Silicon Valley has wrestled for years with a persistent question: How valuable are product managers? These professionals serve as the connective tissue between engineers, designers, sales, and leadership—orchestrating the often-chaotic process of building products people actually want.
Now, artificial intelligence is changing the equation.
As AI-powered coding tools accelerate development cycles, engineers are shipping faster and iterating more frequently than ever. But while engineering capacity expands, the rest of the product team isn't necessarily growing at the same pace. The result? Product managers and designers find themselves stretched thinner, supporting what effectively feels like a much larger engineering force.
The Productivity Gap
Amol Avasare, Anthropic's head of growth, recently discussed this dynamic on "Lenny's Podcast." He noted that engineers are seeing the most immediate gains from AI tools like Claude Code, with productivity jumps of 2–3x becoming commonplace. Yet team structures haven't adjusted accordingly.
"PM and design are just squeezed," Avasare observed.
Two Paths Forward
Anthropic is responding by hiring more product managers to absorb the increased workload. But Avasare suggests a different model may emerge—especially at larger companies building technically complex products: empower engineers to wear both hats.
Anthropic is already piloting this approach internally. For projects requiring two weeks or less of engineering effort, the engineer assumes product management responsibilities: defining scope, coordinating with legal, and engaging cross-functional stakeholders.
"That, I think, is the approach that I expect more companies will start to do, which is just deputize the engineers to be mini PMs," Avasare said.
The Rise of the "Product Engineer"
Avasare isn't alone in spotting this shift. At last year's HumanX AI conference, Zencoder CEO Andrew Filev described a similar evolution: the emergence of the "product engineer"—a hybrid role blending technical execution with product strategy, fueled by the rise of vibe coding and AI-assisted development.
What This Means for Tech Teams
This transition isn't just about titles—it's about rethinking how product gets built. As AI lowers the barrier to shipping code, the bottleneck may shift from *building* to *deciding what to build*. That demands a stronger product sense across the team, not just from dedicated PMs.
For organizations, the question becomes: Do you scale the PM function to match engineering velocity? Or do you cultivate engineers who can think strategically about user needs, business goals, and cross-functional alignment?
For professionals, it signals a new skill set to develop: technical builders may need to sharpen their product intuition, while product leaders may need to deepen their technical fluency.
One thing is clear: as AI reshapes how software is made, the roles that surround it won't stay static. The teams that thrive will be those willing to adapt—not just their tools, but their structures, expectations, and definitions of who "owns" the product.