Courtney Dean

How do you want to approach AI? Do you:

1. Lay off anyone not directly contributing to your AI initiative, and use those savings to go all in?
2. Wait, watch the tea leaves, and see how things play out?
3. Invest earnestly (but don't bet the farm) in an AI initiative, starting with discovery and needs assessment — hire (not fire) key persons who can further your AI investigation, and keep your talented staff involved so that when you find those winning solutions, you can quickly bring them to market?

Option 1 feels like putting half your money on one number on the roulette table. Option 2 feels like you might miss the boat entirely. Option 3 is the right combination of risk and bold initiative to produce meaningful results.

This AI renaissance is looking more and more like the dotcom bubble. Every organization is going mad with FOMO, or counting the money before it's been made — thinking AI just automatically comes with a value proposition. It's not that the internet didn't add value (it's omnipresent today) — it's that so many just assumed the money would flow without asking "how?"

In 2025, companies weren't asking "how?" either. Will there be a similar bubble? Folks are adamant on both sides. Regardless, there will be severe consequences — some good, some bad, some great. And a whole lot of people are going to have a #OpenToWork banner on their profile.

📖 Related: HBR — Companies Are Laying Off Workers Because of AI's Potential, Not Its Performance ↗

And yes, I used an em dash. On my own. No help from a chatbot. And I am proud of it —

I've unlocked $50M in sustained funding and doubled graduation rates from 50% to 100% — not by managing backlogs, but by turning product teams into missionaries and customers into evangelists.

Great products don't happen by accident. They happen when a PM obsesses over the right problem, aligns the team around real customer needs, and maintains a value creation mindset from discovery through delivery.

My practices make missionaries of product teams, evangelists of customers, and ensure products meet the needs of the business — across segments, across the full product lifecycle.

I'm looking for empowered teams ready to discover their next flagship product. If that's you, let's talk.

I started with formal instruction — taking courses on AI Product Management and trying to add things to my resume that would help me stand out. At the same time, I've been doing a little vibe coding.

Using OpenAI, I've built a Ghost Job Detector Chrome Extension, a Resume and Cover Letter Customizer, and an article writer called Product Salad — which helps me write those The Onion-inspired satire stories about product management and AI.

Today, I am building an app for Alpine ski racing technicians — Alpine Prep Pro. It isn't really revolutionary. But it is giving me the opportunity to keep my skills fresh and develop some more nascent ones.

I'm starting pretty basic. The app lets users put in information about skiers, skis, tuning equipment and wax, and events. It provides recommendations for waxing and tuning for an upcoming race or training day — but it assumes the user knows how to tune and wax. It's really just a database for equipment and events to start.

I'll expand the app with more support features next — make it more accessible to the other parents of junior racers who may not consider ski maintenance a fun hobby. The app will become more instructional as I mature it.

The point here is that I am borrowing from the Lean Startup Movement. I'm trying out the build, measure, and learn mindset.

Vibe coding isn't just a skill for your resume. It should be a hobby. If you want to land a job in AI, you have to genuinely like AI. You can't just see its potential for your company. You have to try, experiment, ideate, and reveal that potential.

You should have been doing this in 2022. But it is not too late. You just have some aggressive catching up to do.

So, if you want to be a part of the AI revolution — don't get on the bandwagon. Get in the saddle, grab the reins, and start leading the way.

— Forgive the clichés. This was done without the aid of an LLM.

I see posts about Claude or OpenAI enabling a PM to produce PRDs during lunch, or produce a prototype in the morning and a second in the afternoon after using that same copilot to test the first. AI is not going to make a PM a one-person product team. It is not going to exponentially accelerate product development.

It may continue this trend of rushed, under-tested, poorly thought-out products that fail. AI may help us automate some things. It may even help us get a prototype in a morning. But it won't do the thinking for us.

AI is the ultimate yes-man. Even when you program your chatbot to be critical and merciless, it is still going to enable you to mature a mistake right into the danger zone.

What makes a good Product Manager valuable is his or her ability to think. Dozens of decisions need to be made every day, in every stage of the product lifecycle. Those decisions cannot be made in isolation. They shouldn't be made with just a chatbot either ("Yes. Brilliant. You're killing it today!"). They should not be made without getting real data from real humans — users, designers, developers, executive sponsors, competitors.

The decisions we make as product managers come from using messy data, experts' opinions, and our own internal neural network. We make decisions based on experience, data, and the outcomes of the last decision we made.

If you want to be a great PM — or if you want to hire one — prioritize good analytical skills. Anyone can move sticky notes on a Kanban board. But not everyone can figure out the "what" or "why" that differentiates a Claude from a Fraud.*

*"Fraud" being my hypothetical failed AI initiative from a hypothetical company that never got off the ground.

"...Doing A, B, C"
"to x, not just y."
"...at the intersection."

My resume stank of ChatGPT. I'm one of those, now. I don't know how I got into the trap. But I did. It was just so easy. I knew I should be more diligent. I knew if I wasn't careful, it would get out of control. I figured I could quit anytime.

How many did I send out like this? To whom did I blow my chances?

I shook off the stink of AI as best I could. I reviewed and rewrote every bullet. But I fear there's an AI essence that persists.

For all you job seekers out there — don't let a few job descriptions that reek of AI convince you that you can offer the same. Hiring managers have the power right now. And they're inundated with applications. Don't make it easy for them to dismiss you.

Write your own resume.

We cannot turn PMs into coders. Not that PMs can't code — they shouldn't. They should do what someone else can do better.

Further, they are one person. The product lifecycle takes many minds. Taking one away — even if it's just so that the PM can run a few experiments — takes away an informed opinion, a creative perspective, a voice of reason, and an opportunity to stop or fix before time and resources are wasted.

When we make PMs wear more hats, who's to say they should not wear all of them? What's next? PMs must be UX folks too? And PMMs? And Account Managers? Customer Service Reps? Why not just have a PM do it all with their trusty chatbot copilot?