Dr. Nancy Li - Director of Product

$1.5M.
46%.
4,000 people.

That’s not a funding round.

That’s OpenAI’s talent retention strategy.

To keep its best AI engineers, OpenAI reportedly granted ~𝟒,𝟎𝟎𝟎 𝐞𝐦𝐩𝐥𝐨𝐲𝐞𝐞𝐬 𝐚𝐧 𝐚𝐯𝐞𝐫𝐚𝐠𝐞 𝐨𝐟 $𝟏.𝟓𝐌 𝐞𝐚𝐜𝐡 𝐢𝐧 𝐬𝐭𝐨𝐜𝐤 𝐨𝐩𝐭𝐢𝐨𝐧𝐬 — the most aggressive employee equity package in startup history.

For context:
- Google before its IPO? ~$210K per employee
- Adjusted for inflation, OpenAI’s number is ~7× Google
- Compared to other pre-IPO tech giants? ~18× higher

This isn’t generosity.

This is survival.

💸 The hidden cost of AI

- In 2025, 46% of OpenAI’s revenue is expected to go to salary + benefits

- Google pre-IPO: 15%

- Facebook pre-IPO: 6%

In other words:

AI companies aren’t burning cash on GPUs alone — they’re burning it on humans.

Meta is reportedly handing out compensation packages worth hundreds of millions — even up to $1B for elite AI leaders.

OpenAI has paid multi-million-dollar retention bonuses just to keep engineers from walking.

Why?

Because a small group of people can shift the trajectory of an entire company — or an entire industry.


⚠️ The risk no one likes to talk about
- Operating losses are growing fast
- Early investors are getting diluted
- Future AI data centers will cost tens of billions
- Stock-based compensation is expected to rise another $3B by 2030

OpenAI even removed its 6-month lockup, allowing new hires to sell stock sooner — great for employees, expensive for the company.

So the real question isn’t:
“Is AI the future?”

It’s:
“Is this a sustainable business model — or a talent-driven bubble?”

One thing is clear:
In the AI era, the scarcest resource isn’t compute.

It’s 𝐩𝐞𝐨𝐩𝐥𝐞 𝐰𝐡𝐨 𝐤𝐧𝐨𝐰 𝐡𝐨𝐰 𝐭𝐨 𝐮𝐬𝐞 𝐢𝐭.


🎯 Want to break into companies like OpenAI?

Start by understanding how they hire.

I put together a free 𝐓𝐨𝐩 𝟔𝟎 𝐎𝐩𝐞𝐧𝐀𝐈 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 — real signals, real expectations, no fluff.

Download it here: www.pmaccelerator.io/OpenAI-Interview

#PMAccelerator #AIPMBootcamp

1 day ago | [YT] | 4

Dr. Nancy Li - Director of Product

Nobody wakes up one day with “real” product manager experience.

I didn’t.

And neither did any PM you admire today.

Early in my career, I kept hearing the same question:

“You’ve never been a PM before… so how do we know you can be one?”

That question used to terrify people.

Now I tell my students: 𝐠𝐨𝐨𝐝 — 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐭𝐡𝐞 𝐚𝐧𝐬𝐰𝐞𝐫 𝐢𝐬 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐬𝐢𝐦𝐩𝐥𝐞.

The first time I felt like a product manager wasn’t at a big tech company.

It was at a 𝐡𝐚𝐜𝐤𝐚𝐭𝐡𝐨𝐧.

40+ hours.

A weekend.

Barely any sleep.

You’re thrown into a team, given a vague problem, and expected to:

- Talk to users
- Decide what not to build
- Design something scrappy
- Ship an MVP
- And explain your decisions under pressure

In other words… compressed product management.

That weekend forced me to do, in days, what normally takes months:
customer interviews, prioritization, design tradeoffs, execution.

I even won 2nd place — and yes, that became a standout resume highlight.

𝐁𝐮𝐭 𝐡𝐚𝐜𝐤𝐚𝐭𝐡𝐨𝐧𝐬 𝐚𝐫𝐞𝐧’𝐭 𝐭𝐡𝐞 𝐨𝐧𝐥𝐲 𝐰𝐚𝐲.

Some of my students gained PM experience by helping early-stage startups:
- Running voice-of-customer interviews
- Supporting product launches
- Shaping features when there were no resources and no hand-holding

Here’s the part most people get wrong 💡

𝐘𝐨𝐮 𝐜𝐚𝐧’𝐭 𝐟𝐚𝐤𝐞 𝐭𝐡𝐢𝐬.

Hiring managers can tell in minutes whether someone actually built something…
or just “added a line” to their resume.

Intent matters.
Execution matters more.

If you genuinely build products — even without the PM title — interviewers feel it.

That’s why I put together a checklist of 13 side projects to build PM experience before your first PM job.

If you’re trying to break into product:

👉 Download the checklist: www.pmaccelerator.io/pm-project-list

No shortcuts.

The fastest way to learn product is to actually build something.

#PMAccelerator

2 days ago | [YT] | 0

Dr. Nancy Li - Director of Product

Urgent hiring: Data Scientist at Capital One

Capital One is looking for a Principal Associate, Data Science to join their Risk Management Product Data Science team.

𝐖𝐡𝐚𝐭 𝐭𝐡𝐢𝐬 𝐫𝐨𝐥𝐞 𝐰𝐢𝐥𝐥 𝐝𝐨:

• Build and deploy end-to-end data science and machine learning solutions

• Analyze large, complex datasets to generate actionable insights

• Partner closely with product managers, engineers, and business teams

• Translate technical findings into clear business impact

• Leverage Python, AWS, Spark, and modern ML tools in production environments


𝐖𝐡𝐚𝐭 𝐭𝐡𝐞𝐲’𝐫𝐞 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐟𝐨𝐫:

• Strong background in data science, analytics, or machine learning

• Hands-on experience with Python and cloud-based data platforms

• Solid foundation in statistics and model validation

• Experience influencing decisions with data

• Quantitative degree (Bachelor’s + experience, or advanced degree)


📍 Location: McLean, VA / Richmond, VA / Chicago, IL / New York, NY / Plano, TX


Ideal for data scientists ready to operate at a principal level and drive real business outcomes with data.

If you're interested or know someone who'd be a great fit, feel free to reach out!

👉 LIKE this post and DM me with the job title and company, and I'll ensure your resume gets straight to the hiring manager.

#PMAccelerator #TechHiring

5 days ago | [YT] | 4

Dr. Nancy Li - Director of Product

Why Senior PMs & Directors Get Rejected First (And Don’t Even Know It)

When I was already leading large products, I made a mistake that cost me interviews.

I assumed seniority would “speak for itself.”

It doesn’t.

After reviewing thousands of Senior PM and Director resumes, here’s the uncomfortable truth:

𝐓𝐡𝐞 𝐦𝐨𝐫𝐞 𝐬𝐞𝐧𝐢𝐨𝐫 𝐲𝐨𝐮 𝐚𝐫𝐞, 𝐭𝐡𝐞 𝐥𝐞𝐬𝐬 𝐟𝐨𝐫𝐠𝐢𝐯𝐞𝐧𝐞𝐬𝐬 𝐲𝐨𝐮 𝐠𝐞𝐭.

Recruiters expect clarity immediately — and most senior resumes fail that test.

Here’s why senior-level PM resumes get rejected faster than junior ones:

𝟏. 𝐒𝐞𝐧𝐢𝐨𝐫 𝐫𝐞𝐬𝐮𝐦𝐞𝐬 𝐚𝐫𝐞 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐞𝐝 𝐟𝐨𝐫 “𝐬𝐜𝐨𝐩𝐞,” 𝐧𝐨𝐭 𝐬𝐤𝐢𝐥𝐥𝐬

At Director level, recruiters aren’t asking:
- Can you write PRDs?
- Can you run sprint planning?

They’re scanning for:
- Org-level ownership
- Business impact
- Decision-making authority

If your resume reads like an IC with a fancy title, you’re filtered out.


𝟐. 𝐓𝐢𝐭𝐥𝐞𝐬 𝐝𝐨𝐧’𝐭 𝐦𝐞𝐚𝐧 𝐦𝐮𝐜𝐡 — 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐝𝐨𝐞𝐬
“Director of Product” without context is meaningless.

Recruiters immediately look for:
- Team size
- Budget ownership
- Revenue or cost impact
- Product portfolio scope

If those signals aren’t visible in seconds, they assume:

“Inflated title. Limited scope.”

That’s a silent rejection.


𝟑. 𝐒𝐞𝐧𝐢𝐨𝐫 𝐏𝐌 𝐫𝐞𝐬𝐮𝐦𝐞𝐬 𝐟𝐚𝐢𝐥 𝐡𝐚𝐫𝐝𝐞𝐬𝐭 𝐨𝐧 𝐦𝐞𝐭𝐫𝐢𝐜𝐬

From analyzing resumes at scale:
- 59% of resumes have fewer than 3 quantifiable outcomes
- Senior resumes are often worse than junior ones

Why?


Because senior PMs write:
- “Led strategy”
- “Oversaw execution”
- “Drove alignment”

Those statements tell recruiters nothing.


What they want instead:
- Revenue moved
- Markets launched
- Teams scaled
- Complexity managed

Numbers = credibility.


𝟒. 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 ≠ 𝐛𝐮𝐳𝐳𝐰𝐨𝐫𝐝𝐬

Words like:
- Spearheaded
- Championed
- Evangelized

Actually hurt senior resumes.

Leadership at Director level is demonstrated by:
- Tradeoffs made
- Scale handled
- Outcomes delivered through others

Not adjectives.


↩️𝐓𝐡𝐞 𝐭𝐮𝐫𝐧𝐢𝐧𝐠 𝐩𝐨𝐢𝐧𝐭 𝐟𝐨𝐫 𝐦𝐞

Once I rewrote my resume to:
- Show business outcomes
- Clarify decision scope
- Make org-level impact obvious


I stopped being “a senior PM.”
I became “a low-risk hire.”


That’s what senior resumes are really about:
Reducing perceived hiring risk.


𝐖𝐚𝐧𝐭 𝐚 𝐜𝐨𝐧𝐜𝐫𝐞𝐭𝐞 𝐰𝐚𝐲 𝐭𝐨 𝐚𝐮𝐝𝐢𝐭 𝐲𝐨𝐮𝐫 𝐨𝐰𝐧 𝐫𝐞𝐬𝐮𝐦𝐞?

I put together a free resource I wish I had earlier in my career: The Senior Product Manager Career Upgrade Checklist.

📥 Download it here (free):
www.pmaccelerator.io/senior-product-manager-checkl…

#PMAccelerator

6 days ago | [YT] | 11

Dr. Nancy Li - Director of Product

🌊 “AI is a tsunami.”

That’s the word the IMF’s managing director used at Davos this week.

Not “a wave.”
Not “a trend.”

A tsunami hitting the global labor market.

And once you hear why, it’s hard to unsee it.

A few years ago, work felt stable.

You studied.
You got an entry-level job.
You learned on the job.
You moved up.

That ladder is now breaking at the bottom.

According to the IMF:
• ~𝟔𝟎% 𝐨𝐟 𝐣𝐨𝐛𝐬 𝐢𝐧 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐞𝐜𝐨𝐧𝐨𝐦𝐢𝐞𝐬 will be affected by AI
• ~𝟒𝟎% 𝐨𝐟 𝐣𝐨𝐛𝐬 𝐠𝐥𝐨𝐛𝐚𝐥𝐥𝐲 will change
• 𝐄𝐧𝐭𝐫𝐲-𝐥𝐞𝐯𝐞𝐥 𝐫𝐨𝐥𝐞𝐬 are the most exposed

Why?

Because those roles are built on routine, repeatable tasks — exactly what AI learns fastest.

Here’s the uncomfortable part.
AI doesn’t just replace jobs.

It 𝐫𝐞𝐦𝐨𝐯𝐞𝐬 𝐭𝐡𝐞 𝐬𝐭𝐞𝐩𝐩𝐢𝐧𝐠 𝐬𝐭𝐨𝐧𝐞𝐬 people used to grow.


Young workers are being asked to “have experience”
… while the jobs that used to create experience disappear.



But this isn’t a doom story.

It’s a signal.

💡 Jobs that use AI don’t vanish — they evolve.
💡 Workers who learn to direct, evaluate, and design with AI gain leverage.
💡 Skills, not titles, become the real currency.

The real divide won’t be:

“AI vs humans.”

It will be:
People who 𝐥𝐞𝐚𝐫𝐧 𝐡𝐨𝐰 𝐭𝐨 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐀𝐈
vs
People who wait and hope their role survives.

If you’re ready to future-proof your career — don’t wait.

I put together a free resource:

👉 𝑇ℎ𝑒 𝑇𝑜𝑝 8 𝑅𝑒𝑐𝑜𝑚𝑚𝑒𝑛𝑑𝑒𝑑 𝐴𝐼 𝐶𝑜𝑢𝑟𝑠𝑒𝑠

(practical, career-relevant, no fluff)

Download it here: www.pmaccelerator.io/aicourses

The tsunami is coming either way.

The question is:

Are you building a surfboard — or standing on the shore? 🏄

#PMAccelerator #AIPMBootcamp

1 week ago | [YT] | 7

Dr. Nancy Li - Director of Product

The AI hiring war is real.

Right now, AI talent is one of the scarcest resources in tech.

Big Tech and AI-native startups aren’t “exploring AI” anymore—they’re hiring aggressively.

If you’re pivoting into AI, aiming for top companies, or trying to read where the industry is headed, these 10 names keep showing up:


𝟏. 𝐆𝐨𝐨𝐠𝐥𝐞 (𝐀𝐥𝐩𝐡𝐚𝐛𝐞𝐭)

The AI king. DeepMind + Google Brain are merged, pushing hard toward AGI.

Rumors say top researchers earn up to $𝟐𝟎𝐌/𝐲𝐞𝐚𝐫.

Hiring globally: ML Scientist, AI Engineer, AI Strategist, AI PM.



𝟐. 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭

𝐀𝐥𝐥-𝐢𝐧 𝐨𝐧 𝐀𝐈. Deeply tied to OpenAI, $80B invested in AI infra, AI everywhere on Azure.

Despite layoffs, Research opened 100+ AI roles.

Roles include Applied Scientist, ML Engineer, LLM Infra, AI PM.



𝟑. 𝐀𝐦𝐚𝐳𝐨𝐧

AI across AWS, Alexa, and retail.

CEO Andy Jassy: 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐜𝐫𝐞𝐚𝐭𝐞 𝐣𝐨𝐛𝐬.

Heavy hiring in NLP, speech, robotics, and AWS AI.



𝟒. 𝐌𝐞𝐭𝐚

An all-out AI talent war.

Superintelligence Lab, rumored $𝟏𝟎𝟎𝐌 𝐩𝐚𝐜𝐤𝐚𝐠𝐞𝐬 for top talent.

Hiring GenAI experts, AI researchers, recommender engineers, AI PMs.



𝟓. 𝐎𝐩𝐞𝐧𝐀𝐈

The hottest AI company—no debate.

Out of 312 open roles, 233 are AI-related.

Hiring across research, infra, policy, and safety.



𝟔. 𝐍𝐕𝐈𝐃𝐈𝐀

The infrastructure king of AI. No GPUs, no AI boom.

𝟗𝟎𝟎+ 𝐀𝐈 𝐫𝐨𝐥𝐞𝐬 open, from chips to AI solutions.



𝟕. 𝐀𝐩𝐩𝐥𝐞

Quiet, but ambitious. Focused on on-device AI.

Planning ~𝟐𝟎,𝟎𝟎𝟎 𝐀𝐈/𝐑&𝐃 𝐡𝐢𝐫𝐞𝐬 in Siri, Apple Silicon, CV, Health AI.

Actively hiring from Google and Meta.



𝟖. 𝐈𝐁𝐌

Enterprise AI leader. From Watson to Watsonx.

Hiring AI researchers, ethics specialists, industry AI experts, AI PMs.

Strong in healthcare and finance AI.



𝟗. 𝐀𝐧𝐭𝐡𝐫𝐨𝐩𝐢𝐜

$61B+ valuation, safety-first AI unicorn (Claude).

Hiring research engineers, policy analysts, safety engineers, AI PMs.

Great place for high-growth AI startup experience.



𝟏𝟎. 𝐓𝐞𝐬𝐥𝐚

Elon Musk’s “hardcore AI company.”

AI-driven autonomy + Optimus robots.

Hiring CV, Autopilot AI, Robotics AI, Simulation, AI PMs.


Different companies. 𝐎𝐧𝐞 𝐬𝐢𝐠𝐧𝐚𝐥: 𝐀𝐈 𝐬𝐤𝐢𝐥𝐥𝐬 𝐚𝐫𝐞 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐨𝐩𝐭𝐢𝐨𝐧𝐚𝐥.


Whether you’re an engineer or a PM, the pattern is clear:

- Engineers → Python, PyTorch, LLMs

- PMs → AI technical depth + business and domain insight

If you’re serious about AI careers, start here.

I put together a free resource:

𝐓𝐨𝐩 𝟖 𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐞𝐝 𝐀𝐈 𝐂𝐨𝐮𝐫𝐬𝐞𝐬—curated for engineers and PMs who want real, career-relevant AI skills.

👉 Download it here: www.pmaccelerator.io/aicourses

The fastest way to catch up is to learn what the top companies already expect.

#PMAccelerator #AIPMBootcamp

1 week ago | [YT] | 8

Dr. Nancy Li - Director of Product

Most people ask me this question:

“𝐇𝐨𝐰 𝐢𝐬 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐟𝐫𝐨𝐦 𝐭𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭?”

At first, I gave long answers.
Frameworks. Buzzwords. Fancy diagrams.

But over time, I realized the answer is actually very simple.

𝐎𝐧𝐞 𝐰𝐨𝐫𝐝: 𝐃𝐚𝐭𝐚.

Traditional PMs focus on what to build and why.
AI PMs must also deeply understand 𝐰𝐡𝐚𝐭 𝐝𝐚𝐭𝐚 𝐦𝐚𝐤𝐞𝐬 𝐭𝐡𝐞 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐰𝐨𝐫𝐤 𝐚𝐭 𝐚𝐥𝐥.

Here’s what that looks like in practice 👇

As an AI PM, your job starts before MVPs and roadmaps.

You have to ask:

- Is this problem even suitable for AI?
- What data will train the model?
- How do we measure model quality?
- Do we build our own model—or leverage an existing LLM?

Before users ever touch the product, you’re already validating 𝐀𝐈 𝐡𝐲𝐩𝐨𝐭𝐡𝐞𝐬𝐞𝐬, partnering with engineers to design 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, and thinking about 𝐦𝐨𝐝𝐞𝐥 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐫, not just features.

Only then do you layer on traditional PM skills:

- Voice-of-customer interviews
- Building MVPs with engineering
- Designing go-to-market strategies

But the job doesn’t stop at launch.

Because AI products 𝐜𝐡𝐚𝐧𝐠𝐞 𝐨𝐯𝐞𝐫 𝐭𝐢𝐦𝐞.

Models hallucinate.
Data drifts.
User behavior shifts.
Concepts evolve.

Which means an AI PM isn’t just shipping a product.

They’re managing the 𝐞𝐧𝐭𝐢𝐫𝐞 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐀𝐈 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞—from data → model → product → user → feedback → back to data.

That’s the real difference.

AI Product Management isn’t “PM + AI buzzwords.”
It’s a fundamentally broader responsibility.

And once you see it that way, the role finally clicks.

👉 𝑊𝑎𝑛𝑡 𝑟𝑒𝑎𝑙, ℎ𝑎𝑛𝑑𝑠-𝑜𝑛 𝐴𝐼 𝑃𝑀 𝑒𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒 (𝑛𝑜𝑡 𝑗𝑢𝑠𝑡 𝑡ℎ𝑒𝑜𝑟𝑦)?
I put together a free resource: 𝐓𝐨𝐩 𝟐𝟎 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐈𝐝𝐞𝐚𝐬 you can use to start building your own AI product and gain real, hands-on AI experience right away.

Download it here:
www.pmaccelerator.io/aiproductideas

#PMAccelerator #AIPMBootcamp

1 week ago | [YT] | 0

Dr. Nancy Li - Director of Product

Why Most PM Resumes Fail (Even for Highly Qualified Candidates)


I moved to the U.S. with $800 in my pocket.

I had a PhD.
I had strong technical training.
I had shipped real projects.

And yet — I couldn’t get interviews.

At first, I blamed the market.
Then I blamed my background.
Then I blamed bad luck.

What I eventually discovered was far more uncomfortable:

𝐌𝐲 𝐫𝐞𝐬𝐮𝐦𝐞 𝐰𝐚𝐬 𝐢𝐧𝐯𝐢𝐬𝐢𝐛𝐥𝐞 𝐭𝐨 𝐫𝐞𝐜𝐫𝐮𝐢𝐭𝐞𝐫𝐬.

After later reviewing 𝟏𝟐𝟓,𝟎𝟎𝟎+ 𝐫𝐞𝐬𝐮𝐦𝐞𝐬 and interviewing recruiters myself, I learned something most candidates never realize:

𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐞𝐫𝐬 𝐚𝐫𝐞 𝐧𝐨𝐭 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐧𝐠 𝐩𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥.
𝐓𝐡𝐞𝐲 𝐚𝐫𝐞 𝐬𝐜𝐫𝐞𝐞𝐧𝐢𝐧𝐠 𝐟𝐨𝐫 𝐬𝐢𝐠𝐧𝐚𝐥𝐬.

Here’s what that means in practice:

𝟏. 𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐞𝐫𝐬 𝐝𝐨𝐧’𝐭 𝐫𝐞𝐚𝐝 𝐫𝐞𝐬𝐮𝐦𝐞𝐬 — 𝐭𝐡𝐞𝐲 𝐬𝐜𝐚𝐧
On average, a resume gets ~𝟔 𝐬𝐞𝐜𝐨𝐧𝐝𝐬 of attention.
If your value isn’t obvious immediately, you’re out.

𝟐. 𝐌𝐨𝐬𝐭 𝐫𝐞𝐬𝐮𝐦𝐞𝐬 𝐟𝐚𝐢𝐥 𝐛𝐞𝐟𝐨𝐫𝐞 𝐬𝐤𝐢𝐥𝐥𝐬 𝐚𝐫𝐞 𝐞𝐯𝐞𝐧 𝐜𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐞𝐝
The most common reasons:
- No clear role level (IC vs Senior vs Director)
- No visible impact
- No keyword alignment with the job description

Great experience doesn’t matter if it’s 𝐩𝐨𝐨𝐫𝐥𝐲 𝐞𝐧𝐜𝐨𝐝𝐞𝐝.

𝟑. 𝐑𝐞𝐬𝐮𝐦𝐞 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐢𝐬 𝐦𝐞𝐚𝐬𝐮𝐫𝐚𝐛𝐥𝐞
When recruiters scored resumes:
- Self-written resumes averaged 𝟑.𝟗 / 𝟕
- Professionally structured resumes averaged 𝟔.𝟐 / 𝟕

Same candidate.

Different structure.

Massively different outcomes.

This is why so many talented PMs apply to hundreds of jobs and hear nothing back.

The problem isn’t you.
The problem is 𝐡𝐨𝐰 𝐲𝐨𝐮𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐢𝐬 𝐭𝐫𝐚𝐧𝐬𝐥𝐚𝐭𝐞𝐝 𝐨𝐧𝐭𝐨 𝐩𝐚𝐩𝐞𝐫.

Once I fixed that, interviews started appearing — fast.

If you’re not getting interviews, stop asking:
“Am I qualified enough?”

Start asking:
“Is my resume readable by hiring systems?”

That question alone changes everything.

I put together a free Killer PM Resume Template used by 14,000+ product managers to turn experience into interview-ready signals.

Grab it here:
👉 lnkd.in/eGked8jS

6 𝒔𝒆𝒄𝒐𝒏𝒅𝒔 𝒊𝒔 𝒂𝒍𝒍 𝒚𝒐𝒖 𝒈𝒆𝒕. 𝑴𝒂𝒌𝒆 𝒕𝒉𝒆𝒎 𝒄𝒐𝒖𝒏𝒕.

#PMAccelerator

1 week ago | [YT] | 3

Dr. Nancy Li - Director of Product

I Didn’t Have a PM Title — But I Still Got the PM Job

Early in my career, I kept seeing the same requirement in job descriptions:
“Prior product management experience required.”

And I remember thinking:
How do you get PM experience if no one gives you a PM job?

That’s when I realized something most candidates miss.
𝐏𝐌 𝐡𝐢𝐫𝐢𝐧𝐠 𝐢𝐬 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞-𝐛𝐚𝐬𝐞𝐝, 𝐧𝐨𝐭 𝐭𝐢𝐭𝐥𝐞-𝐛𝐚𝐬𝐞𝐝.

Hiring managers don’t actually care about your job title.
They care whether you understand:

- Customers
- Tradeoffs
- Requirements
- MVPs
- Execution from concept to launch

So instead of waiting for permission, I built proof.

I created a product portfolio — not a designer portfolio, but a decision-making portfolio:

- Who the customer is
- What problem matters most
- Why certain features exist
- How I validate assumptions before building

𝐓𝐡𝐚𝐭 𝐩𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐝𝐢𝐝 𝐰𝐡𝐚𝐭 𝐦𝐲 𝐫𝐞𝐬𝐮𝐦𝐞 𝐚𝐥𝐨𝐧𝐞 𝐜𝐨𝐮𝐥𝐝𝐧’𝐭.
It showed I already 𝐭𝐡𝐨𝐮𝐠𝐡𝐭 𝐥𝐢𝐤𝐞 𝐚 𝐏𝐌.

That’s how I broke into product without the title.
👉 Want to build the same kind of proof?

I put together 13 proven side projects you can use to create a real PM product portfolio — even without prior PM experience.

Download it here:
www.pmaccelerator.io/pm-project-list

#PMAccelerator

2 weeks ago | [YT] | 8

Dr. Nancy Li - Director of Product

“I knew how to build products.
I just didn’t know how to package myself.”

That’s what David told us when he joined PM Accelerator.

David came in with:
- An engineering background
- Founder experience (started his own company)
- Strong technical skills

But he was stuck on two things that stop many strong PM candidates:
👉 Telling a compelling career story
👉 Cracking PM interviews

During the program, he learned how to:
- Turn his experience into a clear, persuasive narrative
- Use a repeatable framework to handle any PM interviews
(product sense, product execution, product strategy...)

The result?

🎉 2 PM offers
🎉 Amazon & Meta
🎉 Now a Product Manager at Meta

His words, not mine:
“I believe I could not achieve this without your help.”

Talent alone isn’t enough.
If you can’t communicate your value, interviewers won’t see it.

And that’s exactly what we fix.

Watch his full story here: https://youtu.be/6RGP3utKp4g

If you’re preparing for PM interviews right now and want results fast:

👇 Download the Top 50 Product Manager Interview Questions
— compiled from Tier 1 companies
— designed to help you land a PM offer in 60 days

🔗 www.pmaccelerator.io/50FAANG

#PMAccelerator #PMAcceleratorReview

2 weeks ago | [YT] | 0