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Talk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less.
Passed 20 of 22 test cases with the skill, and 13 of 22 without it.
and 7 more in the full report
8 fixed12 passed either way1 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
In a user chat, the participant said 'I usually review my team's code PRs every morning before 9 AM.' How should I evaluate this statement, and what question should I ask immediately after?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies the statement 'I usually' as unverified generic fluff | Missed | Passed |
| Asks for a specific recent instance, such as 'Walk me through what happened yesterday morning' | Missed | Passed |
The instructions your model reads when the skill loads.
Framework for customer conversations that won't lead you astray, based on a fundamental truth: everyone is lying to you -- not maliciously, but because you're asking the wrong questions. The Mom Test provides rules for asking questions so good that even your mom can't lie to you.
Good customer conversations are about their life, not your idea. The moment you mention what you're building, people switch from sharing truth to performing politeness. Talk about their problems, their lives, and their existing behavior instead of pitching, and ask about specifics in the past, not hypotheticals about the future. Above all, talk less and listen more.
Goal: 7/7. Score a conversation (or interview plan) by the seven-row Quick Diagnostic below: 1 point per row that passes.
Always state the current score out of 7, name the failing diagnostic rows, and give the specific fix for each.
Core concept: Three rules that make it impossible for even your most supportive loved ones to give you false validation, shifting conversations from opinion-gathering to fact-finding.
Why it works: People are unreliable predictors of their own future behavior, so opinions are worthless. Past behavior is the only reliable data and can genuinely inform product decisions.
Key insights:
Product applications:
| Context | Application | Example |
|---|---|---|
| Idea validation | Ask about the problem, never the solution | "Tell me about the last time you tried to [problem area]" not "Would you use an app that does X?" |
| Feature prioritization | Discover what people do vs. what they say | "Walk me through how you handled this last week" |
| Pricing research | Anchor to existing spending behavior | "What are you currently paying to solve this?" not "Would you pay $X?" |
test cases passed, vs 13 / 22 without
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