I build AI products from zero to one, and I teach others how to do the same.Over 12+ years, I've taken AI/ML products from proof-of-concept to launch at Amazon, Nike, T-Mobile, and Disney. The work I love most is early-stage: validating ideas, getting executive greenlight, and shipping MVPs that prove value before scaling. At Nike, that approach drove a $100M annual reduction in product returns.I also teach what I build. I co-created and lead the AI Product Management Certificate at the University of Washington, where experienced PMs ship real GenAI products complete with evaluation plans and GTM strategies. Previously, I trained 4 cohorts at Product School.What I bring: the ability to translate messy AI capabilities into clear product value, align technical and business stakeholders, and move fast without breaking trust. I write about AI PM craft at aipmguru.substack.com.I'm currently exploring opportunities to lead 0→1 AI product work at companies solving meaningful problems. I'm especially energized by AI in healthcare and education, though I'm open to any domain where the product can genuinely improve lives. 

Shaili Guru

95% of product managers know AI is the future.

But only 5%  know how to break into it, let alone lead it.

That’s where I come in.

I’m currently a Product Director at Netflix, previously building AI systems at Meta and AWS. 

Over the past 13+ years, I’ve worked across infrastructure, platforms, and applications, leading high-stakes product development in some of the most innovative AI teams in the world.

But what I’m most proud of?

Helping 𝟭,𝟱𝟬𝟬+ 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗺𝗮𝗻𝗮𝗴𝗲𝗿𝘀 make the leap into AI roles - many landing jobs at top companies like Google, Microsoft, and fast-growing startups.

𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗴𝗮𝗽 𝗜 𝗵𝗲𝗹𝗽 𝗣𝗠𝘀 𝗰𝗹𝗼𝘀𝗲:

✔ You’ve got product chops, but feel stuck trying to “speak AI.”
✔ You’ve taken a few courses, but still get rejected for lack of experience.
✔ You want to lead AI initiatives but lack the frameworks, confidence, and portfolio to show you’re ready.

𝗧𝗵𝗿𝗼𝘂𝗴𝗵 𝗺𝘆 𝟱-𝘄𝗲𝗲𝗸 𝗔𝗜 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗽𝗿𝗼𝗴𝗿𝗮𝗺, 𝗜 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂:

→ Build real-world, hire-ready portfolio projects
→ Learn how to scope, evaluate, and ship AI features like a pro
→ Translate your existing product skills into AI fluency
→ Walk into interviews knowing you belong at the table

This isn’t about theory.

It’s about building 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗽𝗿𝗼𝗼𝗳, 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲, 𝗮𝗻𝗱 𝗺𝗼𝗺𝗲𝗻𝘁𝘂𝗺, so you stop watching the AI wave and start leading it.

𝗪𝗵𝗼 𝗶𝘀 𝗶𝘁 𝗳𝗼𝗿? 

Mid-career product managers with 3–8 years of experience. 

You’re looking to future-proof your career, land high-paying AI roles, and lead with credibility, without needing to become a data scientist.

𝗪𝗵𝗲𝗻 𝘆𝗼𝘂’𝗿𝗲 𝗿𝗲𝗮𝗱𝘆, 𝗵𝗲𝗿𝗲 𝗶𝘀 𝗵𝗼𝘄 𝗜 𝗰𝗮𝗻 𝗵𝗲𝗹𝗽:

1️⃣  Become an AI product manager → https://enterprisereadyaipmroadmap.com/

Or just DM me - I’d love to hear your story.

Jyothi Nookula

Fun fact about me:

I became a Product Manager by accident.

In 2013, I was at NASA Moffett Field through Singularity University.

I was working on a project that combined AI, sensors, and 3D printing to build an automated oral-cleaning device.

On presentation day, something unexpected happened.

My teammates backed out.

They were too nervous to present.

So I stepped in.

I presented the product.
Handled every technical question.
Defended our decisions.
Explained the market opportunity.

After the session, the CEO of 3D Systems, Avi Reichental, walked up to me.

He said, “Would you consider working with us?”

There was just one complication.

I didn’t have an employment visa.

I assumed that was the end of the conversation.

It wasn’t...

He arranged legal support and brought me to the U.S.

And then said, “You can choose your own title.”

Product management was booming at the time.

So I chose Product Manager.
… And that’s how I became one.

I spent the next three years launching multiple consumer 3D printers.
I even won the Glenn Taylor Memorial Award.

Here’s what I want you to take away from this:

Careers rarely unfold in straight lines.

Sometimes, just demonstrating your value is enough for someone to give you a chance.

So begin to take ownership.

Build something and talk about it.

The internet is the biggest stage you’ll ever have.

Happy Sunday ❤️

P.S. The image is of me with the 3D printer I launched in 2013.

P.S.S. Thank you, Avi, for giving me a chance.

AI Product Leader | Coaching PMs to become AI Product Leaders | ex-Meta, Amazon, Netflix | Founder @ Next Gen PM

There are moments in your life where one person’s decision changes your trajectory.

For me, that person is Marianna Ryan.

In 2013, a mentor from high school told me about a global program at NASA Moffett Field through Singularity University.

They were selecting one person from each country to train in exponential technologies.

I applied.
And then… silence.

The interview email never reached me.

Most programs would’ve just moved on.

But Marianna, the program director, felt something was off.
So she picked up the phone and called me herself.

I remember that day clearly.

I was at the cinema with friends when my phone started ringing.

She told me she had emailed to schedule my interview, but I never received it.
The list of selected candidates were being made that same day.

If I wanted a shot, I had to interview immediately.

I wasn’t prepared, but I did it anyway.

I thought I had ruined my chance.

Later that day, my phone rang again...

I had been selected with a full scholarship.

At NASA Moffett Field, I was suddenly immersed in deep learning, brainwave decoding, EEGs, 3D printing, and exponential technologies.

Up until then, I genuinely thought “deep learning” had something to do with meditation.

That experience completely changed how I saw the world.

I worked on a project combining AI, sensors, and 3D printing to build an automated oral-cleaning device.

Looking back, so much of my career in AI traces back to that one phone call.

I said all of that to say, sometimes the biggest accelerators in your career is just one person who’s willing to take a gamble on you.

Marianna, wherever you are in the world today, thank you for making that call.

P.S. If someone has ever quietly changed your trajectory, tag them below. Let’s appreciate the people who opened doors for us.

P.S.S. The image is me at the NASA hangar around 13 years ago.

I graduated from university almost 18 years ago, but If I could go back in time...

Here's the advice I'd give my younger self about building a successful career:

Keep finding unconventional routes to get what you need.

Because the obvious path is rarely the easiest.
It's the most crowded lane.

And breakthroughs often sit one layer outside of it.

For example...

When I knew I wanted to go to ISB, I could have done what everyone else did.

Fill out the application.
Write the essays.
Submit.
Hope.

Instead, I searched for alumni and figured out where they spend their time.

I discovered a group of them playing frisbee at 5 AM on a nearby beach.

I do not enjoy frisbee whatsoever.
I went anyway.

Consistently.

I built relationships.
I got insider advice on essays and applications.

I even secured the introductions that helped me get feedback, an interview, and admission.

Now here's where the actual teaching starts...

Because I have never followed formal channels.
I've always found a way.

But there were moments when I felt scared.

Looking back, I realized there was nothing to be afraid of.

So I'd want my younger self to understand this:

Life won't be easy, but don't be afraid.
Keep doing what you're doing.

Persistence has been one of my greatest assets throughout my career.
It’s the reason why I am where I am today.

So I guess there’s 2 lessons in this message…
 
1. Always look for unconventional routes to get what you need
2. Life won’t be easy, but that’s nothing to fear

I hope this helps someone at the beginning of their career.

P.S. What advice would you give your younger self?

Choosing the wrong metric can quietly kill a great product.

That’s why I use a simple framework called MAPS when selecting metrics...

It forces clarity before optimization.

Here’s how it works:

(𝗠)𝗶𝘀𝘀𝗶𝗼𝗻

Before talking about metrics, get painfully clear on:
 
• What problem are we solving?
• For whom specifically?
• What does success actually look like?

“Busy people” is not specific enough.

“Working professionals aged 25–40 in major cities with 20 minutes or less for wellness activities” is.

That level of specificity shapes everything that follows.

If the mission is vague, your metrics will be too.

(𝗔)𝗰𝘁𝗶𝗼𝗻𝘀

Now map the user journey.
 
• What are the key touchpoints?
• Where are the critical conversion moments?
• Where is drop-off most likely?

When I’m in interviews or strategy sessions, I literally sketch the flow.

It forces structured thinking and makes it obvious where metrics matter most.

tl;dr: Metrics should measure behavior.

(𝗣)𝗿𝗶𝗺𝗮𝗿𝘆 𝗺𝗲𝘁𝗿𝗶𝗰𝘀

Choose 2–3 maximum.

That’s it.
 
• One North Star metric (ultimate success indicator)
• Supporting primary metrics
• A mix of leading and lagging indicators

Your North Star should answer, "If this improves sustainably, does the product win?"

Everything else should either drive it or predict it.

If you need 8 primary metrics, you don’t have a strategy.

(𝗦)𝗮𝗳𝗲𝗴𝘂𝗮𝗿𝗱𝘀

This is where senior product thinking shows up.

Ask:
 
• What could go wrong if we optimize this?
• How might this be gamed?
• What user experience might we accidentally degrade?

If you optimize for session time, users might get stuck in confusing flows.

If you optimize for sign-ups, you might attract low-quality users who churn immediately.

Every primary metric needs a counter-metric.

Growth without safeguards is how products break trust.

𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗰𝗼𝗿𝗲 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆:

Great PMs design a measurement system.

MAPS ensures you optimize intentionally.

♻️ Share this with a PM who’s defining their North Star.

Follow me for frameworks that help you build smarter AI and product systems.

M.A.P.S_Framework

This is the most underrated AI PM skill:

(Hint: it takes a lot of courage)

Knowing when to say "No."

According to MIT’s 2025 State of AI in Business Report, 95% of enterprise AI tools fail.

And it’s not because the models don’t work...

It’s because they were deployed where they shouldn’t have been.

I blame the seduction of shiny tools.

Every week brings new models, new benchmarks, and new possibilities.

It’s exciting.

But it can be dangerous.

Why?

Because many of the tools only work just enough to be shipped.

This doesn't mean they work well enough to solve the problem it was supposed to address.

Many AI products fail for this reason - it's misjudged opportunity.

Hence, why I say the most underrated skill is knowing when to say "No."

Great AI PMs slow down to ask sharper questions like:
 
• Is the problem stable enough for automation?
• Do we have the right data and feedback loops?
• Will users trust this system’s output enough to rely on it?
• What’s the cost of being wrong?

Discernment is a skill (and it's not talked about enough).

Because anyone can say, "Let's build."

But it takes plenty of courage to say, "Not yet."

That’s how you protect user trust, team focus, and long-term credibility.

I recently hosted a fireside chat with one of my alumni, Felix Biju.

He's now a director of product... Here's 5 gems he shared during the convo:

𝟭) 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗰𝗿𝗲𝗮𝘁𝗲 𝗽𝗿𝗼𝗼𝗳

Felix said the biggest shift wasn’t “learning AI.”
It was having real artifacts to point to.

Before: “I’m learning AI.”
After: “Here’s what I built, what broke, how I fixed it, and the outcome.”

This changed his LinkedIn to a funnel.

𝟮) 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗶𝘀 𝗮 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝗲𝗻𝗴𝗶𝗻𝗲 (𝗶𝗳 𝘆𝗼𝘂 𝘂𝘀𝗲 𝗶𝘁 𝗰𝗼𝗿𝗿𝗲𝗰𝘁𝗹𝘆)

His interviews didn’t come from cold applications...
They came from visibility.

Posting projects created conversations.
Conversations created inbound.
Inbound created interviews.

𝟯) 𝗔𝗜 𝗣𝗠 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗮𝗿𝗲 𝗯𝗲𝗰𝗼𝗺𝗶𝗻𝗴 𝗽𝗿𝗼𝗷𝗲𝗰𝘁-𝗹𝗲𝗱

His interviews were about:
 
• What he built with tools like Bolt and Lovable
• What model choices he made and why
• How he thought about cost, UX, and business impact
• How he handled iteration cycles

He even shared a tactic I loved:

When companies gave him build challenges, he mirrored their product look and feel by feeding screenshots into his build tools.

It signaled: “I did my homework.”

𝟰) 𝗙𝗶𝗻𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 “𝗔𝗜 𝗰𝗼𝗺𝗽𝗮𝗻𝘆” 𝗶𝘀 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗷𝗼𝗯

Felix didn’t only ask “Do you use AI?”
He asked, “Where does AI show up?”

Using ChatGPT to quickly analyze a company’s product, marketing, and leadership posts helped him spot who was serious vs who was just using the word “AI.”

𝗠𝘆 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗱𝗶𝘀𝗰𝘂𝘀𝘀𝗶𝗼𝗻:

Opportunities compound when you’re visible.

Not by sharing articles.
By sharing what you’re building, testing, learning, and thinking.

The market can’t reward what it can’t see.

P.S. If you’re trying to build the foundations to transition into AI PM (without drowning in random resources), I put together a free 5-day email course.

Check it out here: https://lnkd.in/gYGXGriZ

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