Hello Reader,

Every other week, a product manager asks me some version of the same question: "If AI can write the spec, run the analysis, and summarize the meeting, what's left for me?"

It's a fair question. Most of the answers floating around are either dismissive ("you'll be fine") or catastrophic ("half of you won't have jobs by 2027"). Neither is useful.

Here's the honest version. The PM role is being rewritten faster than any career playbook can keep up with. Some of the skills that used to define the job are becoming commodities. Others are compounding in value. The PMs who figure out which is which, and invest accordingly, are going to pull ahead. The ones who don't will find their role quietly shrinking around them.

The Middle Is Getting Commoditized

On a recent Product Thinking episode, Oji and Ezinne Udezue put it in a way I keep coming back to. They said AI is going to change "the middle" of the PM job. Not the edges.

The middle is what you spend most of your week on. Writing PRDs. Managing backlogs. Translating needs into specs that make it into code. Summarizing user interviews. Pulling together a status update for the VP and stakeholders. Answering questions for engineering and design so they have what they need.

All of that is getting faster and cheaper by the quarter. Oji estimated that maybe a fifth of what we hire PMs for is that middle work, but it tends to be the most visible fifth. If your job is mostly that fifth, your job is in trouble.

That line from the episode captures the shift. The translation layer between "what we want" and "what gets built" is collapsing. Which is fine. That was never the hard part anyway.

The Edges Are Compounding

What doesn't get commoditized is the work that requires judgment, context, and trust.

Deciding what is actually worth building. Understanding the customer well enough to direct creativity toward real problems. Navigating the org so the CRO doesn't ship a side project behind your back over the weekend and declare it a product. Leading across engineering, design, and executives so the room trusts you to call the shots.

Systems thinking about AI is a new one on that list, and it matters more every month. How does this model behave when it fails? Where does automation amplify a bad decision at scale? Which parts of the user journey should feel effortless and automated, and which need a human in the loop?

These skills compound because every situation you navigate gives you more pattern recognition for the next one. AI can assist, but it cannot replace lived judgment about a specific business, a specific team, and a specific customer.

Where to Invest Right Now

If you are a PM, stop measuring your productivity by how many tickets you wrote, how many pages of documentation you spun up, or how fast you closed the loop on the last sprint. That work is going to keep getting easier.

Measure your productivity by how often you changed a decision that mattered, how often you saw around a corner, how often a senior leader walked out of a room thinking differently because of something you said. How often your shipped features translate into real customer outcomes is what matters.

If you run a product org, look at where you are putting your training budget. Most companies over-fund tooling for the middle, where AI is about to do the heavy lifting anyway, and under-fund the thinking that actually differentiates your teams.

This is the gap we have been working on at Product Institute and in the CPO Accelerator for years. Long before the AI conversation got this loud, we were pushing PMs and product leaders to elevate their thinking beyond execution, into strategy, org design, and executive partnership. As one alum put it:

That's the muscle that compounds. And it's the one most product orgs still haven't systematically built.

What This Means for Your Team

If you are thinking about where to invest on the org side, look at the evergreen skills product managers need and the operating model work that will support that. Skills that emphasize product craft, good decision making, prioritization, cross-functional collaboration, and communication will always be important. Understanding your customers is something no AI can do well. While it’s important for Product Managers to understand how to utilize AI tools to accelerate their work, if they don’t have the foundations, they’ll just be shipping more of the wrong thing.

These compounding skills only pay off when the system around your PMs supports them. Denise Tilles is running our ProdOps 101 workshop on June 18, and it's a good place to start if you want to build the scaffolding. You can register here.

The PM role will keep rewriting itself. The real question is where you are putting your investment: in skills that disappear in two years, or in skills that compound for twenty.

What are you currently spending the most of your week on, and does it fall on the commoditizing side or the compounding side?

PS: you can fill in our AI in Product survey to get a personalized benchmark of where your team stands in the AI adoption spectrum.

Until next time, Melissa Perri Founder Product Institute, Board Member, and Teacher

​