---
name: product-assumption-testing
description: 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.
license: MIT
metadata:
author: Pawel Huryn
source: phuryn/pm-skills/pm-product-discovery/skills/brainstorm-experiments-existing
source_url: https://github.com/phuryn/pm-skills/blob/8607e3b077817f89bf4a9b623246219734ac3be0/pm-product-discovery/skills/brainstorm-experiments-existing/SKILL.md
upstream-commit: 8607e3b077817f89bf4a9b623246219734ac3be0
original-name: brainstorm-experiments-existing
packaged-by: AutoGPT
packaged-on: '2026-09-25'
---
> 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.
---
### Further Reading
- [Testing Product Ideas: The Ultimate Validation Experiments Library](https://www.productcompass.pm/p/the-ultimate-experiments-library)
- [Assumption Prioritization Canvas: How to Identify And Test The Right Assumptions](https://www.productcompass.pm/p/assumption-prioritization-canvas)
- [What Is Product Discovery? The Ultimate Guide Step-by-Step](https://www.productcompass.pm/p/what-exactly-is-product-discovery)
- [Continuous Product Discovery Masterclass (CPDM)](https://www.productcompass.pm/p/cpdm) (video course)