the match, preserve uncertainty, and make it easy for the musician or teacher to correct what does not fit.
The funding wedge is practical: use Neon to make Ben's existing teaching archive genuinely useful first, then package the pattern for other musicians whose knowledge is already public or recorded but not yet queryable, teachable, or method-aware.
