Hello Reader,

Happy New Year! I hope you had a chance to rest, reflect, and recharge. We’re back for a new year, and I’m really looking forward to continuing to support you and your teams as you navigate the challenges ahead.

PMs spend too much time with Ops

Last week, I shared a post that sparked a surprisingly deep reaction. PMs, product leaders, and executives all described the same pattern from different angles: talented product people burning out not because they’re weak or inefficient, but because they’re quietly doing the work of holding the organization together. Building dashboards. Creating frameworks. Translating between teams. Reconciling data. Filling gaps that no one formally owns.

What stood out to me wasn’t just the agreement, but the realization many people shared: this isn’t product leadership, it’s infrastructure work. And when that infrastructure doesn’t exist, it lands on the desks of the most capable people in the room.

This is why Product Operations and, more importantly, a clear product operating model are more relevant now than they’ve ever been.

A Product Operating Model is essential

As companies grow, complexity doesn’t increase linearly, it compounds. More products, more markets, more stakeholders, more regulatory pressure, more data, more tools...

Without an explicit way of deciding how product strategy gets set, how data flows, how decisions get made, and how teams stay aligned, product managers end up becoming the operating system of the company by default. That’s not leverage. It’s a slow drain on strategic capacity, and it’s one of the biggest reasons I see strong PMs disengage after 12–18 months.

AI has made this tension impossible to ignore.

Someone posted on my LinkedIn the other day: “I think you need to come to terms with the fact that AI is reducing any need for Product Operations. If you care about the community, you need to help them understand how Product Ops will be eroded, in the same way Product Management will be.” This person completely misses the point. A product operating model still has to exist in a world with AI.

AI doesn’t define the model. A person still needs to define how decisions get made, what good looks like, which data matters, how teams work together, and how change actually happens across a large organization. AI doesn’t make that work disappear.

Teams without a product operating model didn’t suddenly become more effective with AI. They became faster at producing noise. More dashboards without shared definitions. More insights without agreed priorities. More experiments without alignment on outcomes. AI is an amplifier. If you have clarity, it multiplies value. If you have confusion, it multiplies chaos.

And while AI can automate parts of the work, it cannot own the system itself. A human still has to design it, evolve it, and guide the organization through change. Whether that ownership sits with a product leader or a small Product Ops team, the work is real, ongoing, and more important than ever.

How company size matters

This gap is most visible in larger organizations and scaling companies. I’ve seen leaders invest heavily in AI tooling while skipping the hard work of aligning on strategy, governance, and decision rights. Executives ask for AI-driven dashboards without agreeing on what “good” looks like.

Product leaders are told to “move faster” while still mediating every cross-functional conflict and rebuilding the same processes team by team.

In those environments, AI adoption doesn’t fail because the technology isn’t powerful enough; it fails because the organization isn’t designed to absorb it.

A product operating model is what turns new capability into repeatable outcomes. Without it, every new tool just adds another layer of cognitive load.

Get your foundations right first

Looking ahead, the companies that thrive won’t be the ones chasing AI trends the fastest. They’ll be the ones who slow down long enough to get the foundations right. Clear strategy that cascades. Shared metrics that mean the same thing across teams. Defined roles so PMs can lead instead of patching gaps. Product Operations that enables leverage rather than adding bureaucracy.

AI will absolutely be part of that story, but as an accelerant, not a shortcut. You don’t win by adopting more tools. You win by building an organization that knows how to decide, align, and learn together.

If your product teams feel busy but stuck, or energized but overwhelmed, it’s worth asking a simple question: are they building products, or are they spending their days building the operating system of the company? The answer usually tells you exactly where to focus next.

If you're curious about how Product Operations can support you in this journey, you should check the Prod Ops 101 Workshop on March 4th, hosted by my co-author Denise Tilles.

Wishing you a strong start to 2026 and a year of meaningful progress for your product organization.

Until next time,