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AI Prompts for Executives
Executive work is a handful of high-stakes artifacts — the big decision, the board update, the hiring bar, the operating review, the competitive read. A language model won't make the call, but with the right structure it pressure-tests your thinking, names the downside consensus is hiding, and drafts the honest version of a mixed quarter. These prompts are built to structure judgment, not replace it. Paste them into ChatGPT, Claude, Copilot, or Gemini — the analysis is a scaffold; the judgment stays yours.
3 free prompts you can run right now
Decision stress-test: pre-mortem, base rates, and pre-committed tripwires
A big call is hardening into consensus. Stress-test it with the advisor who is paid to disagree — before the money moves.
You are a skeptical board advisor whose job is to disagree with me productively. I will describe a strategic decision, my rationale, and my data. Produce: A) STEEL-MAN TABLE — my 3 strongest stated reasons, each with the strongest honest counter-argument and the evidence that would settle the disagreement. B) PRE-MORTEM — it is 18 months later and this decision failed: the top 5 causes ranked by likelihood times damage, each with its earliest observable warning indicator. C) BASE RATES — the reference class this decision belongs to and what typically happens in it, explicitly labeled "from general knowledge — verify current figures before relying on this". D) VERDICT — proceed / proceed-with-tripwires / pause, with 3 tripwires (metric + threshold + the pre-committed action when hit). Inputs: [THE DECISION + DEADLINE] · [MY RATIONALE + KEY DATA] · [ALTERNATIVES I CONSIDERED] · [WHAT WOULD MAKE ME WRONG] Rules: Do not invent market data or figures — keep my facts separate from your general knowledge and flag every external claim for verification against current sources. Do not soften the counter-arguments to be agreeable. I will not paste material non-public information or personnel records, and you must not ask for them.
Pre-mortem: assume the decision failed, then work backward to why
You're about to make a big call and everyone's nodding. Run a pre-mortem that surfaces the failure modes optimism is hiding.
You are a decision advisor running a pre-mortem — a thinking aid; the judgment stays yours. Produce: A) FAILURE SCENARIO — assume it's 18 months later and this decision failed badly; write the two-paragraph story of how, grounded in the real risks I described. B) FAILURE MODES — the top 5 specific causes from that story, each rated on likelihood and how early we'd see it coming. C) EARLY WARNINGS — for the top 3 modes, the concrete leading indicator to watch and the pre-committed action if it trips. D) REVERSIBILITY — an honest read on how reversible this decision is and the cheapest way to preserve optionality. Inputs: [THE DECISION] · [WHY WE'RE LEANING YES] · [KNOWN RISKS] · [WHAT'S AT STAKE / TIMELINE] Rules: Do not invent facts or manufacture false risks — build only from what I described, and separate plausible risks from remote ones. This structures the downside; the decision and the judgment stay yours. Verify anything uncertain against the source before relying on it; keep confidential and identifying data out of consumer AI tools.
Board memo: the pre-read that kills surprises
Board meeting in two weeks. Draft the pre-read that surfaces the hard topic on your terms — before a director does it on theirs.
You are a chief of staff drafting a board pre-read memo. I will paste the quarter's numbers and the situation. Produce: A) MEMO SKELETON — a headline paragraph (state of the business in 5 sentences, no adjective without a number behind it), a KPI table vs plan with variance explanations that state causes rather than describe gaps, a hard-topic section (what happened, impact, what we are doing, what we need), and the asks of the board. B) QUESTION ANTICIPATION — the 10 hardest questions a director could ask, each with a crisp 3-sentence answer, flagging which answers need pre-verified data. C) TONE CHECK — flag every instance of hedging, spin, or unexplained jargon in my draft sections. Inputs: [PASTE KPI DATA VS PLAN] · [THE HARD TOPIC + FACTS] · [LAST MEETING'S OPEN ITEMS] · [MY DRAFT SECTIONS, IF ANY] Rules: Do not invent numbers or variance explanations — every explanation must come from my inputs or be marked "CFO to confirm". Verify all figures against the finance system before circulation. Never include material non-public information handling guidance or individual compensation data.
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Board narrative: the story your metrics tell, good news and bad
The board deck is due and the numbers are mixed. Build a narrative that's honest about the misses and clear on the plan.
You are a CEO advisor drafting the narrative spine of a board update — a drafting aid; the message is yours. Produce: A) HEADLINE — the one honest s
Org design review: structure follows strategy, with a migration plan
The org chart grew by accretion and the strategy changed. Review structure against strategy before the next planning cycle locks it in.
You are an organizational-design advisor. I will describe our strategy, current structure, and observed pain. Produce: A) STRESS POINTS — a table of
Role scorecard: define the job before you write the job post
You're about to hire and the role is fuzzy. Define outcomes and competencies first, so you hire for the job, not a resume.
You are an org-design advisor drafting a role scorecard — a drafting aid; the hiring judgment stays yours. Produce: A) MISSION — one sentence on why
Operating cadence audit: fewer meetings, real decision velocity
The calendar is full and decisions still take three weeks. Audit the operating rhythm — meetings, metrics, decision rights — end to end.
You are an operating-system designer for executive teams. I will describe our current rhythm. Produce: A) CADENCE MAP — a table of every recurring fo
Operating review: the meeting that catches a slipping goal in week 3, not month 3
Your operating reviews are status theater. Redesign the cadence so a slipping metric gets caught and acted on early.
You are an operations advisor designing an operating-review cadence — a design aid; the calls stay yours. Produce: A) METRIC SET — the 5-7 metrics t
Competitive scan brief: signal-ranked moves and the response option set
Quarterly strategy review. Turn scattered competitor news into a ranked read on what actually threatens you — with response options costed.
You are a competitive-intelligence analyst preparing an executive brief. I will paste the raw signals I have collected. Produce: A) SIGNAL TABLE — fo
Competitive teardown: what a rival's moves reveal about their strategy
A competitor made a move and the team is reacting emotionally. Get a cold read on what it signals and whether it changes your plan.
You are a market-strategy advisor doing a competitive teardown — an analysis aid whose inferences I will pressure-test. Produce: A) MOVE READ — what
Frequently asked
Can AI actually help with executive decisions?
Not by making them — by structuring them. The strongest use is a pre-mortem: assume the decision failed, work backward to the causes, and convert them into leading indicators you watch. It surfaces the downside optimism and consensus suppress. The model organizes the risk; the call, and the accountability for it, stay entirely with you.
How do CEOs and founders use ChatGPT for board prep?
To draft the honest narrative spine faster. Paste your metrics-vs-plan and have the model name the real reason for each miss (no euphemisms) and tie last quarter's commitments to this quarter's results, so the story stays consistent over time. It drafts; you verify every number. Keep confidential financials out of consumer AI tools.
Which AI model is best for strategy work?
They're model-agnostic — ChatGPT, Claude, Copilot, and Gemini all work. A larger context window helps when you paste a full board deck or a stack of competitive intel. What matters more than the model is the prompt structure and separating observation from inference so you act on evidence, not projection.
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