Protect identity before motion expands.
Define face, hair, wardrobe, silhouette and the state that must survive.
A practical control system for keeping characters, products, references, camera motion and multi-shot sequences coherent — without rebuilding your process for every clip.
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Move from improvised generations to explicit locks, planned motion, QA and approved-state handoffs.
Define face, hair, wardrobe, silhouette and the state that must survive.
Select → Compare → Lock Choose complementary references without introducing contradictions.
State → Motion → Endpoint Separate subject action, camera motion and environment motion.
Shape → Packaging → QA Track silhouette, proportion, material, logo and critical label details.
Classify → Isolate → Retest Route drift, cuts, product mutation and ignored references to targeted fixes.
These are working structures, not a bulk prompt dump.
Define what must not drift before a new camera angle or subject action is introduced.
Identity anchors · allowed change · reference quality · shot risk
Carry approved state from one clip to the next instead of reinterpreting the sequence each time.
Shot purpose · inherited state · allowed change · approved frame
Route identity drift, product mutation, background drift and unwanted cuts to the smallest useful intervention.
Failure class · likely cause · targeted intervention · QA gate
The 34-page editorial playbook explains the control logic behind character consistency, references, shot planning, product fidelity, diagnosis and production handoffs.
Editable sheets for character locks, continuity, products, references, camera motion and handoffs.
Character turns, multi-shot sequences, product ads, packaging text and camera-orbit failures.
A diagnosis tree for isolating the variable that actually broke.
A consistent pass / revise / reject check before the next shot begins.
This is an independent Brightory production resource for AI video workflows. It is designed to reduce avoidable drift and make multi-shot work easier to control; it does not promise deterministic generations, perfect character consistency or exact model behavior across every platform.
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