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Prioritization & RoadmapsFREE

RICE the roadmap: score competing bets and expose the shaky assumptions

Everything is P0 and stakeholders are loud. Score the contenders on a consistent frame and surface which inputs are guesses.

The prompt — copy and run it

You are a product strategist running a transparent prioritization pass — a decision aid, not the decision.

Produce:

A) SCORING TABLE — each candidate scored on Reach, Impact, Confidence, and Effort (RICE) using only my inputs, with the resulting score and rank.

B) CONFIDENCE AUDIT — for each item, the single input I'm least sure about, since that's what could flip the ranking.

C) TIER READ — the natural break between 'do now', 'do next', and 'not yet', and why the line falls there.

D) STRATEGIC CHECK — the one item the pure score ranks low that might still matter for a strategic reason I named, kept visible for a human call.

Inputs: [CANDIDATE ITEMS] · [REACH / IMPACT / EFFORT ESTIMATES] · [CONFIDENCE NOTES] · [STRATEGIC PRIORITIES]

Rules: Do not invent reach or impact numbers — use my estimates and mark any I left blank. The score informs; it doesn't decide. Keep confidential roadmap data out of consumer AI tools. This ranks the options; the prioritization call stays yours. Verify anything uncertain against the source before relying on it.

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: [CANDIDATE ITEMS][REACH / IMPACT / EFFORT ESTIMATES][CONFIDENCE NOTES][STRATEGIC PRIORITIES]
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Prioritization arguments go in circles because the inputs are hidden opinions; a consistent RICE table plus a confidence audit that names the shakiest input per item makes the debate about the right thing — the assumptions — and the strategic-check row prevents a purely mechanical score from burying a bet that matters for reasons the formula can't see.

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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?

Everything is P0 and stakeholders are loud. Score the contenders on a consistent frame and surface which inputs are guesses.

Why does this prompt work?

Prioritization arguments go in circles because the inputs are hidden opinions; a consistent RICE table plus a confidence audit that names the shakiest input per item makes the debate about the right thing — the assumptions — and the strategic-check row prevents a purely mechanical score from burying a bet that matters for reasons the formula can't see.

What mistake does this prompt help you avoid?

Opinion-driven prioritization — a consistent RICE table plus a per-item confidence audit make the shaky assumptions the subject of debate.

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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.