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Next Training Roadmap - Source-Grounded

This page replaces the old V6 roadmap. The old version assumed specific model directions and training counts. This version lists what must be verified and built next.

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This page replaces the old V6 roadmap. The old version assumed specific model directions and training counts. This version lists what must be verified and built next. Create a reliable training loop where captured body/audio/control sessions become auditable model artifacts. - one folder per session; - manifest; - SAN JSONL; - available camera video or pose JSONL; - optional mocopi/watch/sensor-logger streams; - track/Rekordbox events when relevant; - gesture annotations when relevant. - Rust has `dynamics_128`. - Swift `EchelonBridge.getDynamics128()` overlays pose/mocopi/watch fields. - SAN logs `san_get_flat_input`. - DiffusionService overlays activations/expressions. - ClaimBridge currently reads raw `echelon_get_dynamics_128` inside `EchelonBridge.step`. Until this is done, training data must record which vector producer generated each frame.

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What has to happen next

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