Ops Deck Outline · 7 Slides to Decide 1 Thing
Outline an ops topic into 7 slides — peak slide first, then Keynote. Avoid 20-slide empty decks.
Pain addressed · Ops opens Keynote and starts stacking slides. The real work — 'what one thing am I saying + which slide is the peak' — never happens, and the deck drags you along.
Ops Deck Outline · 7 Slides to Decide 1 Thing
You're my deck outline partner. I'm an ops lead presenting a 7-10 slide deck to my manager / cross-functional team.
# Topic
- Title (≤ 15 words): {deck_title}
- Audience: {audience} (manager / CMO / cross-functional / all-hands)
- Duration: {duration} (5 / 10 / 20 min)
- The one action I want them to take after this: {one_action}
- Materials I have (data / cases / takes): {materials}
# Output the outline
## 1. Deck thesis in one sentence (30 words)
The one sentence the audience must leave with. Not a title, not a description — judgment + number + action.
## 2. 7-10 slide outline (60 words per slide)
Each slide:
- Slide title (a conclusion sentence, not a topic)
- 3-5 bullets (≤ 12 words each)
- One "if you only remember one thing" line
- Note: is this slide context / data / judgment / action / Q&A primer?
## 3. Peak slide mark (20 words)
Name which slide is the peak — the one where the audience first goes "ohh". Every other slide serves this one.
## 4. Cut list (40 words)
3 things I might want to include but should cut. e.g. "product story background" / "last-Q detail data".
## 5. Q&A pre-draft (3 items, 30 words each)
The 3 most likely audience questions + one-line answer direction.
# Boundaries
- 7-10 slides max. More = you haven't decided.
- Every slide title is a conclusion sentence, not "Q3 data" topic title.
- Exactly one peak slide. Multiple peaks = none.Open directly on your favourite AI
One click copies the prompt and opens the platform in a new tab — just paste (⌘/Ctrl + V). Recommended platforms are ordered by content fit.
Workflow · 5 steps
- 1
T-24h before presenting: dump topic, audience, duration, the one action you want them to take, and the materials you have.
- 2
Run in Claude (strongest at structured outline). Fill the 5 placeholders.
- 3
Audit the deck thesis sentence. If it's not judgment + number + action, push back for specifics.
- 4
The cut list is gold — the model surfaces what you'd be reluctant to cut yourself. Add 1-2 more cuts of your own.
- 5
Open Keynote with the outline in hand. Write title + 3 bullets per slide. Don't open a template first — it'll drag you back to template-think.
Verify before you ship
AI's "almost right" is the #1 pain. Tick these off so reviewers can't find the obvious holes. (Checkbox state stays local — we don't track it.)
Why this prompt works
This prompt isn't a generic “write me a Slide Deck Outline”. It folds in the concrete context a Operations & Content actually faces (target reader, info density, deliverable format). LLMs deliver an order-of-magnitude better answer when they get role × scenario × constraints together — they can make the right tradeoffs about what to spotlight and what to cut.
When to use
Best moment: you know roughly that you need to do a Slide Deck Outline, but you're stuck on “how do I even ask the AI?” Muscle memory has no template. Copy this card, tweak 2-3 fields per the workflow, and get a first revisable draft in 30 seconds.
Common pitfalls
- Send without tweaking placeholders · the draft reads as default-GPT and your reviewer spots it in 3 seconds.
- Skip the verify checklist · “almost right” failures usually hide in a thing you assumed the model handled but it didn't.
- Stop after the first answer · a single follow-up like “make section X tighter / more formal” usually pushes a 70 → 90.
Variants & extensions
Want to use this card more aggressively? Three extensions:
- Swap languages: both EN/ZH prompts ship in the card — use the EN version when shipping to a Western audience.
- Swap platforms: the same prompt has slightly different taste on ChatGPT / Claude / Kimi. The recommended-platform pill marks the best fit.
- Stack the checklist: paste the verify checklist back into the chat and ask the AI to self-audit — error rate drops sharply.
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