The PM role has always been a weird one. You are called the CEO of the product but you manage no one. You are the bridge between engineering, design, and business, but every group thinks you are slightly in their way. Engineers think you lack technical depth. Designers think you kill their ideas. Stakeholders think you are too slow. I have felt all of that across 20 years, and I think AI resolves a lot of it, in a way that changes the shape of the role permanently.
The old model and its friction
Traditional product development runs on handoffs. The PM writes the spec and hands it to design. Design creates mockups and hands them to engineering. Engineering asks clarifying questions, builds something slightly different from what anyone imagined, and everyone regroups. Each handoff loses information. Each transition adds time. Nobody owns the whole thing end to end. I saw this at Microsoft, at Salesforce, at every big company. The process worked, sort of, because each person brought deep specialized skill, but the coordination cost was enormous. Half the meetings existed just to keep everyone aligned on decisions that kept shifting.
What AI changes
AI tools are collapsing the distance between disciplines. A PM can build a working prototype without writing a line of code, using AI coding assistants: describe what you want, iterate, have something clickable in a couple hours. A designer can generate functional UI without waiting for an engineer to stub it out. An engineer can test multiple UI approaches without waiting for design to deliver options. Each person can do more of the full stack than before, and the boundaries between roles blur.
The archetype
Out of that, a new archetype emerges: someone who can think strategically about what to build (the PM skill), create and iterate on the experience (the design skill), and build and ship it (the engineering skill), with AI amplifying each. This is not a new title. It is how the best product people already work across the lifecycle. AI analyzes market data and feedback so you reach a hypothesis faster. Instead of writing specs, you build a prototype in hours. You put it in front of customers and AI transcribes and surfaces themes in minutes. Low-code and AI-assisted development let one person ship what used to need a full squad. When I was at Quip, before it merged into Slack, we restructured engineering around ownership, sometimes just one engineer owning an area end to end. AI takes that further: one person, augmented by AI, can own an entire product surface.
It is not everyone going solo
The solo AI product engineer works great for internal tools, early-stage products, and quick experiments. It is not a replacement for deep specialization at scale. Complex systems still need dedicated engineers. Nuanced experiences still need dedicated designers. But the threshold for when you need a full cross-functional team moved. Three people and four weeks became one person and four days.
If you are a PM, you already have the hardest skill: customer empathy and strategic thinking. AI gives you the how. This week, take one feature idea, skip the spec, open an AI coding tool, and build it yourself until you can show it to a customer.