Interview Me
Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence.
What people ask for and what they actually want are different things. This skill closes the gap before it costs anything.
When to Use
- The ask is missing at least one of: who, why, what success looks like, or the binding constraint
- The request is conventional rather than specific ("build me X", "make it faster")
- You're tempted to start with assumptions you haven't surfaced
- The user explicitly invokes: "interview me", "grill me", "stress-test my thinking"
The Process
Step 1: Hypothesize, with a confidence number
Before asking anything, write down your current best read plus an honest confidence number (0–100%):
HYPOTHESIS: You want a way to answer "how are we doing?" in standup, and "dashboard" was the convention that came to mind.
CONFIDENCE: ~30% — missing: who it's for, what "metrics" means, and what success looks like
Step 2: Ask one question at a time, each with a guess attached
Q: <one focused question>
GUESS: <your hypothesis for the answer, with reasoning>
Why one at a time, not a batch:
- The user can't react to your hypotheses if you bury them in a list
- The third question often depends on the answer to the first
- The user's energy for thinking carefully is finite
Why attach a guess:
- The user reacts faster to a wrong guess than they generate an answer from scratch
- It commits you to a hypothesis you can be visibly wrong about
Step 3: Listen for "want vs. should want"
Watch for:
- Answers that pattern-match best-practice talk without specifics
- Answers that defer to convention ("the standard approach")
- Buzzwords as goals — "modern", "scalable", "robust"
When you hear these, ask:
"If you didn't have to justify this to anyone, what would you actually want?"
Step 4: Restate intent in the user's own words
When confidence is high, write back what you think the user wants:
Here's what I now think you want:
- Outcome: <one line>
- User: <one line — who benefits>
- Why now: <one line — what changed>
- Success: <one line — how we know it worked>
- Constraint: <one line — the binding limit>
- Out of scope: <one line — what we're explicitly not doing>
Yes / no / refine?
Step 5: Confirm — explicit yes, not "whatever you think"
The gate is an explicit "yes." These are not yes:
- "Whatever you think is best." → Re-ask with two concrete options
- "Sounds good." → Ask: "Anything you'd refine?"
- "Sure, let's go." → Often a polite exit, not an endorsement
The 95% Confidence Stop
You're done when you can answer yes to this:
Can I predict the user's reaction to the next three questions I would ask?
If yes, you have shared understanding. Stop interviewing and produce the restate.
Example
User: build me a dashboard for our metrics
Agent:
HYPOTHESIS: You want a way to answer "how are we doing?" in standup.
CONFIDENCE: ~30% — missing: who it's for, what "metrics" are, success criteria
Q: When you say "how are we doing?", who's asking — you alone, the team, or up the chain?
GUESS: engineering team in standup, because "we" usually scopes that way
User: It's actually for me. I keep losing track of which experiments are running.
Agent:
Updated read: not a team dashboard. It's a personal experiment tracker. Confidence: ~60%
Q: Is the gap that you don't know which experiments exist, or that you can't see their results in one place?
GUESS: the second one. Results live in five different tools.
User: First one actually. I literally don't have a list.
Agent: Two questions in, the actual ask isn't "a dashboard." It's "a list."
Verification
After applying interview-me:
- A hypothesis with confidence number was stated in the first turn
- Questions were asked one at a time with guesses attached
- A concrete restate was written back to the user
- The user confirmed with an explicit yes
- The agent could predict reactions to the next three questions at the stop point