Run meetings with agendas and action minutes
A purposeful agenda before the meeting and clean decisions/actions minutes after.
This is a practical, copy-paste process for recurring meetings drift.. Use it when you want a clear structure, then add your own details and the linked evidence.
Published by Deepstory Research. Reviewed Sep 2026.
How to use this method
- 1. Copy or downloadCopy the prompt below, or download the method file and attach it to your chat.
- 2. Paste into any AIChatGPT, Claude, Gemini or Copilot. Replace each [PLACEHOLDER] with your details, or let the AI ask you.
- 3. Add evidenceAttach the evidence files listed on this page so the AI works from sourced numbers, not guesses.
The prompt
Paste it as-is. The AI will ask for anything still in [BRACKETS].
# Run meetings with agendas and action minutes Method by Deepstory Research: deepstoryresearch.com/method/meeting-agenda-and-minutes You are an executive assistant who runs effective meetings. Follow the method below step by step. Goal: A purposeful agenda before the meeting and clean decisions/actions minutes after. ## My inputs - Meeting purpose: [MEETING_PURPOSE] (example: quarterly supplier review) - Attendees: [ATTENDEES] (example: roles) - Transcript or notes (after): [TRANSCRIPT_OR_NOTES_AFTER] (example: paste) Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source. ## Steps to follow 1. Before: write objective, agenda with time boxes and pre-reads. 2. After: extract decisions, actions (owner, due date) and open questions. 3. Draft the follow-up message. ## Deliver the output in this structure - Agenda - Minutes: decisions, actions, open questions - Follow-up message ## Quality rules - Every action has one owner and a date. - Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION. - If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED]. - End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.
What you need to give the AI
| Input | Placeholder | Example |
|---|---|---|
| Meeting purpose | [MEETING_PURPOSE] | quarterly supplier review |
| Attendees | [ATTENDEES] | roles |
| Transcript or notes (after) | [TRANSCRIPT_OR_NOTES_AFTER] | paste |
Use it when
- Recurring meetings drift.
- You have a raw transcript to turn into actions.
What you get
- Agenda
- Minutes: decisions, actions, open questions
- Follow-up message
The procedure, step by step
Read this before you run it, so you can check the AI actually followed the method.
Before: write objective, agenda with time boxes and pre-reads.
After: extract decisions, actions (owner, due date) and open questions.
Draft the follow-up message.
Quality checks built into the prompt
- • Every action has one owner and a date.
- • Every number labelled FACT, ESTIMATE or ASSUMPTION; claims outside attached evidence tagged [UNVERIFIED].
Evidence to use with this method
Methods tell the AI how to think. Evidence gives it sourced numbers to think with. Download a context file and attach it with the prompt.
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A common-country, common-period baseline for real growth, inflation, modeled unemployment and trade exposure across the United States, China, India, Germany, the United Kingdom and Japan.
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Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment decisions need a qualified professional.