Building an AI Video Workflow with MiniMax H3: Text-to-Video and Image-to-Video

Jaysean Brambila — Sun, 23 Aug 2026 09:39:50 +0000

AI video generation has become much easier to experiment with, but building a useful workflow still involves more than simply entering a prompt.

I've recently been exploring MiniMax H3 for both text-to-video and image-to-video generation. In this post, I'll share a simple workflow for getting more consistent results.

1. Start with a clear visual goal

Before writing a prompt, define:

Subject
Environment
Camera movement
Lighting
Visual style
Desired motion

Instead of:

A woman walking in a city

Try something more structured:

A woman in a black coat walking through a rainy Tokyo street at night, cinematic lighting, reflections on wet pavement, slow tracking shot, shallow depth of field.

The goal is not necessarily to make the prompt longer. It is to make every part of the prompt useful.

2. Text-to-video works best with controlled motion

For text-to-video generation, I usually separate the prompt into three parts:

Scene + Motion + Camera

For example:

A futuristic train moving through a neon city, rain falling across the windows, camera slowly tracking alongside the train.

This makes it easier for the model to understand what should move and how the camera should behave.

3. Image-to-video needs a different approach

With image-to-video, the source image already defines most of the visual information.

The prompt should focus more on motion:

Character movement
Camera movement
Environmental effects
Changes over time

For example:

The camera slowly pushes forward while the character turns toward the window. Curtains move gently in the wind and sunlight shifts across the room.

This is often more reliable than describing the entire image again.

4. Keep iterations small

One mistake I made early on was changing too many things between generations.

A better workflow is:

Generate a basic version
Identify the biggest problem
Change one or two prompt elements
Generate again
Compare the result

Small iterations make it much easier to understand what is actually improving the output.

5. A simple browser-based workflow

For anyone experimenting with this process, I've been using MiniMax H3 to test text-to-video and image-to-video workflows in the browser.

The main thing I'm interested in is reducing the number of steps between an idea, a reference image, and a usable video result.

Example prompt structure

A reusable structure I've found useful is:

Subject + Action + Environment + Camera + Lighting + Style

Example:

A vintage sports car driving along a coastal highway at sunset, ocean visible in the background, low-angle tracking shot, warm cinematic lighting, realistic film look.

For image-to-video:

Subject Motion + Environmental Motion + Camera Motion

Example:

The character slowly raises her head, hair moving gently in the wind, clouds drifting in the background, camera slowly pushing forward.

Final thoughts

AI video generation is improving quickly, but prompt structure and iteration still make a noticeable difference.

I'm especially interested in how these tools can become easier for creators who don't want to think about the underlying model or technical workflow.

If you're experimenting with AI video generation too, I'd be interested to hear what prompt structures or workflows have worked best for you.

DEV Community: Jaysean Brambila