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Prompt SystemsApr 2026 · 4 min read
Prompt patterns that produce more consistent AI video results
Three practical prompt patterns for locking subject identity, simplifying motion, and keeping test batches comparable across revisions.
Stable prompts are modular prompts.
Consistency needs fewer variables per test.
Libraries of winning phrases compound over time.
Pattern 1: identity first
Open with the subject definition before describing environment or finish. This keeps the model anchored to who or what matters most before style choices enter the frame.
- Subject, environment, motion, camera, finish.
- Use one clear noun phrase to anchor the prompt.
- Repeat identity markers when consistency matters.
Pattern 2: one motion beat
Choose one motion intention per shot so the model does not try to satisfy multiple conflicting requests. Cleaner motion descriptions usually lead to cleaner outputs.
- Pick reveal, push, or orbit, not all three.
- Keep speed language soft and minimal.
- Move complexity to the edit, not the prompt.
Pattern 3: reusable test scaffold
Create a short scaffold prompt that stays fixed across a batch. Then change just one variable such as environment, offer angle, or mood. This turns creative testing into something measurable.
- Use the same camera grammar across the batch.
- Tag each prompt version with one hypothesis.
- Keep successful scaffolds in a living prompt library.
Keep exploring
Prompt patterns that produce more consistent AI video results
