AI Video Prompting Guide: Write Prompts That Actually Work

What Makes an AI Video Prompt Good?

A good AI video prompt answers five questions in one ordered sentence block: what is the subject, what is it doing, how is it shot, where does it happen, and how should it look. Video models like Runway Gen-3, Luma Dream Machine, Kling, and Pika respond far better to structured, concrete language than to loose descriptions. A prompt like "a woman walking through rain-soaked Tokyo streets at night, handheld camera tracking from behind, neon reflections on wet asphalt, cinematic, shallow depth of field" will beat "cool video of a woman in Tokyo" almost every time.

The key difference from image prompting is motion. Every video prompt should contain at least one explicit motion instruction, whether for the subject ("she turns her head slowly") or the camera ("slow dolly-in"). If you leave motion undefined, the model chooses for you, and the result is usually subtle drift or morphing that reads as low quality.

The Five-Block Prompt Structure

Use this order every time. Consistency makes prompts editable: if a clip fails, you know which block to change.

1. Subject block: who or what, with one or two visual details. "A grey heron with folded wings standing in shallow water."
2. Action block: one clear movement, with speed or manner. "Unfolds wings slowly and takes off."
3. Camera block: shot type plus movement. "Low-angle shot tracking subject, camera tilts up as it flies."
4. Scene block: environment, time of day, weather. "Misty lake at dawn, fog hovering over water."
5. Style block: look and tone. "Shot on 35mm film, muted colors, soft natural light, cinematic."

Keep the full prompt under about 60 words for most models. Over-long prompts dilute attention, and models tend to drop details from the middle of long sentences. Put the most important element first, because most video models weight early words more heavily.

Camera Language That Actually Changes the Output

Video models are trained partly on footage that includes metadata and descriptions, so real cinematography vocabulary has measurable effects. Use these terms deliberately:

• Shot types: wide shot, medium shot, close-up, extreme close-up, over-the-shoulder, aerial, macro.
• Camera moves: dolly in, dolly out, pan left/right, tilt up/down, trucking, orbit (360-degree), crane, handheld, locked-off.
• Lens & focus: shallow depth of field, deep focus, telephoto compression, fisheye lens, rack focus foreground to background.
• Speed terms: slow motion, 120fps, time-lapse, hyperlapse.

One move per prompt is the rule. Combining "camera orbits while dollying in and tilting up" usually produces wobbly, indecisive motion. If you need a complex move, generate the clip with one clean move and plan a cut, not a compound camera instruction.

Model Differences: Same Prompt, Different Results

Models do not interpret prompts identically, and knowing the quirks saves hours of trial and error.

Practical takeaway: write a base prompt and keep a per-model variant file. When you switch tools, you usually only need to rewrite the camera and style blocks, not subject and action.

Image-to-Video vs Text-to-Video Prompting

Text-to-video gives the model full control; image-to-video gives you composition control and only asks the model for motion. Most pro workflows use image-to-video for anything that needs a specific look.

When prompting image-to-video, do not re-describe the image. The model can already see it. Instead, tell it only what must change: "woman turns to camera and smiles, hair moves in wind, camera pushes in slightly." Re-describing static elements often makes the model regenerate and distort them.

When prompting text-to-video, you carry all the descriptive weight, so the five blocks matter. Expect to iterate more: two to four generations per shot is normal even with a good prompt.

A Repeatable Prompting Workflow

Follow these steps to go from idea to usable clip without guessing:

1. Write the shot list first. Break your video into 3–8 second single-action shots. One clip = one action.
2. Draft each prompt in five-block order (subject, action, camera, scene, style), under 60 words.
3. Generate a test batch on low settings if available. Generate 2–3 variations per prompt.
4. Diagnose failures by block. Wrong subject? Fix block one. No motion or weird motion? Fix block two or three. Bad look? Fix block five. Change one block at a time.
5. Lock the style block. Once you have a working look, reuse the exact same style phrasing across every shot for visual consistency.
6. Save winning prompts to a library. Reusable prompt skeletons are your highest-value asset across projects.

Common Prompting Mistakes to Avoid

• Negative instructions. Most video models handle "no blur, no shake" poorly. Say what you want, not what you don't.
• Too many simultaneous actions. "She runs, jumps, and waves" produces mush. One action per clip.
• Abstract mood words as the whole prompt. "Ethereal, dreamy, emotional" does nothing without a concrete subject and motion attached.
• Ignoring length limits. Asking a 5-second model for a 20-second scene forces it to slow down or loop motion. Plan cuts.
• Copying image prompts verbatim. Image prompts optimize composition; video prompts must also specify time. Always add motion before reusing an image prompt.

Treat every prompt like a shot direction you'd give a camera operator. If a human DP couldn't shoot your sentence, the model probably can't either.

Example Prompts You Can Adapt

Nature documentary style: "A red fox pacing through deep snow, sniffing ground, locked-off low-angle camera, telephoto lens, shallow depth of field, golden hour light, snowy forest background, shot like a BBC nature documentary."

Product shot: "A matte black wristwatch rotating slowly on a reflective surface, macro lens, studio lighting, dark gradient background, camera orbits 90 degrees, high-end commercial style."

Narrative scene: "A man in a trench coat pauses at a crosswalk and looks up at the sky, medium shot, camera pushes in slowly, rain falling, city street at dusk, moody teal-orange color grade, cinematic."

Key Takeaways

Effective AI video prompting is structural, not magical: subject, action, camera, scene, style, in that order, under 60 words, with exactly one motion per clip. Learn real camera vocabulary because models understand it, adapt your style block per model instead of rewriting everything, and iterate one block at a time so failures tell you exactly what to fix. Build a prompt library as you go, and within a dozen generations you'll have reusable skeletons that make every future video faster and more predictable.