A practical workflow for AI-generated vertical video: premise, shot list, prompt structure, editing, export settings, sharing, and a weekly review loop.
An AI-generated clip can look expensive and still lose a viewer in the first second. What separates a vertical video that travels from one that gets scrolled past is rarely the model behind it — it is the workflow in front of it: a premise sharp enough to survive a caption, a shot list that holds up in the edit, prompts written for a phone screen, and an export that does not fall apart under compression. This guide walks through that workflow end to end, from the first sentence of an idea to the moment you publish the finished clip or send it to a friend.
The feed rewards a repeatable pipeline, not a lucky render
Most people treat AI video generation like a slot machine: type something, pull the lever, hope. That produces a handful of lucky clips and no channel. Creators who post consistently run a pipeline. They know what the video is about before they generate anything, they know which shots they need, and they know how the clip will be cut, captioned, and exported before the first frame exists.
A pipeline also protects you from the most common failure in AI short-form: beautiful footage with no reason to exist. A slow push-in on a neon skyline is pleasant for two seconds and forgettable by the third. A twenty-second story about a courier who delivers a parcel to the wrong version of the same city is something people finish, rewatch, and send to a friend — which is exactly the behavior the platform rewards.
Think of the eight stages as a loop rather than a line: concept, shot list, prompt, generation, edit, export, publish, review. Each stage has three or four decisions that genuinely matter and a long tail of decisions that do not. Spend your attention on the first group and stop agonizing over the rest. The creators who burn out are usually the ones who spend forty minutes choosing a render style and four minutes writing the premise.
Pre-production: decide the video before you generate anything
Generation is the expensive part of the process, both in time and in attention. Do the thinking while it is still free — on paper, in a notes app, anywhere that is not a generation queue.
The one-sentence premise
A usable premise has three parts: a subject, a turn, and a consequence. “A night-shift baker finds a loaf that keeps rising” is a premise. “Cozy bakery vibes” is a mood, and moods generate pretty clips that nobody finishes. Write the sentence down and keep it visible while you generate, because the moment you start chasing interesting frames you will drift away from it.
A good test: can a stranger repeat your premise after watching the video once? If not, the idea is still too vague to survive the feed. A second test: does the sentence describe something that changes? If nothing changes between the first and last second, you have made a wallpaper, not a video.
The six-shot list
Short-form video rarely needs more than six shots. For each one, write three things: what the camera sees, what changes during the shot, and how long it lasts. A workable list for the baker story might be: hands kneading dough in close-up (3s), the loaf twitching on the counter (2s), the baker stepping back in surprise (2s), the loaf rising toward the ceiling (3s), a wide shot of the tiny kitchen with a giant shadow (3s), and a final beat on the baker's face lit by oven glow (3s).
That list does two useful jobs. It tells you which generations are essential, so you stop making ten versions of the same shot. It also tells you what the edit will look like, so you generate matching coverage instead of hoping clips will cut together. Keep the list in the same document as your premise; if a shot does not serve the premise, delete it before you spend anything on it.
Pick one format and commit
The three formats that survive repeated posting are the loop, the micro-story, and the demonstration. Loops end where they begin and reward rewatching. Micro-stories run on a single turn, usually in under twenty seconds. Demonstrations show a process or a transformation and suit product, tutorial, and craft accounts. Pick one per video. Mixing a loop with a demonstration usually produces something that is neither, and the audience cannot tell what they are supposed to do at the end.
Prompting for a vertical, compressed feed
A vertical, mobile, heavily re-compressed medium punishes prompts written for a cinematic widescreen showcase. Write for the delivery format instead of the preview window.
Name the camera, the height, and the motion
The single strongest improvement most creators can make is to state the camera explicitly. “Low-angle tracking shot, 35mm lens, slow forward push, shallow depth of field” gives a generator far more to work with than “cinematic shot of a baker.” Name the movement (push, pull, orbit, handheld follow, static lock-off), the height (eye level, low angle, overhead), and the lens feel (wide and exaggerated, normal and neutral, long and compressed).
Keep one motion per shot. A prompt that asks for a push-in, an orbit, and a rack focus in six seconds produces mush, because the model has to average three intentions into one. If you want two movements, make two shots and cut between them — the cut is free, and it reads as intent rather than noise.
Composition matters more in vertical than in landscape. Leave the middle band clean for captions, keep the subject's eyes in the upper third, and avoid dense background detail near the bottom edge where the interface sits. A prompt that names a “clean mid-frame” and a “single subject, uncluttered background” will save you an edit later.
Lock identity across shots
Continuity is what separates a story from a collage. Reuse an exact description block for your subject — age range, build, hair, wardrobe, one distinguishing detail — and paste it into every prompt in the sequence. If your tool supports reference images or character consistency features, use them and keep the same reference across the batch. Lock the palette too: naming two or three colors (“teal shadows, warm tungsten highlights, one red accent”) does more for visual consistency than a paragraph of style adjectives.
Write the description block once, save it as a snippet, and never paraphrase it. The moment you rewrite “silver buzz cut” as “grey crop,” you have created a different person.
Four prompt mistakes that flatten good ideas
Negations backfire. “No text, no watermark, no extra fingers” often plants exactly those ideas. Describe what should be there instead: “clean surfaces, single subject, uncluttered background.”
Stacking style keywords from different eras produces a washed-out average. Two is usually plenty; four is a soup.
Verbs of intent do not photograph. “A character who realizes” is a story note. Translate it into visible behavior: “her eyes widen, she steps back, the tray slips from her hands.”
Finally, do not ask one generation to carry a whole scene. Generators are good at single beats. Six short, deliberate clips will beat one ambitious eight-second render almost every time. Keep a running file of prompts that worked — a curated personal library beats any generic list because it encodes your taste. The prompt library is a reasonable starting structure to adapt rather than copy.
Choose tools by job, not by release date
Every week brings a new model announcement, and chasing all of them is a fast route to inconsistent output. A calmer approach is to assign tools to jobs.
For fast iteration and idea testing, you want something quick and cheap enough that you can afford to discard nine out of ten attempts. For hero shots, you want a model that holds detail and obeys precise camera language. For continuity across a sequence, you want whatever offers reference images and stable characters. For stylized transitions and motion experiments, unpredictable models are worth the unpredictability.
That means most creators end up with two or three tools rather than ten. Sketch the sequence in the AI video generator, then move only the hero shots into a heavier model. When you are deciding between platforms, comparison pages such as Orelon vs Runway are more useful than feature tables, because they frame the choice around workflow rather than raw specifications. Browsing model examples before committing also saves a lot of wasted generation, since you can see the actual texture of the output rather than the promise of it.
One practical rule: never switch tools mid-sequence unless you are deliberately breaking continuity. Mixed renders read as inconsistent even when each individual shot is strong. If you must mix, give each tool a distinct job — for example, one for the live-action beats and one for the impossible beats — so the difference looks like a choice.
The edit: earn the first two seconds
The edit is where AI footage becomes a video. Three decisions dominate everything else.
The opening frame
Open on motion, a face, or an unanswered question. Not on a logo, not on a slow establishing drone shot, not on a title card. If your best shot is at second eight, move it to second zero and rebuild the sequence around it. Many successful AI shorts are simply the strongest clip, trimmed tighter, with the story reordered to protect it.
A useful exercise: watch your cut with the sound off and the first second removed. If the video still makes sense, the opening was doing nothing. If it collapses, the opening was load-bearing and you should protect it.
Sound design and captions
Generated audio is optional; sound design is not. A whoosh on the cut, a low room tone underneath, and one distinct sound effect tied to the turn of the story will do more for perceived production value than another render pass. Silence is a tool too — drop the music for half a second before the payoff and the payoff lands harder.
Captions should be burned in at a readable size, with high contrast, positioned above the interface elements at the bottom of the screen. Keep them short — three to five words per line — and on screen long enough to read twice. Do not caption every word of a voiceover if the voiceover is already clear; caption the beats.
Pacing
Cut on motion, not on stillness. If a clip has a natural gesture — a hand moving, a head turning — cut two frames into that gesture and the transition disappears. Keep your average shot length between one and three seconds for loops, and let demonstrations breathe a little longer. When in doubt, remove one shot entirely and see whether the video improves. It usually does.
Export settings that survive re-compression
Upload platforms re-encode everything you give them, and the encoding is not gentle. Protect your detail before it reaches that stage.
Export vertical 1080×1920 at a high bitrate, then check the file on a phone before uploading, not on a monitor. Detail hides in dark gradients, so if your video is moody, add a touch of grain before export: grain survives compression better than smooth shadow, which tends to band into blocky patches. Keep contrast slightly higher than feels natural on a calibrated screen — phones in daylight eat contrast for breakfast.
Avoid stacking compression passes. Do not export, send the file through a messaging app, and then upload. Every pass removes a little more of the texture that made the clip worth watching. Keep a clean master file and derive uploads from it rather than from each other.
Finally, name your files sensibly — project, version, date — so you can find the master three weeks later when someone asks for a repost.
Publishing natively and sharing on purpose
A finished clip has two lives: posted publicly, or sent directly to people. Both matter, and they follow different rules.
Post natively, without foreign watermarks
Re-uploaded video carrying another platform's watermark is consistently deprioritized, and viewers treat it as an ad. Export clean, upload from the device, and write the caption inside the app. Use the platform's own text, sticker, and sound tools for at least one element — it signals that the video belongs there rather than being syndicated through it.
Direct sends and small-group sharing
Sending a clip to a friend or a small group is the most underrated distribution channel available. A direct send is a strong interest signal, and a clip forwarded privately often gets a second wind publicly. Practical habits: keep a short list of five to ten people who genuinely enjoy your niche, send the strongest clip of the week to two of them with a one-line note, and never send the same clip to everyone at once. Ask a specific question — “does the ending land?” — rather than “thoughts?” You will get better feedback and more replies.
Cross-posting without penalties
If you publish the same video elsewhere, remove the other platform's watermark, rewrite the caption rather than copying it verbatim, and stagger the timing so you can be present in the comments on each platform. Cross-posting is fine; automated, identical, watermarked syndication is what gets suppressed. Adjust the aspect ratio deliberately too — a vertical clip letterboxed inside a horizontal frame reads as an afterthought.
Disclosure, likeness, and music: three risk areas
Almost every problem creators run into with AI video comes from one of these three.
Disclosure: platforms increasingly expect synthetic media to be labeled, especially when a realistic person, product, or event is depicted. Label it yourself rather than waiting to be flagged, and read the current community guidelines before running a campaign that depends on realism. A short on-screen label or a line in the caption is enough, and audiences are far more forgiving of visible AI when they are not being fooled.
Likeness: do not generate a recognizable real person, and be careful with lookalikes of public figures even in parody. Keep a written record of prompts and reference images for anything commercial, because “I did not intend it” is not a defense anyone accepts.
Music: commercial tracks inside a generated video can trigger claims even when the video itself is original. Use the in-app sound library or licensed instrumentals, and keep audio and video rights notes separate so you know what you can reuse later. If a track is essential to the joke, that is a reason to license it, not a reason to skip the question.
A weekly review loop that improves the next batch
Review once a week, not once a day. Daily checking produces anxiety; weekly checking produces decisions.
Pull three numbers per video: how many people watched past two seconds, average watch time, and shares (public and private combined). Those three tell you whether the hook worked, whether the middle held, and whether the idea was worth sending to someone. Ignore follower count for this exercise — it moves too slowly to teach you anything about a single clip.
The four buckets
Classify every video into one of four buckets. Strong hook and strong retention: repeat the format. Strong hook and weak retention: the idea was good but the payoff arrived late, so move the turn earlier. Weak hook and strong retention: the opening shot is wrong, so swap it and repost with a new first second. Weak on both: the premise was thin, so retire it without ceremony.
After four weeks you will have a table that tells you more about your channel than any trend report. Five fixes that raise quality fast: cut the first second of every clip; replace one wide shot with one extreme close-up; add a single sound effect at the turn; shorten captions to three words per line; end on a frame that invites a second viewing.
Mistakes that cost the most time
Generating before writing the premise. You will produce attractive footage you cannot use.
Rewriting the character description between shots. Continuity dies quietly and you will not notice until the edit.
Making ten variations of shot one and none of shot five. The middle of your video is where viewers leave.
Uploading the file you sent to a friend. That is two compression passes; export a fresh master.
Chasing a new model mid-project. Finish the sequence, then experiment on the next one.
And the quiet one: captioning the process instead of the story. Nobody watches a video because it was made with AI. They watch because something happened.
FAQ
How long should an AI-generated vertical video be?
For loops and micro-stories, eight to fifteen seconds. For demonstrations and tutorials, twenty to forty. Length is not a virtue on its own — every extra second has to earn the next one. If you cannot describe what happens in a given second, cut it.
Do I need to tell viewers the video is AI-generated?
You should, especially when the footage looks realistic or depicts people, products, or events that could be mistaken for real. A short on-screen label or a caption line is enough. Beyond policy, disclosure builds trust, and it protects you if the clip is later shared out of context.
Why do my generated clips look soft after uploading?
Usually it is compression meeting smooth gradients and motion blur. Shoot for contrast, add subtle grain, avoid long slow fades, export at a high bitrate, and never route the file through a messaging app on the way to the upload screen.
Can I reuse the same character across many videos?
Yes, and you should — it is the fastest way to build recognition. Keep a reusable description block plus a reference image, and paste both into every prompt. Reintroduce the character visually in the first second so new viewers are not lost.
How many attempts should one usable shot take?
Expect five to ten while you are exploring a new look, and two to three once you have a proven prompt structure. If you are consistently burning far more than that, the problem is usually specificity in the prompt rather than the model.
Is it better to post daily or to post well?
Post at a cadence you can sustain for a month without degrading quality. Three strong videos a week beat seven rushed ones, and the review loop only works if you have enough videos to compare.
Start with Orelon
Good short-form AI video is a craft of small decisions: a premise with a turn, a shot list you actually follow, prompts that describe what a camera can see, an edit that respects the first second, and a clean export that survives the upload. Get those right and the model becomes the least interesting part of your process — which is exactly where you want it.
Orelon is built for that kind of work: cinematic ideas in motion, generated quickly enough to iterate, with templates to start from and a prompt library to sharpen your language. Take one premise you have been sitting on, build a six-shot list, and generate the first shot today. The pipeline gets faster every time you run it.
