Learn how to plan, prompt, and edit vertical AI video for short-form feeds: a step-by-step workflow, prompt patterns, quality checks, and common mistakes.
A vertical video lives or dies in about two seconds. The opening frame has to promise something — a transformation, a joke, a reveal, a small mystery — and everything after it has to pay that promise off quickly. AI video generation has become genuinely useful in that window, not because it replaces craft, but because it collapses the distance between a rough idea and a watchable first draft.
This guide is about making that draft reliable: how to plan a short-form video, how to write prompts that hold up after compression, how to keep a series visually coherent, and where editing still has to do the heavy lifting. If you want the practical version of AI-assisted short-form creation, this is the workflow.
What AI video generation actually does well
Text-to-video is strongest at atmosphere and motion. It is very good at establishing shots, product hero moments, abstract transitions, weather, slow camera moves, stylized environments, and anything where the viewer's eye is following movement rather than reading fine detail. It is also excellent at variations: render the same idea five times with small changes and pick the one that lands.
It is weaker at anything that demands precision. Hands interacting with small objects, on-screen text inside the generated frame, complex multi-character continuity, and dialogue-driven performance are all places where generation tends to wobble. Knowing this up front saves hours. Design shots that play to the strengths, and use editing, captions, and overlays for the parts that need exactness.
A useful mental model: the generator produces footage, not a finished video. Footage is raw material. The finished video is footage plus pacing, sound, text, and a reason to keep watching.
Plan in beats, not in seconds
Most short-form videos fail at the planning stage, not the rendering stage. People open a tool, type a prompt, and hope a narrative appears. It rarely does. A better approach is to sketch the video as four beats before you generate anything.
- Hook (roughly the first two seconds): the single most visually arresting moment. Not a logo, not a slow fade-in. A collision, a close-up, a reveal, a strange scale.
- Context (two to five seconds): one clear idea that tells the viewer what they are watching. One idea only.
- Payoff (five to twelve seconds): the reason the hook existed. The result, the punchline, the finished look, the before-and-after.
- Loop (final two to three seconds): a return to the opening image, or a cut that makes the video feel complete enough to rewatch.
Once those four beats exist on paper, each one becomes one or two generated clips. That is the whole trick: you are not generating a video, you are generating a handful of shots that an edit will assemble into a video.
Write each beat as a single sentence with a subject and an action. "A ceramic cup slides across a wet steel counter and stops just short of the edge" is a beat. "Coffee vibes" is not.
The prompt skeleton that survives compression
Vertical video is watched on a small screen, often with sound off, often at arm's length on a commute. Detail you paid for in the prompt can vanish into a 1080×1920 compression pass. Prompts should therefore favor big shapes, clear silhouettes, strong contrast, and one dominant motion.
A skeleton that works across most models:
- Subject — who or what, described in concrete nouns, with material and color.
- Action — one verb-led motion, present tense. Two actions maximum.
- Camera — shot size plus movement: close-up, slow push in, handheld follow, locked-off wide.
- Environment — location plus one atmospheric detail (steam, dust, rain, neon reflection).
- Light — direction and quality. "Low side light, warm, hard shadows" is more useful than "cinematic."
- Look — film stock, lens character, color palette, grain level.
- Technical — aspect ratio, duration, frame rate, motion intensity.
Keep the whole thing under about 60 words. Long prompts dilute attention: when you name fifteen things, the model picks its own five. If you need more control, split into two shots rather than one crowded one.
Three example prompts
Product macro: "A matte black fragrance bottle rotates slowly on a wet obsidian slab, single hard beam of side light raking across the glass, thin mist drifting, macro lens, shallow depth of field, deep charcoal background, subtle film grain, vertical 9:16, five seconds, slow constant rotation."
Human moment: "A cyclist in a yellow rain jacket rounds a corner at dusk and disappears into fog, camera locked off at knee height, sodium streetlights behind, wet asphalt reflections, 35mm look, muted teal palette, vertical 9:16, four seconds, only the cyclist moves."
Abstract transition: "Liquid chrome folds in on itself and resolves into a smooth sphere, studio lighting with two soft boxes, dark neutral background, high-speed photography feel, crisp specular highlights, vertical 9:16, three seconds, single continuous morph."
Notice what these have in common: one subject, one motion, one light idea, and a stated duration. That structure is portable across models and easy to iterate on.
Words that quietly hurt your prompt
"Cinematic" alone does almost nothing. "4K ultra HD masterpiece" is noise. "Best quality" is noise. Vague emotional words like "epic" or "beautiful" push the model toward generic stock imagery. Replace each of them with a physical fact: what is lit, what is moving, what lens, what color, what texture.
Also avoid stacking contradictory instructions. "Handheld locked-off shot with fast dolly and static camera" gives the model an impossible brief and it will resolve it by ignoring two-thirds of your sentence.
Consistency across a series
A series needs to look like a series. Viewers recognize a visual signature before they recognize a topic. Three practical levers get you there.
A look bible. Write down four to six fixed attributes: palette, light direction, lens, grain, motion speed. Paste them into every prompt unchanged. Only the subject and action vary. This single habit does more for series coherence than any advanced technique.
Reference frames. Generate or upload a still that captures your look, then use it as a visual anchor for subsequent shots. You can build those anchors quickly with an AI image generator and reuse them across a batch.
Character sheets. For recurring human characters, describe them once in exhaustive physical detail — hair, build, wardrobe, distinguishing feature — and reuse that paragraph verbatim. Faces will still drift between clips, which is why most successful AI series keep their human on screen briefly, in motion, or partly obscured.
Start from a proven structure rather than a blank page. Browsing video templates is a fast way to see how pacing and shot counts differ between a tutorial, a product drop, and a comedy sketch.
Where generation stops and editing begins
This is the part beginners skip, and it is the difference between a clip that looks generated and a video that looks made.
Cut on motion. Trim each clip so the cut lands mid-movement. Static frames at the start and end of a generated clip are the biggest tell. Two frames of dead air before motion begins will read as cheap.
Speed-ramp selectively. A slight ramp into the payoff beat adds energy that generation cannot supply on its own. Keep it subtle; aggressive ramping on already-fast motion looks chaotic.
Caption everything. Most short-form viewing happens muted. Burned-in captions with high contrast, large type, and safe-zone placement are non-negotiable. Keep text out of the bottom 15 percent and top 10 percent where platform UI sits.
Sound carries the illusion. A whoosh on the cut, a low sub hit on the reveal, ambient room tone under everything. Generated footage with no sound design feels like a screensaver. Even a simple three-layer mix — ambience, impact, music bed — changes perception dramatically.
Hold the frame you want remembered. End on a composed image, not a clip that ran out of frames. Freeze, extend, or re-render the last beat deliberately.
A quality control checklist before you post
Run every video through the same seven checks. It takes ninety seconds and catches most embarrassments.
- Does the first frame work as a still image on its own?
- Is there motion inside the first half second?
- Do hands, faces, and text survive a full-screen watch?
- Is the captions' reading speed comfortable at normal playback?
- Does the audio peak cleanly without clipping on phone speakers?
- Is anything important hidden behind the platform interface?
- Does the final frame invite a rewatch or a scroll-stop?
If a clip fails checks one through three, re-render that shot rather than trying to fix it in the edit. Fixing generated flaws with editing is usually slower than generating a better take.
Mistakes that make AI video look cheap
Too many ideas per clip. Three subjects in one prompt produces mush. Split it.
No stated camera. Without a shot size the model defaults to a mid-wide, which reads as generic. Always name the lens and distance.
Uniform lighting. Flat light is the fastest way to look synthetic. Commit to a direction: hard side light, backlight rim, single practical source.
Ignoring the loop. A video that ends abruptly loses the replay. Design the last beat to point back at the first.
Rendering before scripting. Every minute spent on the beat sheet saves five minutes of re-rendering. This is the highest-leverage habit in the entire workflow.
Overusing the same motion. Slow push-ins on everything becomes a tic. Alternate locked-off shots, follows, and static macro frames.
Choosing a tool without getting lost
Model quality changes monthly, so choose on workflow fit rather than on a leaderboard. Five criteria matter more than raw fidelity.
Native vertical output. Generating wide and cropping loses composition. You want 9:16 framing built in.
Iteration speed. The tool you can re-prompt eight times in ten minutes beats the tool with slightly better output that takes an hour per attempt.
Prompt adherence. Test with a prompt containing three specific constraints — a color, a camera move, a duration — and see how many survive.
Motion realism. Watch examples with human movement and fabric. Cloth and hair reveal a lot about a model's temporal coherence.
Reviewable output. Look at real sample galleries rather than cherry-picked hero clips. Seedance 2.5 examples are a good reference point for what current motion quality looks like in practice, and comparison pages such as Orelon vs Runway help you map strengths to your specific use case.
A pragmatic approach: pick one primary generator for hero shots and one faster option for B-roll and transitions. Mixing two tools is normal in professional short-form work.
A weekly system that scales
Consistency beats intensity. A batch workflow looks like this:
Monday — plan. Write ten beat sheets in one sitting. Ten is enough for two weeks of posting at a sustainable pace.
Tuesday — prompt. Convert each beat sheet into shot prompts using your fixed look-bible paragraph. Save them in a reusable prompt library so successful phrasing is never lost.
Wednesday — render. Generate everything in one long session. Batching keeps you in the same visual headspace and makes inconsistencies obvious.
Thursday — edit. Assemble, caption, sound-design, and export. Do not generate new footage on edit day unless something is genuinely broken.
Friday — review. Watch every finished video muted, on a phone, at arm's length. Cut anything you would scroll past.
The output of this system is roughly five publishable videos per week with about six hours of total work — and, more importantly, a body of prompts and look references that compound over time.
Frequently asked questions
How long should an AI-generated short-form video be? Between eight and twenty seconds for most formats. Under eight seconds rarely earns a rewatch; over twenty-five seconds demands a narrative strong enough to justify it. If the idea is thin, shorter is almost always better.
Can I build a whole series with one consistent character? Yes, with caveats. Keep the character's on-screen time short, favor motion and partial framing, and reuse an identical description paragraph in every prompt. Expect occasional drift and plan around it rather than fighting it.
Do I need to disclose that the video is AI-generated? Follow the rules of the platform you publish on and any applicable local requirements. Many platforms now expect a label on realistic synthetic media, and audiences generally respond better to transparency than to a reveal in the comments.
Why does my generated footage look soft or mushy? Usually one of three causes: too many subjects in one prompt, low-contrast lighting, or heavy motion combined with fast camera movement. Reduce to one subject, add a directional light source, and slow the camera down.
Should I generate at a higher resolution and downscale? Downscaling can clean up artifacts, but native vertical composition matters more than resolution. A well-composed 1080×1920 clip outperforms a cropped wide shot every time.
How many renders should I expect per usable shot? Plan for three to six. Treating the first render as a draft rather than a deliverable is what separates a smooth workflow from a frustrating one.
Make your next vertical video with Orelon
Orelon is built for cinematic ideas in motion — vertical-first generation, fast iteration, and a workflow that keeps your look consistent from the first prompt to the final cut. Start with the AI video generator, sketch your four beats, and render the hook before anything else. Once the opening two seconds work, the rest of the video tends to follow.