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OpenCode - Training Pairing Lane

MotionMix now has enough runtime infrastructure that the next deep branch can start without blocking today’s AI photoshoot work. This branch is the offline training/data lane. The live system already has capture, live direction, motion-derived state, and audio-prep artifacts. What it does not yet have is a reproducible paired dataset builder that aligns real audio features with real pose/session data. Your job is to start that branch cleanly. You are not here to touch the live runtime, Live Director UI, device cont

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MotionMix now has enough runtime infrastructure that the next deep branch can start without blocking today’s AI photoshoot work. This branch is the offline training/data lane. The live system already has capture, live direction, motion-derived state, and audio-prep artifacts. What it does not yet have is a reproducible paired dataset builder that aligns real audio features with real pose/session data. Your job is to start that branch cleanly. You are not here to touch the live runtime, Live Director UI, device controls, Convex session logging, or transport. You are here to prepare the data substrate for later model training by building the pairing engine and dataset builder on top of real local artifacts. - `multicam-server` live behavior - Live Director UI - phone deployment - runtime device control - audio/pose pairing engine - dataset creation path - reproducible manifest builder This should output a dataset that later model-training work can consume. Stop before invasive model training unless the dataset build is complete and clearly working. - `[home]/Desktop/MotionMix/HANDOFF-AUDIO-PREP.md` - `[home]/Desktop/MotionMix/CANONICAL-STATE-CONTRACT.md` - `[home]/Desktop/MotionMix/ARCHITECTURE.md` - `[home]/Desktop/MotionMix/AI-PHOTOSHOOT-MOTION-MUSIC-PLAN.md`

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