AI Video Prompts: Shot Descriptions That Actually Work
A strong AI video prompt has four components: subject with specific detail, action and motion, camera type and movement, and style anchor. Vague prompts produce generic output; cinematic vocabulary produces cinematic results.
AI video prompting is closer to directing than writing. The mental model that works is: imagine you are briefing a cinematographer. You would not say "make it look good." You would say "wide angle, low camera, slow push-in from behind, golden hour backlight, slight lens flare." That level of specificity translates directly into better AI output.
The common failure mode is confusing creative intent with technical description. "A sad woman in a city" is an intent. "Medium close-up, a woman's face in a rain-blurred window, warm interior light behind her, city lights defocused in background, static camera, 35mm" is a technical description. The first leaves everything to the model; the second directs it.
Different platforms respond to slightly different vocabularies. Runway Gen-4 understands DoP-level camera language. Kling responds well to motion description and character action. Pika is effective with style adjectives and mood. The templates below are tuned to work across all major platforms.
The four-element prompt structure
Build every video prompt in this order:
- Subject — who or what, with specific visual details: "a young woman in a red silk dress," not "a woman."
- Action — what they do, how they move: "walks slowly into the crowd, glancing back over her shoulder."
- Camera — shot type, angle, movement: "tracking shot, low angle, slow push-in, handheld, slight shake."
- Style — era, format, grade, lighting: "35mm film grain, teal shadows, warm highlights, overcast diffused light."
Camera language that models understand
These camera direction terms consistently produce the named movement:
- Push-in / dolly-in — camera moves toward the subject.
- Pull-back / dolly-out — camera retreats from the subject.
- Pan left / pan right — camera rotates horizontally on a fixed axis.
- Tilt up / tilt down — camera rotates vertically.
- Orbit / arc shot — camera circles the subject.
- Crane up / crane down — camera rises or descends vertically while moving.
- Handheld / Steadicam — handheld adds organic shake; Steadicam implies smooth but mobile.
- Static / locked-off — no camera movement; subject moves through the frame.
Genre-specific prompt templates
These templates are ready to adapt — replace bracketed sections with your specifics:
- Cinematic drama — "Medium close-up, [subject], [action], slow push-in, anamorphic 2.39:1, shallow DOF, warm backlight, film grain, cinematic."
- Music video (urban) — "Low angle, [subject] in [urban setting], confident walk toward camera, neon reflections on wet pavement, handheld, blue-orange grade, night."
- Lo-fi / nostalgic — "Wide shot, [subject in quiet environment], static camera, Super-8 film, light leak left edge, golden hour, soft grain."
- Anime / stylized — "Anime cel-shaded, [subject] performing [action], dynamic angle, Studio Ghibli color palette, 2D hand-drawn look, expressive motion."
- Nature / atmospheric — "Aerial establishing shot, [landscape], slow drift forward, golden hour side light, cinematic color grade, mist."
- Abstract / experimental — "Abstract macro, [texture or element], slow rotation, extreme close-up, [color palette], smooth, dreamlike, no fixed subject."
Negative prompting and quality boosters
Many platforms support negative prompts (things to exclude). Common useful negatives: "no text overlay, no watermark, no fast cuts, no distortion, no motion blur artifacts."
Quality booster terms that generally improve output: "4K, high detail, photorealistic, professional lighting, sharp focus, clean motion." Add these to the end of any prompt — they act as a general quality signal without overriding your specific direction.
Free PDF — the prompt recipes our desk actually uses. One email a week.
Frequently asked
How long should an AI video prompt be?
40-100 words is the effective range. Too short loses specificity; too long can cause the model to deprioritize important elements. Cover subject, motion, camera, and style in that order.
Does the same prompt work on Runway and Kling?
Mostly, but expect different output. Runway responds better to precise camera language; Kling handles character motion and longer clips better. Test the same prompt on both if quality matters.
Can I reuse successful prompts as templates?
Yes — save your best-performing prompts and create style templates you paste at the end of each new prompt. This keeps visual consistency across clips for a multi-shot project.
What is negative prompting in AI video?
A negative prompt tells the model what to exclude — distortion, motion blur, text, watermarks, fast cuts. Not all platforms support explicit negative prompts, but many accept them in a "negative" field or as "no [element]" language in the main prompt.
Why does my AI video look generic even with a long prompt?
Generic output usually means vague style descriptors. Replace "cinematic" with specific lens language; replace "dramatic" with a specific lighting setup. The more concrete the visual instruction, the less the model falls back on its average training output.