How to Turn Any Video Into an AI Prompt

Have you ever seen a video and thought:

"I want to recreate something like this with AI — but I have no idea what prompt to write."

This is becoming a common problem as AI image and video generation tools get better.

A reference video may contain dozens of useful visual details:

• subjects and objects
• composition
• camera angles
• camera movement
• lighting
• colors
• environment
• actions
• visual style
• transitions between scenes

Turning all of that into a useful AI prompt manually can take a surprising amount of time.

A simpler approach is to use a video-to-prompt workflow.

What Is Video to Prompt?

Video to prompt is the process of analyzing an existing video and converting its visual information into a structured text description that can be used with AI generation models.

Instead of writing something generic like:

A cinematic video of a woman walking through a city.

A detailed video prompt might describe:

A woman walking through a neon-lit city street at night, medium tracking shot, shallow depth of field, wet pavement reflecting blue and magenta lights, slow forward camera movement, cinematic lighting, realistic photography, atmospheric urban environment.

The second prompt gives an AI model much more information about what the original video actually looks like.

What Should a Good Video Prompt Capture?

When reverse-engineering a video into a prompt, I usually want to extract several types of information.

1. Subject

Identify the main subject of the scene.

For example:

• a person
• a car
• a product
• an animal
• a landscape

Then describe important visual characteristics.

2. Scene and Environment

Describe where the action happens.

For example:

• futuristic city
• minimalist studio
• forest at sunset
• crowded street
• modern office

Environmental details often have a major impact on the generated result.

3. Camera Angle and Composition

This is one of the easiest details to miss when manually writing prompts.

Useful information includes:

• close-up
• medium shot
• wide shot
• aerial shot
• low-angle shot
• over-the-shoulder shot
• centered composition

4. Camera Movement

For video generation, camera movement can be especially important.

Examples include:

• slow zoom in
• tracking shot
• camera pan
• dolly forward
• handheld movement
• orbit around the subject

A prompt describing only the subject and style may reproduce the appearance of a scene but completely miss its motion.

5. Lighting

Lighting can dramatically change the result.

Look for things such as:

• soft natural light
• golden-hour lighting
• dramatic side lighting
• neon lighting
• studio lighting
• high contrast
• cinematic shadows

6. Visual Style

Finally, describe the overall visual language.

For example:

• cinematic
• photorealistic
• anime
• documentary
• commercial photography
• retro film
• cyberpunk
• minimalist

The Manual Way

You can analyze a video manually.

Pause the video at important moments and write down:

1. What is happening?
2. Who or what is the main subject?
3. What does the environment look like?
4. Where is the camera?
5. How is the camera moving?
6. What kind of lighting is being used?
7. What visual style does the scene have?

For a short clip, this works reasonably well.

For longer videos or videos with multiple scenes, however, it quickly becomes tedious.

Automating the Process

I wanted a faster workflow, so I built VideoToPrompt.dev.

The basic workflow is simple:

1. Upload a video or paste a supported video URL.
2. Let the tool analyze the visual content.
3. Detect important scenes and visual elements.
4. Generate a structured AI prompt.
5. Use or modify the resulting prompt for your preferred AI model.

The goal isn't simply to produce a generic video summary.

Instead, the analysis focuses on information that is useful when creating AI-generated visual content, such as:

• scene descriptions
• subjects
• actions
• camera angles
• camera movement
• lighting
• composition
• visual style

Example: From Video to Prompt

Imagine a reference video showing a sports car driving through a city at night.

A basic description might be:

A sports car driving through a city.

That's technically correct, but not particularly useful.

A more detailed prompt could look something like:

A black sports car driving through a modern city at night, low-angle tracking shot from the rear side of the vehicle, wet asphalt reflecting neon signs, blue and red ambient lighting, shallow depth of field, subtle motion blur, cinematic commercial photography, dynamic forward movement, high contrast, realistic details.

Now the prompt contains much more of the visual structure of the reference video.

You can then adapt it depending on whether you're using an AI image generator or an AI video generator.

Video Prompts vs. Image Prompts

There is an important difference between the two.

For an image model, you usually care most about:

subject + environment + composition + lighting + style

For a video model, you also need to think about:

action + camera movement + temporal changes

For example, an image prompt might say:

Close-up portrait of a woman standing in the rain, cinematic lighting, shallow depth of field.

A video prompt can add:

The camera slowly pushes toward the subject while she turns toward the camera, rain falling in the foreground and background.

That extra motion information can make a significant difference.

Where Can You Use the Generated Prompt?

Once you have extracted the visual language of a video, the resulting prompt can be adapted for different generative AI workflows.

For example, you might use it as a starting point for:

• AI image generation
• AI video generation
• storyboarding
• shot analysis
• creative references
• prompt experimentation
• recreating the visual style of your own reference footage

The generated prompt doesn't have to be the final prompt.

I find it more useful to think of it as a structured starting point.

You can keep the camera movement but change the subject.

You can keep the composition but change the environment.

Or you can extract the lighting and visual style while creating an entirely different scene.

A Better Prompt Workflow

My preferred workflow is:

Reference video → Visual analysis → Structured prompt → Edit the important variables → Generate

This is much easier than trying to invent every detail from scratch.

It also makes reference-based generation more systematic.

Instead of saying:

"Make something that looks like this."

you can understand why the reference looks the way it does.

Try It

If you have a reference video and want to see what kind of prompt can be extracted from it, you can try:

👉 VideoToPrompt.dev — Video to AI Prompt Generator

Upload a video or provide a supported video URL, generate the prompt, and then modify it for your own workflow.

The interesting part isn't necessarily copying a video exactly.

It's turning visual references into reusable information:

camera + composition + lighting + motion + style + subject

Once those elements are separated, it becomes much easier to experiment with AI-generated images and videos.