How to Make AI Videos: The Shot-by-Shot Method (2026)

To learn how to make AI videos, think like a director, not a typist. You plan the video as a list of short shots, write one specific prompt per shot (subject, action, scene, camera, light, sound), generate a few takes of each, keep the one that holds together, and join them in an editor. Today's models produce clips measured in seconds, so a 30-second ad is often several separate generations stitched together. The prompt matters, but the plan matters more.

How to make AI videos: the method in six steps

Every good AI video, from a product teaser to a short story, goes through the same six moves. Skip one and you pay for it later in wasted retries.

1. Decide the kind of video. A cinematic clip, an edited video with voiceover, or a presenter talking to camera. Each needs a different tool.
2. Write a shot list. One line per shot: what we see, how long it lasts, what we hear. Keep shots short.
3. Write one prompt per shot. Describe a single moment, not the whole story.
4. Generate a few takes per shot. Compare them side by side and keep the one that holds together.
5. Assemble and add sound. Put the shots in order, trim, add music, voice or captions.
6. Export, label and save. Keep the prompt and settings next to each file, and disclose realistic AI content where the platform asks for it.

The order is the point. People who start at step 3 end up with ten beautiful clips that do not fit together.

Three kinds of AI video, and which one you need

"AI video" covers three different jobs, and most disappointment comes from using a tool built for another one. The first is the generated clip: a text to video generator invents moving footage from your words, a few seconds at a time. Kling AI, Google Flow, Runway, Luma AI and Higgsfield work here. The second is the edited video: an agent turns a prompt or script into a finished cut with voiceover, music and subtitles. The third is the presenter video, where an AI avatar reads your script, which is what Synthesia builds.

Ask yourself one question. Is the picture the product, or is the message the product? If the look of the footage is what sells (an ad, a music video, a mood piece), you need generated clips. If the information is what matters (a tutorial, an explainer, a training module), an edited or presenter video gets you there with less effort. You can mix them: a presenter video can carry a few generated shots as b-roll. For how the models themselves work, our guide to AI video generation goes deeper.

Subject, action, camera and sound in one AI video prompt

A text-to-video model reads your prompt as a description of one shot. Google's prompting guide for its video models breaks a prompt into parts: the subject, the action, the scene or context, the camera angle, the camera movement and lens effects, plus audio described in separate sentences ^[1]. The same guide describes negative prompts as a list of what the model should leave out. Specific beats generic. A woman is vague; a barista in a green apron gives the model something to hold.

A workable pattern is one sentence for the core shot, then the details. Here is a weak and a strong version of the same idea.

The strong version answers the questions the model would otherwise guess at: who, what, where, how it looks, how the camera moves, what we hear. If you want to build a reusable prompt sheet by hand, our AI video prompts guide walks through the columns and examples.

A worked example: a 20-second coffee teaser

Say a small coffee roaster wants a vertical teaser for social media. The plan comes first. Shot 1, four seconds: beans tumbling out of a roaster drum, steam rising. Shot 2, six seconds: the barista pour from the table above. Shot 3, six seconds: a customer's first sip by the window, a small smile. Shot 4, four seconds: the bag on the counter, the brand name in clean light. That is four prompts, not one.

Each shot gets three or four takes. You keep the one where the hands look right and the cup does not change shape halfway through. Then you assemble the shots in an editor, lay one music track under all of them so the sound does not jump between clips, and add the brand name as a text layer rather than asking the model to write it. Twenty seconds of finished video can easily take a dozen generations. Plan for that from the start.

Common mistakes when you make an AI video

Most failed AI videos fail for the same few reasons.

• One prompt for the whole story. The model compresses or ignores half of it. Split it into shots.
• Several camera moves in one shot. A pan, a zoom and an orbit together usually produce mush. One move per shot.
• Forgetting sound. Some models generate audio with the video; others are silent. Runway's Gen-4.5 has no sound of its own, and Luma AI's Ray3.2 (June 2026) output is silent, so you add audio after or pick a model with sound.
• Using free output for a client. Kling AI's free Basic account and Higgsfield's Free plan do not allow commercial use, and Luma AI's trial output is for internal evaluation only.
• Not saving your prompts. A clip you cannot recreate is a clip you cannot fix.
• Using a real person's face or voice without permission. You need the right to use any likeness you put in a video.

Publishing has its own step. YouTube requires creators to disclose AI-generated or altered content that seems realistic, through the AI use setting in YouTube Studio during upload ^[2]. Clearly unrealistic content and minor edits do not need it. Every output from Google Flow also carries an invisible SynthID watermark, whatever you do with the file.

When it gets hard: longer videos, the same character, retired models

Three things push a project past what careful prompting alone can handle.

Length

Clips are short by design. Runway's Gen-4.5 makes 2 to 10 seconds per generation; Google Flow's Veo 3.1 Lite makes 4, 6 or 8 seconds; Kling 4.0, released to all in October 2026, reaches 30. Runway itself says long videos are assembled from short clips. Past a minute, you are managing dozens of files, and the editor becomes as important as the generator.

The same character in every shot

A face, an outfit or a product label that drifts between shots breaks the illusion. Luma AI warns that key elements may change between versions unless you re-anchor its agent to master reference assets. Tools now answer this with reference images and multi-shot generation: Kling 3.0 can make up to six shots in a single generation, and Runway's Agent plans and builds multi-shot videos from a conversation.

Models that retire

AI video models change on a months-long horizon. Runway removed Sora 2 on April 3, 2026 and retired Gen-3 Alpha in mid-2026. Google Flow retired Veo Extend on November 5, 2026, and Veo 3.1 Fast, Veo 3.1 Quality and Omni Flash 1.1 retire there on December 5, 2026. Your prompts are the asset that survives. Keep them in a sheet with the model name and date, and a retired model becomes a re-run, not a restart.

Every retry is paid

Generating is metered on most tools. Runway keeps the cost of a result you dislike and refunds only generation errors; InVideo AI charges every retry again. Luma AI's Draft Mode makes low-resolution 360p drafts for exploration, and Luma's own advice is to draft low and finish at 1080p. Lock the shot in drafts, then render the final once.

Handing steps 3 to 5 to a tool

If you would rather hand over part of the method, three tools take it from different ends. The first suits single shots on a free account, which is where most people learn to prompt.

Kling leaves the assembly to your own editor. In the coffee teaser above, the four shots would still need ordering and trimming somewhere, and Flow keeps that step next to the generator.

Both of these still expect you to write the shot list. When the message matters more than the picture, as with a tutorial or explainer, a script-to-edit agent does the assembling and adds the voice and captions.

For directors who want lens and camera controls, Higgsfield's Cinema Studio 4.0 builds scenes of up to 30 seconds from a director's panel, though it blocks real faces. Every tool that fits this job, grouped by the kind of person it suits, is in our text to video AI guide.

Why the shot list outlives every model

Treat an AI video as a production job with a very fast camera. Decide which kind of video you need, break it into short shots, write one specific prompt per shot with subject, action, scene, camera, light and sound, and expect several takes per shot. Assemble in an editor, add sound and text there, save every prompt with its model and date, and label realistic content where you publish. The method stays the same as tools and models change. The prompt sheet you build today is what lets you rebuild tomorrow.