The era of spending weeks on a video shoot is over. With modern AI text-to-video generators, a well-crafted prompt is all you need to produce cinema-worthy footage. But there is an art to writing prompts that consistently produce breathtaking results. In this guide, we break down the exact framework used by Nano Banana's top creators.

Why Prompt Engineering Matters for AI Video

Unlike image generation, video AI must maintain temporal consistency, every frame must flow naturally into the next. This means your prompt needs to communicate not just what the scene looks like, but how it moves, where the camera is, and the overall mood.

A weak prompt like "a woman walking in a city" gives the AI almost no direction. A strong prompt like "Cinematic slow-motion tracking shot of a woman in a red dress walking through a neon-lit Tokyo street at night, shallow depth of field, rain-slicked pavement reflections, 24fps film grain" unlocks the full potential of the model.

The 5-Part Prompt Framework

Every high-converting prompt on Nano Banana Video uses some combination of these five components:

1. Shot Type & Camera Movement

Start your prompt by defining the camera perspective. The AI uses this as the foundational constraint for the entire generation.

  • Static shots: "Close-up portrait shot", "Wide establishing shot"
  • Moving shots: "Slow tracking shot", "Cinematic dolly push-in", "Aerial drone flyover"
  • Dynamic: "Handheld follow cam", "360-degree orbit around subject"

2. Subject & Action

Describe your subject with precision. Include physical details, clothing, and the specific action they are performing.

Weak: "a chef cooking"

Strong: "A professional chef in a white uniform, mid-30s, passionately tossing a flaming wok in a commercial kitchen"

3. Environment & Lighting

Lighting is the single biggest factor in cinematic quality. Always specify your light source and time of day.

  • "Golden hour sunlight through glass windows"
  • "Dramatic high-contrast studio lighting, deep shadows"
  • "Overcast natural light, soft diffusion"
  • "Neon city lights reflecting off wet surfaces at night"

4. Style & Mood

Reference a visual language the AI understands. Film references, photographic styles, or genre cues all work.

Examples: "Shot on 35mm film, slight grain", "Hyperrealistic commercial aesthetic", "Dark moody cinematic like a Christopher Nolan film", "Bright airy editorial style"

5. Technical Parameters

Finish with technical specs that refine the output quality. In Nano Banana, you can specify these directly in the API or dashboard: resolution (1080p / 4K), motion intensity (subtle / medium / high), clip duration (2s – 10s), and aspect ratio (16:9, 9:16, 1:1).

Real-World Example Walkthrough

Let's build a prompt together from scratch for a luxury car commercial scene.

Step 1, Shot type: "Cinematic low-angle tracking shot"

Step 2, Subject: "of a matte black sports car accelerating on a wet mountain road"

Step 3, Environment: "at dawn, misty atmosphere, pine trees on both sides, golden light breaking through the fog"

Step 4, Style: "ultra-realistic, shot on ARRI Alexa, shallow depth of field, bokeh headlights"

Step 5, Technical: Set to 1080p, medium-high motion, 5 second clip, 16:9.

Final prompt: "Cinematic low-angle tracking shot of a matte black sports car accelerating on a wet mountain road at dawn, misty atmosphere, pine trees on both sides, golden light breaking through the fog, ultra-realistic, shot on ARRI Alexa, shallow depth of field, bokeh headlights"

Pro Tips from the Nano Banana Community

  • Use negative prompts wisely: Adding terms like "no blur", "no distortion", "no artifacts" helps the model avoid common failure modes.
  • Iterate fast: Generate 3–4 variations of your prompt, then pick the best seed and refine. Each generation only takes ~2 seconds.
  • Chain with Multi-Scene API: Use Nano Banana's multi-scene sequencing feature to maintain consistent character appearance and color grading across multiple clips.
  • Reference real cinematographers: Prompts like "shot by Roger Deakins" or "in the style of Emmanuel Lubezki" reliably produce gorgeous cinematic framing.

Common Mistakes to Avoid

Even experienced creators fall into these traps:

  1. Over-complicating a single prompt, If you want 3 different scenes, use 3 prompts and chain them. Don't try to describe everything in one generation.
  2. Ignoring motion descriptors, Words like "static", "slow", "fast", "panning" are critical for temporal consistency.
  3. Being too abstract, "Feelings of longing" won't generate well. Translate emotion into visual cues: "character stares out a rain-streaked window, tight close-up on their eyes".

Conclusion

Mastering AI video prompts is a superpower for any modern creator. With the Nano Banana Video platform, you have access to one of the fastest and most capable text-to-video pipelines available. Apply the 5-part framework, iterate quickly, and you will be producing studio-quality content that takes traditional production teams days to achieve.

Ready to try it? Start generating for free with 25 credits, no credit card required.