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brainstorm-experiments-existing

Design experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods. Use when validating assumptions, testing feature ideas cheaply, or planning product experiments.

Published by phuryn ↗phuryn/pm-skills

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brainstorm-experiments-existing

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Use brainstorm-experiments-existing to design low-effort experiments for [product idea] to validate [assumptions] within [constraints], with a table of experiments, behavioral metrics, success thresholds, and risk mitigation for any production tests.

Required inputs

  • [product idea]
  • [assumptions]
  • [constraints]

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SKILL.md

name: brainstorm-experiments-existingdescription: "Design experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods. Use when validating assumptions, testing feature ideas cheaply, or planning product experiments."

Design Experiments (Existing Product)

Design low-effort experiments to test product assumptions before committing to full implementation.

Context

You are helping a product team design experiments for $ARGUMENTS. The team has a feature idea and assumptions that need validation.

If the user provides files (PRDs, assumption lists, designs), read them first.

Instructions

The user will describe their idea and assumptions. Work through these steps:

  1. Clarify the idea and assumptions: Confirm what the team wants to build and what they need to validate.

  2. Suggest experiments for each assumption. Consider methods like:

    • First-click testing or task completion with a prototype
    • Feature stubs or fake door tests
    • Technical spikes
    • A/B tests on production (with risk mitigation)
    • Wizard of Oz approaches
    • Survey-based validation (behavioral, not opinion-based)
  3. Key principles to follow:

    • Measure actual behavior, not users' opinions
    • Test responsibly — don't put users or the business at risk
    • For production tests (e.g., A/B tests), explain risk mitigation strategies
    • Aim for maximum validated learning with minimal effort
  4. For each experiment, specify:

    • Assumption: What do we believe?
    • Experiment: What exactly will we do to validate it?
    • Metric: What will be measured?
    • Success threshold: The expected value if we are right

Think step by step. Present experiments in a clear table or structured format. Save as markdown if substantial.


Further Reading