Plan and audit customer discovery conversations that produce concrete evidence instead of compliments, opinions, hypotheticals, or feature-request noise.
NewMaintained
Automatic
◆Product Management pack
Last verified 8/15/2026
What it changes
Passed 8 of 23 test cases with the skill, and 15 of 23 without it.
Without skill67%
With skill33%
Checks it passed that the model alone missed
Asks the supervisor to walk through the exact details of the most recent shipping error that occurred.
1 fixed19 passed either way1 still failing2 broke
Pass-rate lift
-33 pp
Tokens
+12%
Agent turns
0%
Response time
-26%
Model gemini-3.6-flashMeasured 8/15/2026v120 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
A test case the skill fixed. Same model, same prompt, with and without the skill.
Prompt
A warehouse supervisor says during an interview: 'We experience shipping errors all the time and it causes major headaches.' How should the interviewer drill down into this generic claim?
What was checked, without and with the skill
Checked
Without skill
With skill
Asks the supervisor to walk through the exact details of the most recent shipping error that occurred.
Missed
Passed
case-20 · gemini-3.6-flash · 8/15/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md86 linessingle file
Customer Discovery Conversations
Use this skill to turn customer conversations into decision-quality evidence.
The goal is not approval for an idea. The goal is to learn concrete facts about
customers' lives, current behavior, constraints, costs, workarounds, and risks.
Source Traceability
Primary source: The Mom Test by Rob Fitzpatrick, especially chapters 1-4 and 8.
Guidance is paraphrased for this MIT repo; authoring notes used converted EPUB
lines 236-2362 and 3613-4108.
Workflow Routing
Need
Use
Rewrite an interview script
workflows/rewrite-interview-questions.md
Run a batch of conversations
workflows/run-conversation-batch.md
Recover from compliments, hypotheticals, or ideas
workflows/recover-bad-data.md
Segment is too broad
customer-segment-slicing
Product or sales meeting needs a real next step
customer-commitment-validation
Raw notes need synthesis
customer-learning-notes
Conversation Workflow
State the decision the conversations should improve.
Name the riskiest assumptions, including at least one uncomfortable question.
Choose the narrow customer or stakeholder type. If the segment is fuzzy, use
customer-segment-slicing first.
Prepare up to three learning goals for this type of person.
Rewrite questions toward current behavior and specific past examples.
Keep the conversation about the customer until there is enough evidence to
discuss a solution.
During the conversation, anchor vague claims to recent examples and dig into
current costs, workarounds, constraints, and goals.
Capture notes, signals, and follow-up tasks for review.
Question Rules
Talk about the customer's life, work, tools, constraints, and recent past.