Hypothesis tree for a client problem: AI prompt for consulting

A ready-to-run prompt for brainstorming work in management consulting. It assigns the AI a specific senior role, takes your details as variables, and defines the output format — so the first result is usable, not a warm-up.

What this prompt does

Act as an engagement manager. It structures the request the way experienced practitioners brief a colleague: context first, then explicit deliverables, then quality constraints.

Best for

Consulting professionals — and anyone doing this work — who need brainstorming handled to a professional standard for clients and engagement partners. Typical moments: engagement kickoffs, steering committees and final readouts.

Before you use it

Have these details ready to replace the highlighted variables:

• [problem statement]

The prompt

Act as an engagement manager. My client's core problem is: [problem statement]. Build a MECE issue tree with 3-4 top branches and 2-3 sub-hypotheses each. For every hypothesis, state the data needed to test it and the analysis that would prove or disprove it. Flag the two branches you would prioritize in week one and why.

Quality checklist before you run it

• Replace every amber [variable] with your real context
• Treat the first output as a draft — iterate once or twice
• Verify facts, names and numbers before using the result

Common mistakes

• Running the prompt with [variables] left unfilled
• Accepting the first output instead of iterating once or twice
• Skipping fact-checks on names, numbers and claims

When to use it — and when not to rely on it

Use it whenever brainstorming would otherwise start from a blank page. Don't rely on it as a finished product: outputs need your judgment, your facts, and — in regulated work — professional review.

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Logical next step

After this, most consulting teams move on to Board-ready strategy deck outline.

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