How To ACE AI Product Design Interviews (Anthropic PM Mock Interview)

The first AI product design mock interview on YouTube. Join our cohort to perform like this: https://www.landpmjob.com/ Full Writeup: https://www.news.aakashg.com/p/ai-product-design-interview 🎥 Timestamps: 0:00 - Intro 0:50 - Five Types of AI Product Design Questions 2:24 - The OpenAI Question 3:02 - Clarification Questions 4:09 - Structuring the Framework 4:47 - User Segmentation 6:13 - Selecting Pet Types 7:20 - Picking the Target Buyer 8:01 - Problem Brainstorming 9:18 - Prioritizing Problems 10:09 - Connecting to the AGI Goal 11:45 - Solution Brainstorming 15:25 - Prioritization Framework 18:53 - Selecting the Final Solution 20:21 - Core Flows Design 24:22 - Key Design Decisions 26:56 - Prompting Lovable for Prototypes 28:53 - Progress Toward AGI 30:05 - Risks and Mitigations 30:54 - The Story: Sarah and Max 31:35 - How the Interview Was Evaluated 36:46 - Land PM Job Cohort Info 📝 Key Takeaways: 1. AI product design is the hardest PM interview type in 2026 - OpenAI, Meta, Anthropic all ask these questions. Regular product design frameworks don't work. You need AI-specific approaches. 2. Always clarify before diving in - Pet type, standalone vs integrated, success metrics. These constraints shape everything. Don't assume. 3. Start with users, not features - Segment by buyer motivation: new pet owners, owners with behavioral issues, aging pet owners, professionals. Pick the one with highest pain and willingness to pay. 4. Connect problems to company mission early - OpenAI cares about AGI progress. Behavioral understanding in simpler organisms builds empathy systems that transfer to humans. Frame your solution within their strategic goals. 5. Visual narration separates exceptional from good - Draw your structure. Number your solutions. Build comparison tables. Interviewers follow your thinking easier when they can see it. 6. Prioritize using explicit criteria - User impact, technical feasibility, differentiation, engagement potential. Rate each solution. Show your math. 7. Combine complementary solutions into one product - Real-time behavioral coach plus conversation simulator. One solves the foundational problem, the other creates the magic moment. 8. Design core flows, not screens - Setup phase, passive monitoring, active coaching, conversation mode. Think in user states and transitions. 9. Offer modern prototyping alternatives - When time runs short, switch to prompting Lovable or Cursor. Shows you can work with AI tools, not just talk about them. 10. End with risks and mitigations - Bad advice, over-anthropomorphization, privacy concerns, pet type limitations. Shows product maturity beyond feature excitement. 👨‍💻 Where to find Aakash: Twitter: https://www.x.com/aakashg0 LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com Land PM Job: https://www.landpmjob.com/ #mockinterview #pminterview 🧠 About Product Growth: The world's largest podcast focused solely on product + growth, with over 200K+ listeners. 🔔 Subscribe and turn on notifications to get more videos like this.

Aakash Guptahost

Jan 19, 202639mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

Mock AI product design interview: pet communication, frameworks, AGI alignment

The video introduces five common AI product design interview question types and argues new-product design is where most candidates fail.
In the mock interview, the candidate clarifies constraints (pet type, standalone vs integrated, success metric) and aligns on OpenAI’s mission as the primary evaluation criterion.
A structured approach is modeled: define user/buyer segments, select a target, brainstorm problems, prioritize foundational problems, and generate multiple solution concepts.
The candidate prioritizes solutions using a simple scoring table (impact, feasibility, differentiation, engagement), then designs core product flows for a “real-time behavior coach” plus a “conversation simulator” magic moment.
The interviewer debriefs how responses are evaluated (structure/execution, creativity, user-centricity, prioritization transparency) and highlights common failure modes, followed by promotion of a PM interview-prep cohort.

IDEAS WORTH REMEMBERING

5 ideas

Start by pinning down ambiguity with targeted clarification questions.

The candidate quickly asks about pet scope, integration choices, and the success metric, then adapts the whole approach when the interviewer states the metric is “progress toward AGI.”

Anchor on the paying/using human, not the “end subject.”

Even in “pet communication,” the interview emphasizes identifying the buyer/user (pet owners) and their pain points, rather than treating the pet as the primary product customer.

Use a repeatable structure that forces convergence to a design.

The proposed sequence—users → problems → solutions → prioritize → design flows → AGI + risks—prevents rambling and ensures the answer reaches concrete UX/product decisions.

Prioritize “foundational” problems before higher-level features.

The candidate frames a pyramid where understanding “why behavior happens” and “catching it in the moment” are prerequisites to advice, diet optimization, or compatibility guidance.

Generate multiple concepts, then make prioritization legible.

Seven solutions (smart collar, vision app, edge hub, real-time coach, dietician, match advisor, conversation simulator) are compared via a simple table to show tradeoffs transparently.

WORDS WORTH SAVING

5 quotes

The hardest new PM interview in 2026 is the AI product design interview.

— Aakash Gupta

If this moves us towards [AGI], that's the only metric we are really interested in.

— Interviewer (Bart)

We need to be really careful about anthropomorphization… we want to frame it as interpretation not translation.

— Aakash Gupta

Interview aside, Smart Collar sounds like the first AI hardware that actually makes sense.

— Interviewer (Bart)

The visual way of narrating… was beneficial… without proper structure… the best ideas… will be ruined.

— Interviewer (Bart)

Five AI product design question typesClarifying questions and success metricsBuyer vs user vs “pet” stakeholder framingProblem pyramid and prioritizationSolution ideation (7+ concepts)Scoring framework (impact/feasibility/differentiation/engagement)Core flows: onboarding, passive monitoring, active coaching, conversation modeAGI mission alignment and “automated general intelligence” framingRisks: hallucinations, anthropomorphism, privacy, uneven pet coverageInterview evaluation rubric and common pitfalls

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