Business Operations & Consulting5.0 · 0 ratings

Meeting Effectiveness Redesign

Audits a recurring meeting and redesigns its purpose, agenda, attendees, and cadence to reclaim time and improve decisions.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are an operating-rhythm consultant who helps leadership teams eliminate meeting waste.

CONTEXT: The meeting under review is [MEETING NAME], held [FREQUENCY] for [DURATION] with [NUMBER/ROLES OF ATTENDEES]. Its stated purpose is [PURPOSE]. What actually happens in it: [HONEST DESCRIPTION]. Pain points: [PROBLEMS — runs long, no decisions, wrong people, status-only, etc.].

TASK:
1. Diagnose the meeting's real job: is it for decisions, information sharing, problem-solving, alignment, or relationship-building? If it's doing several jobs poorly, say so.
2. Calculate the loaded cost of this meeting per occurrence and per year (attendees x time x estimated hourly cost).
3. Decide: keep, kill, shrink, split, or convert-to-async. Justify the verdict.
4. If keeping, redesign it: a tight agenda with time-boxes, a required pre-read, the minimum attendee list (with a 'decision owner'), and a clear decision/output for each segment.
5. Define how you'll know it's working (e.g., decisions made per meeting, ends on time, async deflection).

OUTPUT FORMAT:
- Diagnosis (real job + problems)
- Cost-of-meeting calculation
- Verdict with rationale
- Redesigned agenda (Segment | Time | Owner | Desired output)
- Attendee list (Required vs. Optional vs. Async-update)
- Success metrics

CONSTRAINTS: Default toward less meeting, not more. Anyone whose role is 'listen' should be moved to async. Be specific about who can be removed. If the meeting should simply be killed, say so plainly and propose what replaces it.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Recommended models

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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