I did not start this with a theory about virality. I started with a bad habit. I kept generating one pretty clip, watching it once, and deciding it was not right. The problem was not the model. The problem was that I had no hook, no platform decision, and no way to compare versions. So I rebuilt the process as a social media production log.

Now I can go from one idea to testable 9:16 videos without spending credits on random beauty. This is the workflow I use for TikTok, Instagram Reels, and YouTube Shorts in 2026.

Decide the platform before the prompt

The first thing I changed was the order. Instead of generating and cropping, I write down where the video will run. TikTok and Reels reward a fast visual decision. Shorts can handle slightly clearer setup. A website hero can be slower, but that is not a social video.

For 9:16, I plan the frame as vertical from the beginning. The subject stays near the center, the action happens in the middle third, and there is space for a caption. A 16:9 video cropped to 9:16 often loses the subject or makes text feel pasted on.

Design the first second

I write the first frame before writing the full prompt. If the viewer cannot tell what is happening immediately, the rest does not matter. My hooks fall into three types. A visual surprise starts with an unexpected object or motion. A problem hook starts with a frustration. A payoff hook starts with the finished result.

Then I write one action. Not three. Not a scene change. One clear action that can be understood without sound.

A red sneaker lands on wet pavement, water splashes around the sole, slow-motion push-in, urban evening light, vibrant commercial style

This prompt works because the first frame is recognizable and the action is simple. If I want a story, I make two clips and edit them together.

The model ladder I use

I use a cheap draft before a premium render. Agnes Video V2 is free and useful for checking framing. If the composition is promising, I move to Seedream 5.0 Lite or Nano-Banana 2 for a stronger still. For motion, Seedance 2.5 is good when I want expressive energy. Kling v3 Omni is better for controlled shots and offers native audio. Veo 3.1 is the premium cinematic option, but I only use it after the concept is approved.

This ladder changed my economics. I stopped paying premium rates to discover that a prompt had the wrong framing. The free draft answers the cheap question. The premium model answers the quality question.

Build variants, not duplicates

For each hook, I make at least two variations. One uses a close-up. One uses a slightly wider context. One changes lighting. One changes motion speed. I do not change everything at once. If I alter the subject, the camera, the scene, and the color in one generation, I cannot tell what worked.

For social content, the strongest variation is often the simplest one. A subtle push-in usually feels more native than a wild orbit. AI can do spectacle, but the feed rewards clarity.

Avoid the generic AI look

I stopped using vague words like cinematic by itself. Instead, I name the light, the place, the texture, and the camera. I also keep real-world imperfections when they help. A hand-held feel, slight grain, or imperfect background can make the clip feel less like a stock render.

Then I check for AI tells. Fingers, text, logos, and liquid movement are the usual suspects. If a human hand enters the frame, I watch it frame by frame. If there is text, I usually overlay it in the editor instead of generating it. If liquid or fabric behaves strangely, I reduce motion.

Cut for sound-off viewing

Most social viewers start with sound off or decide visually. I design the clip so the action explains itself. Captions carry the promise. The model carries the visual proof. Music comes later.

I keep captions in the safe area, not too close to the edge, and I avoid placing them over the most important motion. If the clip needs dialogue, I generate the visual first, then add voiceover or native audio only after the concept is approved.

My test loop

I publish or seed three clips, not one. Clip A uses the visual surprise. Clip B uses the problem hook. Clip C uses the payoff. I keep length between four and eight seconds. Then I compare the first three seconds, not just total views. If people leave immediately, the hook failed. If they stay but do not act, the message or call to action failed.

This is the part that makes AI video useful for social media. It is not about producing more noise. It is about testing enough distinct ideas to learn something.

What I would repeat

Start vertical. Write the first frame. Use one action. Generate a free draft. Approve a still before premium motion. Change one variable per test. Keep captions editable. Check hands and text. Then save the winning prompt as a reusable template.

That is how a social team can move from one lucky clip to a system.

AI Video for Social Media: TikTok, Reels, and Shorts in 2026