Your Org Structure Is My Opportunity

Why AI "copilots" don't fix what's actually broken

A founder told me that his hardest problem isn’t the product or the customers. It’s hiring. He can’t find people who can do more than one thing well. And I think I know why. A generation of talent spent the last decade inside companies that trained them to do exactly one job, in exactly one box, on exactly one org chart.

On the flip side, I talked to an exec who was proud of his AI rollout. Every team had copilots, dashboards tracked adoption, and he walked me through efficiency gains for twenty minutes. I asked how his hiring plan had changed. It hadn’t. He couldn’t name a single metric that moved because of AI, and headcount was still going up. He’d given every person in every role an AI assistant and left the structure exactly where it was.

Same dependencies between product and design. Same review cycles between design and eng. Same meetings with eight people so everyone “has context.” Product still says “prioritize.” Eng still says “capacity.” The board wants Q2 projections and something about “product velocity.” Everyone’s busy. They look around the room and it feels like progress.

These roles used to make sense. The PM had the idea, the engineer built it. That separation existed because you could not do the next step yourself. It was a real skill constraint, not some process thing. AI blew that up and nobody seems to have noticed, or at least nobody redrew the org chart.

At an event for non-technical folks using Claude Code, I watched an investment banker build a shopping app and push it live for customers that same afternoon. The distance between idea and done is basically zero now, for everyone, and most companies are still organized around a distance that no longer exists.

No fast-growing startup I know is hiring just a PM or just a marketer anymore. They want tinkerers. The person who talks to the customer in the morning, builds the fix by noon, and ships it before dinner. One brain holding the whole problem, start to finish. Not because they can’t afford to specialize. Because every time work changes hands, context leaks. And they learned to just not have that problem.

The best AI-native startups I see are spending thousands a month on token costs instead of adding headcount. Their biggest line item isn’t salaries. It’s compute. I think that says more about where companies are headed than any AI “strategy” deck.

Your company still has a role for every function and a gap between each one. Those gaps add up to weeks, and in those weeks your customers are already talking to someone who doesn’t work that way.

Every Fortune 500 is hiring a Chief AI Officer right now. Same instinct as “VP of Innovation” a decade ago. You created a role so the rest of the org could stay exactly as it is. Tobi Lutke doesn’t have a CAIO. He is the CAIO. His conviction comes from building, not briefings. Most CEOs would rather hire someone to have that conviction on their behalf, and it shows.

Startups have always been faster, that’s not news. What changed is that AI lets every person on a team take something from idea to shipped product without needing anyone else to touch it. Per-seat incumbents have the same tools on every laptop and a structure that forces the separation anyway.

The pot keeps boiling.