Text-to-video works best when a prompt reads like a compact shot brief, not an essay. “Wan 3” has not been officially announced as a model name, so these instructions are deliberately workflow-focused and applicable to the currently selected Wan-family option in Wan 3 AI.
Use a six-part prompt
Write: subject + action + environment + camera + light/style + ending. For example: “A yellow commuter bicycle passes through a rainy neon street, wheels throwing small reflections; low tracking shot; blue-hour light; it exits frame right.” Put the most important visual constraint first and avoid asking for multiple unrelated scenes.
Make the first render diagnostic
Choose one aspect ratio for the destination, one clear action, and a short duration. Review whether the subject stays recognizable, the action finishes, and the camera does what the prompt says. If motion distorts, reduce movement before adding more descriptive words. If composition misses, create or upload a reference image instead.
The practical improvement
Pain point: generic prompt lists imply that more adjectives equal more control. Our added value: every word must have a job. Label the failure—subject, motion, camera, light, or ending—then edit only that part. Generate a first Wan video draft, and keep successful prompts in a shared library.
Sources
- Wan-AI GitHub — official model-family resources.
- Wan paper — technical background.
- Wan-AI Hugging Face — official model collection.
- C2PA specification — synthetic-media provenance.
