---
name: ai-powered-linkedin-video-insights-post-generator
description: >-
  A LinkedIn post that pulls the key points from a video transcript and ends with a question to start discussion. Adapted from Daniel Disney.
  Task type: Create. Built for Sales.
  Use when the request sounds like "LinkedIn Post from a Video".
  Do NOT use it to invent numbers, customer names, or quotes that were not supplied.
license: MIT
metadata:
  author: The Revenue AI Report
  suite: Meetings and Follow Up
  version: "1.0"
  source: https://www.therevenueaireport.com/prompts/ai-powered-linkedin-video-insights-post-generator
---

# LinkedIn Post from a Video

A LinkedIn post that pulls the key points from a video transcript and ends with a question to start discussion. Adapted from Daniel Disney.

One job only: a LinkedIn post that pulls the key points from a video transcript and ends with a question to start discussion. Anything outside that job belongs in another file in the Meetings and Follow Up suite.

## When to use this skill

- The request matches the job above and the work repeats often enough to be worth a standard.
- You have, or can ask for, the inputs listed below.
- A person will review the output before it reaches a customer, an executive, or a board deck.

## When not to use it

- The answer needs a number, a benchmark, or a quote nobody supplied. Ask for it instead of producing one.
- The task is a different job in the same suite. Open that file rather than stretching this one.
- The output would be sent, published, or written into a system without a human read.

## Inputs to collect first

- video transcript
- intro

Ask for anything missing before running. Do not fill a gap with a plausible guess.

## Process

1. Confirm the job, the audience, and the decision the output feeds.
2. Collect the inputs above. Name anything still missing out loud.
3. Run the instruction block below exactly as written, with the placeholders replaced.
4. Separate what came from the supplied inputs from what is your inference. Label the inference.
5. Hand back the output plus a short list of open questions and assumptions.

## Instruction block

Run this text with the placeholders filled in.

```text
Your task is to write an engaging LinkedIn post that highlights some of the key points raised in a video and includes an engaging question at the end to drive engagement. Here are the steps to follow:

1. Read the provided video transcript carefully:
<Video Transcript>
{$VIDEO_TRANSCRIPT}
</Video Transcript>

2. Begin your LinkedIn post with an introductory paragraph explaining the purpose and context of the post. For example:
<intro>
In this LinkedIn post, I want to share some insights from a recent video on [topic/theme of the video]. The video raises some thought-provoking points about [brief 1-2 sentence summary of the main idea/message]. I believe these ideas are valuable for professionals in [relevant fields/industries] to consider.
</intro>

3. Summarize the key points or ideas discussed in the video transcript. Focus on the most important or impactful messages. Aim for 2-4 concise bullet points or short paragraphs highlighting these key takeaways.

4. After summarizing the key points, include an engaging question that encourages readers to share their thoughts, experiences or perspectives related to the topic. The question should be open-ended and thought-provoking.

5. Format your LinkedIn post according to the following guidelines:
- Total character count: 2500 characters maximum
- Structure:
 <LinkedIn Post>
 [Introductory paragraph from step 2]
 
 [Key point summaries from step 3]
 
 [Engaging question from step 4]
 </LinkedIn Post>

6. Review your post to ensure it is clear, concise and engaging. Make any necessary revisions before providing your final response.

Write your LinkedIn post inside <LinkedIn Post> </LinkedIn Post> tags.
```

## Decision rules

- Supplied evidence beats inference. If the two disagree, say so and keep the evidence.
- Unknown is a valid answer. Write "unknown" rather than estimating.
- Keep one recommendation per output. If the evidence supports two, present both and name the deciding input you do not have.
- Match the reading level of a working operator. Short sentences. Explain any term the reader may not use daily.

## Quality checks

- Every number, name, date, and quote traces to an input the user supplied.
- No vendor claim is repeated as fact without naming the source.
- Assumptions are listed separately from findings.
- The output answers the original request and nothing else.
- A reviewer could re-run this file with the same inputs and get the same shape of answer.

## Guardrails

- Do not send email, change CRM records, post publicly, or share data outside the workspace.
- Do not invent benchmarks, adoption rates, win rates, or customer references.
- Flag anything that needs a human decision instead of deciding it.

## Source

- Prompt page: https://www.therevenueaireport.com/prompts/ai-powered-linkedin-video-insights-post-generator
- Suite: https://www.therevenueaireport.com/agent-skills/suites/meetings-and-follow-up
- Publication: The Revenue AI Report, https://www.therevenueaireport.com