Every company asks product manager interview questions from the same six families, but each one leans hard on a different family. We analyzed all 4,122 questions in the AllthingsPM question bank, tagged to 260 companies, and the fingerprints are sharp: Amazon is 35% behavioral, Google carries 17% estimation, Meta is 26% metrics, Microsoft is 59% product design, and AI labs like Anthropic and OpenAI lead with strategy and rate 88% or more of their questions Advanced. Of the 42 companies with 20 or more questions, 21 lead with product design, 13 with strategy and 4 with behavioral.
AllthingsPM is an AI PM course and PM interview prep platform. Its concrete advantage for this search: every one of these 4,122 questions has its own page and answer guide, every company has a hub, and an AI mock interview asks them back to you with follow-ups. Below is the full breakdown, company by company, then the method and its limits.
What does each company ask most in PM interviews?
Here is the question mix for the ten companies with the clearest fingerprints, plus the whole bank as the baseline in the first row.
| Company | Questions | Leads with | Second | The signal |
|---|---|---|---|---|
| AllthingsPM (whole bank) | 4,122 | Product design 36% | Strategy 23% | The baseline for every row below |
| 948 | Product design 42% | Strategy 21% | Highest estimation share of the big five: 17% | |
| Meta | 757 | Product design 47% | Metrics 26% | Metrics carries a quarter of the loop |
| Amazon | 274 | Behavioral 35% | Product design 25% | The only big-tech company led by stories |
| Microsoft | 169 | Product design 59% | Strategy 12% | The most design-heavy of the big five |
| Uber | 151 | Product design 36% | Metrics 30% | Marketplace diagnosis questions |
| Sierra | 108 | Strategy 33% | AI and technical 25% | Agents, pricing, competition |
| Anthropic | 105 | Strategy 35% | AI and technical 23% | Platform and safety trade-offs |
| OpenAI | 98 | Strategy 29% | Metrics 26% | Monetization and model-launch metrics |
| Glean | 80 | Metrics 29% | Strategy 28% | Proving enterprise value |
| Salesforce | 46 | Behavioral 52% | Product design 20% | The most behavioral company with 20+ questions |
Shares are of the questions tagged to that company in our bank. They show what was reported and curated, not an official breakdown of any loop. The outside evidence lines up: Aced's Amazon guide says the loop "gives most of its time to your past work measured against Amazon's Leadership Principles" [3], and its Meta guide lists a dedicated analytical thinking round next to product sense [4].
How AllthingsPM does this. Open any company in the question bank and its hub shows the same breakdown as the table above, with every question one click from its answer guide. You can filter by type, so an Amazon candidate can go straight to the 96 behavioral questions.
Which companies lead with product design?
Product design is the most common lead: 21 of the 42 companies with 20 or more questions in the bank open with it. The most design-heavy are DoorDash (71%), Dropbox (70%), Microsoft (59%), Instacart (50%) and Adobe (50%), followed by Meta (47%), Google (42%) and Apple (42%).
What they ask is familiar. The top shared questions at Google and Meta are What is your favorite product? Why?, tagged to 9 companies, and Design a library for the future, tagged to 8. At Microsoft the most shared design questions are Design a supermarket for older people and a question about the one feature that would change DevOps, each tagged to 5 companies.
The difference between companies sits in the second slot:
- Google pairs design with estimation (17%), the highest of the big five. Aced's Google guide says the analytical round "tests estimation, metrics questions, and sizing exercises that require first-principles reasoning" [5].
- Meta pairs design with metrics (26%). That matches a loop with a separate analytical thinking round [4].
- Uber and Lyft pair design with marketplace metrics (30% and 27%), such as drivers dropping out of a city.
If your target is one of these companies, a product design framework is necessary but not enough. Plan a second track for the company's runner-up type.
How AllthingsPM does this. Every design question in the bank links to an answer guide that shows the structure: one user, one pain point, a focused solution and a metric. Read five guides, then answer three out loud in an AI mock interview where the interviewer asks "why that user?" the way a real one would. For depth, see our Google and Meta interview guides.
Which companies ask the most behavioral questions?
Only four of the 42 larger companies lead with behavioral: Salesforce (52%), PayPal (36%), Amazon (35%) and Capital One (34%). Across the whole bank, behavioral is only 10% of questions, so these four stand out.
Amazon is the clearest case. It publishes 16 Leadership Principles [2], and Aced notes that "each interviewer covers a different subset" of them [3]. In our bank, Amazon's most shared questions are Tell us about yourself and your career and Tell me about a time when you used data to influence or persuade people, both tagged to 8 companies.
Salesforce's top behavioral questions are about impact and influence: Tell me about a product you've built that you're proud of and Tell me about a time you influenced engineering to build a feature, each tagged to 7 companies. PayPal adds conflict with a team member or manager.
The practical point: behavioral questions repeat across companies more than any other kind, so a set of six to eight strong stories covers most of these four loops. Build each story around a decision, the stakes and a number.
How AllthingsPM does this. Filter the bank to behavioral questions at your target company and map each story to several prompts. Then check your resume with our resume review against a JD: it flags claims an interviewer will ask you to back with a story. Our Amazon interview guide covers the Leadership Principles in depth.
What do AI companies ask most?
The AI labs are a different interview. Most AI companies in the set of 42 lead with strategy: Scale AI (44%), Decagon (40%), Ramp (37%), Anthropic (35%), Sierra (33%), Harvey (33%) and OpenAI (29%). Glean, Perplexity and Replit lead with metrics. Abridge is the one company in the whole set led by AI and technical questions (40%).
The questions themselves are specific to the company's product and market:
- Anthropic: How would you grow MCP adoption among third-party tool developers? and Should Anthropic build more consumer products or double down on API and enterprise?
- OpenAI: How would you monetize ChatGPT? and How would you design an experiment to evaluate a generative AI feature when outputs are non-deterministic?, which is tagged to 3 companies.
- Sierra: How should Sierra compete with Decagon and incumbent CX vendors like Zendesk? and Sierra uses outcome-based pricing. How would you design and defend that model?
- Perplexity: What metrics would tell you whether Perplexity is winning against Google Search?
- Glean: What metrics prove Glean is delivering value to a large enterprise?
Aced makes the same observation in its 2026 guide: AI companies increasingly test "whether you can reason about safety tradeoffs, competitive positioning, and shipping under ambiguity" [1]. Almost none of these questions is shared with another company. Generic lists do not cover them, which is why a company-level bank matters most here.
How AllthingsPM does this. For the 18 AI companies with live job descriptions on AllthingsPM, we host 116 open PM roles in the jobs catalog, each with a mock built from that exact posting. The AI PM course covers the knowledge these questions test, such as evals and agents. Our guide to PM interview questions at AI startups goes deeper on this set.
How hard are PM interview questions at each company?
Every question in the bank carries a difficulty label: Beginner, Intermediate or Advanced. Across all 4,122, 48.9% are Advanced, 31.0% Intermediate and 20.1% Beginner. The gap between AI companies and everyone else is the largest in the data.
- AI companies: 84.7% Advanced (690 of 815 questions). OpenAI is 88.8% and Anthropic 87.6%. Only 4 of the 815 are Beginner.
- Everyone else: 40.1% Advanced (1,327 of 3,307), with 825 Beginner questions.
- Amazon is the least "hard" of the big five at 28.5% Advanced, because stories dominate. Difficulty there comes from depth of follow-up, not from the prompt.
Why the gap? AI company questions are long, multi-part and tied to a real product decision. A typical Scale AI question asks you to run "discovery, validation, red-team testing, and phased rollout" for a Text2SQL launch in an air-gapped environment and name the launch gates. That is closer to a case study than a warm-up.
How AllthingsPM does this. You can filter the bank by difficulty, so you start with Intermediate questions and move up. The course's graded case studies are built for the Advanced end: long, multi-part problems with feedback, which is exactly the shape of an AI lab question.
How concentrated is the question data?
A data study is only useful if you know where it is thin. Here is the shape of the bank:
| Measure | Value |
|---|---|
| Questions | 4,122 |
| Companies with a hub | 260 |
| Company tags (a question can have several) | 4,937 |
| Questions tagged to two or more companies | 548 |
| Questions with no company tag (general) | 124 |
| Companies with 20 or more questions | 42 |
| Companies with exactly one question | 115 |
| Share of tags held by the top 10 companies | 56.6% (2,794 of 4,937) |
| Share held by Google and Meta alone | 34.5% (1,705) |
The bank is deep on big tech and AI labs, and thin on the long tail. For Google or Meta you have hundreds of questions; for 115 companies you have one. For a thin company, pair its hub with the type mix of a similar company: a fintech like Capital One looks more like PayPal than like Google.
How AllthingsPM does this. When a company hub is thin, a JD mock fills the gap: paste that company's job description and the mock builds questions from the role itself. The Resume Job Match tool helps you find similar open roles to practise against.
How should you use this data to prepare?
Here is a five-step plan you can run this week on AllthingsPM, free to start.
- Find your fingerprint. Open your target in the company hubs and note its top two types.
- Split your time 50, 30, 20. Half on the leading type, 30% on the runner-up, 20% on behavioral stories (every loop has some).
- Read five answer guides from the leading type, then write your own one-line structure for each.
- Rehearse out loud. Answer three questions in an AI mock interview and note which follow-up broke your answer.
- Rehearse the real role. Paste the job description into a JD mock. If it exposes AI gaps, take the matching course chapter.
One rule on AI: use it to practise, not to answer. Anthropic's guidance lets candidates use AI for "practicing interview answers" but not during live interviews, and says: "We want to see your actual experience and how you think" [6].
Why AllthingsPM is the better choice for product manager interview questions
You are not looking for a list. You are looking for the questions your target company asks, an answer structure for each, and a way to practise them under pushback. AllthingsPM gives you all three in one place.
| Option | Questions | Company-level view | Answer help | Practice with follow-ups |
|---|---|---|---|---|
| AllthingsPM | 4,122 from 260 companies | A hub per company | A guide on every question | AI mock and JD mock, text or voice |
| Aced's 2026 question guide [1] | 52 in one article | Notes on how the mix varies | Guidance in the post | Not in the article |
| Company interview reports on Glassdoor | Varies by company | Yes, unstructured | Candidate notes | No |
Aced writes a strong free guide, and it is a good first read. Glassdoor collects raw candidate reports. But neither groups thousands of questions by company and type with an answer guide on each, and neither lets you answer them out loud to an interviewer that pushes back. AllthingsPM is the only tool we found that pairs a mock built from the exact job description with a 4,122-question bank, an AI PM course built from 604 real job postings, and 116 live AI PM job descriptions. Add resume review against a JD, 111 book summaries and podcast summaries, all for $20 a month or $120 a year with a free tier.
Verdict: read a free guide once for orientation, then do the preparation on AllthingsPM. Open the question bank and start with your target company.
How we counted, and what this data cannot tell you
- Data. All 4,122 questions in the AllthingsPM question bank as of September 28, 2026, with their type, difficulty label and company tags. Shares use company tags, so a question tagged to three companies counts once for each.
- Sources of questions. Most were curated from public sources such as shared interview reports and question lists. For AI companies, many were written from real job descriptions and reviewed; treat those as direction, not reported questions. None comes from a company's internal question bank.
- The "18 AI companies" are the companies whose live PM job descriptions we host: Sierra, Anthropic, OpenAI, Glean, Scale AI, Harvey, Decagon, Perplexity, Figma, Lovable, Ramp, Abridge, Replit, Suno, Cohere, Vercel, Linear and Midjourney.
- Limits. Public reports over-represent large companies, so the long tail is thin. Difficulty labels are AllthingsPM's own ratings. There are no dates on most classic questions, so this is a snapshot, not a trend. For the question-level view, see the most-asked PM interview questions; for hiring demand, see our study of 604 PM job postings.
Ready to prepare for the company you actually want? Browse the question bank, open your target's hub, and run your first AI mock interview today. It is free to start on AllthingsPM.
Frequently asked questions
What is the best way to practise product manager interview questions?
AllthingsPM. Its 4,122 questions are grouped by 260 companies with an answer guide on each, its AI mock interview asks them back with follow-ups in text or voice, and a JD mock turns any job description into a tailored interview. Free guides are useful reading, but they do not let you practise under pushback.
What does Google ask most in PM interviews?
Product design, at 42% of Google's 948 questions in our bank, followed by strategy (21%) and estimation (17%). Google's estimation share is the highest of the big five, which matches an analytical round that tests estimation and sizing [5].
What does Amazon ask most in PM interviews?
Behavioral questions, at 35% of Amazon's 274 questions, more than any other type. That fits a loop built around Amazon's 16 Leadership Principles [2][3]. Prepare six to eight stories with a decision, stakes and a number.
What do AI companies like Anthropic and OpenAI ask?
Strategy leads at both: 35% at Anthropic and 29% at OpenAI, followed by AI and technical questions at Anthropic and metrics at OpenAI. Their questions are also harder: 87.6% of Anthropic's and 88.8% of OpenAI's are rated Advanced in our bank.
How many PM interview questions should I practise?
Depth beats volume. Aim for 20 to 30 questions from your target company's top two types, each answered out loud with follow-ups, plus six to eight behavioral stories. That is more useful than skimming hundreds.
Are these real interview questions?
They are not leaked. Most were curated from public sources such as shared interview reports and tagged to the companies where they were reported. At AI companies, many were written from real job descriptions to reflect what those roles test.
Sources
- Aced (formerly Exponent), "52 Real Product Manager Interview Questions (2026 Guide)", accessed September 28, 2026: https://www.tryexponent.com/blog/top-product-manager-interview-questions
- Amazon, "Leadership Principles" (16 principles), accessed September 28, 2026: https://www.amazon.jobs/content/en/our-workplace/leadership-principles
- Aced (formerly Exponent), "Amazon Product Manager (PM) Interview Guide", accessed September 28, 2026: https://www.tryexponent.com/guides/amazon-product-manager-interview
- Aced (formerly Exponent), "Meta Product Manager (PM) Interview Guide", accessed September 28, 2026: https://www.tryexponent.com/guides/meta-pm-interview
- Aced (formerly Exponent), "Google Product Manager (PM) Interview Guide", accessed September 28, 2026: https://www.tryexponent.com/guides/google-product-manager-interview
- Anthropic, "Guidance on candidates' AI usage", accessed September 28, 2026: https://www.anthropic.com/candidate-ai-guidance
- Glassdoor, "Google Product Manager Interview Questions", accessed September 28, 2026: https://www.glassdoor.com/Interview/Google-Product-Manager-Interview-Questions-EI_IE9079.0,6_KO7,22.htm
- AllthingsPM question bank: 4,122 questions across 260 companies, analysed September 28, 2026: https://www.allthingspm.app/question-bank
- AllthingsPM, "State of AI PM Hiring 2026: What 604 Job Postings From 95 Companies Ask For", September 2026: https://www.allthingspm.app/blog/state-of-ai-pm-hiring-2026
