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Prd V10 Mom Test Interview

Community
mattgierhart
prd-v10-mom-test-interview

Apply Rob Fitzpatrick's Mom Test discipline to customer interviews during PRD v1.0 Market Adoption. Triggers on requests to interview customers, run discovery calls, validate ideas with users, or when user asks "how do I interview customers?", "Mom Test", "Rob Fitzpatrick", "customer interview", "user research without lies", "talking to humans", "discovery conversation". Outputs CFD-* discovery entries with Mom Test-calibrated confidence.

Overview

Publishermattgierhart
RepositoryPRD-driven-context-engineering
Skill nameprd-v10-mom-test-interview
Stars
179
Forks
11
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mattgierhart on GitHub. Read the source before you install it.

Installation

Install the Prd V10 Mom Test Interview AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mattgierhart/PRD-driven-context-engineering.git /tmp/PRD-driven-context-engineering
mkdir -p .claude/skills
cp -r /tmp/PRD-driven-context-engineering/plugins/prd-ce/skills/prd-v10-mom-test-interview .claude/skills/prd-v10-mom-test-interview
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prd V10 Mom Test Interview in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Prd V10 Mom Test Interview on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Prd V10 Mom Test Interview is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Mom Test Interview Discipline

Position in workflow: v1.0 Continuous Discovery (Torres) → v1.0 Mom Test Interview → v1.0 Case Study Builder, Testimonial Collector

Execution Mode

Default is standard. See .claude/rules/08-skill-execution-modes.md for selection logic.

ModeWhat this skill produces
quickSingle interview prep + question list + CFD-* discovery entry post-interview
standardInterview prep + scripted opening + 5–7 questions + CFD-* entry with confidence calibration + Bad Data flagged
deepMulti-interview cohort plan + cross-interview synthesis + pattern flagging at 3-mention threshold + assumption-test handoff

Framework: The Mom Test

From The Mom Test: How to Talk to Customers and Learn If Your Business is a Good Idea When Everyone is Lying to You (Rob Fitzpatrick, 2013). Premise: People lie to spare your feelings — especially about your business idea. Learn to ask questions that get truth.

The three Mom Test rules

  1. Talk about their life, not your idea. Ask about how they actually live and work, not whether they'd like your hypothetical feature.
  2. Ask about specifics in the past, not generics or opinions about the future. "Last time you faced X, what did you do?" beats "Would you use a tool that does Y?"
  3. Talk less and listen more. If you're talking more than 30% of the time, you're pitching, not learning.

Three types of Bad Data to avoid

Bad Data typeExampleWhy it's badWhat to do
Compliments"That sounds awesome!"Politeness; not predictiveDiscard; don't update confidence
Fluff"I usually..." "I would probably..."Generics, future hypotheticalsAnchor to specifics: "When did you last do that?"
Ideas"You should add X"Solution suggestions disguised as needsNote as IDEA; ask "what would solving X enable you to do?" — get the underlying job

Confidence calibration

Mom Test-disciplined interviews produce higher-confidence CFD- entries because the data is grounded in observed past behavior, not opinion. Confidence floors per P4:

  • 2/5 — Generic statement ("I sometimes have this problem")
  • 3/5 — Specific past instance ("Last Tuesday, I spent 2 hours doing X")
  • 4/5 — Specific past instance + paid-money-for-a-workaround / hired-a-person / built-a-script ("I'm paying $30/mo for a tool that almost solves this")
  • 5/5 — Repeated specific past instances + ongoing willingness to invest in better solution (commit > talk)

Consumes

  • ADO-BEACHHEAD-* and PER-* personas — Defines the interview pool; non-segment interviews are still useful but get lower weight
  • Opportunity Solution Tree (from prd-v10-continuous-discovery-torres) — Interview goals trace to specific opportunities being tested
  • CFD-* prior research — Patterns to validate or contradict
  • KPI-* outcomes — Why we're interviewing (anchor to what we're trying to move)

Produces

  • CFD-* discovery interview entries — One per interview, with confidence calibrated by Mom Test rules
  • CFD-* pattern entries — When 3+ interviews mention the same specific behavior, promote to a pattern entry with frequency
  • Bad Data inventory — Compliments, fluff, ideas captured for context but not data
  • Discovery Tree updates — Each interview either strengthens an opportunity, weakens an opportunity, or surfaces a new one

Execution

Step 1: Define the goal of this interview

Not "validate the idea." Specifically: which opportunity / assumption from the Opportunity Solution Tree is this interview testing?

GoalExample
Validate opportunity exists"Do beachhead pragmatists actually struggle with pricing-tier selection?"
Test assumption"Will users engage with a pricing wizard before signup?"
Map workaround"How are they solving this today?"
Quantify pain"How much time/money does this cost them currently?"

Write the goal at the top of the interview notes.

Step 2: Prep the question list (Mom Test-shaped)

Use specifics-in-the-past form. Avoid hypotheticals.

Bad questionBetter (Mom Test) version
"Would you use a pricing wizard?""Walk me through how you picked the tier when you signed up."
"Do you think analytics is important?""Tell me about the last time you looked at analytics."
"What features do you wish we had?""Tell me about the last time the tool didn't do what you needed."
"How would you describe X?""Tell me about the last time X came up at work."

5–7 questions is plenty for a 25–30 minute interview. Leave room to follow threads.

Step 3: Run the interview

  • Open with a short framing: who you are, why this conversation, no sales pitch
  • Ask the past-behavior questions, listen, follow threads
  • Probe specifics when they generalize: "When was that specifically?" / "What was the dollar / time cost?" / "What did you do next?"
  • Flag Bad Data internally: when they compliment, smile and move on; when they fluff, anchor to specifics; when they suggest ideas, note as IDEA and dig for the underlying job
  • Talk less than 30% of the total minutes
  • Don't pitch. If they ask what you're building, give a one-sentence answer and pivot back

Step 4: Write up the CFD-* entry within 4 hours

Memory decays fast. Within 4 hours of the interview, write up the CFD- entry. Include:

  • Verbatim quotes (the best evidence)
  • Specific past instances (the gold)
  • Bad Data inventory (compliments, fluff, ideas) — kept for context but not counted as data
  • Confidence per P4 calibration

Step 5: Update the Opportunity Solution Tree [standard+]

Did this interview:

  • Strengthen an existing opportunity (add to frequency count)?
  • Contradict an existing opportunity (note dissenting evidence)?
  • Surface a new opportunity (add to tree)?

Promote a pattern to "Active" focus when 3+ interviews mention the same specific behavior.

Step 6: Cross-interview synthesis [deep only]

After every cohort of 5–8 interviews, synthesize:

  • What patterns emerged at the 3+ mention threshold?
  • What hypotheses were contradicted?
  • What new opportunities surfaced?
  • What's the next interview cohort target?

Output Template

CFD-XXX: Mom Test Interview — [Brief title]
Type: Discovery-Interview
Date: YYYY-MM-DD
Length: [minutes]
Interviewee: [PER-XXX + in-beachhead: yes/no]
Interviewer: [Name]
Goal: [Specific opportunity/assumption being tested]

Specific past instances captured (the gold):
  - "[Verbatim quote — describes a specific past behavior]"
    Context: [When, where, what they did, what it cost]
    Confidence: 3/5 or 4/5 (per P4 calibration)

Workarounds observed:
  - [What they currently do; tools/spend/time invested]

Bad Data (logged but not counted):
  - Compliments: ["That sounds awesome"]
  - Fluff: ["I'd probably use that"]
  - Ideas: ["You should add X"]  → underlying job: [What X would enable]

Pattern strengthening:
  - O1 [opportunity]: +1 mention (now N total)

New opportunity surfaced (if any):
  - [Description]

Overall confidence of this interview's data: X/5
Linked IDs: PER-XXX, ADO-BEACHHEAD-XXX, KPI-XXX, Opportunity-Tree-Node

Anti-Patterns

PatternSignalFix
Pitching disguised as interviewInterviewer talking >40% of the timeTalk less; ask follow-ups; let silence happen
Future-hypothetical questions"Would you use..."Reframe to past-behavior
Treating compliments as data"5 people said it sounds great → strong signal"Compliments are not data; discount
Recording feature requests as opportunities"User asked for dark mode → opportunity: dark mode"Dark mode is a solution; the opportunity is the underlying job (e.g., late-night use, eye strain)
No specifics-probeInterview ends without a single "what specifically" follow-upBuild the habit; specifics are the gold
Writing up days laterInterview Friday, CFD- entry MondayMemory decays; write within 4 hours
No goal for interview"Just talking to users"Each interview tests one specific opportunity or assumption
All interviews from outside beachheadStrong patterns but not in segmentIn-segment interviews dominate; out-of-segment is supplementary

Quality Gates

For each interview:

  • Goal stated before interview (which opportunity/assumption is being tested)
  • Question list is past-behavior shaped, not hypothetical
  • Interviewer talked <30% of minutes
  • At least one "what specifically" follow-up was asked
  • Bad Data inventory exists (compliments / fluff / ideas — even if empty)
  • CFD- entry written within 4 hours
  • Confidence per P4 calibration (not "feels good")
  • Discovery Tree updated (pattern strengthen / contradict / new opportunity)

Downstream Connections

ConsumerWhat it usesExample
Continuous Discovery (Torres)Every interview updates the Opportunity Solution TreeThis skill is the how; Torres is the what to do with
Chasm Adoption (Moore)In-beachhead interviews update ADO-STAGE-* and ADO-BEACHHEAD-*Patterns strengthen stage assessment
Case Study BuilderHigh-impact interviewees become case-study candidatesCFD- with 5/5 confidence + outcome → ADO-REF-*
Testimonial CollectorStrong endorsement interviews become testimonial sourcesSpecific past-instance quote + consent → testimonial
Feedback Loop SetupMom Test is the discipline for the structured-interview armInbound feedback ≠ Mom Test (still useful, lower confidence)

Detailed References

  • Rob Fitzpatrick, The Mom Test (2013) — canonical source, short and readable
  • Rob Fitzpatrick, The Workshop Survival Guide (companion)
  • Steve Portigal, Interviewing Users (complementary depth)
  • wondelai's mom-test skill (wondelai/skills)
  • (No bundled references/ — read the book; it's 130 pages)

Frequently asked questions

What does the Prd V10 Mom Test Interview AI skill do?

Apply Rob Fitzpatrick's Mom Test discipline to customer interviews during PRD v1.0 Market Adoption. Triggers on requests to interview customers, run discovery calls, validate ideas with users, or when user asks "how do I interview customers?", "Mom Test", "Rob Fitzpatrick", "customer interview", "user research without lies", "talking to humans", "discovery conversation". Outputs CFD-* discovery entries with Mom Test-calibrated confidence.

Why use Prd V10 Mom Test Interview on TypingMind?

Because you install it once and use it with any model. Prd V10 Mom Test Interview is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Prd V10 Mom Test Interview in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mattgierhart/PRD-driven-context-engineering/tree/main/plugins/prd-ce/skills/prd-v10-mom-test-interview. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prd V10 Mom Test Interview?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Prd V10 Mom Test Interview?

As many as you like. As long as a model supports skills, you can use Prd V10 Mom Test Interview with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prd V10 Mom Test Interview AI skill free?

Yes. It is published on GitHub by mattgierhart under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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