Example Inputs
Length
12 minutes
Topic
How creators can build a simple sponsorship system
Viewer
Mid-size YouTubers with growing inbound interest
Build a structured long-form video outline with sections, pacing, proof points, and examples.
This prompt helps you move from a rough idea to a fuller outline with a clearer narrative arc. It is especially useful for educational, commentary, or strategy videos that need stronger pacing and section logic.
Copy-And-Paste Prompt
Works well in ChatGPT, Claude, Gemini. Replace any bracketed variables before you run it.
Variables to customize
Act as a YouTube content strategist building long-form outlines. Your task is to create a detailed YouTube outline for a long-form video using the topic, audience, promise, and desired pacing. Use these inputs when available: - [Video Topic] - [Target Viewer] - [Main Promise or Thesis] - [Desired Video Length] - [Any Stories, Examples, or Proof Points to Include] Requirements: - Structure the video for clarity and pacing. - Include sections that naturally maintain interest. - Call out where examples, proof, or visuals should appear. - Avoid repetitive filler sections. Return the answer in this format: 1. Video outline with section-by-section beats 2. Suggested pacing notes 3. Ideas for visuals or inserts that strengthen each section Tone and style: structured and creator-savvy Ask me concise follow-up questions only if a missing detail would materially change the quality of the final answer.
Length
12 minutes
Topic
How creators can build a simple sponsorship system
Viewer
Mid-size YouTubers with growing inbound interest
Section 1: Why sponsorship chaos starts earlier than creators expect. Section 2: The minimum viable workflow for inbound and outbound deals. Section 3: Rate setting, deliverables, and negotiation guardrails.
This is a mock example only. Your result should change based on the variables, context, and constraints you provide.
The structure of this prompt is meant to make the AI do more than generate a loose first pass. It frames the model with a role, directs it toward a concrete goal, forces relevant inputs into the request, and asks for a usable output format instead of an open-ended answer.
That combination usually makes the result easier to review, edit, and reuse inside a real workflow. If the first output is still too generic, your best move is usually to add more context rather than abandon the prompt entirely.
These related calculators and guides add more depth when you want to connect this youtube prompt to real numbers, strategy, or supporting tools.
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Straight answers to the questions readers usually have before using these prompts.
Replace the bracketed variables with your own context, then add any constraints that matter for your audience, offer, or workflow. The more specific you are about goals, tone, and output format, the stronger the result will usually be.
Yes. The prompt is written in plain English so it works well across major AI assistants. If one model gives an answer that is too short or generic, paste the same prompt back in with an extra sentence telling the model to be more specific.