pmprompt Domain Context
This skill implements a proven product management framework. The approach combines best practices from industry leaders and is designed for practical application in day-to-day PM work.
Input Requirements
- Context about your product, feature, or problem
- Relevant data, research, or constraints (recommended but optional)
- Clear articulation of what you're trying to achieve
Trustworthy Experiments
What It Is
Trustworthy Experiments is a framework for running controlled experiments (A/B tests) that produce reliable, actionable results. The core insight: most experiments fail, and many "successful" results are actually false positives.
The key shift: Move from "Did the experiment show a positive result?" to "Can I trust this result enough to act on it?"
Ronny Kohavi, who built experimentation platforms at Microsoft, Amazon, and Airbnb, found that:
- 66-92% of experiments fail to improve the target metric
- 8% of experiments have invalid results due to sample ratio mismatch alone
- When the base success rate is 8%, a P-value of 0.05 still means 26% false positive risk
When to Use It
Use Trustworthy Experiments when you need to:
- Design an A/B test that will produce valid, actionable results
- Determine sample size and runtime for statistical power
- Validate experiment results before making ship/no-ship decisions
- Build an experimentation culture at your company
- Choose metrics (OEC) that balance short-term gains with long-term value
- Diagnose why results look suspicious (Twyman's Law)
- Speed up experimentation without sacrificing validity
When Not to Use It
Don't use controlled experiments when:
- You don't have enough users — Need tens of thousands minimum
- The decision is one-time — Can't A/B test mergers or acquisitions
- There's no real user choice — Employer-mandated software
- You need immediate decisions — Experiments need time
- The metric can't be measured — No experiment without observable outcomes
Resources
Book:
- Trustworthy Online Controlled Experiments by Ronny Kohavi, Diane Tang, and Ya Xu