Do you see what these questions are asking? You need to combine a depth of knowledge on product sense and AI.

Today’s guide helps you do so.

Not Just Google

Ankit Virmani, former Group Product Manager at Meta, just finished a full AI PM job search - nabbing offers at Cisco, Uber, and Atlassian. He told me something I didn’t expect.

70-80% of his rounds were still traditional behavioral and product sense. The same “tell me about yourself” and “improve Snapchat” stuff. But the one round that showed up at every single top AI company was AI product sense.

To show you exactly what a 10/10 looks like in April 2026, I recorded a full mock with Ankit on one of the hardest AI product sense questions in circulation right now -

The question - “How would you increase Claude Code weekly active users 10x?”

This is the type of question top AI companies actually ask. And what makes the mock realistic is the curveball. Halfway through Ankit’s answer, I threw him a pivot he didn’t see coming.

For Live Coaching

Want live coaching like this from Ankit and I? Apply for our Land PM Job cohort which starts Monday. Here’s our teaching schedule:

This is our third cohort. We have added in both AI PM and PM fundamental mini-courses. This is the only PM cohort I'm aware of that runs dedicated AI PM and PM fundamental mini-courses alongside the core curriculum.

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Why Now

Six months ago, I published the first AI product sense interview guide on the internet. I did a mock with Dr. Bart Jaworski on “How would you double ChatGPT image creation WAU with 3 engineers?”

That guide has been read by 80,000+ people. And in the six months since, I’ve coached another 80 candidates through 2 cohorts - including folks who encountered AI product sense rounds at OpenAI, Anthropic, Figma, Meta, and Amazon.

The round has changed again. Significantly.

In October 2025, AI product sense was a niche round at a handful of AI-native companies. Today, it’s spreading everywhere. Meta literally added it as a 4th interview.

Per IGotAnOffer's deep dive with ex-Meta Sr. Product Leader Audrey, the "Product Sense with AI" round is for IC6+/M1/M2 roles in their Central Products org, where candidates vibe-code a prototype while the interviewer evaluates judgment.

Google’s AI teams test it like Jaclyn, inside existing interviews. Even Stripe and Uber are weaving AI into their product sense rounds now.

And the bar has moved since October.

Today’s Post

I’ve updated everything I know about AI product sense based on 6 months of new coaching data:

1. What Changed Since October 2025

2. How to Pass the Updated Interview

   • 2 practice tools (Claude Skill, Custom GPT)

   • What Ankit did differently from every candidate I’ve coached below a 7

   • The 5 AI-specific thinking shifts that separate strong from weak

3. The Full Breakdown

   • The Ankit mock analyzed in detail (what I scored and why)

   • How the top 5 companies ask this differently in April 2026

   • Where to practice next

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1. What Changed Since October 2025

When I wrote the first guide, I said “this interview doesn’t exist yet, but it’s coming.” Six months later, it’s here.

The round is no longer optional. It’s spreading everywhere.

Ankit categorized the landscape into three tiers based on what he actually experienced during his search -

1. Tier 1 - In Everything. OpenAI, Anthropic, Google DeepMind. AI product sense is part of every interview in some way. At OpenAI, you get questions like “how would you double ChatGPT image creation with just three engineers?” At Anthropic, “how would you increase Claude Code WAU 10x?”

2. Tier 2 - Added to existing loops explicitly. Meta is the biggest shift here. They literally added a 4th interview called “Product Sense with AI” for IC6+/M1/M2 roles. This is specific to the Central Products org. Figma has also added a specific round called ‘AI Product Sense.’

3. Tier 3 - Woven into 1-2 rounds. For instance, LinkedIn asked Ankit about how OpenAI and Anthropic launching into their markets should reshape product strategy in another interview. This is the sneaky one. Your recruiter email won’t mention “AI product sense.” But if you’re interviewing for an AI PM role, expect it.

Here’s the thing Ankit said that hit me hardest.

“Even at companies that don’t have a dedicated AI round, AI fluency is being evaluated inside the regular and traditional product sense round. The bar has very much shifted.”

I’d triple-click on this for you. If your recruiter doesn't list 'AI product sense,' that doesn't mean you won't be tested on it. It means it's embedded inside a round with a different name. The candidates who prep for it specifically are the ones who walk out knowing they nailed it.

The nature of what’s being tested has changed.

In a traditional product sense interview, you’re designing features for a deterministic system. User clicks a button, something predictable happens. You can use CIRCLES. You can follow a template. You can honestly pattern-match your way through it.

That’s the fundamental shift. Traditional frameworks can’t solve for this. You can’t CIRCLES your way through “how would you increase Claude Code WAU 10x?” because the answer requires you to understand how agentic workflows work, what Opus 4.6 is capable of, how slash-loop infrastructure enables proactive behavior, and what Cowork is as a product surface.

The round now decides your level, not just your pass/fail.

This is the insight from our Land PM Job cohort data that blew my mind.

Across 80 cohort candidates, the pattern I keep seeing is that AI product sense correlates more with level placement than behavioral. Candidates who came back saying 'I was expecting L5, I got L4' more often than not pointed to the AI round when we debriefed.

Ankit's framing on this was the clearest I've heard. 'Behavioral gets you through the door. AI product sense is the round that truly decides your offer. The level, the money, the negotiation leverage all flow from this round.

The compensation makes this the highest-stakes round in PM.

The Tier 1 comp data below comes from public Levels.fyi medians and cohort candidates who interviewed at the frontier labs over the last six months -

1. OpenAI - $860K median, ranges from $300K (Manager) to $950K+ (Staff). PPU-driven equity.

2. Meta - $515K median, ranges from $173K (L3) to $2.24M (Senior Director). L7 PMs at $987K median.

3. Google - $473K median, ranges from $182K (APM1) to $2.45M (L9/L10). Group PM at $757K median, public equity.

4. Anthropic - $468K median, ranges $468K-$651K. Pre-IPO equity at $60B+ valuation, which could change the comparison materially over 4 years.

These are public-data US medians for the PM role at each company, not specifically AI PM medians (which Levels doesn’t break out separately). Ankit’s experience and what I’ve seen in cohort placements suggest AI PM roles cluster at or above these medians at frontier labs. Specific offers vary by team, level, and negotiation. AI PM roles in India, Europe, and at non-frontier-lab companies (think enterprise AI, healthcare AI, fintech AI) operate on different curves.

The takeaway from Section 1 - If you’re interviewing for an AI PM role in April 2026, you will face AI product sense. The question is whether you’ve prepared for it differently from traditional product sense. If you’re still using CIRCLES or the old frameworks, you are bringing a knife to a gunfight.

🔒 The rest of this post is for paid subscribers only. You’ll get -

1. The 5 AI-specific thinking shifts with before/after examples from real interviews

2. The full Ankit mock breakdown (what I scored 10/10 and what cost him 1 point)

3. How OpenAI, Anthropic, Google, Meta, and Amazon ask this differently in April 2026

4. 2 practice tools I built (Claude Skill, Custom GPT)

5. Where to go from here

Read more

Aman Goyal just went through an AI PM job search successfully. You know what question he didn’t get? Product design.

Design a pencil for the blind.
How would you create a dating app for Facebook?

These questions used to be the bread and butter of PM interviews. He didn’t get asked a single one. Instead, he did face one round several times: AI system design.

I’ve covered AI product sense, product design, success metrics, and behavioral interviews. Today, I cover AI system design.

Why Now

Companies want to know if you can architect an intelligent system end to end. Not wireframes. Not feature lists. Data pipelines. Model selection trade-offs. Orchestration layers. Agent architectures. Failure modes.

And the stakes are absurd.

At OpenAI, stock-based compensation averages $1.5 million per employee per year. Google and Meta are competing with equally aggressive equity packages for AI talent. Senior AI PM roles at these companies pay $500K-$800K+ in total compensation, with staff-level and above clearing $1M when equity is included.

But here’s the gap that blows my mind. There are hundreds of guides on product sense interviews. Same for system design. But AI system design for PMs? Zero resources exist.

That’s wild. Because many of the top AI companies are now asking it.

So I built the guide myself.

Today’s Post

This is the first and only comprehensive PM AI system design interview guide on the internet:

1. What they evaluate

2. The DASME framework

3. Practice AI tools + mock takeaways

4. Company-by-company breakdowns

5. Anti-patterns to avoid and how to fix them

6. 64-question practice bank + 2 worked examples

Subscribe now

Want live coaching through the AI PM job search? Apply for my Land PM Job cohort. Next Cohort starts May 4. Both of the prior cohorts sold out, so secure your seat.

I’m giving a free webinar on getting AI PM interviews next week. Join us.

1. What They Evaluate

This is not an engineering system design interview.

You are not being compared against software engineers. You don’t need to whiteboard load balancers or discuss database sharding algorithms.

But you absolutely need to go deeper than a standard product design answer.

Technical Fluency - 30-40% of the score

Can you speak intelligently about model selection? Do you know when to use an LLM versus a traditional ML model? Can you articulate why an XGBoost classifier might be better than GPT-4 for churn prediction?

This is the dimension where most PM candidates fail. Not because they need to write code. But because they freeze when the interviewer asks “are you going to use an LLM or an ML model for this?”

One candidate I coached told me the interviewer asked about F1 scores. She said she’d have to check. Interview was over in their minds.

System Architecture Thinking - 25-30%

Can you draw a coherent diagram showing how data flows through the system? Can you identify the distinct components and explain how they connect?

Product Judgment Within Technical Constraints - 20-25%

Your user segmentation and pain point analysis still matter. But they need to serve the system design, not replace it.

Trade-off Articulation - 10-15%

Can you proactively surface trade-offs without being asked? Latency versus accuracy. Cloud versus on-premise. LLM versus ML model. The best candidates name these trade-offs before the interviewer has to prompt them.

How it differs from other cases

In a product design or product sense interview, you focus on users, pain points, solutions, and success metrics. The deliverable is a product concept.

In an AI system design interview, you still start with users and pain points. But the deliverable is an architecture diagram showing data flows, model choices, agent roles, orchestration patterns, and failure handling. You spend 60% of your time on the technical system.

The candidates who get rejected treat it like a product design question. They spend 30 minutes on user personas and pain points, then sketch a vague “AI layer” at the end.

The ratio should be flipped. 30-40% product framing. 60-70% system architecture.

Quote me on this: “If you spend more time on personas than on your system diagram, you will not pass this round.”

🔒 The rest of this post is for paid subscribers only. You’ll get -

1. The DASME framework with architecture diagrams, model selection table, and exact time allocations

2. 3 practice tools I built to help you prepare (Claude Skill, Custom GPT, Gemini Gem)

3. How 5 top AI companies ask this question differently

4. 7 anti-patterns with exact fixes

5. 64 practice questions with category guidance and 2 full worked examples (search/retrieval and content moderation)

Read more

I’ve coached 200+ PM candidates. 30+ landed AI PM offers in the last 12 months at OpenAI, Anthropic, Google, Meta, and Amazon.

And what I’ve watched happen to the interview process is wild.

Candidates who would have cruised through a PM loop in 2023 are getting rejected.

The AI PM interview in 2026 tests a completely different set of skills. Most candidates are studying for the old test.

Mock Example

To show you what the new test looks like, I recorded a full, unedited mock interview with Dr. Bart Jaworski (12,000+ PMs helped, former Microsoft AI PM):

Watch it. Then read the breakdown below. (I break down the 10 specific things I did in this mock that most candidates miss, with a pinnable infographic, in the paid section.)

Want live coaching like this three times a week? Apply for my Land PM Job cohort (Cohort 3, May 4, 75 seats).

Why Become an AI PM

The competition is for modern AI PM roles is brutal because the roles pay so well:

If you want to break in, you can’t bring the old playbook.

Today’s Post

I’ve put together the ultimate guide to PM behavioral interviews in 2026:

1. What’s Changed and Why the Old Prep Fails

2. How to Pass the New Interview:

   • A custom GPT, Claude Skill, and Gemini Gem to grade your responses

   • 10 takeaways from my mock to emulate

   • The 6 questions you must nail

3. The Reference Vault:

   • Real questions by company

   • Interview prep bank

   • Cheat sheet

Subscribe now

1. What’s Changed and Why the Old Prep Fails

I’ve seen five big shifts in working with candidates.

Change 1 - They test whether you’ve built AI, not whether you understand it

The old interview accepted “I understand how transformers work.”

The new one asks: Tell me about a time your model degraded in production and what you did.

They’ll probe technical details to verify you drove the work. If you can’t name the architecture, the eval metrics, and the business impact, they assume you were adjacent. Not driving.

One candidate I coached at Google told me:

“They asked me what the F1 score was. I said I’d have to check. Interview was over in their minds.”

Change 2 - Vibe coding is a real round now

Google India. Figma. Perplexity. v0. Netflix. Stripe.

PMs are being asked to build prototypes in 45 minutes using Cursor, Bolt, or Lovable. I wrote the web’s first vibe coding interview guide because this caught so many candidates off guard. It’s also been confirmed on Blind.

If you’ve never opened these tools, you will fail this round. No framework saves you. You need reps.

Change 3 - AI product sense replaced traditional product sense

Google removed the standalone technical interview for PMs entirely. OpenAI made AI product sense a required round.

The questions sound similar (”design a feature for X”) but the evaluation is different. They want you to separate model-layer from application-layer problems, address safety without being prompted, and prioritize with real math. Not “high/medium/low.” Actual estimates with numbers attached.

Change 4 - Behavioral questions got harder

“Tell me about a time you failed” became “Walk me through an AI product decision you made that seemed right but you’d approach differently now.”

“Tell me about a trade-off” became “Describe a time you chose between model accuracy and serving latency, and explain the technical reasoning.”

Generic STAR stories don’t survive these questions. You need AI-specific depth in every answer.

Change 5 - Safety is tested everywhere

Anthropic has a dedicated AI safety & ethics round. OpenAI embeds it throughout. Google tests it inside “Googleyness.”

If you hit minute 40 of a case without mentioning safety, you’ve told them you don’t understand AI product management. You don’t need a separate safety answer. You need safety woven into everything.

These five shifts add up to one thing: the prep that worked in 2023 gets you rejected in 2026.

I built 3 practice tools and broke down the 6 questions that actually decide AI PM offers. Here's the full system.

The rest of this post is for paid subscribers only. You’ll get:

1. The 6 behavioral questions every AI PM company asks, with fresh answers for 3 candidate archetypes (career changer, lateral mover, engineer pivot)

2. Real questions by company (OpenAI, Anthropic, Google, Meta, Amazon, Netflix, Nvidia)

3. 3 practice tools I built: a Claude Skill, Custom GPT, and Gemini Gem that grade your responses

4. The complete 84-question bank (downloadable)

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“I think we’ve achieved AGI.”

Whether or not you agree with his definition, something real has shifted. AI agents can now do work that creates economic value. They can research, write, build, and execute multi-step workflows autonomously.

So the question I’ve been asking myself: if AGI is here, what does that mean for job search?

I think the answer is that we can build the first product in the world that actually automates a job search end to end. Not a chatbot. Not a resume template. A system that does the work while you sleep.

I started building one. Then I saw this tweet blow up:

I had to investigate. Spent the last week running Cowork through a full job search workflow.

The tweet is technically accurate. You can point Cowork at job boards with your resume, and it fills forms and submits.

But it’s the wrong strategy, and the wrong tool.

Mass-applying with AI doesn’t work. And Claude Cowork isn’t the right harness for the job (yet).

You need a system that helps you apply to a few targeted roles. And the harness needs to be customizable.

That harness is Claude Code - with a Job Search OS.

The people getting hired in 2026 look different. They apply to fewer roles, but each one is surgically targeted. Their resumes never contain a fabricated bullet. They have referrals stacked before they submit. And they spend 20 minutes a day on their search instead of 3 hours.

I know this because I’ve coached hundreds of candidates through job searches. I run a job search cohort (Cohort 3 starts May 4, 75 seats). I’ve placed people at OpenAI, Anthropic, Meta AI, and Google in the last year.

Over two thousand people now use my PM Operating System. I spent the last 6 months encoding the same depth of knowledge into a system for the full job search funnel: from discovering roles to landing offers.

What Your Morning Looks Like

30-minute one-time setup. Then:

• You open your laptop. Your daily briefing is waiting. The OS scanned your target companies for new postings in the last 24 hours. The top roles that match your profile are scored and ranked. A customized resume for each one, built from your real experience. Already reviewed and corrected. Ready to submit.

• Below the roles: your outreach for the day. Draft messages personalized to each person. Follow-ups for recent connections. Referral requests for roles you applied to. Nudges for referrals that have gone quiet.

• Prep for your upcoming interviews. The questions that company actually asks (from web research plus insider data from hundreds of candidate debriefs), the interviewer’s background, recent product news, and a game plan for your specific candidacy gaps. Mock interviews grade your answers and tell you which stories to swap in.

• After the interview. Every question categorized. Every answer scored. The exact moments where you left value on the table, with rewrites. A personalized thank-you email referencing what you actually discussed. Each interview makes the next one sharper.

• Your daily time: 20-30 minutes. The system handles the rest. The OS can apply to as many roles as match your criteria. The difference is that every single application is tailored, reviewed, and backed by a referral strategy. Volume AND precision.

If you’re full-time job searching after a layoff, this is a no-brainer. The OS does in 20 minutes what used to take 3 hours. The math on ROI is simple: the average job switch leads to a 10-15% raise. At a $200K salary, that’s $20-30K. This costs $49.

Introducing the Job Search OS

I want everyone using this to be operating at the level of the best job searchers I’ve coached. So I’ve put together a copy-paste system to go from zero to a fully automated job search.

This is more than a collection of prompts. This is months of figuring out what actually works. Hundreds of iterations. Testing, improving, learning.

It’s the actual system I use with my coaching clients and cohort members. Not theory. Not templates from the internet. Not bloat.

18 skills. That’s it. Not 200 skills with filler, not a pile of files you’ll never open. 18 skills, each one mapping to a specific step in my system for getting interviews. Every file earns its place. Nothing extra. The bare minimum you need and nothing else.

How to Get It

You have two options to get the Job Search OS:

1. Buy it one-time on Gumroad for $49

2. Join my Founders Plan for $250

   • Get access to all of my digital products (including PM OS and prompt library)

   • Plus a year of the newsletter

   • And my AI bundle

Get the Job Search OS ($49)

Upgrade to Founding Plan

What You Get

What’s Inside

Here’s a small preview:

Today’s Deep Dive

I’m covering everything you need to use the Job Search OS:

1. How to install the Job Search OS

2. Using the Job Search OS (every skill, every workflow, with screenshots)

3. Pro tips, mistakes, and FAQ

Putting it all together, it’s the most comprehensive job search system for Claude Code + Cowork available anywhere.

This post is for subscribers in the Founding Member plan

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This is what a Senior AI PM at Google’s Github looks like:

If you want to break into AI PM or a technical PM role, you definitely want a Github. If you want to break into any PM role, you should strongly consider one.

Today’s post is how to build one that stands out.

The GitHub Reality Check

All PM candidates have resumes. 17% have a portfolio. Only 24% have a Github.

One interpretation might be: these aren’t that important.

But here’s what hiring managers told me when I interviewed 10+ AI PMs leaders at top companies: if there’s a Github linked, they will check it.

You see, a strong GitHub signals three things that certificates and resumes can’t:

1. You actually build things (not just talk about building)

2. You understand how technical teams work

3. You can navigate the tools engineers use daily

Shubham’s GitHub helped him transition from Dev Rel to Senior AI PM at Google Cloud.

But There Are No Resources

There’s literally not a single guide on the web on how PMs should put together their own Githubs:

So I had to build one for you.

Today’s Post

I’ve put together the web’s first guide on PM Githubs:

1. What is Github and Why do Devs Use It

2. What Makes Shubham’s Github Work

3. How to Create Your Github

4. What to Avoid

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1. What is Github and Why do Devs Use It

Github is like the Google Docs for software projects.

When a developer writes code, they save it to GitHub. When another developer wants to improve that code, they can see the full history of changes, suggest edits, and track what worked and what didn’t.

Just like Google Docs for PMs (except even better with history).

And just like every PM writes docs, but not all use Google Docs, every developer uses Git, but not every developer uses Github.

There are alternatives like GitLab and Bitbucket. But they all run on Git underneath.

Git provides two things professional developers can’t work without:

1. Version Control: Every change is saved. If something breaks, developers can revert to any previous version. They never lose work.

2. Collaboration: Multiple people can work on the same codebase without overwriting each other’s changes. GitHub tracks who changed what and when.

Github adds a third benefit on top: it’s a public portfolio. Open source projects live on GitHub. Developers showcase their work, contribute to popular projects, and build reputation through their profile.

For developers, GitHub is standard infrastructure. For PMs, it’s optional. That’s exactly why it matters.

When you have a GitHub profile as a PM, you signal something hiring managers rarely see: you build things. You understand the tools your engineering team uses daily. You’ve crossed the line from talking about products to shipping them.

Most PMs list skills on their resume. PMs with GitHub profiles prove those skills with working code.

That proof is what opens doors.

2. What Makes Shubham’s Github Work

Normally, the transition from DevRel to PM is almost impossible. Especially when moving from one company to another. Usually, my advice is to move internally.

How did Shubham manage to do it with an external switch? And how can you replicate it?

For Shubham, his Github marketed him.

Google reached out to him because of it (and the marketing he does of it on X). The best Githubs do that. They act as inbound lead magnets for recruiters.

And when companies reach out to you, you are much more likely to go from interview to offer.

But even if your Github is not a lead magnet, it’s a big differentiator atop your resume:

The latest PMs I placed at OpenAI, Anthropic, Meta AI all had Githubs. They didn’t have 76K star repositories, either. But the Githubs still helped the PMs stand out.

Of course, you can’t have a bad github. That’s an anti-signal! So let’s help you create a Github that actually helps, and give you the roadmap to one that even markets you, like Shubham’s.

What paid subscribers get below:

• The 6 elements that made Shubham’s GitHub get him hired at Google

• Step-by-step guide to building your PM GitHub from zero (with Cursor/Claude Code)

• The PM GitHub Starter Kit: templates, prompts, and a 3-week checklist (fork and go)

• 50 GitHub project ideas mapped to PM skills (infographic)

• The 6 mistakes I see candidates make that kill their chances

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How would you measure the success of GPT-6?
What evals would you look at for the success of our AI agent launch?

Sound tough, right?

These are the types of questions companies are asking in AI product success metrics interviews.

It’s a 30-45 minute case interview that everyone from OpenAI to Meta - and even companies like Ford - are taking up.

So if you want to land a high-paying AI PM job, it’s a must to master.

But There is No Content

Unfortunately, there is literally ZERO content online about these questions!

Everything you find online is just about success metrics.

But success metrics for AI are quite different:

1. You need to consider offline evals

2. You have to handle the non-deterministic nature of AI

3. You're always balancing latency against output quality

4. Models drift over time

   And so much more…

That’s why you need a guide to the AI product success metrics interview specifically.

Continuing my AI PM Interview Series

I’ve been working to help you crush AI PM interviews. We’ve covered AI product sense and AI product design.

Today, we’re back with the next most important interview to nail: AI product success metrics.

Today’s Post

I’ve put together the web’s deepest guide to the AI success metrics interview:

1. Mock interview

2. What they are evaluating

3. The framework to use to ace these

4. The companies asking, their formats, and questions

5. Anti-patterns that kill candidates

6. 83-question practice bank

7. 3 worked examples

8. My practice GPT

Subscribe now

1. Mock Interview

To get yourself into the right mindset to ace this case, I’ve recorded an end-to-end mock interview on this topic.

We answer a question that many companies have been asking:

How would you measure the success of our new agents launch?

Do you want my coaching to perform like this? Join my 12-week accelerator where we prepare you on every step of the job search:

Apply for the Cohort

It starts Monday. We only have 2 seats left, and the next one will be all the way in May. So if you’ll be job searching soon, join.

2. What They Are Evaluating

I talked to a few hiring managers and successful candidates. Here’s how to think about what they’re looking for. They want you to demonstrate:

• Structured problem approach (15%): ideally with a custom framework that’s easy to follow

• Metric selection & rationale (25%): with a strong hierarchy that addresses topics like gaming

• Measurement & implementation (20%): you need to be able to to show exactly how you’ll operationalize metrics

• Tradeoffs & risks (15%): some candidates forget this altogether, but they want to see deep tradeoff analysis

• AI-specific understanding (25%): they want you to demonstrate deep AI metrics fluency

So how do you ace this rubric? That’s the rest of today’s deep dive: the framework to use, how companies vary in what they’re looking for, and worked examples.

Read more

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Annual subscribers get a free year of 9 premium products: Dovetail, Arize, Linear, Descript, Reforge Build, DeepSky, Relay.app, Magic Patterns, and Mobbin (worth $28,336).

The AI PM Behavioral Interview

I’ve coached dozens of PMs through OpenAI, Anthropic, Google, and Meta AI PM processes this year.

Many folks clear the tough case and technical rounds only to get a rejection.

Their problem? AI PM behavioral interviews.

So, on Tuesday, I released the PM Behavioral Interview Guide with the 3 Laws that govern every behavioral interview.

Today’s guide is for AI PM roles specifically.

Today’s Post

These are the techniques that helped PMs I coach land AI PM offers at OpenAI, Anthropic, and Google this year:

1. Why AI PM behavioral is different

2. Tell Me About Yourself for AI PMs

3. How to flip weaknesses into strengths

4. The 5 AI PM behavioral categories with scripted responses

5. 40 AI PM-specific questions

6. My custom GPT to practice

7. Common mistakes

Subscribe now

This is Part 5 of my AI PM Interview series. For part 1, check out The AI PM Interview Guide. For part 2, check out The AI Product Sense Guide. For part 3, check out the Vibe Coding Interview Guide. For part 4, check out my OpenAI Interview Guide.

1. Why AI PM Behavioral Is Different

Regular PM behavioral tests whether you can communicate, lead, and make decisions.

AI PM behavioral tests all that plus four additional dimensions.

1. Whether you’ve actually shipped AI products

Not side projects. Not prototypes. Production AI that serves real users. They’ll dig deep into technical details to verify you’re not faking it.

2. Whether you can work with ML engineers

This is its own skill. ML development cycles are different. Model iteration is different. The PM-engineer dynamic is different. They want proof you’ve navigated this.

3. Whether you understand AI-specific tradeoffs

Accuracy vs latency. Model complexity vs cost. Explainability vs performance. These decisions define AI PM work. You need stories that demonstrate you’ve made them.

4. Whether you can handle AI failures gracefully

Models break in production. Hallucinations happen. Bias surfaces. They want to know you’ve been through this and handled it well.

The 3 Laws from Tuesday’s post still apply… But the execution is completely different.

The rest of this post is for paid subscribers only. You don’t want to miss:

• All 5 behavioral categories with full scripted responses

• 40 AI PM-specific practice questions real companies ask

• My custom GPT to practice yourself (worth the price of subscription itself)

Read more

No offer.

The feedback?

We found someone else more qualified than you.

That is a polite lie.

When I go in and diagnose the problem, what I almost always learn is the reason this is actually happening is they are messing up the behavioral interviews.

Because the reality is, even in 2025, basic behavioral questions really matter to whether you get the offer.

So this week, I’m releasing two articles:

1. The PM Behavioral Interview Guide

2. The AI PM Behavioral Interview Guide

Today is the foundational piece.

Today’s Post

After coaching 100+ mentees this year and hiring over 50 PMs over my career, I’ve distilled behavioral interviews into 3 universal laws that govern everything.

We’ll be applying them to the 12 most common behavioral questions:

1. The mindset you need to win

2. The 12 questions you must prepare

3. The 3 laws that govern your responses

4. Applying the laws to the 12 questions

5. The improvement framework

6. Most common mistakes

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1. The Mindset You Need to Win

Before we get into the questions and the laws though, we have to talk mindset. Because if you get your mindset wrong, you are hopeless to begin with.

Here’s the mindset you need to have: confidence you are enough and can do this.

I’ve worked with countless candidates who have “all of the buts” syndrome.

It looks like this.

When I say that they need to speak with confidence:

But I struggle with imposter syndrome.

Or when I say they need to speak in a more concise manner:

I understand, but interview time I just can’t do it.

These ‘buts’ are endless!

And it’s what holds them back.

I was coaching someone who didn’t land a job for four months due to insecurities after a layoff. Week after week, we talked confidence. 2 weeks ago? He landed a $280K TC PM job.

So you need to start this article by changing your frame.

Throw out the ‘buts.’

We’re going to have the confidence. I like how one of my favorite public speaking coaches, Vinh Giang, puts it:

You already know how to do all this well. You already are great at using your voice to talk about yourself.

Trust us.

This piece is going to give you the scaffolding and frameworks to pull it out of you.

2. The 12 Questions You Must Prepare

Before we dive into the laws, you have to know what you’re up against.

These are the tough questions you need to prepare for, ranked by prevalence:

1. Tell me about yourself

2. What is your current pay?

3. What are your compensation expectations?

4. Why do you want to work here?

5. Why this job?

6. Why are you leaving your current job?

7. What is your greatest weakness?

8. What is your biggest failure?

9. Fast forward three years. What will you be then?

10. What’s something everyone takes for granted that you think is hogwash?

11. What work accomplishment are you most proud of?

12. Describe a scenario in which you had to say no

The top 3 account for the majority of rejections I see. Not because they’re hard conceptually. Because candidates completely misplay them.

Let’s fix that.

3. The 3 Laws

The rest of this piece is for paid subscribers only. I cover:

• The 3 laws, plus:

• Real question responses to the 12 most common questions

• My mega prompt + Claude skill for feedback on your transcripts

• All of the advice I’ve learned to give after getting 100s of students offers

(Honestly, just the Claude skill alone is worth the $15 subscription)

Read more

• In 2025, 2x as many people move into the role as the year before.

• Between January of last year and October of this year, over 12,000+ people globally moved into AI PM roles.

How do I know these specific numbers? I’ve teamed up with Alex Hamilton and the amazing team at Live Data to get you all the details.

This report explores who’s hiring, how fast roles are evolving, and what this means for Product Managers everywhere.

Today’s Post

1. The Big Picture

2. Hiring Trends: Who’s Hiring

3. Educational Backgrounds

4. Retention

5. Industry Dynamics

6. Promotion Timelines

7. AI PM Compensation

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First: About the Data

Any good analyst starts with understanding the dataset. Let’s start there.

We’ve analyzed 18,145 professionals who held AI PM titles, with 12,339 qualifying hires between January 2024 and October 2025 in the Live Data dataset.

Although the dataset is global, there is a heavy US concentration (47%).

Now, into the report…

1. The Big Picture

Here’s all the top findings in a picture:

I’ve been knee deep in AI PM for the last year. What surprised me from this specific study?

1. Backgrounds: 60% of AI PMs don’t come from computer science. The path from Marketing Manager to AI PM exists at scale. So does Analytics Lead to AI PM. And Product Owner to AI PM. I’ll show you which backgrounds companies actually value and why domain expertise often trumps technical credentials.

2. Compensation: Senior AI PMs at top companies earn between $286K and $569K. But the spread across companies is massive. OpenAI pays differently than Anthropic. Google’s structure differs from Amazon’s. The data shows exactly where the premium compensation is.

3. Promotion speed: Internal moves to AI PM happen in a median of 21 months. But Amazon promotes in under 2 years while Verizon takes 2.6 years. IBM sits at 2.0 years, Google at 2.5 years. These timelines tell you where to focus.

4. Geographic distribution: While 18 countries have 50+ AI PM hires, three markets dominate. The US leads with 5,765 hires, but India and the UK show different patterns.

Now let’s go deeper on all of this.

The full report covers who’s building AI PM teams internally versus buying talent externally, which companies promote fastest, where compensation clusters, and which career paths actually work.

You’ll see specific company-by-company hiring breakdowns, promotion timelines across 15+ major employers, retention patterns by seniority level, and the educational backgrounds that companies actually value.

Read more

You’ll find plenty of regular product sense interview guides. But AI product sense specifically?

It literally doesn’t exist. That’s wild.

Because OpenAI, Anthropic, Google AI, and Meta AI are ALL asking AI product sense questions.

And what works for AI product sense is not the same as product sense.

This is a 45-minute case interview where they give you a specific AI product problem, and you need to speed-run through the entire product management process - but with AI-specific considerations layered throughout.

So you need a guide to it.

The Mock Interview: ChatGPT Image Creation

To show you exactly what this looks like in practice, I did a live mock interview with fellow cohort instructor Dr. Bart Jaworski, who has helped over 12,000 PMs land jobs and was a PM at Microsoft AI:

The question: How would you increase weekly active users of ChatGPT image creation from 175M to 350M in 3 months with only 3 engineers?

This is the type of question OpenAI actually asks. It combines growth thinking, resource constraints, and AI-specific considerations into one messy, realistic problem.

Notice how the interview isn’t a monologue. It’s a discussion. I check in constantly, adjust my framework based on feedback, and demonstrate how I think through ambiguity in real-time.

What Makes AI Product Sense Different?

If you’ve read my complete guide to the product sense interview, you know the traditional format well. But AI product sense adds three critical layers that traditional product interviews don’t test.

Layer 1: Model Considerations

You’re not just thinking about features. You’re thinking about how the underlying AI model impacts what’s possible.

Should you work with the research team on model improvements, or focus on application-level changes? Can the model even support what you’re proposing, or are you designing for a capability that doesn’t exist yet?

Layer 2: AI Safety & Ethics

Every AI product decision has safety implications.

• How do you prevent misuse?

• What about bias (or debate about bias) in your outputs?

• How do you handle edge cases where AI could cause harm?

These aren’t nice-to-haves - they’re core to the product strategy at companies like Anthropic and OpenAI.

Layer 3: Unique AI Metrics

Traditional product metrics still matter, but AI products require new measurement approaches:

• How do you measure hallucination rates?

• What about model performance versus user satisfaction?

• How do you know if your AI feature is actually solving the problem it claims to solve?

Why This Interview Matters More Than Ever

Let me be blunt: The AI product sense interview is now more important than the technical interview at most top AI companies.

Here’s what’s changed:

• Google removed the technical interview entirely from their PM process

• OpenAI has made AI product sense a required round for all PM candidates

• Anthropic uses it to evaluate a candidate’s product thinking

The reason? Traditional product sense interviews test creativity, data acumen, and user understanding.

But they don’t test whether you can think strategically about AI capabilities, limitations, and implications.

Companies building AI products need PMs who can bridge the gap between cutting-edge research and real user needs. They need people who understand what’s possible with current models, what requires research breakthroughs, and how to build products that are both powerful and safe.

What You’ll Learn in the Deep Dive

The video above shows you the raw interview. But that’s just the starting point.

In the paid deep dive below, I break down exactly what made this interview successful - and more importantly, what separates candidates who pass from those who fail at companies like OpenAI and Anthropic.

You’ll get:

1. The key takeaways that made my example answer work

2. The 7 types of questions you might get

   + A framework implementation for each

   + Practice questions for each

3. My Custom GPT to help you practice

This is everything I coach candidates on when helping them land $500K+ offers at top AI companies. And it’s what you need to stand out in the hardest PM interview format that exists right now.

Read more

• “I want to break into AI PM but can’t get past the resume screen.”

• “I’ve been applying to AI roles for months with no response.”

• “How do I stand out when everyone is suddenly pivoting to AI?”

The AI PM job market is the most competitive it’s ever been. Everyone wants in. But most people are doing it wrong.

After coaching 100s of PMs through pivots into AI roles at companies like OpenAI, Anthropic, Google DeepMind, and Microsoft, I’ve developed a systematic approach that builds on my proven interview system.

And here’s what people say works best:

“Your AI-specific guidance helped me go from zero AI experience to landing an AI PM offer at Meta in 3 months.”

So today, I’m sharing the complete system: The AI PM Job Search System.

This includes exactly how to use AI tools to automate and accelerate every step of your search.

Should You Even Target AI PM Roles Now?

Before we dive into tactics, let’s do a market reality check.

Supply of AI PMs: Exploding

Everyone is pivoting to AI. Product managers, consultants, engineers, even marketers. The number of people targeting AI PM roles has increased dramatically year over year.

But here’s the good news: most of them aren’t qualified and aren’t approaching it systematically.

Demand for AI PMs: Through the Roof

Meanwhile, AI PM headcount is growing faster than any other PM specialization:

• OpenAI grew AI PM team by 150% in 2024-2025

• Anthropic increased AI PM hiring by 200%

• Google, Microsoft, Meta all have 50+ AI PM openings each

• Even traditional tech companies (Uber, Airbnb, Netflix) are building AI PM teams

AI PM roles now represent 20% of all PM openings at top tech companies, up from 10% in 2024, and <2% in 2023.

The Equilibrium: High Competition, But Massive Opportunity

Yes, competition is fierce. But if you approach this systematically and use AI tools to 10x your efficiency, you can stand out.

Here are some of the top companies with open AI PM postings right now:

• OpenAI, Anthropic, Google DeepMind, Microsoft AI

• AI-first startups: Perplexity, Character.AI, Runway, Glean

• Big tech AI divisions: Meta AI, Amazon AI, Apple AI

• Traditional tech going AI: Uber, Airbnb, Spotify, Netflix

Most of the companies have been consistently hiring all year. And the hiring managers just feel like they can’t find the right talent:

So, the reality is: there hasn’t been a better time to break into AI PM if you do it right.

The AI PM Job Search System: 9 Steps

Here’s the system that’s worked for 100s of people I’ve coached.

The key insight? Use AI tools at every step to work smarter, not harder.

Read more

Here’s the funny thing that I’ve learned coaching PM job seekers over the last 5 years: the 18% who have a portfolio are seeing outsized success in the job market.

PM Portfolio = Your Job Search Hack

At this point, you might be asking: How does a PM portfolio actually help?

To answer this question, first ask: where do we even showcase our portfolio? How do people get there?

Most people mess up at this stage itself. They publish it to a website and then complain when they get no traffic. You publish a portfolio three places, and each translates to a different benefit:

1. On the open web → so people can discover you

2. Atop your resume → so people can learn more details

3. In the featured section of your LinkedIn → so you can convert more inbound

Most PMs actually have no idea what I just said for #3. So let’s quickly cover that. This is where the featured section is located:

15/20 PM profiles I just reviewed aren’t even using this space - what a huge wasted opportunity! It’s the #3 section on your profile, so it is one of the most important spaces to optimize.

Inbound LinkedIn is the #1 source of PM jobs for my mentees this year (76/124 job offers).

And the LinkedIn game is all about optimizing:

• Profile visits

• Profile visit → message conversion rate

This makes the third section on the page really important! A portfolio is a rich canvas to further explain yourself than just words on the page.

Indeed, with such low adoption of PM portfolios, it is your job search hack.

The ROI has Never Been Better

And the crazy thing is: the PM portfolio has completely changed with AI.

With modern vibe coding tools, you can create much richer portfolios much faster.

The ROI equation has never been better:

1. Cost: 30 minutes

2. Benefits:

   • Getting more inbound

   • More interviews after applications

   • Succeeding more in interviews

That’s an insane ROI. Especially compared to the low ROI you’d get with activities dropping your resume to yet another company.

As a result, I consider this the single most powerful job search hack that AI has enabled. More than customizing resumes, writing cover letters, or generating work products.

This is Especially True for AI PM Roles

Let’s take a second to understand why AI PM roles are growing so fast (at 120% per year when PM roles are only growing at 1% per year).

The reason is that Boards are telling their CEOs that they need to change for AI. They need to have more revenue per headcount, they need to build AI more into their product, and AI needs to power their GTM (go-to-market) motion.

Those CEOs then go to the VPs of Product and assign them those priorities. The VPs of Product realize that they don’t have any AI experts on their team:

• Their PMs aren’t at the bleeding edge of adopting AI tools

• Their PMs barely understand AI evals, AI prototyping, and AI discovery

This creates the argument to open up headcount for AI PMs. And that’s why the role is growing so fast - from 10 to 20% of PM roles in the last year:

This means that as an AI PM you need to demonstrate AI expertise. If you don’t have AI expertise yet, you need to take on:

• Side projects

• Fractional work

• Free consulting

• Certificates

And other activities that don’t normally show up well in a resume. That’s where a portfolio can come in: it can help you flip weaknesses into strengths.

(Which is the #1 most important thing to do in any job application.)

Today’s Deep Dive

So I’ve put together an ultimate guide on how to create your PM portfolio - including my full PM portfolio (only for subscribers). I’ve tested all the tools with the best prompts and context. This is the dead fastest way to get an amazing portfolio:

1. Which Tool to Use

2. How to Vibe Code Your PM Portfolio

3. How to Make a Portfolio for AI PM Roles

4. The 30 minute, 8 Hour, and 40 Hour Portfolios

5. The Most Common Portfolio Mistakes

Read more

But it’s a sprawling set of 50+ newsletter posts, 40+ podcast episodes, and 300+ social media posts.

Today, I’m putting all the most important resources together into a step-by-step curriculum:

Here’s all those links.

CORE CURRICULUM

101: The Core Concepts

• Right Overall Strategy for Interviews: Exactly how you should be preparing for interviews and coming in with the right mindset to win

• What Interviewers Care About: Empathizing with the other side so you can put your best self forward

• How to Win at Remote Interviews: Techniques to stand out when you aren’t in-person

201: Behavioral Interviews

• Conquer Behavioral Interviews: Since these are 85% of questions, you need to master the frameworks that turn stories into offers

• Ace Tell Me About Yourself: Transform the most common question into your most powerful 2-minute pitch

• Answering the Top 10 Questions: The best way to learn is to see what actual full, scripted responses look like

• Product Estimation Questions: Master the analytical frameworks that show you can think quantitatively about products

301: Case Interviews

• Product Sense Interview: This is the most common case interview, so learn the frameworks to master it

• Product Design Interview: Learn the systematic approach to designing products that users actually want

• Product Strategy Interview: Less common but high-stakes - show you can think like a CEO

• Vibe Coding Interview: Handle AI coding challenges without looking like a deer in headlights

• Product Execution Interview: The case that separates dreamers from doers - prove you can ship

• Product Metrics Interview: Most PMs fail this because they pick vanity metrics instead of business drivers

• System Design Interview: Think through technical architecture at the level engineering expects

GUEST SPEAKERS DEPARTMENT

302: Advice from Experts

• Phyl Terry: Group-based job search strategies that 3x your interview rate

• Gayle McDowell: From the Author of "Cracking the PM Interview," the structured approach that works

• Lewis Lin: From the Author of "Decode and Conquer," frameworks used by 500K+ professionals

• Diego Granados: FAANG insider tactics from someone who actually works at Google

• Dr. Nancy Li: How to Ace PM Interviews

• Marily Nika: How to Ace AI PM Interviews

GETTING INTERVIEWS DEPARTMENT

303: How to Get Interviews

• Step-by-Step Guidance: Go from zero interviews to multiple offers in 90 days or less

• How to Build Your PM Portfolio: Create work samples that prove you can do the job

• How to Write Your Cover Letter: Get past ATS filters and into human hands

• How to Customize Your Resume: 6 tactics that make recruiters actually notice you

304: Advanced Search Tactics

• The Small Market Recruiting Strategy: Land opportunities in markets outside the big cities

• The 1-Hour/ 7-Hour/ 40-Hour Per Week Job Search: Match your effort to your timeline and situation

• How to Win Referrals: Turn your network into a recruiting machine with proven scripts (Advanced Referrals Tips)

• How to Ace Homework + Presentations: The toughest part of modern job searches. Here’s how to differentiate

305: AI PM Specialization

• How to Land an AI PM Interview: Get into the highest-growth PM specialty before everyone else catches on

• How to Use AI Job Search Tools: 10x your application volume without sacrificing quality

306: Transitions

• How to Become a PM without Experience: The proven path for career changers who start from zero

• How to Transition from Designer: Translate design skills into PM language that hiring managers understand

• How to Transition from Software Engineer: Bridge from building products to defining what gets built

LEADERSHIP DEPARTMENT

401: Landing Leadership Roles

• Product Leadership Interviews: Navigate the subtle differences that separate IC interviews from leadership evaluations

• Director+ Interviews: Avoid getting down-leveled with strategies from 6 successful senior PM hires

BIG TECH DEPARTMENT

402: Landing Roles at Top Tech

• Microsoft & Apple: Insider strategies and cultural nuances for landing offers at both companies

• Google: Crack Google's unique process and understand what they actually evaluate

• OpenAI: Position yourself for the most competitive PM roles in AI

• Meta: Learn from 12 current and former Meta PMs who know the system inside out

Now that we’ve helped you through the content I have written so far. Let’s cover some more advanced topics.

The Rest of Today’s Deep Dive

I want to cover some juicy topics that I haven’t had much of a chance to get into. These are what my mentees continually have challenges with:

1. How to handle layoffs and firings in interviews

2. How to use AI tools and notes to “cheat” in interviews

3. The number one method to practice that not enough of you are doing

4. The ultimate guide to a killer remote interview setup

5. How the PM interview has changed over time

6. The top 150 interview questions to practice

Let’s get into it…

Read more

In fact, they are the category that is driving overall PM job listings up:

Companies currently hiring AI PMs include many of the top names in tech: Atlassian, Figma, Airtable, Anthropic, OpenAI, Google, and many more….

And the roles are listed to go past $300K+ compensation! Which is the second point: AI PMs are paid better than other PMs.

Best of all: you can break in without a technical or PM background.

Since this is the job opportunity of a lifetime, I wanted to give you a clear roadmap.

Today’s Post

This roadmap is designed to take you from zero to a $300K+ AI PM role in under 12 months - even if you don’t have a technical or PM background:

1. Complete Roadmap to Getting an AI PM Job

2. Survey of the AI PM Job Market

3. How to Get AI PM Interviews

4. How to Ace the Interviews

5. Real Interview Questions

6. AI PM Pay and Negotiation

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1. Complete Roadmap to Getting an AI PM Job

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PART 1 - Master the Skills + Knowledge

AI Knowledge

• AI Basics: The first principles of AI so that you can transform your products with new AI applications

• Context Engineering: Break down of RAG vs fine-tuning vs prompt engineering and when to use each

• Prompt Engineering: Deep dive into all the research on how to write an amazing system prompt for your AI agents and product features

AI PM Skills

• AI Evals: The crucial testing suites to guard against nightmare scenarios, hallucinations, lack of quality, and other LLM-specific issues

• AI Experimentation: A critical skill for all PMs to rapidly growth test front-end changes quickly, without reliance on engineering or design

• AI Agents: You have to be able to use AI agents for your own productivity, as well as be able to build them into your products

• AI Feature Execution: You should be able to build features where AI is baked into the cake, not sprinkled on top

• AI Product Strategy: It’s important to be able to drive not just feature execution, but the high-level strategy; here’s how

AI PM Tools:

• AI Discovery: How to use AI across all 5 stages of product discovery, Wonder → Explore → Make → Impact

• AI Prototyping: The critical pairing to the PRD and a crucial tool for exploring the solution space now that LLMs can code

• AI Co-Pilot: How to create a co-pilot that drives success for you and helps you be more productive

PART 2 - Get the Interview

Strategy

• How to Get $700K+ AI PM jobs: The exact strategic advice for students, non-top 50 tech PMs, and career switchers to switch into these lucrative jobs

• The 2025 Strategies That Work: The meta-advice to decide which job channels to focus on and which one’s aren’t worth your time

• How Actual Job Seekers Have Succeeded: In-depth case studies into 5 successful job seekers in this market, and how they did it

Use The Right Tools

• The AI Job Search Tools To Use: Complete survey of all the tools that are being used by candidates to enhance their job search

• How to Get People’s Contact Information: Guide into a really under-used but very powerful technique to get on hiring manager’s radars

Outbound

• System: Step-by-step guide on how to execute an application system that actually gets interviews, and doesn’t get lost in the application blackhole

• Break Down: How to break through in a tough job market that’s flooded with laid off PMs everywhere

• How To Write Cold Emails: This technique still works in 2025, and is very powerful for standing out in this market

• How to Build Work Products: This is often the differentiator between outreach that gets ignored and that which gets a response

Strong Applications

• How to Write an AI PM Resume: It’s not the same as a regular PM resume. You should add in lots of AI-specific stuff

• How to Build Your AI PM Portfolio: It’s not easy as you may think, but you can build one that drives interviews

• How to Write a Good AI PM Cover Letter: It’s a lost art, but you can actually write a cover letter that helps you stand out

Inbound

• Inbound Job Search Overview: To get senior or hard-to-get roles, you need to get recruiter outreach; this is how

• How to Optimize Linkedin Profile: This is the #1 most important tool in your job search, here’s how to go from good to great

• LinkedIn Posting: This is the ultimate hack to drive profile views and increase recruiter outreach—but beware of your employer’s side-eye

PART 3 - Ace the Interview

AI Product Sense

• Product Sense Interviews: They trip up many, but they are still a fundamental skill in the AI era

• Product Design Interviews: It’s one of the most common case interviews, so you have to be ready with the skills

• Product Strategy Interviews: AI strategy is tougher than ever, so you need to be good at product strategy

AI Product Execution

• Product Execution Interviews: How to break through the flip-side of strategy interviews: the details

• Product Metrics Interviews: PM leaders love to test PMs on how well they can figure out the metrics

• Success Metrics Interview: It’s the most common execution question, so you should be very good at it

AI Technical

• Technical Interviews: AI PMs have to be ready for a multitude of technical questions, so it’s not something to ignore

• System Design Interviews: It’s something that the Google and Stripe’s of the world love to ask, so stay up on it

Behavioral

• The Framework to Conquer Behavioral Interviews Forever: These are still going to be 70% of your questions, so prepare heavily for them

• How to Ace Tell Me About Yourself: Most people squander the first question in every interview - here’s how to seize the opportunity

Presentation & Homework

• How to Ace the Presentation Round: There are so many companies asking for presentation these days that you better be prepared

• How to Ace the Homework: Since take home assignments are everywhere, you should bring a sophisticated approach to answering them

PART 4 - Win the Negotiation

• The Art of Negotiating an AI PM Job Offer: How exactly to bring data to the table, how much hard-ball to play, and the techniques that work beyond money

• How to Avoid Down-Leveling: It’s the most common thing that happens when you go upmarket, here’s how not to let it happen to you

• How to Get a Raise: Even in this market, it’s possible to get 25% or even 100% bumps, but you need to be strategic

Now let’s get into all the advanced strategy and information you need to secure the job…

2. Survey of the AI PM Job Market

I’ve often said you need a clear sense of the market to have a differentiated strategy. Knowing exactly where to focus your applications can save months of wasted effort.

These are all the AI Companies you should be considering. The companies below represent over $2 trillion in market cap and are actively competing for AI PM talent:

Read more

The #1 thing that people come to me for coaching about is:

• “I’ve been on the market for months, and I can’t get any interviews.”

• “I’ve just gotten back on the job market, and what I’m doing isn’t working.”

• “I want to target US-based employers but can’t get interviews. How can I?”

Consistently, the interview stage is where people struggle with getting a job.

After coaching 100s of candidates through the processes, I’ve just about perfected the systematic steps you need to take. And that’s what I get the best feedback about:

“Your step-by-step guidance was the most helpful in landing an offer. It helped me know what to do next at any point in time.”

So, I’m putting it all together in today’s newsletter: The How to Get Interviews System.

(This includes exactly how to build an AI agent to assist you with the process.)

Subscribe now

P.S. I’m working on an exclusive group coaching offer for a small group of job searching PMs. If you are interested, apply here.

Should You Even Job Search Now? A Quick Check on the Job Market

Before we get there, let’s check if it even makes sense to pop your head up right now and search for a job.

Supply of Job Seekers: Decreasing

So far this year, US-based tech companies have announced 744K job cuts. That’s the highest year to date since 2020 (when 1.6M job cuts had been announced). You might think that means: don’t job search! But, the last three months have seen a pleasant drop in intensity of cuts:

So, it’s an overall improving picture, but didn’t start from a great base given Q1’s layoff bloodbath.

Demand for Tech Workers: Increasing

Meanwhile, overall tech jobs are up 45% from their lows. There were two particular periods of quick growth at the starts of 2024 and 2025 that helped increase demand:

So, demand is also an overall improving picture as well.

Overall Economics of Job Searching: Stronger Than In Recent Memory

This has led to a different dynamic from the past few years. The past few years have been horrible for job seekers, because supply was up but demand was down.

Finally, now, supply is decreasing and demand is increasing. As a result:

It’s as good a time as any in the past few years to pop your head up for a job.

You just have to target the right companies.

Who is Hiring

Where should you target? At the winning companies (like Databricks and Coinbase). There, tech and PM jobs are seeing healthy growth year over year:

In organizations with rolling layoffs like Meta, Google, and Amazon, the growth is slower. But, it’s still growth (2.7-5.5%). PM roles are being eliminated in money losing products but added in profitable and AI products.

So, overall, there hasn’t been a better time in years to apply to the top companies.

The How to Get Interviews System: Step-by-Step

How do you capture this timing that is better than ever?

This is where my proven step-by-step process comes in.

Read more

A new interview’s broken into the Google PM Process:

If you’re like many PMs, your reaction to this news was along the lines of the most upvoted Reddit comment:

I've been a PM for a while now and I don't know what any of this is.

That’s what today’s piece is for.

Yes, It’s Real

Now I know what you’re asking:

• Is Google really doing this?

• And why didn’t the recruiter warn them?

I reached out to several Google PMs and interview coaches.

Here’s what I learned: right now this is relegated to the Google AI PM roles in India. It is not a standard part of Google’s process for all PMs in the US.

As of now. It very well could be in the future. In fact, I expect it to.

That’s because many other companies are already using this interview.

I’ve coached several people who have encountered this round, including PMs interviewing at v0, Bolt, Figma, and Perplexity (ie, the hottest companies around).

And I forecast that many more companies will be adding this round.

Today’s Post

So, ahead of that, in today’s post, I’m going to build up all the knowledge you need to know to nail this interview:

1. The Basics

   • What is vibe coding and what is the format of the interview

   • The new PM skill set and why they are asking (plus why more will)

2. Nailing the Interview

   • What separates a winning from a failing response on this interview

   • My framework to use for any vibe coding interview

   • What to do if you’re totally caught off guard

3. Examples and Practice

   • The most common mistakes I’ve seen coaching candidates on it

   • The ultimate vibe coding interview question bank

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1. The Basics

1.1 What is vibe coding and what is the format of the interview

Vibe coding, in this context, is the use of an AI coding (eg, Cursor, Windsurf, or Replit) or AI prototyping tool (eg, Lovable, Bolt, Base44, or v0).

My mentees have encountered three different formats of this interview

1. The 45-minute prototyping case

2. The product design case with a prototyping component

3. The homework assignment where a prototype is mentioned in the prompt

Here’s how each actually unfolds in the room.

Type 1: The 45-minute prototyping case

This first type of case is what the Google AI PM interviewee in India faced.

Typically, the prompt is clear: use any vibe coding tool of your choice to create a version of x feature. The prompts fall into three major buckets:

• Design X feature for us

• Design Y feature on Z famous product

• Build a prototype of X new 0 to 1 product

In this type of case, you need to build a structured framework to design the feature before just prototyping it.

But a lot of the assessment is how well you prototype.

Type 2: The product design case with a prototyping component

This second case is anywhere from 30-60 minutes and typically involves a more challenging design prompt. For instance:

• Design Google Maps for the Blind

• How would you prototype a Facebook Dating app

These types of cases require a strong product design case up front (identifying user needs and brainstorming creative solutions), followed by a good but quick prototyping session.

Type 3: The homework assignment where a prototype is mentioned in the prompt

This final type of vibe coding interview has been used at places as mainstream as Stripe and Netflix.

They give you a broad prompt, like:

Design a Netflix product to support Partner Studios.

Then you have to go through all the elements of a strong product design interview.

Multiple candidates I’ve coached had to submit a final 1 pager with a link to the prototype.

So, that covers the three main types of PM vibe coding interviews!

1.2. The new PM skillset and why they’re asking (plus more will in the future)

The nature of the PM role is undergoing its biggest shift since the shift from input to output metrics ~5 years ago.

AI is ushering in a new era of AI PMs, who:

• Build AI features, getting into technical details like evals

• Use AI to focus on high leverage tasks

• And prototype with AI

That’s why PM interviews are now focusing on all three of these topics.

Just like the shift to output metrics and strategy led to the growth of product metrics and product strategy interviews, this latest shift to AI PMs is driving the growth of the product vibe coding interview.

Many companies are still in the process of adapting to this AI-first reality. Their PMs don’t have licenses to AI prototyping and vibe coding tools.

But as those companies fall further behind and replace their old IT policies with AI-first ones, the nature of the PM job will shift there as well.

And a short while after the job shifts, the interviews will have to shift as well.

Interviews exist to find candidates who can do the job: and vibe coding (aka AI prototyping) is a core part of the PM job for forward-looking companies.

AI prototyping tools are a better way to convey ideas than a PRD, and help PMs actually think through all the edge cases & flows around the periphery.

So the growth of this interview type is inevitable.

2. Nailing the Interview

2.1 What separates a winning from a failing response in this interview

Having worked with so many different candidates who have failed and succeeded on this round, here’s what I’ve learned.

Read more

Metrics interviews are deceptively difficult:

• How would you measure the launch of GPT-4.5?

• Instagram stories are suddenly down 7% today. What do you do?

• If we were to launch a new pricing plan tomorrow, how would you measure success?

These are questions we all can answer to some degree… but answer in a way that’s impressive for a senior PM audience at top companies? That’s quite a bit harder.

And these questions are really relevant: they actually simulate what being a PM is like. Which means you’ve likely already seen several “normal” guides on this interview.

But to succeed in today’s brutal job market requires you to not just follow the standard playbooks, but do things to stand out.

That’s what today’s piece is for.

Tried and Tested Strategies

In my career, I've sat on both sides of the table for 100s of metrics interviews. So I had a good idea of what to include in this post.

But over the last 3 months, I’ve taken it up a notch. I’ve been working with several PMs stuck in the interview stage product metrics.

All of them have now gotten jobs. So, today, I’m ready to crack open the advice column for you. This will include “earned advice” you can only get from having sat on all three sides of the aisle: interviewee, interviewer, and coach.

Structure

Here’s the outline for our journey over the next 14,000 words.

Part 1: The Basics

• History of the Product Metrics Interview

• Common Users of the Product Metrics Interview

• What Doe the Product Metrics Interview Actually Test?

Part 2: The Toolkit

• Principles + Frameworks

• Unconventional Techniques to Stand Out

• Top 93 Questions to Prepare in 5 Key Categories

Part 3: 8 Question Response Examples

• Behavioral Questions

• Real Case Interview Examples

Part 4: Practice Smart with My Interview GPT

It’s the value of a $500 course and $200 coaching call - as part of one of the 100 articles you receive a year for just $150.

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Part 1: The Basics

1.1 History of the Product Metrics Interview

Believe it or not, PM metrics questions are amongst the oldest of PM interview questions.

But they really took off as the PM case interview took off ~2008-2009:

Why? Because they’re amongst the most realistic assessments of the PM job. These are the types of assessments most PMs have to make - especially in big companies.

While they’re not as sexy as product sense, or product design, some type of metrics interview question began embedding itself in nearly every big tech company’s hiring process:

• Microsoft calls it “Analytical”

• Google calls it “Analytics & Metrics”

• Meta used to called it “Execution” and now calls it “Analytical Thinking”

As big tech goes, so go medium-size companies - a few years later.

And as go mid-size companies go startups - a few years further delayed.

This process continued so that, as of 2025, a majority of PM interview processes will throw you at least one metrics question.

Meaning: any job-searching PM has to be prepared to master them.

1.2 Most Common Users of the Product Metrics Interview

Who specifically uses products metrics interviews?

These are who I know to:

• MAANG: Meta, Amazon, Apple, Netflix, Google… they all are using metrics questions.

• Companies with case interviews: Almost all companies that have PM case interviews have one that is some variant of success metrics. I’ve advised people who faced these questions at all of the below.

  • Marketplaces: Doordash, Uber, Wayfair

  • SaaS: Slack, Notion, Atlassian, HubSpot

  • AI: OpenAI, Anthropic, Jasper, Midjourney

  • HealthTech: Ro, Zocdoc, Noom, Headspace

  • FinTech: Stripe, Square, Robinhood, Plaid

  • Gaming: Epic Games, Roblox, Riot Games, Zynga

• Companies with PM founders: Companies like Asana, Coda, and others with founders of PM backgrounds use the interview

The places where you won’t see product metrics interview questions are those that focus on homework, behavioral questions, and presentations.

1.3 What does a Product Metrics Interview test?

The funny thing about the product metrics interview is companies differ on whether there is a right answer! There are two main flavors of companies:

1. “There is a right answer, let’s evaluate the percent they got”

   This is exemplified by companies like DoorDash and Wayfair, where if you miss a major part of the case, you will likely not pass
   

2. “There is a rubric, and we’ll grade them against skills, but there’s not right answer”

   This is what you’ll find at most big tech companies like Google and Meta (with Amazon as a notable exception), where they focus on the skills you demonstrate

So the first thing you want to do is figure out what kind of company you are interviewing at. Your recruiter should be able to help you with this information. If they don’t, be sure to send strategic cold emails and personalized LinkedIn invites to people who were formerly PMs at the company to have them spill the tea. Also check your network to see if you know someone who works there and is willing to share.

If you’re at a company with a rubric, this is typically how those rubrics are structured (this is 90% of what the rubric we had at Apollo.io when I was VP of Product):

1. Structured Problem Approach: Did you ask the right clarifying questions and do the right thinking before diving in to understand all elements of the case?

   • Strong Pass candidates identify all stakeholders, talk about all sides of the marketplace, talk about positive and negative metrics, and identify trade-offs well

2. Strategic Metric Selection: Did you choose the right overall goals for metrics?

   • Strong Pass candidates choose the right things to look at in terms of metrics, holistically covering everything

3. Technical Operationalization: Did you operationalize metrics well?

   • Strong Pass candidates choose the right specific definitions of metrics that are sensitive, trustworthy, efficient, debuggable, interpretable & actionable, and inclusive/fair

4. Trade-off Evaluation: Did you address the right positive and negative sides of a change? Do you understand the both sides and tradeoffs?

   • Strong Pass candidates always speak to tradeoffs, cover both positive and negative sides, and speak to potential guardrail/tripwire metrics

Company-Specific Nuances

There’s often some company-specific nuances, too. Several I’m aware of are:

• Meta: Scale thinking (billions of users) and 2 cases per interview

• Amazon: Leadership principles demonstration and customer obsession

• Google: Technical depth and estimation skills

• Stripe: Technical problem-solving and precision in quantification

• DoorDash: A/B testing expertise and marketplace dynamics understanding

Types of Cases

There are 5 major types of PM metrics cases you will see:

1. Success Metrics: Test your ability to define and measure a new product or feature’s success.

   How would you measure the success of launching GPT-4.5? If we introduced a new pricing plan, what metrics would you track to evaluate its impact?

2. Diagnostics: Test your ability to diagnose a sudden metric change systematically.

   Instagram Stories dropped 7% today. Why? DAUs are down 5%. How would you investigate?

3. Experimentation: Test your ability to design experiments and measure outcomes.

   How would you design an A/B test to measure the impact of a new onboarding flow? If we want to test a new recommendation algorithm, what metrics would you track?

4. Metric Definition: Test your ability to create measurable, goal-aligned metrics.

   How would you define a metric to measure user engagement on a new social media feature? What metric would you create to track the adoption of a new payment feature?

5. Trade-off Analysis: Test your ability to measure trade-offs with positive and negative metrics.

   If we prioritize faster content loading but it reduces content quality, how would you measure the trade-offs? How would you assess the impact of increasing ad frequency on user retention?

Clearly, each is different. So we’ll include an entire example of one of each at the end of this piece. But before that, let’s go through the common principles.

Part 2: The Principles

So now that we know all the basics, let’s get into the meat: how do you actually rock the Product Metrics interview?

Read more

This article was updated on April 23, 2026

What if you took notes on all of the interviews you’ve ever conducted?

In the newsletter, I try to bring you data that you can’t find anywhere else.

That’s what Mikhail Shcheglov, CPO at Umico—formerly at Bolt, OLX, and Yandex—compiled. He collected and coded the results of over 500 PM interviews he conducted.

In today’s post, we’re going to break down what 500 PM interviews reveal (at least from one interviewer):

1. The Skills that Drive Offers

2. How Skills Vary by Level

3. 🔒 How to Read your Interviewer

4. 🔒 Advanced Tactics to Impress Interviewers

5. 🔒 How to Avoid Being Down-Leveled during Interviews

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And, if you enjoy this, don’t Mikhail’s Substack, Corporate Waters:

Corporate waters.

Actionable insights into product management and leadership to skyrocket your career.

By Mikhail Shcheglov

1. The Skills That Drive Offers

Is it business skills or technical skills that matter most? That is the question.

Mikhail coded each person from 1-5 on all these skills. Then, we looked at the correlation of people’s ratings to whether they got an offer or not.

These are the results:

As you can see, business skills rated the highest and technical skills the lowest.

So there you have it. PM roles mirror the change in PM generally:

• Business skills—like the ability to think about strategy and impact sizing—really matter

• Technical skills are useful—especially in certain roles—but demonstrating them in an interview isn’t going to guarantee an offer

Now let’s go a layer deeper on this data. Let’s look at the top 3 skills, the middle, and the bottom 3.

1.1 The Three Top Skills to Demonstrate in Interviews

The three key skills that had the highest correlation with the positive outcome were business skills, structured thinking, and strategic thinking.

Now, you may be asking, is this only for senior roles?

Interestingly - this was the same across all the seniority levels.

How to Demonstrate Each Skill

Since every PM needs to demonstrate each skill, let’s go deeper on what each is:

1. Business skills - these are understanding the business model (e.g. marketplaces/SaaS/Ads). To do well here, you need to have a mastery of how to make money and the metrics associated with it.

2. Structured thinking - this is all about putting a structure to how you navigate cases and how you give answers. Notice how executives generally speak in “the rule of 3”? It works for PM interviews as well.

3. Strategic thinking - you have to think beyond the feature to analyze market position and create a compelling future of winning monetarily.

You might be nodding, “I already know all this.” Here’s where it gets interesting…

Why People Fail to Demonstrate the 3 Key Skills

Breaking down the interview notes of those who didn’t get coded on those key skills, we noticed 3 predictable patterns:

❌ Forgetting to clarify the goal

Interviewers purposefully conceal the goal. Depending on the goal the case might have different solution structures. Skipping this part and jumping into problem solving is a red flag. It can slide for junior-mid level candidates, but it can be rejection-worthy for Senior/GPM/Director level roles.

❌ Not understanding the business model

Where most candidates crumbled is that they couldn’t differentiate product strategy (build a business) and product design (build a feature). When Mikhail was expecting a candidate to take a step back and look at the bigger picture - the macro, the business model, the operations; most candidates shrinked their responses to the “customer-problem-solution” framework.

❌ Not having a solution framework

Many candidates didn’t outline the solution framework and just randomly jazzed through ideas. They immediately down scored themselves on problem solving. Over the past 5 years there was only a single candidate that managed to crack a case open without sketching down a framework in advance. He was a Director-level candidate. No matter what maturity level you are at, do not risk it.

1.2 The Skills that Help, But Aren’t Most Important

Now, let’s take a look at those skills that got a middling impact rating:

• Storytelling

• Culture-Fit

• Data Fluency

• Customer Empathy

• People Management Skills

What can we take away from this?

Storytelling Matters

Well, at the top, storytelling is important.

Product managers are the communication hubs that converge business and customer needs with the technical capabilities. If a candidate is too boring and emotionally dry - they will just be less effective.

The key indicator of boredom is when the interviewer loses track of what the candidate is saying. This psychological switch happens with verbose and emotionally dry candidates.

PMs we’ve never hired were the ones who were doing the dry and robotic framework recital.

The ones that we were excited to hire were down to earth, speaking a simple and engaging language.

This is crucial - as hiring managers are expecting to work with a real person.

Above all, storytelling positively correlates with maturity.

• The lower maturity candidates tend to compensate for the lack of experience with memorization.

• On the flipside, high maturity candidates speak freely from experience and can improvise.

Don’t Get Dinged for Culture-Fit

Interviewers are looking at the candidate through a magnifier lens.

Any sign of toxicity or off behavior would be amplified in high-stress situations during day-to-day work.

Key red flags for are:

• Victim vibes towards the past employer

• “Know-it-all” attitudes

• Blaming or even poking the interviewer

Dilemmas between highly-skilled and culturally off candidates are rare (maybe 1 in a 100). In the absolute majority of cases, such candidates are rejected.

Data, empathy, and people management aren’t that important

All these skills, of course, matter! You can’t be a 0 on data or empathy or people management.

BUT, making these the emphasis of your interview should not be a focus!

When these get rated your top skills, you’re not likely to get the offer.

1.3 The Skills You Shouldn’t Focus on

Three skills rated at the bottom of the correlation:

• Creativity

• Project Management

• Technical Skills

What’s the takeaway?

All of these matter, but none will win you an offer.

Creativity Isn’t Enough (On Its Own)

Being creative or thinking out of the box is a relevant skill, but on its own it will not grant you an offer.

Some candidates played it to their advantage by suggesting both “low-effort mvp” and a “moonshot” solution for the problem.

However, in most cases, creativity by itself is not a key skill required of a product manager.

Project Management can be a Red flag

Sometimes we all have to put on a project management hat and execute the milestone by the deadline.

But project management skills themselves have very little impact on your chances of getting an offer.

On the contrary, putting too much emphasis on project management, agile and similar certifications can backfire.

We personally treat it as a mild red flag during the CV review stage.

Technical Skills Only Matter for Technical Roles

Technical skills have the lowest impact on the outcomes of the offer.

You need to understand the basic concepts, but no one would expect you to code or be well versed in technical architecture.

There are platform/technical product roles—that’s the case where this changes.

And that concludes our skills x offer analysis. Now let’s look at skills a different way…

2. How Skills Vary by Level

The data reveals fascinating patterns across seniority levels.

Here’s how PMs did on the top 3 most important skills:

The data reveals some predictable - but also insightful things.

Strategic Thinking Is a Differentiator

PM and SPM candidates consistently rated poorly on strategic thinking (averages of 2 and 2.5 respectively).

This goes to show how much you can differentiate yourself at early stages by demonstrating strategy.

Here’s how:

1. Always bring it back to the bigger picture before you end a case

2. Show an awareness of how the business wins, not just products and features

Not that Many People Have Great Business Skills

The big trend in PM right now is to demand more business impact, impact sizing, and growth modeling from PMs.

But of the three important skills, people tend to score pretty poorly on it.

So if you can talk about:

• How you built a growth model

• How you might estimate business metrics from product metrics

You’ll have a big leg up on the competition.

Expectations rise

What makes for successful APMs differs dramatically from what makes successful Directors.

For junior roles, execution and customer empathy carry the day. As you rise to senior levels, the entire evaluation framework shifts—strategic vision and business impact become paramount.

At Director level, something fascinating happens in the data: scores drop across all skills, not because Directors lack capability, but because they're measured against an entirely different standard.

So if you’re at this senior level, pay especially close attention to the three key skills.

And that covers our ‘by level’ analysis. Now let’s move to what we can learn about interviewers…

3. How to Read your Interviewer

There’s some fascinating sings your interviewer is giving you. You just have to read them right. Here’s how:

Read more

This article was updated on April 23, 2026

If there is one key takeaway from my research of 5 job seekers who found jobs in this market, it’s that referrals are the key to job searching.

They do 3 really important things:

1. They get you a deeper look from recruiters

2. They get you a better look even during interviews

3. They give you crucial information about the company’s hiring

This is a critical insight. They don’t just make it easier to get interviews - they help even afterwards.

Referrals worked for me to get my jobs at Google and Epic Games. So I have firsthand experience with how powerful they can be.

But They Aren’t Working For Many of You

Surprisingly, though, many of you come to me complaining about referrals:

“Even though i get referrals, I don’t get any interviews”

“I have applied via referral for 25 jobs and not had a single response.”

What’s going on here, and how can these people turn it around?

I decided to work with 4 of these people to turn it around. The result is today’s piece.

Today’s Post

I’ve broken down why this works and its details, today I’m going to give you the tactics to debug problems you are having with it:

1. The Number 1 Strategy

2. Why Yours Referrals Aren’t Working

3. 🔒 The Framework to Track Referrals

4. 🔒 How Exactly to Get Referrals in Hard Places

5. 🔒 Case Studies in Referrals to Get Jobs (With Exact Messages)

6. 🔒 Most Common Mistakes

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(Email productgrowthppp at gmail dot com for affordable PPP options.)

1. The Number 1 Strategy

I have to be honest:

When it comes to a reliable strategy to break into jobs, there is no better method than referrals.

And I have data to back it up. Dr. Nancy Li and I did a survey of 100 PMs who got jobs last year.

Here’s how the techniques broke down for them:

Of course, inbound does well also, and we talked about that last week.

But nearly 1/2 of PMs found their last job via referral. It shows the power of the channel.

It also shows the channel is ubiquitous…

And yet, despite their popularity, many job seekers struggle to make referrals work effectively for them.

2. Why Your Referrals Aren’t Working

With so many people pursuing referrals as their strategy to get their next job, you need a differentiated strategy to get referrals.

I am finding that people fall into one of three traps:

1. They are pursuing weak referrals - these are referrals from people who haven’t worked with you, and just drop you into the ATS (which people do because their company has a monetary bonus).

2. Their resume doesn’t meet the minimum qualifications - you may have gotten the person to refer you, but the recruiter gives a 6-second look at your resume and decides you don’t meet the minimum requirements (eg, years as a PM in that industry).

3. They don’t follow up after the referral - you assume that the referral is enough, but you’re not checking in and fade into the background, instead of remaining top of mind.

The way to avoid these mistakes is to create a system.

Referrals aren’t a “set it and forget it” strategy.

3. The Framework to Track Referrals

Here’s my system to manage referrals well (complete with Google Sheets and Notion templates):

Read more

This article was updated on April 23, 2026

So many people are focused on applying to jobs. But what if you could get the jobs to come to you?

The Best Jobs Come to You

Let me share a secret about my own career:

• How did I get my job as a Senior PM at Google? They came to me.

• How did I get my Head of Product Growth job at Affirm? They came to me.

• How did I get my VP of Product job at Apollo.io? They came to me.

The truth is: the best jobs will come to you.

I informally messaged 15 PMs working at the hot AI companies last week. 12/15 of them? The AI company came to them. Not the other way around.

All the best jobs—especially as you get more senior—have a budget for recruiters to reach out to the unicorn candidates currently employed in that position.

If you want one of those jobs, you need to get on their radars.

Tested Techniques

Today’s post equips you with market-tested techniques.

These techniques worked for people THIS year.

So far, I’ve gotten >10 people jobs with inbound. Here are a few samplings of what they said:

Today’s Post

I’ve interviewed 6 product recruiters, advised 10 people in this market, and used the results to put together the web’s most tactical guide on how to get jobs to come to YOU:

1. The Drivers of Inbound

2. 🔒 Optimizing the 4 Channels

   • LinkedIn Profile Optimization

   • Architecting The Places You Work

   • How to Write Content to Drive Inbound

   • How to Get on Podcasts and Speak at Conferences

3. 🔒 Advanced Topic: How to Develop Your Unicorn-Market Fit

4. 🔒 Top Mistakes in Inbound I’ve Seen Advising

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1. The Drivers of Inbound

If you remember only one thing from this post, remember the 4 channels that drive inbound:

1. LinkedIn profile: this is the biggest and most important

2. Where you worked: this is a sad reality that drives a lot

3. Content: a double-edged sword that can pay off

4. Speaking gigs: credible but infrequent

Now let’s explain each of these channels and how to master them.

2. Optimizing the 4 Channels

Channel 1 - LinkedIn Profile Optimization

By far the #1 most important thing you can do to drive Inbound is to optimize your LinkedIn.

So let’s break it down.

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