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Issue tree builder: from vague client ask to testable hypotheses

New engagement, vague problem statement. Build the issue tree and the week-one analysis plan before the team burns days boiling the ocean.

The prompt — copy and run it

You are an engagement manager structuring a new client problem. I will paste the raw ask and context. Produce:

A) PROBLEM STATEMENT — restate the ask as one specific, measurable, time-bound question, using the client's own words where possible. List what the question deliberately excludes.

B) ISSUE TREE — 3 levels, MECE at each level, every branch phrased as a testable hypothesis (not a topic). Present as a table: hypothesis, data needed to prove or kill it, likely source, effort (S/M/L).

C) WEEK-ONE PLAN — the 5 analyses ranked by kill-power: which would change the overall answer fastest if the hypothesis fails.

Inputs: [PASTE CLIENT ASK / RFP EXCERPT / KICKOFF NOTES] · [INDUSTRY + CLIENT CONTEXT] · [ENGAGEMENT LENGTH + TEAM SIZE]

Rules: Do not invent client facts or market numbers — mark every assumption as an assumption and keep them in a separate list. Verify data availability with the client before committing the plan. Never include client-confidential material beyond what I pasted, and anonymize the client in your output.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Fill in your inputs. Replace each bracketed placeholder with your specifics: [PASTE CLIENT ASK / RFP EXCERPT / KICKOFF NOTES][INDUSTRY + CLIENT CONTEXT][ENGAGEMENT LENGTH + TEAM SIZE]
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

An issue tree is only useful if the branches are testable — 'understand the market' is a topic, not a hypothesis. Ranking week one by kill-power operationalizes the 80-20 rule: you spend the first week on analyses that could change the answer, not the ones easiest to start.

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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?

New engagement, vague problem statement. Build the issue tree and the week-one analysis plan before the team burns days boiling the ocean.

Why does this prompt work?

An issue tree is only useful if the branches are testable — 'understand the market' is a topic, not a hypothesis. Ranking week one by kill-power operationalizes the 80-20 rule: you spend the first week on analyses that could change the answer, not the ones easiest to start.

What mistake does this prompt help you avoid?

Boiling the ocean in week one — branches must be testable hypotheses and analyses get ranked by kill-power, not by ease of starting.

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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.