{
“title”: “3 Prompt Structures for Cinematic AI Video”,
“Text1”: “
TL;DR: A Reddit user shared three distinct prompt structures for Seedance 2.0 that cover keyframe interpolation, shot-by-shot scripting, and continuous action takes to generate cinematic video results.
I recently came across a fantastic set of examples from u/Accomplished-Tax1050, who has been experimenting with Seedance 2.0. While many people struggle to get consistent video output from AI, this contributor found a few specific formats that yield \”solid results\” for cinematic styles. I think these structures are incredibly useful regardless of which video generation tool you are using, as they demonstrate clear direction and temporal control.
Here are the three prompts the author shared, along with a breakdown of why they work.
1. The Keyframe Interpolator
This first example appears to be designed for an image-to-video workflow where the user provides start and end frames.
\”These are the opening and closing frames of a tavern martial arts fight scene. Based on these two scenes, please generate a smooth sequence of a woman in black fighting several assassins. Use storyboarding techniques and switch between different perspectives to give the entire footage a more rhythmic and cinematic feel.\”
Why it works:
This prompt succeeds because it defines the trajectory. By referencing provided images (\”opening and closing frames\”), the author gives the AI a definitive destination. The instruction to use \”storyboarding techniques\” and \”switch perspectives\” prevents the video from looking like a static, morphing image. It forces the model to hallucinate cuts and movement rather than just warping pixels.
2. The Screenplay Structure
This is the most robust example provided by the expert. It breaks the video down into precise time blocks.
Style: Hollywood Professional Racing Movie (Le Mans style), cinematic night, rain, high-stakes sport.
Duration: 15s.
\[00–05s\] Shot 1: The Veteran (Interior / Close-up)
Rain lashes the windshield of a high-tech race car on a track. The veteran driver (in helmet) looks over, calm and focused. Dashboard lights reflect on his visor.
Dialogue Cue: He gives a subtle nod and mouths, ‘Let’s go.’
\[05–10s\] Shot 2: The Challenger (Interior / Close-up)
Cut to the rival car next to him. The younger driver grips the wheel tightly, breathing heavily. Eyes wide with adrenaline.
Dialogue Cue: He whispers ‘Focus’ to himself.
\[10–15s\] Shot 3: The Green Light (Wide Action)
The starting lights turn green. Both cars accelerate in perfect sync on the wet asphalt. Water sprays into the camera lens. Motion blur stretches the stadium lights into long streaks of color.
Why it works:
Video models often struggle with coherence over long durations. The author solves this by acting as a director. Using timestamps (e.g., `[00–05s]`) creates strict boundaries for the AI, ensuring it knows exactly when to cut from the interior shot to the wide action shot. Specifying lighting details like \”dashboard lights reflect\” and \”motion blur\” adds realism to the render.
Variation to try:
Keep the timestamp structure but change the genre to a cooking show. Use `[00-05s]` for chopping ingredients (close-up), `[05-10s]` for the pan sizzle (macro), and `[10-15s]` for the plating (wide shot).
3. The Continuous Take
This final prompt focuses on camera movement and flow.
\”Cinematic action movie feel, continuous long take. A female warrior in a black high-tech tactical bodysuit stands in the center of an abandoned industrial factory. The camera follows her in a smooth tracking shot. She delivers a sharp roundhouse kick that sends a zombie flying, then transitions seamlessly into precise one-handed handgun fire, muzzle flash lighting the dark environment.\”
Why it works:
Terms like \”continuous long take\” and \”smooth tracking shot\” are critical here. They tell the AI to maintain temporal consistency without cutting. The prompt also links two distinct actions (a kick and a gunshot) with the phrase \”transitions seamlessly,\” which helps avoid the glitchy movement often seen when AI characters change activities.
🎬 Use Cases
- Pre-visualization: Filmmakers can use the screenplay structure to test lighting setups before shooting.
- Mood Boards: The keyframe prompt is excellent for connecting two pieces of concept art to see how they might relate in motion.
- Social Content: The 15-second duration in the racing prompt is perfectly optimized for short-form video platforms.
If you are testing out new video models, try adapting that timestamped format: it is a great way to force better composition!
Check out the full discussion on Reddit.
”
}
Sharing a few Seedance 2.0 prompt examples
by u/Accomplished-Tax1050 in PromptEngineering