GOOGLE PM TECHNICAL EXPECTATIONS

Research Summary

Sources Consulted:

• Product Alliance Google PM Interview Guide (official prep resources)
• Exponent PM Interview Guide (2025 updated)
• IGotAnOffer Google PM Interview resources
• Glassdoor reviews (618 PM interview reviews analyzed)
• RocketBlocks interview preparation guides
• GeeksforGeeks technical interview compilation
• Multiple Medium articles from successful candidates
• Company interview guides and prep materials

Confidence Level: High - Google provides extensive public resources and there is abundant recent interview data across multiple platforms

Last Researched: December 03, 2025

---

Role Overview

Product Manager at Google:

Google PMs lead cross-functional teams to build products that solve user problems at massive scale. Unlike other FAANG companies, Google has the highest technical bar for PMs - you’re expected to get into technical details with engineers and guide granular technical decisions, especially for lower-level positions.

Key Characteristics:

• Technical depth required: Very High (highest among FAANG companies)
• Google specifically screens for technical aptitude unlike Amazon and Meta
• Must have influence and credibility with senior engineers
• Expected to communicate effectively on technical architecture
• Technical requirements ease up for senior leadership roles (APM/PM handles details)

What Makes Google Different:

• Only ~50% of Meta PMs have technical degrees; Google prefers engineering/CS backgrounds
• Amazon separates PM and PM-T roles; Google expects all PMs to be technical
• Engineering-driven culture (vs Amazon’s PM-driven culture)
• Preference for candidates with software engineering experience

---

Technical Interview Format

Overall Process Timeline: 4-8 weeks (average 38 days from application to hire)

Interview Stages:

Week 0-2: Recruiter Screen (30 minutes)

• Background and motivation
• High-level product philosophy
• Cultural alignment check

Week 2-4: Phone Screen with PM (45 minutes)

• Product sense questions
• Analytical thinking assessment
• First technical evaluation
• Sample: “How would you improve Google Maps for drivers?”

Week 4-7: Onsite Loop (5 rounds × 45 minutes each)

The standard onsite consists of:

1. Product Design Round #1 (45 min) - with PM

   • Open-ended product design
   • User empathy and creativity assessment

2. Product Design Round #2 (45 min) - with PM

   • Different product scenario
   • Scalability considerations

3. Analytical Round (45 min) - with PM

   • Market estimation questions
   • Metrics definition and data interpretation
   • Prioritization frameworks

4. Technical Round (45 min) - with Senior Engineer

   • System design (more architecture than coding)
   • Technical explanations
   • Understanding of tech stack
   • This is the dedicated technical assessment

5. Behavioral/“Googleyness” Round (45 min) - with PM/EM

   • Leadership examples
   • Cross-functional collaboration
   • Cultural fit assessment

Plus: Informal PM Lunch

• Technically “ungraded” but treat as real interview
• Ask thoughtful questions
• Show genuine interest in Google’s culture

Post-Onsite: Team Matching

• Individual teams assess experience fit
• Product area alignment

---

Technical Depth Expected

✓ What IS Expected

Technical Communication:

• Explain complex technical concepts to non-technical stakeholders
• Fluently converse with engineering teams
• Understand technical architecture fundamentals
• Communicate product implications of technical decisions

System Design Understanding:

• High-level architecture diagrams and component breakdown
• Scalability discussion for Google-scale products (millions/billions of users)
• Trade-off reasoning (CAP theorem, SQL vs NoSQL, etc.)
• API design and data flow understanding
• Load balancing, caching, CDN concepts
• Database choices and sharding strategies

Technical Stack Knowledge:

• Multi-tiered web applications architecture
• Client-server communication (HTTP/HTTPS, APIs, protocols)
• Data storage in databases (SQL/NoSQL)
• DNS, browsers, and internet infrastructure
• Mobile app architecture basics
• Cloud infrastructure concepts

Algorithm Comprehension:

• Explain how algorithms work conceptually
• Understand system functions (e.g., “What happens when you search on Google?”)
• Data structures appropriate for different scenarios
• No implementation required, but conceptual clarity needed

Product-Specific Technical Knowledge:

• Deep understanding of the product area you’ll work on
• For AI/ML products: familiarity with ML concepts
• For infrastructure: understanding of distributed systems
• For consumer apps: mobile/web platform differences

✗ What is NOT Expected

• Writing production code - No coding challenges in PM interviews
• LeetCode-style problems - “People keep asking if they need to do Leetcode for PM at Google and the answer is a resounding no”
• Deep implementation details - Focus is conceptual, not implementation
• Advanced CS theory - No need to prove algorithms or write proofs
• Memorizing specific frameworks - Understanding trade-offs matters more
• Being able to build systems independently - You guide, engineers build

Critical Distinction: Google’s “PM Technical Round no longer includes coding challenges.” The shift moved toward “craft and execution questions” to replace traditional technical rounds, with focus on explanation over implementation.

---

Common Question Types

1. Technical Explanation Questions (30% of technical questions)

Format: Explain technical concepts simply

Sample Questions:

• “Explain what an SDK is to a 7-year-old”
• “Explain the concept of APIs to a child”
• “How would you explain cookies to your grandmother?”
• “What is the difference between HTTP and HTTPS?”
• “Explain how DNS works”
• “What’s the difference between C and SQL?”
• “How would you explain what an API is to someone who is completely non-technical?”

What They’re Testing: Can you bridge technical complexity and clear communication?

2. System Design / Architecture Questions (40% of technical questions)

Format: Design a system or explain existing architecture

Sample Questions:

• “Design a load balancer for Google.com. What data structure would you use?”
• “What do you think is happening on the back-end when you search on Google?”
• “Imagine you’re a PM on Gmail and you decide to launch a new ‘schedule an email’ feature. What parts of the Gmail tech stack would this feature require you to touch?”
• “How would you design a URL shortening service?”
• “Design a web crawler”
• “Design a messaging system for a mobile app”
• “Design Instagram/YouTube” (high-level architecture only)

What They’re Testing:

• Can you think about architecture at the right level?
• Do you consider scalability, APIs, data flow?
• Can you identify components and their interactions?

3. Technical Trade-off Questions (20% of technical questions)

Format: Evaluate competing technical approaches

Sample Questions:

• “SQL vs NoSQL for user profiles - how do you decide?”
• “When would you choose client-side vs server-side rendering?”
• “Caching strategy trade-offs for real-time vs static content”
• “Microservices vs monolithic architecture - what factors matter?”
• “REST API vs GraphQL - when to use each?”

What They’re Testing:

• Understanding of technical implications
• Ability to reason about constraints
• Considering user impact, cost, maintainability

4. Estimation Questions (10% of technical questions but common in analytical round)

Format: Estimate technical capacity or volume

Sample Questions:

• “Estimate the storage space required for all images on Google Street View”
• “Calculate the number of queries Google handles per second”
• “What is the required internet bandwidth for an average college campus?”
• “Estimate YouTube’s daily storage costs”
• “How many servers does Gmail need?”

What They’re Testing:

• Quantitative reasoning
• Breaking down complex problems
• Making reasonable assumptions

Note: Estimation questions are “way more common than metrics questions at Google” compared to other companies.

---

Google-Specific Topics

Googleyness (Culture Fit) - Evaluated in ALL Rounds

What is “Googleyness”?

Not about being quirky or unconventional. Google evaluates whether you exhibit:

• Comfort with ambiguity - Can you operate without perfect information?
• Bias to action - Do you move quickly or get stuck in analysis paralysis?
• Collaborative nature - Can you build consensus and work across teams?
• Intellectual humility - Can you accept feedback and admit mistakes?
• Passion for technology - Genuine enthusiasm for tech’s potential to improve lives

How It’s Assessed:

• All interviewers evaluate Googleyness alongside their primary focus area
• Behavioral questions target how you react to situations based on values
• “Put your team first, empathize with users, and communicate respectfully”

Common Googleyness Failures:

• Brilliant candidates who can’t demonstrate they’d thrive in collaborative, feedback-heavy culture
• Unable to explain handling constructive criticism
• Not incorporating diverse perspectives
• Being defensive or ego-driven in responses

In Technical Rounds: Show you can:

• Collaborate with engineers respectfully
• Ask for clarification rather than assume
• Accept feedback on your approach
• Credit team members appropriately

Four Core Evaluation Criteria

Every interviewer assesses you on:

1. Role-Related Knowledge - PM skills, product sense, technical understanding
2. General Cognitive Ability - Problem-solving, structured thinking, learning ability
3. Leadership - Influence without authority, ownership, driving outcomes
4. Googleyness - Cultural fit as defined above

Interviewers “take copious notes and file detailed reports” - be thorough and specific.

Product Sense at Google

Google pays “particular attention to creativity, scalability, and user empathy” in product responses. Every product answer should consider:

• Scale - How does this work for millions/billions of users?
• Simplicity - Google values elegant solutions over complex ones
• User-centricity - Start with user problems, not technology
• Global perspective - Consider diverse user bases

Analytical Expectations

Google expects strong analytical thinking:

• Define clear success metrics
• Make data-driven decisions with limited information
• Structure ambiguous problems methodically
• “Focus less on precision and more on clarity—Google cares more about your logic than the final number”

---

Sample Technical Questions from Real Interviews

Technical Explanation (Beginner-Friendly)

1. “Explain what an SDK is to a 7-year-old”
2. “Explain the concept of APIs to a child”
3. “How would you explain cookies to your grandmother?”
4. “What happens when you type google.com and press enter?”

Technical Architecture (Intermediate)

5. “Design a load balancer for Google.com”
6. “What parts of the Gmail tech stack would a ‘schedule email’ feature touch?”
7. “Design a notification system for the Google mobile app”
8. “How would you design a web crawler?”

Technical Trade-offs (Advanced)

9. “SQL vs NoSQL for storing user profiles - what factors matter?”
10. “Client-side vs server-side rendering for a new Google product”
11. “Caching strategy for YouTube video recommendations”
12. “Microservices vs monolithic architecture for a new feature”

System Design (Google Scale)

13. “Design YouTube” (high-level architecture)
14. “Design Google Drive file sharing”
15. “Design a URL shortening service at Google scale”
16. “Design a real-time collaborative editing system (Google Docs)”

Technical Capacity Estimation

17. “Estimate storage required for Google Street View images”
18. “Calculate queries per second for Google Search”
19. “Estimate YouTube’s daily storage costs”
20. “Required bandwidth for streaming to all Gmail users”

---

Preparation Recommendations

Study Plan for 4 Weeks: Total ~50-60 hours

Week 1: Technical Foundations (15 hours)

Systems & Architecture (8 hours):

• Multi-tiered web applications (client, server, database)
• HTTP/HTTPS, DNS, browsers, APIs, REST
• Load balancing, caching, CDNs
• Database fundamentals (SQL vs NoSQL)
• Resources: “System Design Interview” by Alex Xu (Vol 1, first 3 chapters)

Data Structures & Algorithms - Conceptual (4 hours):

• Understand what hash tables, trees, graphs are used for (no coding)
• Know when to use arrays vs linked lists vs hash maps
• Basic algorithm concepts: sorting, searching, traversal
• Resources: GeeksforGeeks “System Design for Product Managers” articles

Cloud & Scale (3 hours):

• Basic cloud concepts (compute, storage, networking)
• Horizontal vs vertical scaling
• Sharding, partitioning, replication
• Resources: Google Cloud architecture docs (conceptual reading)

Week 2: Google Product Knowledge (12 hours)

Google Products Deep Dive (6 hours):

• Use 5+ Google products extensively (Gmail, Drive, Maps, Search, YouTube)
• Understand how they work technically at a high level
• Read product announcements and engineering blog posts
• Resources: Google Blog, Google Engineering Blog

Google Strategy & Culture (3 hours):

• Study Google’s 10-year strategy
• Understand competitive positioning
• Learn about Googleyness and company values
• Resources: Alphabet investor relations, Google careers page

Competitive Analysis (3 hours):

• Compare Google products to competitors
• Understand technical differentiators
• Resources: Tech news sites, product reviews

Week 3: Interview Question Practice (18 hours)

Technical Explanation Practice (6 hours):

• Practice explaining 20 technical concepts to “a child”
• Record yourself or practice with non-technical friends
• Get feedback on clarity and simplicity
• Resources: Create flashcards with concepts; practice daily

System Design Practice (8 hours):

• Practice 10 system design questions at PM level (not engineer level)
• Focus on: clarifying requirements, high-level architecture, APIs, scalability
• Draw diagrams on whiteboard or paper
• Resources: Exponent PM course, IGotAnOffer system design guide

Estimation Practice (4 hours):

• Practice 15 estimation questions using CAV framework (Clarify, Approach, Validate)
• Practice stating assumptions clearly
• Get comfortable with rough math
• Resources: RocketBlocks estimation guide, PM Exercises

Week 4: Product Sense & Mock Interviews (15 hours)

Product Design Questions (8 hours):

• Practice 15 product design questions
• Always include: user problems, metrics, technical feasibility, scale
• Structure: Clarify → User Segments → Pain Points → Solutions → Prioritize → Metrics
• Resources: Product Alliance Google PM course, Exponent

Behavioral Stories - with Googleyness (4 hours):

• Prepare 8-10 STAR stories covering:
  • Failure and resilience
  • Disagreement with manager/engineer
  • Cross-functional collaboration
  • Ambiguity and bias to action
  • Team-first mentality
• Weave in Googleyness traits naturally
• Resources: IGotAnOffer behavioral guide

Mock Interviews (3 hours):

• 2-3 full mock interviews with peers or paid services
• Get feedback on communication style
• Practice whiteboarding system designs
• Resources: Exponent peer matching, Pramp, interviewing.io

---

Interview Tips

Do ✓

Technical Round:

• Draw diagrams to explain systems and architecture
• Start with clarifying questions (scope, constraints, scale)
• Think aloud - interviewers evaluate your thought process
• State assumptions explicitly and justify them
• Break down complex problems into components
• Consider scalability from the start (this is Google!)
• Discuss trade-offs between different approaches
• Connect technical decisions to user impact and business value
• Ask for feedback and iterate on your approach
• Use specific examples from Google products when relevant

All Rounds:

• Demonstrate Googleyness: collaborative, humble, action-oriented
• Structure your answers clearly (frameworks help)
• Show genuine curiosity about Google’s products and mission
• Ask thoughtful questions about the team and product area
• Be data-driven but also acknowledge limitations of data
• Show intellectual humility - admit what you don’t know
• Focus on user problems before jumping to solutions

Don’t ✗

Technical Round:

• Jump straight to solutions without clarifying requirements
• Try to code or get into implementation details
• Pretend to know things you don’t understand
• Ignore scalability considerations (everything at Google is at scale)
• Forget about APIs, data flow, and component interactions
• Over-engineer simple problems
• Make assumptions without stating them
• Skip discussing trade-offs and alternatives
• Focus only on “what” without explaining “why”

All Rounds:

• Be arrogant or dismissive of feedback
• Memorize answers without understanding
• Rush through problems without structure
• Focus on features before understanding user problems
• Ignore the collaborative nature of the PM role
• Speak negatively about previous teams or companies
• Treat the lunch interview as purely social
• Forget to connect answers to user value

Common Failure Modes:

• Candidates who are brilliant but can’t demonstrate collaborative culture fit
• Jumping to solutions before clarifying the problem (lack of structure)
• Can’t explain technical concepts simply (communication failure)
• Ignoring scale implications (everything must work for billions)
• Weak on metrics and data-driven decision making

---

How This Differs from Other Companies

Aspect	Google PM	Amazon PM/PM-T	Meta PM	Microsoft PM
Technical Depth	Highest in FAANG	High (PM-T), Medium (PM)	Medium	Medium
Technical Screening	Dedicated round with engineer	PM-T only	Minimal	Limited
Interview Focus	System design, explanation	Architecture, AWS	Metrics, growth	Enterprise
Technical Background	Strong preference for eng/CS	PM-T requires eng degree	~50% non-technical	Mixed
Culture Emphasis	Googleyness (all rounds)	Leadership Principles	Execution focus	Business value
Estimation Questions	Very common	Common	Less common	Rare
Scale Considerations	Billions of users	Varies by product	Billions for core	Enterprise
Interview Length	4-8 weeks (avg 38 days)	4-6 weeks	4-8 weeks	4-6 weeks
Coding Required	No	No	No	No
Analytical Round	Dedicated round	Integrated	Dedicated	Limited

Key Differentiators for Google:

1. Highest Technical Bar:

• Google has the highest technical bar for PMs in FAANG
• All PMs expected to be technical (vs Amazon’s PM/PM-T split)
• Dedicated technical round with senior engineer

2. Engineering-Driven Culture:

• Google is “more engineering driven” vs Amazon’s “PM driven” culture
• Must have credibility and influence with senior engineers
• Technical depth enables PM effectiveness

3. Googleyness Evaluation:

• Unique cultural assessment across all rounds
• Emphasis on intellectual humility and collaboration
• Can reject brilliant candidates who don’t fit culture

4. Estimation Emphasis:

• Estimation questions “way more common than metrics questions at Google”
• Tests quantitative reasoning and structured thinking
• Must be comfortable with rough math and assumptions

5. Scale Assumptions:

• Everything designed for billions of users
• Scalability is not optional - it’s assumed
• Global, diverse user base considerations

6. Interview Rigor:

• “Interviewers take copious notes and file detailed reports”
• Very structured process with clear evaluation criteria
• Offer rate <5% even with referrals

---

Official Resources

Google-Provided

Google Interview Prep:

• Google Careers: careers.google.com/how-we-hire/interview/
• Google PM Interview Guide (PDF): Available on Google Careers
• Sample interview questions on Google Careers

Company Culture:

• Google’s approach to Googleyness
• Product philosophy and strategy
• Engineering blog: blog.google/technology/

Recommended Third-Party Resources

Interview Prep Platforms:

• Exponent - Google PM Interview Guide (2025 updated)
• IGotAnOffer - Comprehensive Google PM prep with sample answers
• Product Alliance - Google PM Interview Cheat Sheet with insider tips
• RocketBlocks - Practice questions and frameworks
• PM Exercises - Question bank organized by type

Books:

• “Decode and Conquer” by Lewis C. Lin - PM interview fundamentals
• “Cracking the PM Interview” by Gayle McDowell - FAANG PM prep
• “System Design Interview” by Alex Xu (Vol 1) - PM-appropriate depth
• “The Product Manager Interview” (TPMI) by Lewis C. Lin - 30-day study guide

Community Resources:

• Glassdoor: 618 PM interview reviews analyzed (search “Google Product Manager interview”)
• Blind (teamblind.com): Tech employee discussions on Google PM interviews
• Medium: Articles from successful candidates (search “Google PM interview”)
• LinkedIn: Google PM posts and insights

---

Red Flags to Avoid

Technical Round Red Flags

1. Can’t explain technical concepts simply - Core PM skill is bridging technical/non-technical
2. Jumping to solutions without clarifying - Shows lack of structured thinking
3. Ignoring scale considerations - Everything at Google is at massive scale
4. Can’t discuss trade-offs - PMs must evaluate competing approaches
5. Trying to code or getting too detailed - Wrong level of abstraction for PM
6. Making assumptions without stating them - Transparency matters
7. Unfamiliar with basic web architecture - Client-server, APIs, databases are fundamental

Googleyness Red Flags

8. Arrogance or defensiveness - Google values intellectual humility
9. Can’t demonstrate collaboration - “Lone wolf” PMs don’t succeed at Google
10. Negative talk about previous teams - Shows poor cultural fit
11. Can’t handle ambiguity - Google PMs operate with incomplete information
12. No bias to action - Analysis paralysis is a failure mode
13. Weak on user empathy - Products must serve diverse, global users

Product/Analytical Red Flags

14. Feature-first instead of problem-first - Must start with user problems
15. Weak on metrics and data - Data-driven decision making is critical
16. Can’t structure complex problems - Frameworks and clear thinking required
17. Ignoring competitive landscape - Must understand market context
18. Poor communication clarity - Can’t explain thinking clearly

---

Readiness Checklist

Technical Readiness

✓ Can explain 20+ technical concepts simply (APIs, SDKs, HTTP, DNS, caching, load balancing, etc.)

✓ Can design high-level architecture for common systems (messaging, file sharing, video streaming)

✓ Understand client-server model, APIs, databases, and data flow

✓ Can discuss trade-offs: SQL vs NoSQL, scaling strategies, caching approaches

✓ Comfortable drawing architecture diagrams on whiteboard

✓ Understand Google-scale implications (billions of users, global distribution)

✓ Can estimate technical capacity (storage, bandwidth, servers) with reasonable assumptions

✓ Practiced 10+ system design questions at PM level (not engineer level)

Product Readiness

✓ Can design products using structured approach (clarify → users → problems → solutions → metrics)

✓ Practiced 15+ product design questions with emphasis on scale

✓ Can define success metrics for various product types

✓ Understand Google’s product portfolio and strategy deeply

✓ Used 5+ Google products extensively and can critique them

✓ Can perform market sizing and estimation questions using frameworks

✓ Practiced 15+ estimation questions with clear assumptions

Behavioral/Googleyness Readiness

✓ Have 8-10 STAR stories prepared covering key themes:

• Failure and resilience
• Disagreement with manager/engineer
• Cross-functional collaboration
• Ambiguity and decision-making
• Bias to action
• Team-first mentality
• User empathy

✓ Can naturally demonstrate Googleyness traits: comfort with ambiguity, bias to action, collaboration

✓ Prepared thoughtful questions about the team, product, and Google’s strategy

✓ Can articulate “why Google” with genuine passion

Interview Mechanics

✓ Completed 2-3 full mock interviews with feedback

✓ Practiced whiteboarding and verbal communication

✓ Comfortable with 45-minute interview format and pacing

✓ Researched interviewers on LinkedIn (when names provided)

✓ Prepared questions for each interview round type

✓ Know Google’s mission, values, and recent product announcements

---

Timeline Estimate

For Your 4-Week Timeline:

Weeks 1-2 (Foundation Building):

• Study technical fundamentals: 15 hours
• Learn Google products and strategy: 12 hours
• Total: ~27 hours (~2 hours/day)

Week 3 (Practice Intensive):

• Practice technical, estimation, system design questions: 18 hours
• Total: ~18 hours (~2.5 hours/day)

Week 4 (Integration & Polish):

• Product sense practice: 8 hours
• Behavioral prep: 4 hours
• Mock interviews: 3 hours
• Total: ~15 hours (~2 hours/day)

Grand Total: 60 hours over 4 weeks

Week-by-Week Focus:

Week 1: Technical foundations + Google product knowledge
Week 2: Continue learning + start question practice
Week 3: Intensive question practice (technical, estimation, system design)
Week 4: Product sense + behavioral + mocks + final review

Daily Commitment: 2-2.5 hours/day on weekdays, 3-4 hours on weekends

Realistic Assessment:

4 weeks is tight but doable if:

• You have some technical background (even if not CS degree)
• You’re familiar with Google products already
• You can commit 2+ hours daily consistently
• You’re comfortable with structured problem-solving

Consider extending to 6-8 weeks if:

• You’re coming from non-technical background
• You’re new to PM interviews entirely
• You want to be very confident (recommended for Google’s high bar)
• You have limited study time availability

Week 4 Priority Sequence (if time is limited):

1. Technical explanation practice (30%)
2. System design at PM level (25%)
3. Product design questions (20%)
4. Estimation questions (15%)
5. Behavioral stories with Googleyness (10%)

---

Final Thoughts

Google PM interviews are among the most rigorous in the industry, with the highest technical bar in FAANG. However, the good news is:

1. No coding required - You don’t need to write code or solve LeetCode problems
2. Conceptual focus - Understanding architecture matters more than implementation
3. Clear evaluation criteria - Four areas assessed consistently across all rounds
4. Abundant resources - More public prep materials than any other company
5. Structured process - Predictable format allows targeted preparation

The key to success: Demonstrate you can think technically at the right level (architecture not code), communicate complex ideas simply, solve problems structurally, and embody Googleyness (humble, collaborative, action-oriented).

With 4 weeks:

• Focus on technical explanation skills (highest ROI)
• Practice system design at PM level with emphasis on scale
• Prepare strong Googleyness stories
• Use Google products extensively and develop thoughtful critiques
• Do 2-3 quality mock interviews in final week

You have enough time to prepare well if you’re focused and consistent. Good luck!

---

Sources:

• Google Product Management (PM) Interview Cheat Sheet 2025 | Product Alliance
• Google Product Manager (PM) Interview Guide | Sample Questions (2025) - Exponent
• Google Product Manager Interview (questions, process, prep) - IGotAnOffer
• Google Product Manager Interview Questions | Glassdoor
• How to prepare for Google product management interviews - RocketBlocks
• Google System Design Interviews (questions, process, prep) - IGotAnOffer
• Google System Design Interview Questions - GeeksforGeeks
• Estimation Interview Questions | PM Exercises
• Google Vs Amazon Vs Microsoft PM Roles: A Deep Dive - Engineer Seeking FIRE
• The Ultimate PM Interview Study Plan (2025 Guide) - Exponent