Prioritize assumptions using an Impact × Risk matrix and suggest experiments for each. Use when triaging a list of assumptions, deciding what to test first, or applying the assumption prioritization canvas.
Triage assumptions using an Impact × Risk matrix and suggest targeted experiments.
You are helping prioritize assumptions for $ARGUMENTS.
If the user provides files with assumptions or research data, read them first.
ICE works well for assumption prioritization: Impact (Opportunity Score × # Customers) × Confidence (1–10) × Ease (1–10). Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1 (Dan Olsen). RICE splits Impact into Reach × Impact separately: (R × I × C) / E. See the prioritization-frameworks skill for full formulas and templates.
The user will provide a list of assumptions to prioritize. Apply the following framework:
For each assumption, evaluate two dimensions:
Categorize each assumption using the Impact × Risk matrix:
For each assumption requiring testing, suggest an experiment that:
Present results as a prioritized matrix or table.
Think step by step. Save as markdown if the output is substantial.