Dr. Nancy Li - Director of Product

Here are 10 AI tools you should know — from beginner to advanced 👇

1️⃣ 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 (𝐎𝐩𝐞𝐧𝐀𝐈)

- Your default AI copilot.

- PRDs, emails, debugging, research, interview prep — this is the modern productivity layer.

- If you're an aspiring AI PM, this is where you practice prompt design and workflow thinking.


2️⃣ 𝐆𝐞𝐦𝐢𝐧𝐢 (𝐆𝐨𝐨𝐠𝐥𝐞)

- Google’s multimodal LLM.

- Strong with real-time information and tightly integrated with Google’s ecosystem.

- Useful for research-heavy tasks and market analysis.


3️⃣ 𝐂𝐥𝐚𝐮𝐝𝐞 (𝐀𝐧𝐭𝐡𝐫𝐨𝐩𝐢𝐜)

- Excellent at long-context reasoning and structured writing.

- Great for strategy docs, reports, and enterprise-level thinking.


4️⃣ 𝐃𝐀𝐋𝐋·𝐄 𝟑

- Text-to-image inside ChatGPT.

- Perfect for rapid prototyping, UI mock concepts, and creative testing.


5️⃣ 𝐌𝐢𝐝𝐣𝐨𝐮𝐫𝐧𝐞𝐲

- High-quality artistic generation.

- Widely used by designers and AI-first startups for branding and visual experimentation.


6️⃣ 𝐆𝐢𝐭𝐇𝐮𝐛 𝐂𝐨𝐩𝐢𝐥𝐨𝐭

- An engineer’s force multiplier.

- Code completion, function generation, bug hints.

- If you’re building AI products, this dramatically increases iteration speed.


7️⃣ 𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰

- Production-grade ML framework from Google.

- Helps you understand how AI systems are actually trained and deployed at scale.


8️⃣ 𝐏𝐲𝐓𝐨𝐫𝐜𝐡

- Flexible, research-dominant deep learning framework.

- Many state-of-the-art models are built on it.


9️⃣ 𝐇𝐮𝐠𝐠𝐢𝐧𝐠 𝐅𝐚𝐜𝐞

- The modern AI model hub.

- Thousands of pretrained models across NLP, CV, and audio.

Critical for fast experimentation in AI products.


🔟 𝐂𝐚𝐧𝐯𝐚 𝐌𝐚𝐠𝐢𝐜 𝐒𝐭𝐮𝐝𝐢𝐨

- AI-powered content creation.

- Great for PMs validating ideas with fast decks, visuals, and marketing assets.


You don’t need to build a foundation model to enter AI.


But you do need to understand:

• What today’s AI tools can and cannot do

• How they integrate into workflows

• Where product opportunities emerge

• Why technical constraints shape product decisions


AI fluency is becoming the new baseline skill.

If you want structured guidance, 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

#PMAccelerator #AIPMBootcamp

2 days ago | [YT] | 9

Dr. Nancy Li - Director of Product

Most people don’t realize how fragile their career positioning is right now.

Not because they’re bad at their jobs.

But because 𝐭𝐡𝐞 𝐫𝐮𝐥𝐞𝐬 𝐮𝐧𝐝𝐞𝐫𝐧𝐞𝐚𝐭𝐡 𝐭𝐡𝐞𝐢𝐫 𝐣𝐨𝐛𝐬 𝐚𝐫𝐞 𝐪𝐮𝐢𝐞𝐭𝐥𝐲 𝐜𝐡𝐚𝐧𝐠𝐢𝐧𝐠.

That’s why I invited Sunny Youn onto the podcast.

On paper, her path looks impressive — Wall Street → Big Tech → now GenAI at Meta.

But what stood out wasn’t the resume.

It was how she reinvented herself before the market forced her to.

During our conversation, she said something that hit hard:

“The market doesn’t care how good you were at your last job.”

Her finance and analytics expertise didn’t disappear when she moved into tech.

But it wasn’t enough.

What mattered more was her ability to:
– Translate her skills into new contexts
– Understand how technology changes decision-making
– Ask: What part of my job can be automated — and what part shouldn’t?


𝐓𝐡𝐢𝐬 𝐢𝐬 𝐰𝐡𝐞𝐫𝐞 𝐦𝐨𝐬𝐭 𝐩𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥𝐬 𝐠𝐞𝐭 𝐬𝐭𝐮𝐜𝐤.


They either panic and try to learn everything about AI.

Or they ignore it and hope experience carries them.

Both are risky.

At Meta, GenAI isn’t about flashy demos.

It’s about:
– Knowing where AI creates real value
– Understanding the cost of wrong predictions
– Designing systems where humans and models work together

It’s less about writing perfect PRDs.

More about asking better questions:

What assumptions is this model making?

Where could this break at scale?

What should never be automated?

Reinvention isn’t a dramatic job change.

It’s a mindset.

Sunny didn’t pivot when she was desperate.

She pivoted 𝐰𝐡𝐞𝐧 𝐬𝐡𝐞 𝐰𝐚𝐬 𝐬𝐥𝐢𝐠𝐡𝐭𝐥𝐲 𝐮𝐧𝐜𝐨𝐦𝐟𝐨𝐫𝐭𝐚𝐛𝐥𝐞 — 𝐛𝐮𝐭 𝐬𝐭𝐢𝐥𝐥 𝐜𝐫𝐞𝐝𝐢𝐛𝐥𝐞.

That’s the sweet spot.

Ask yourself:

If my job disappeared tomorrow,

what problem-solving ability would still be valuable?

That question should guide what you learn next.

If you’re wondering whether your role is future-proof — or whether you need to move into AI — this episode gives you a clear framework.

🎧 Watch Sunny's full story here: https://youtu.be/sjZWA4mWtZ8

And one last thing.

Recruiters aren’t impressed by AI certificates anymore.

They’re asking:
𝐖𝐡𝐚𝐭 𝐡𝐚𝐯𝐞 𝐲𝐨𝐮 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐛𝐮𝐢𝐥𝐭?

That’s why inside our AI PM Bootcamp, you build and launch real AI products in cross-functional teams — not just learn theory.

👉If you’re serious about breaking into AI (or staying relevant as a PM), book a free call with our career advisor.

www.pmaccelerator.io/AI_PM_Course_Application


Theory won’t get you hired.
Real AI experience will.


#PMAccelerator #AIPMBootcamp

3 days ago (edited) | [YT] | 3

Dr. Nancy Li - Director of Product

Product Managers → AI Product Managers

This shift is already happening.

Over 70% of companies are using AI in their daily operations.

More than half of recent VC funding is flowing into AI startups.

AI isn’t “the future.”
It’s the present.

Yet many experienced PMs still struggle with one question:

What does an AI Product Manager actually do — and how is it different from traditional PM?

Let’s break it down.


💡𝐖𝐡𝐚𝐭 𝐢𝐬 𝐚𝐧 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐫?
An AI Product Manager owns the development and deployment of AI-powered products.

At its core, the role sits at the intersection of three things:
- Business
- Data
- Technology

Unlike traditional PMs, AI PMs must go beyond feature delivery and deeply understand how data and models shape product outcomes.

The biggest difference?
Data is no longer an input — it’s the foundation.

💡 𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐚𝐧 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐫 𝐝𝐨 𝐝𝐚𝐲-𝐭𝐨-𝐝𝐚𝐲?

If you look at real AIPM job descriptions, clear patterns emerge:

1️⃣ Define AI product strategy & vision

AI strategy moves faster than traditional product strategy. New models, tools, and competitors emerge constantly. AI PMs must balance short-term adaptability with long-term vision.

2️⃣ Own the end-to-end AI product lifecycle

From AI hypothesis → MVP → launch → scaling.
This includes validating whether AI is a must-have, nice-to-have, or not needed at all.

3️⃣ Make data-driven decisions

Sometimes you build models with data scientists.
Sometimes you integrate existing LLMs.
Either way, AI PMs are accountable for model performance and outcomes.

4️⃣ Lead cross-functional teams

AI PMs work closely with:
- data scientists
- AI/ML engineers
- designers
- legal & compliance teams

5️⃣ Define AI-suitable problem statements
Not every product needs AI.

There are typically three categories:
- Products that cannot function without AI (e.g. self-driving cars)
- Products that create entirely new experiences with AI (e.g. AI chatbots)
- Products that enhance existing workflows with AI features (e.g. smart predictions)

Choosing the wrong category is why most AI products fail.

6️⃣ Still do core PM work
Yes — AI PMs still write PRDs, prioritize backlogs, define MVPs, and own go-to-market strategy.

If users don’t adopt your product, the model doesn’t matter.

7️⃣ Ensure AI compliance & responsible use
Ethics, privacy, and compliance are no longer optional.

AI Product Management isn’t a niche anymore.

It’s quickly becoming the default evolution of product leadership.


If you’re ever thinking, “Do I need to pivot now?”

The answer is: the earlier, the better.

Want a clear, step-by-step path to break into AI Product Management?

I’m hosting a free AI PM workshop where I teach you 𝐡𝐨𝐰 𝐭𝐨 𝐛𝐞𝐜𝐨𝐦𝐞 𝐚𝐧 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐫 𝐢𝐧 𝟗𝟎 𝐝𝐚𝐲𝐬 — even with no prior AI or PM experience.

👉 Jumpstart your AI PM career now: www.pmaccelerator.io/AIPM

#PMAccelerator #AIPMBootcamp

5 days ago | [YT] | 13

Dr. Nancy Li - Director of Product

Amazon cut 16,000 jobs — again.

When the news broke, we were in the middle of our AI PM Bootcamp Product Idea Pitch Day. My students and I were genuinely shocked.

And Amazon isn’t alone.

January marked the highest number of U.S. layoffs at the start of a year since 2009, led by tech and logistics.

If you’re worried you might be next, pause for a moment.

This isn’t the end. It's a reset.

𝐖𝐡𝐚𝐭 𝐭𝐨 𝐝𝐨 𝐫𝐢𝐠𝐡𝐭 𝐚𝐟𝐭𝐞𝐫 𝐚 𝐥𝐚𝐲𝐨𝐟𝐟?

Here’s a simple, practical playbook.

𝟏) 𝐓𝐚𝐤𝐞 𝐂𝐚𝐫𝐞 𝐨𝐟 𝐘𝐨𝐮𝐫𝐬𝐞𝐥𝐟 𝐅𝐢𝐫𝐬𝐭

Before anything else:
- Breathe. You’re not defined by a job title.
- Tell close contacts you’re okay — honesty builds support.
- Confirm details: last pay, benefits continuation, severance, references.

This part matters. You can’t focus on your next role if you’re running on empty.


𝟐) 𝐁𝐮𝐢𝐥𝐝 𝐚 𝐊𝐢𝐥𝐥𝐞𝐫 𝐑𝐞𝐬𝐮𝐦𝐞 𝐓𝐡𝐚𝐭 𝐆𝐞𝐭𝐬 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬

Your resume is your first impression — make it count.

Focus on three things:
✔ Results over responsibilities
✔ Clear metrics ("increased adoption by 40% in 6 months")
✔ A tight format recruiters can scan in 6–10 seconds


A strong structure looks like this:
- Headline + summary: Define who you are and what you do.
- Core achievements: Use bullet points with numbers.
- Skills + tools: Tailor to the role you want next.
- No fluff: Delete generic lines like "detail-oriented."

If your resume reads like a job description, it’s working against you.

At the end of the day, your resume is about how clearly you’re positioned in a crowded market.


𝟑) 𝐂𝐫𝐞𝐚𝐭𝐞 𝐚 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐓𝐡𝐚𝐭 𝐒𝐞𝐥𝐥𝐬 𝐘𝐨𝐮𝐫 𝐒𝐤𝐢𝐥𝐥𝐬

Especially in product roles, resumes only tell half the story.

A portfolio shows your thinking, decision-making, and impact. Here’s how to build one quickly:

✅ Choose 3–5 projects
Focus on work where YOU drove outcomes — not vague team stuff.

✅ Tell why you did it
What problem were you solving?

✅ Show the process
Research → Strategy → Execution → Results

✅ Use visuals
Mockups, charts, flows — let people see your thinking.

Your portfolio doesn’t need to be perfect.

It needs to answer one silent question:
"Can this person move the business forward?"

𝟒) 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐋𝐢𝐤𝐞 𝐘𝐨𝐮𝐫 𝐉𝐨𝐛 𝐃𝐞𝐩𝐞𝐧𝐝𝐬 𝐎𝐧 𝐈𝐭 — 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐈𝐭 𝐃𝐨𝐞𝐬

✔ Reach out to past teammates
Ask for a quick call — no agenda necessary.

✔ Send value, not just "Hey, I’m job hunting."
Share an article, a thought, or feedback.

✔ Update LinkedIn
A thoughtful post about what you learned and where you’re heading invites opportunities.

𝟓) 𝐓𝐫𝐞𝐚𝐭 𝐓𝐡𝐢𝐬 𝐚𝐬 𝐚 𝐏𝐢𝐯𝐨𝐭, 𝐍𝐨𝐭 𝐚 𝐅𝐚𝐢𝐥𝐮𝐫𝐞

You still have your skills.

You still have your experience.

And you still control your next move.

👉 Need help creating your product portfolio in 14 days?

Join my FREE masterclass before the seats are gone.
www.pmaccelerator.io/masterclass

#PMAccelerator

1 week ago | [YT] | 15

Dr. Nancy Li - Director of Product

“I’m not technical — can I still become a Product Manager?”

Short answer: Yes.
Honest answer: 𝐎𝐧𝐥𝐲 𝐢𝐟 𝐲𝐨𝐮’𝐫𝐞 𝐰𝐢𝐥𝐥𝐢𝐧𝐠 𝐭𝐨 𝐟𝐢𝐱 𝐭𝐡𝐚𝐭 𝐠𝐚𝐩 𝐞𝐚𝐫𝐥𝐲.

If you’re coming from finance, marketing, ops, sales, or consulting, this is something most people won’t tell you clearly enough:

It’s generally much easier to train an engineer on:
- pricing
- go-to-market
- business tradeoffs

Than it is to train a non-technical person on how modern software actually works.

Why?

Because software isn’t just “features on a screen.”
It’s systems talking to systems, with real constraints underneath.

As a PM, you are not expected to build the system —
but you 𝐚𝐫𝐞 𝐞𝐱𝐩𝐞𝐜𝐭𝐞𝐝 𝐭𝐨 𝐫𝐞𝐚𝐬𝐨𝐧 𝐚𝐛𝐨𝐮𝐭 𝐢𝐭 every single day.

That means understanding things like:
- how backend and frontend interact
- why an API design can unblock (or completely stall) a roadmap
- why “this should be easy” is sometimes a red flag, not a compliment

When people say “PMs don’t need to be technical,” what they should say is:

👉 PMs don’t need to code
👉 PMs do need to 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞

To be clear — there is no finite checklist of “technical things you need to know.”

But you should gradually build comfort with concepts such as:

- what APIs and SDKs are, and how teams rely on them
- how different services integrate with each other
- how data flows through a system
- how cloud platforms (like AWS) fit into product decisions
- how technical constraints shape timelines, scope, and tradeoffs

These are examples, not the full syllabus.

And here’s the part people underestimate:

Even after you get the PM job,
this knowledge shows up in your day-to-day work:

- roadmap discussions
- tradeoff debates
- sprint planning
- stakeholder alignment
- “Can we do X?” conversations with engineers

If you don’t have an engineering background, my advice is simple:

Don’t wait until you’re “on the job” to learn this.

Instead:
📚 Read books on software architecture (PM-level, not CS textbooks)
🎓 Take a technical bootcamp designed for PMs
🧠 Focus on understanding how systems work, not memorizing jargon

You’re not trying to become an engineer.
You’re trying to become a PM that engineers trust.

And in product, 𝐭𝐫𝐮𝐬𝐭 𝐜𝐨𝐦𝐩𝐨𝐮𝐧𝐝𝐬 𝐟𝐚𝐬𝐭𝐞𝐫 𝐭𝐡𝐚𝐧 𝐚𝐧𝐲𝐭𝐡𝐢𝐧𝐠 𝐞𝐥𝐬𝐞.

If you want a shortcut, I put together a free resource:
𝐓𝐡𝐞 𝐓𝐨𝐩 𝟖 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐟𝐨𝐫 𝐏𝐌𝐬 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐚 𝐜𝐨𝐝𝐢𝐧𝐠 𝐛𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝

No fluff. No CS degree required.

Just practical learning you can actually use.

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

If this was helpful, like or comment so more aspiring PMs see it.

#PMAccelerator

1 week ago | [YT] | 1

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 week ago | [YT] | 5

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

1 week 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

2 weeks 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

2 weeks 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

2 weeks ago | [YT] | 7