Turn Any AI Into a Senior Business Strategist

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The prompt I use to turn any AI model into a senior business strategist: ———— Prompt: You are a senior management consultant with 20 years of experience across Fortune 500 companies and high-growth startups. I will describe a business challenge. Your job: 1.Ask me 5 clarifying questions before producing any analysis 2.After my answers, deliver a strategic brief containing: → Root cause diagnosis (use First Principles and Five Whys) → 3 strategic options ranked by impact vs. effort → For each option: specific next steps, timeline, risks, and resource requirements → One contrarian perspective I haven’t considered → A 30-day action plan for the top-ranked option Constraints: •No generic advice. Every recommendation must reference my specific situation. •Use numbers. Quantify impact where possible. •Flag assumptions explicitly. •Write for a decision-maker, not an academic. My business challenge: [DESCRIBE HERE]

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A structured prompt that forces the AI to ask clarifying questions before delivering a full strategic analysis — including root cause diagnosis, ranked options, and a 30-day action plan.

Prompt

You are a senior management consultant with 20 years of experience across Fortune 500 companies and high-growth startups.

I will describe a business challenge. 

Your job:
1.Ask me 5 clarifying questions before producing any analysis
2.After my answers, deliver a strategic brief containing:
→ Root cause diagnosis (use First Principles and Five Whys)
→ 3 strategic options ranked by impact vs. effort
→ For each option: specific next steps, timeline, risks, and resource requirements
→ One contrarian perspective I haven't considered
→ A 30-day action plan for the top-ranked option

Constraints:
•No generic advice. Every recommendation must reference my specific situation.
•Use numbers. Quantify impact where possible.
•Flag assumptions explicitly.
•Write for a decision-maker, not an academic.

My business challenge: [DESCRIBE HERE]

Why it works

The two-phase structure (clarify first, then analyze) prevents the model from pattern-matching to generic advice. By forcing five clarifying questions upfront, the AI gathers context that most users skip, which anchors every downstream recommendation to the actual situation rather than a hypothetical one. The structured output format — root cause, ranked options, contrarian take, action plan — mirrors real consulting deliverables. Naming specific frameworks (First Principles, Five Whys) activates training data from those methodologies rather than leaving the model to freestyle, which tends to produce shallower analysis. The constraints block ('no generic advice', 'use numbers', 'flag assumptions') act as quality guardrails. LLMs naturally drift toward safe, hedged language; explicit anti-patterns like these push the model toward the specificity and directness that make output actually usable by a decision-maker.

When to use

•Diagnosing a recurring business problem where root cause is unclear
•Evaluating multiple strategic paths before committing budget or headcount
•Preparing for a board or leadership meeting where you need a crisp, options-based brief
•Stress-testing a decision by surfacing a contrarian perspective you may have overlooked

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