More Consistent AI Video Characters, From Prompt to Shot List

Reduce character drift with identity anchors, change budgets, shot decomposition, and reference-asset management.

Key takeawayConsistency comes from limiting simultaneous changes and reusing structured identity information, not from endlessly longer prompts.

Create an identity anchor

Write a character card containing only stable traits: age range, face shape, hair, clothing silhouette, primary colors, and immutable marks. Do not mix emotion, action, camera, or environment into the identity layer. Keep an approved set of reference images and note the angles each image supports.

Give every shot a change budget

Changing clothing, lighting, age, hair, action, and setting in one shot greatly increases drift. Hold identity and clothing stable while changing only a few variables such as action, expression, and camera. For a costume or time shift, create a transition shot or a new reference asset.

Turn long narratives into a shot list

Each shot has four blocks: subject anchor, action, environment, and camera. Give the action a clear start and end, specify one primary camera move, and describe only environmental details that affect the subject. Reuse the same character card between shots instead of freely rewriting it.

Record failures and improve the template

Classify failures into identity, clothing, proportion, motion, camera, and background. A ModelRush workflow saves effective structures as reproducible templates while treating model settings and reference assets as explicit versions.

Evaluate consistency across the sequence instead of selecting one frame. A useful final metric is the percentage of shots that enter editing without rebuilding the character identity.