Optimize Your AI Prompt for Creating Viral Videos on YouTube: Start Higher Retention

Last Updated on December 25, 2025 by Xu Yue

AI video generators aren’t psychic. They’re bureaucrats.

If you want a decent output, treat your prompt like you’re filing paperwork at the world’s weirdest DMV: clear fields, no vibes, no poetry, no “make it viral pls 🙏”.

Because here’s the awkward truth: your AI prompt for creating viral videos on YouTube usually fails for the same reason most videos fail—the viewer doesn’t instantly know what problem you’re solving, why they should care, and what payoff they’re getting for staying. The AI can’t fix that if you don’t give it a job it can actually do.

Let’s build prompts that produce retention, not just “a script that sounds nice.”

The Reason Your AI “Viral” Prompts Don’t Work

You’re prompting without a clear viewer problem

Most prompts start with what you want to talk about. Viewers start with why they should give you their next 30 seconds.

So instead of prompting like this:

“Write a YouTube script about budgeting.”

Prompt like this:

“Write a YouTube intro for people who overspend on food delivery and feel guilty every week, and want a fix that doesn’t feel like punishment.”

That single shift (topic → problem) instantly forces the model to generate useful tension. And tension is retention fuel.

A good “viewer problem” line usually contains:

• Who the viewer is (beginner, broke student, new parent, overwhelmed editor)
• What’s going wrong (wasting time, losing money, blurry footage, low views)
• What they’ve already tried (so you can avoid generic advice)

No payoff = no retention (even with a strong hook)

A hook without payoff is a trailer for a movie that never starts.

Your prompt needs a payoff promise the script must deliver:

• a result (“clean audio in 10 minutes”)
• a comparison (“best vs worst settings”)
• a reveal (“the reason your Shorts die at 12 seconds”)

If you don’t specify payoff, AI fills the space with… motivational fog.

Too broad inputs create generic outputs

When creators complain that ChatGPT “sounds the same,” it’s often because the input is the same: broad topic, no stakes, no constraints.

This is why a popular NewTubers thread about a “solid ChatGPT prompt” frames it as a starting point for generating hook options—then you still have to tailor it to your channel and audience.

The Retention-First Prompt Formula

The 5 hook types viewers actually respond to

You don’t need 47 hook styles. You need a handful that match human behavior:

1. Contrarian truth (“Everyone edits Shorts wrong. Here’s why.”)
2. Specific outcome (“In 8 minutes you’ll have a script outline that doesn’t ramble.”)
3. Open loop (“By the end, you’ll know the one line your title must not include.”)
4. Fast proof (show result first, explain after)
5. Relatable pain (“If your AI scripts feel… weirdly polite, this is why.”)

Here’s a copy/paste hook prompt (built on what creators like in those “give me 3 hook options” prompts, but tightened for retention):

You are writing 3 hook options for a YouTube video. Audience: [who exactly] Viewer problem: [pain + frustration + what they tried] Payoff: [what they’ll get by minute 3] Constraints: no “Hey guys”, no channel intro, no filler. Each hook must:

start with a punchy first sentence (max 12 words)

include a clear promise (what changes if they keep watching)

end with an open loop question or curiosity line Now write 3 hooks in different styles: (1) contrarian, (2) fast proof, (3) relatable pain.

Add constraints: audience, stakes, payoff

Constraints are how you stop “AI oatmeal” (warm, bland, technically edible).

Use these three fields in almost every prompt:

• Audience: “new creators posting Shorts,” “busy students,” “non-native English speakers”
• Stakes: what happens if they ignore it (wasted time, low retention, demonetization risk, low CTR)
• Payoff: what success looks like (a script map, a title set, 3 tested angles)

If you’re writing prompts for AI video generation (text-to-video), the same principle applies: describe what’s in frame and how it moves, using direct language. Runway’s prompting guide explicitly emphasizes describing what appears and how elements move.

One “8th-grade” clarity rule

If a middle-schooler can’t explain your video in one sentence, your intro is probably losing people.

Add this line to your prompt:

Write at an 8th-grade reading level. Short sentences. Concrete words. No buzzwords.

It’s not “dumbing down.” It’s removing friction.

Prompt Packs by Video Type (给出真实搜集到的提示词案例)

Below are prompt packs you can actually run. They’re based on real patterns found in creator communities (like “generate multiple hooks,” “avoid sounding robotic,” “make it practical”), plus common AI video prompt structure guidance (clear subject/action/scene/motion).

YouTube Shorts prompt pack

Shorts die when:

• the hook is slow
• the “point” arrives too late
• the pacing doesn’t reset attention

Create a 25–35 second YouTube Short script. Goal: high retention. Audience: [who] Viewer problem: [pain] Payoff: [result] Structure rules:

0–2s: pattern break hook (no greeting)

2–10s: state the problem + why it happens

10–25s: 2–3 rapid steps (each 1 sentence)

last 5–8s: recap + one CTA that feels helpful Style: punchy, slightly humorous, no corporate tone. Give me: script + on-screen caption lines (max 6 words each).

Bonus add-on (if you’re using an AI video generator):

Also output: a single scene description for AI video generation

(subject + action + setting + camera movement + lighting + style), 1–2 sentences.

That “scene description” part aligns with how AI video prompt guides recommend direct, visual instructions rather than abstract vibes.

Long-form tutorial prompt pack

Long-form isn’t “be longer.” It’s “earn attention repeatedly.”

Write a 6–8 minute YouTube tutorial script. Audience: [who] Promise: [clear outcome] Viewer problem: [pain + failed attempts] Include:

cold open: show the result first in 1 sentence

a simple roadmap (3 steps, 1 sentence)

3 proof beats (examples, numbers, or mini demo moments)

2 “reset attention” moments (quick recap / surprising tip) Tone: friendly, practical, no fluff. End with: one next-video suggestion (not “like and subscribe”). Output: (1) Hook + (2) section headers with timestamps + (3) full script.

Faceless/B-roll voiceover prompt pack

Faceless content fails when the narration is generic and visuals don’t match.

Create a faceless YouTube script + B-roll plan. Topic: [topic] Angle: [specific perspective] Audience: [who] Retention rules:

Every 20–30 seconds: add a visual change (scene switch, overlay, chart, example) Deliverables:

Voiceover script (6–7 minutes)

B-roll shot list aligned line-by-line

On-screen text overlays (short, readable)

3 title options + 3 thumbnail text options Style: confident, slightly witty, not robotic.

Packaging Prompts: Titles, Thumbnails, and A/B Testing Loops

You can write the best script in your niche… and still flop if packaging is confusing.

YouTube’s own guidance is blunt: titles and thumbnails should be clear, and it’s normal to experiment and update them over time.

Also: YouTube has expanded Test & Compare so creators can test multiple titles and thumbnails on a video (up to three variants). That’s an official YouTube Studio update.

Title prompt for CTR (without clickbait)

Create 12 YouTube titles for this video: Topic: [topic] Audience: [who] Promise: [outcome] Constraints:

avoid clickbait words like “INSANE” unless niche fits

match the thumbnail idea (same story, different words)

keep titles under 60 characters when possible Give me 3 groups: A) curiosity titles (open loop) B) benefit titles (clear outcome) C) contrarian titles (challenge common belief)

Thumbnail text prompt

YouTube thumbnails are tiny. Your thumbnail text should behave like it’s being read from across a room.

Give me 12 thumbnail text options (max 1–4 words). Video promise: [promise] Main contrast: [before vs after] or [mistake vs fix] Rules:

no punctuation spam

no vague words like “THIS”

each option must be instantly understandable Also suggest 3 simple thumbnail concepts (subject + emotion + visual contrast).

Test-and-iterate prompt

A/B testing is where creators stop guessing and start learning. YouTube Studio’s Test & Compare makes this more accessible.

Act as a YouTube optimization coach. Here are my metrics:

impressions: [#]

CTR: [#]

average view duration: [#]

retention drop points: [timestamps] Generate:

3 hypotheses for why viewers drop

3 title variants to test (each with a different promise framing)

3 thumbnail concepts to test (each with a different visual contrast)

One script edit recommendation for the first 30 seconds Keep it practical, no generic advice.

Turn a Good Prompt Into a Watchable AI Video: The Anti-Generic Prompt Rewrite

This is the part most “viral prompt” articles skip: turning words into something you’d actually watch. Prompting for generative image/video models is basically a new form of creative direction—you’re using the communication skills you already have, just with clearer, more literal instructions so the model can follow your vision.

1) Start with the two things that actually control watchability

A watchable clip needs:

• Visual description: subject, environment, lighting, style
• Motion description: subject action, camera motion, timing/speed

Runway’s Text-to-Video guide is explicit that strong prompts describe what appears in the frame and how those elements move, using direct language.

Bad (vibes-only):

“Cinematic coffee shop, cool mood, make it dynamic.”

Better (watchable + controllable):

“Medium shot of a busy café. A barista steams milk while a tired customer taps their phone. Warm morning light. Slow handheld push-in. Natural camera shake. 9:16, 10 seconds.”

Notice what changed: the prompt now gives the model a job it can execute—frame + action + motion + format.

2) Use a simple structure so you can edit one piece without breaking the whole prompt

You don’t need a strict formula, but an organization method makes iteration faster. Runway suggests a beginner-friendly structure like: [Camera] shot of [subject] [action] in [environment], then add supporting details.

Here’s a clean template you can paste into your blog:

[Camera] shot of [subject] [action] in [environment].

Visual: lighting, composition/framing, style/aesthetic.

Motion: subject movement + camera movement + speed/timing.

Output: duration, aspect ratio, resolution.

3) Iterate on purpose: simple first, detail second

A lot of creators get stuck because they try to “one-shot” the perfect prompt. Runway recommends embracing iteration: generate, review, then clarify what was missing—like drafting any creative work.

A practical iteration loop:

• Iteration 1: nail the subject + main action
• Iteration 2: add camera angle + environment
• Iteration 3: add motion style/timing + lighting + output constraints

Also important: detailed prompts aren’t automatically better—simple prompts help exploration; detailed prompts help consistency.

4) Add “beat timing” when you care about retention

If you want retention, prompt the sequence, not just the scene. Runway calls this timestamp prompting—you specify when actions should happen to guide timing and order (not perfectly precise, but it steers the result).

Use it for Shorts-style pacing:

5) Don’t forget captions: they’re part of “watchable”

Even a great clip loses people if viewers can’t follow it on mute. YouTube Studio lets you add subtitles/captions and upload caption files (or edit timing/text later). If you want the official workflow, follow YouTube’s guide to create subtitles & captions in YouTube Studio.

If you’re trying to move faster, a tool like GStory Subtitle Generator can auto-generate captions you can tweak and export (e.g., SRT/VTT) before uploading to YouTube—useful when you’re iterating titles, hooks, and pacing and don’t want captions to be the bottleneck.

FAQ

Can an AI prompt actually make a YouTube video go viral?

It can help you produce more testable versions faster—hooks, scripts, title variations—but it can’t guarantee virality. “Viral” is a result of packaging + retention + audience fit. What AI can do reliably is reduce your iteration time, which increases the number of good experiments you can run.

Why do my AI scripts sound the same every time?

Because your input is too broad and the model fills gaps with safe defaults. Communities that share “hook prompts” often describe them as good starting points—but still something you refine and personalize.

Fix it by adding:

• a specific viewer problem (who + what’s failing + what they tried)
• a payoff promise (what changes if they keep watching)
• tone constraints (short sentences, no greetings, no filler)

What’s the best AI prompt for YouTube Shorts?

The best Shorts prompt forces timing and compression:

• hook in 0–2 seconds
• first payoff beat by ~10 seconds
• one idea per line
  Then add a simple motion plan for visuals. If you’re generating video with a model, remember: effective text-to-video prompts describe what’s in frame and how it moves.

How do I prompt for retention, not just views?

Prompt for structure, not inspiration:

• specify the open loop (what you’ll reveal)
• specify the payoff moment (when the viewer “wins”)
• specify attention resets (pattern change every ~20–30 seconds in long-form)
  For AI video generation, use timestamp prompting to guide sequence and pacing.

What should I include to avoid “generic AI” tone?

Use constraints that force human rhythm:

• “No greetings. No ‘in this video.’ No filler.”
• “8th-grade reading level. Short sentences.”
• “Use one concrete example per section.”
• “Write like a creator talking to one friend.”
  And iterate: prompting is a conversation—generate, review, then clarify the missing piece.