AI Hype, PM Identity, and the Illusion of Specialization

You've made a meme with Nano Banana that got 5 laughing emojis in the team Slack channel. Is that enough to call yourself an AI PM?

Photo by Brando Makes Branding on Unsplash

I’ve been watching my feed fill up with people who were “Product Manager” last month and are now “AI Product Manager” this month. Same job. Same company. Same responsibilities. New prefix. And look, I get it. I really do. Some guy posted a compensation chart showing AI PMs making double or triple what regular PMs earn. It had coloured bars and everything. Must be true.

Here’s the thing.

I’ve watched this exact pattern play out at least four times in my career. The prefix changes, the salary hype circulates, and suddenly everyone’s repositioning. Remember when we were all supposed to become Crypto PMs? I knew people who pivoted their entire personal brand around blockchain product management in 2021. They had NFT profile pictures. They joined Discord servers at midnight. They wrote thought pieces about decentralised product strategy.

Where are they now? Back to regular PM work, mostly. The NFT profile pictures quietly disappeared around Q2 2022.

I know because I have been the NFT PM, I’ve built an NFT Marketplace for Fragmented NFT’s.

Before that it was IoT. Everyone was an IoT PM for about eighteen months. Connected toasters. Smart fridges that would order your milk. And before IoT there was the great SaaS migration. If you weren’t a SaaS PM, you weren’t a real PM.

The technology changes. The hype cycle doesn’t. We just keep rotating through prefixes like they’re seasonal fashion.

But here’s what I’ve been wrestling with lately. The real question isn’t whether to add AI to your title. The real question is one we’ve been dodging for years: should you be a generalist or a specialist?

And chasing hype cycles doesn’t actually answer it. It just delays the reckoning.

Think about it. If you’re rebranding yourself as an AI PM because you saw a LinkedIn salary chart, you’re not becoming a specialist. You’re becoming a trend follower. There’s a difference. The actual AI specialists, the ones commanding those salaries, they were building ML products three years ago when the rest of us were still arguing about story points. They didn’t pivot when the hype arrived. They created the hype by shipping things that worked.

By the time a specialism becomes a LinkedIn hashtag, the window for genuine expertise has already narrowed. You’re not early. You’re a consumer of someone else’s innovation.

This is the part nobody wants to hear. Following established hype means you’re already behind. The people who made real money in crypto were building in 2017, not 2021. The IoT specialists who actually matter were thinking about connected devices in 2014. By the time the compensation charts circulate and the recruiters start calling, the first-mover advantage has evaporated.

What’s left is a crowded field of people who all updated their headlines at the same time.

I talked to a recruiter last month who told me AI PM roles are the hottest thing she’s seen in years. When I asked what AI PM actually means, she said it depends on the company. Some want ML background. Some want prompt engineering skills. Some just want regular PMs who aren’t scared of the technology. Most of them, she admitted, don’t really know what they’re hiring for yet.

Which tells you something important about fake specialisation.

The people actually doing interesting AI product work don’t call themselves AI PMs. They call themselves “PM at Anthropic” or “ML Platform PM at Stripe” or whatever. The specificity is the point. They’re not optimising their headlines for LinkedIn algorithms. They’re solving actual problems in actual domains. Their specialism isn’t a prefix. It’s accumulated knowledge that took years to build.

Meanwhile, the generalists keep doing what generalists do. Moving between domains. Applying pattern recognition across contexts. Translating between engineering and business and design. This is also valuable work. Possibly more valuable, depending on where you sit.

The honest answer is that most of us aren’t specialists or generalists. We’re opportunists wearing whichever hat seems most marketable this quarter.

Actually, that sounds harsher than I mean it.

What I’m trying to say is this. Real specialisation takes years. It means going deep on something before anyone’s paying a premium for it. It means being interested in the technology itself, not the salary charts. The AI PMs earning double your salary didn’t become specialists six months ago. They were obsessing over transformer architectures while you were running sprint retros.

And real generalism is also a choice. It means deliberately staying broad. Building transferable skills. Accepting that you’ll never command the specialist premium, but you’ll also never be obsolete when the hype shifts.

The thing that doesn’t work is pretending to be a specialist by following trends. You get neither the depth of true expertise nor the breadth of genuine generalism. You just get a slightly outdated LinkedIn headline and the vague sense that you’re always one cycle behind.

Part of me wants to add AI to my title anyway. Get in on the salary premium before the market corrects. Follow the hype like I probably should have followed crypto or IoT or whatever comes next.

But I’ve been around long enough to know that by the time I’m following, I’ve already lost. The real question isn’t which prefix to chase. It’s whether I want to go genuinely deep on something, or stay genuinely broad across everything.

Everything else is just marketing.

I will keep working on those Nano Banana memes, though. That thing’s going in my portfolio regardless of what I decide.