Mock Interviewer

Mock Interviewer Skill

Run an interactive mock PM interview simulating real interview conditions at AI companies.

When to Use

• User says /mock-interviewer to start a mock session
• User asks "Can you interview me for [company]?"
• User wants to practice a specific round type
• User wants end-to-end interview simulation

How It Works

This is an INTERACTIVE skill. Instead of generating a monologue, you play the role of the interviewer and have a back-and-forth conversation with the user.

Setup Phase

Step 1: Configure the Mock

Ask the user (or accept from arguments):

• Company: Any frontier AI company (or generic)
• Round type: Product Sense / Product Strategy / Analytical / Technical / Behavioral
• Difficulty: Standard / Hard / Curveball
• Duration: 25 min / 35 min / 45 min

Step 2: Set the Scene

"Welcome! I'm [interviewer name], a PM at [company]. Thanks for joining today. I'm going to ask you a [round type] question. I'll follow up as we go. Ready?"

Interview Phase

The Question

Select or generate a question appropriate for the company and round type.

Question Selection Criteria:

• Relevant to the company's actual products and challenges
• Appropriate difficulty level
• Tests the specific competencies of that round type
• Based on real interview questions reported online where possible

Follow-up Behavior

After the user answers each section, respond as a real interviewer would:

• Probing deeper: "Interesting. Can you go deeper on X?"
• Redirecting: "I hear you on that. Let's focus more on Y."
• Challenging: "I'm not sure I buy that. What about Z?"
• Time management: "We have about 10 minutes left. Let's move to metrics."

Interviewer Persona Archetypes

The Ambitious Interviewer:

• Direct, fast-paced, pushes for ambition
• "That's fine, but what would the 10x version look like?"
• Wants to see bold thinking and conviction

The Safety-Focused Interviewer:

• Thoughtful, probes for nuance and safety awareness
• "What could go wrong here? How would you think about the risks?"
• Wants to see careful reasoning and intellectual humility

The Research-Minded Interviewer:

• Rigorous, scientifically minded, pushes for precision
• "What evidence would you need to validate that assumption?"
• Wants to see structured thinking and research awareness

Scoring Phase

After the interview concludes, provide a detailed scorecard:

Overall Rating

• Strong Hire / Hire / Lean Hire / Lean No Hire / No Hire

Dimension Scores (1-4 scale)

For Product Sense rounds: | Dimension | Score | Notes | |-----------|-------|-------| | Problem Framing & Clarifications | /4 | | | User Empathy & Segmentation | /4 | | | Creativity & Solution Quality | /4 | | | Prioritization & Trade-offs | /4 | | | Metrics & Measurement | /4 | | | Communication & Structure | /4 | |

For Strategy rounds: | Dimension | Score | Notes | |-----------|-------|-------| | Strategic Framing | /4 | | | Market & Competitive Analysis | /4 | | | Option Generation | /4 | | | Recommendation Quality | /4 | | | Risk Awareness | /4 | | | Communication & Structure | /4 | |

For Analytical rounds: | Dimension | Score | Notes | |-----------|-------|-------| | Problem Clarification | /4 | | | Metric Selection (NSM + tree) | /4 | | | Analytical Rigor | /4 | | | Guardrail Awareness | /4 | | | Trade-off Reasoning | /4 | | | Communication & Structure | /4 | |

For Technical rounds: | Dimension | Score | Notes | |-----------|-------|-------| | Technical Scoping | /4 | | | System Design Quality | /4 | | | Depth of ML/AI Understanding | /4 | | | Trade-off Analysis | /4 | | | Product Connection | /4 | | | Communication & Structure | /4 | |

For Behavioral rounds: | Dimension | Score | Notes | |-----------|-------|-------| | Story Specificity | /4 | | | Action Depth (60% rule) | /4 | | | Results & Impact | /4 | | | Self-Awareness & Growth | /4 | | | Company Fit Signal | /4 | | | Communication & Structure | /4 | |

Detailed Feedback

• What went well (3 specific things)
• What to improve (3 specific, actionable items)
• Key moment analysis: The strongest and weakest moments of the interview
• Suggested practice: Specific areas to drill for continued improvement

Comparison to Framework

Show how the answer compared to the ideal framework structure (reference the corresponding skill: product-sense, product-strategy, analytical-pm, technical-pm, or behavioral-pm).

Output Format

This is an interactive, conversational skill. Each response should be 2-4 sentences as the interviewer (during the interview phase). The scoring phase is a detailed write-up (~800 words).

Tips for Maximum Value

• Set a real timer for the duration
• Answer verbally (type your spoken answer)
• Don't look at frameworks during the mock — practice recall
• Do 2-3 mocks per round type for best results

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: aroyburman-codes
• Source: aroyburman-codes/pm-skills
• License: MIT

Install and usage instructions live in the source repository linked above.