product-assumption-testing

Packaging adaptation by AutoGPT, 2026-09-25. Original authorship and licence are retained. Changes are limited to the recorded name, metadata and local references; see ATTRIBUTION.md in this package.

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.

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Further Reading

• Testing Product Ideas: The Ultimate Validation Experiments Library
• Assumption Prioritization Canvas: How to Identify And Test The Right Assumptions
• What Is Product Discovery? The Ultimate Guide Step-by-Step
• Continuous Product Discovery Masterclass (CPDM) (video course)