01
Release Prep data cleanup
Organize final metadata, credits, writer shares, and curation notes before a song moves toward release.
Product updates
What recent bigcut updates make possible.
These updates show how bigcut connects practical music work: clean release data, deliberate song selection, privacy-preserving proof, and AI-agent-ready recommendation context.
02
Selection proof
Keep a record that a song was deliberately selected at a specific time, without publishing raw user IDs, song IDs, audio, notes, or embeddings on-chain.
03
AI-agent recommendation context
Use only explicitly submitted Release Prep data to create safer recommendation context that AI agents can understand.
04
File-native collaboration
Keep metadata edits and comments attached to the audio file so handoff does not depend on a separate project portal.