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Problem StructuringFREE

Hypothesis tree: break a fuzzy client question into testable branches

The client asked something huge and vague. Turn it into a MECE tree of hypotheses you can actually test this week.

The prompt — copy and run it

You are a strategy consultant structuring an ambiguous client question into a testable hypothesis tree — a thinking aid, not a conclusion.

Produce:

A) CORE QUESTION — the single decision the client actually needs to make, stated in one sentence.

B) HYPOTHESIS TREE — a MECE breakdown into 3-4 branches, each a falsifiable hypothesis (not a topic), and under each the 1-2 sub-hypotheses that would prove or kill it.

C) TEST PLAN — for each leaf hypothesis, the specific analysis or data that would confirm or refute it, and roughly how hard it is to get.

D) FIRST CUT — which 2 branches to test first for the fastest read on the answer, and why.

Inputs: [CLIENT QUESTION] · [WHAT WE ALREADY KNOW] · [DATA / ACCESS AVAILABLE] · [DEADLINE]

Rules: Keep branches genuinely mutually exclusive and collectively exhaustive — flag any overlap. Do not assert conclusions; these are hypotheses to test. Keep confidential client data out of consumer AI tools. The structure is a scaffold; the analysis and judgment stay yours. Do not invent facts, numbers, or details you weren't given; verify anything uncertain against the source before relying on it.

Why this prompt works

Weak engagements boil the ocean because the question was never decomposed; forcing falsifiable hypotheses (not topics) into a MECE tree with an explicit test per leaf converts a vague ask into a prioritized work plan — and the overlap flag catches the double-counting that quietly wrecks a supposedly MECE structure.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

The client asked something huge and vague. Turn it into a MECE tree of hypotheses you can actually test this week.

Why does this prompt work?

Weak engagements boil the ocean because the question was never decomposed; forcing falsifiable hypotheses (not topics) into a MECE tree with an explicit test per leaf converts a vague ask into a prioritized work plan — and the overlap flag catches the double-counting that quietly wrecks a supposedly MECE structure.

What mistake does this prompt help you avoid?

{'code': 'PF02', 'note': 'Boiling-the-ocean scoping — a falsifiable, overlap-checked MECE tree with a per-leaf test plan forces prioritization before analysis begins.'}

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.