A step-by-step way to work
Dump your thinking first
Give AI your full, unstructured update — everything you know and recommend.
Ask it to lead with the answer
Have it restructure into answer-first order: the recommendation/headline up top, support below.
Compress hard
Ask it to halve the length without losing the decision or the ask.
Make the ask explicit
Have it surface the specific decision you need, if it's buried.
Re-insert your conviction
Make sure the recommendation reads as your considered view, not a hedge.
Real prompts, and what good output looks like
Restructure this into an answer-first exec briefing: 'We've been looking into the churn issue for a few weeks. The data team pulled some numbers, and we ran a few interviews. There are a couple of theories. We think it might be onboarding but also possibly pricing. We'd like to maybe try some experiments...'
Headline: We recommend fixing onboarding first to address churn — and need sign-off to run a 4-week test.
Why: Churn is concentrated in users who never complete onboarding; pricing is a secondary factor with weaker evidence.
Ask: Approve prioritising the onboarding experiment this cycle.
Detail (on request): methodology, the pricing signal, timeline.
I led with the decision and the ask; the hedging ('maybe', 'a couple of theories') is gone — confirm the firmer claims match your actual confidence.
A prompt you can reuse
Fill in the highlighted parts and paste it into your AI tool of choice. Edit the output — it's a starting point, not a finished answer.
Restructure my update into an answer-first executive briefing. Don't overstate my confidence. My full thinking (unstructured): [paste everything — findings, options, your view, the ask] Audience & time: [who, and how long they'll give it] Please: 1. Lead with the headline recommendation/answer. 2. Then the 2–3 reasons that matter, then the specific ask/decision needed. 3. Push supporting detail to a 'detail on request' section. 4. Halve the length. Flag anywhere you firmed up a hedge so I can confirm I actually hold that view.
What AI gets wrong here
Confidence inflation
Compressing nuance can turn your 'maybe' into a definitive claim you don't hold.
Fluent but hollow
AI can produce a polished briefing with no real substance underneath.
Generic exec-speak
AI defaults to corporate phrasing that says little.
AI is genuinely good at the form of an executive briefing — answer-first, compressed, explicit ask. But executives are paying for your judgment, not your formatting, and they can feel the difference between a packaged view and a held one. Use AI to lead with the answer; make sure the answer is actually yours.