ThinkWithPrompt by SynotticThinkWithPrompt

Write an all-hands meeting script with honest results and Q&A prep

A spoken all-hands script that covers results, hard news, and priorities, plus a prepared Q&A list.

Presentations & Public SpeakingFew-ShotStandardMeetingsWritingProductivityWrite

The prompt

Write a script for the all-hands meeting I'm leading. Company size and format: [e.g. "120 people, hybrid, 30 minutes plus Q&A"] Results since the last all-hands: [KEY NUMBERS vs. plan, wins, misses] Hard news people need to hear: [e.g. "missed revenue target", "hiring freeze", "a leader leaving", or "none"] What I want people to focus on next: [2-3 PRIORITIES] People or teams to recognize: [NAMES and what they did, specifically] Rumors or worries I know are circulating: [WHAT people are saying] Structure: 1. Opening (under 1 minute): one honest sentence on where we stand. 2. Results: plain numbers vs. plan, including misses. No spin. 3. Hard news: what happened, why, what it means for people, and what we're doing. Say it early, not buried at the end. 4. Priorities: what matters most for the next quarter and what we're deliberately not doing. 5. Recognition: specific, tied to the priorities. 6. Close: what I'm asking of everyone. Rules: - Write for speaking: short sentences, natural pauses, no jargon or slide-speak. - Mark every number I haven't given you as [CONFIRM]. - Don't promise what I can't guarantee (e.g. "no more layoffs"). Return: - The script with timings per section. - The 10 toughest questions employees are likely to ask (anonymous Q&A included), each with a candid 2-3 sentence answer, and where I should say "I don't know yet, here's when I will."

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • e.g. "120 people, hybrid, 30 minutes plus Q&A"
  • KEY NUMBERS vs. plan, wins, misses
  • NAMES and what they did, specifically
  • WHAT people are saying
  • CONFIRM

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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