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In this edition of “Office Optional with Larry English,” Larry talks about how AI is evolving the product manager role, giving rise to a new title, the product builder. He explains how this shift highlights a bigger question for leaders: Is your organization prepared for a future where work is organized around capabilities instead of functions?
Product managers will disappear by 2030. That was one of the big takeaways from the 2026 Products That Count CPO Impact Report. It sounds like just more “AI is killing jobs” doom and gloom but look deeper and the story is far more interesting and positive.
Here’s what the data says: Product manager roles are indeed down, 30% overall and 70% in SaaS. But at the same time, AI is giving birth to a new role, the product builder.
Products That Count, a global nonprofit network that supports over 500,000 product managers, describes product builders as individuals who combine product thinking, technical fluency, design judgment and business understanding to move quickly from idea to outcome. Product builders can come from engineering, design or product management backgrounds. What matters is their ability to own the entire process of creating value. According to the CPO Impact Report, the number of product builders has nearly tripled in recent years, from 600,000 to 1.7 million people.
This shift in the product world highlights a bigger question for leaders learning to navigate an AI-powered business world. Is your organization prepared for a future where work is organized around capabilities instead of functions?
When Building Gets Cheaper, Building Increases
This evolution in the product world follows an old pattern we’ve seen before throughout technology history. Whenever the cost of creating something falls, demand for creation tends to rise.
For example, when mobile development emerged, many people predicted that easier development tools would reduce demand for developers. But the opposite happened, as lower barriers to building created an explosion of applications, products and businesses. As SC Moatti, founder and board chair at Products That Count and founding managing partner at Mighty Capital, told me in an interview, building the app quickly became the easy part. The real work was maintaining it, evolving it to meet customer needs and keeping it relevant over time.
AI is creating similar economics for software development. For decades, software development was expensive, slow and resource-intensive. Organizations needed large teams of specialists working through lengthy development cycles. Those conditions created functional silos. Product managers managed requirements, while designers created experiences and engineers built solutions.
At my company, Centric Consulting, we recently built an agentic platform designed to accelerate application modernization. Work that previously might have required a team of 10 people working for a year can now be completed by a smaller team in less time with AI support. Legacy applications, technical debt and modernization projects that organizations once considered too expensive are suddenly becoming economically viable.
The New Bottleneck Is Human Judgment
As the cost of execution falls, however, a new constraint emerges. Many companies can now prototype, build and launch products far faster than they can market them. As AI reduces the cost of experimentation, knowing what to build, when to build it and how to create value from it becomes more important.
AI can generate requirements, create prototypes, write code, test applications and produce documentation. What it cannot do is determine whether an initiative solves a meaningful customer problem, aligns with business strategy or represents the best use of organizational resources. The more AI handles execution, the more valuable it becomes to have people who can connect customer needs, business priorities and technical possibilities into a coherent product strategy. This is where the role of product builder comes in.
This is also where many organizations misunderstand AI’s impact. They assume faster execution automatically leads to better outcomes. In reality, AI often amplifies existing weaknesses. If strategy is unclear, AI helps organizations build the wrong thing faster. If customer understanding is lacking, AI accelerates the delivery of features no one wants. And so on.
The Product Builder Is The First AI-Native Role
Most organizations are using AI to make existing processes faster. However, those pulling ahead are using AI to question whether those processes should exist at all. Adding AI to an unchanged process produces incremental results, Moatti said. The organizations moving fastest are redesigning the entire product lifecycle around what AI now makes possible.
The product builder role is what an AI-native product process looks like in practice. The traditional product manager often served as a coordinator. They gathered requirements, managed roadmaps and facilitated communication between specialized teams. That structure made sense when execution required extensive coordination across multiple disciplines.
The product builder is less focused on coordinating work and more focused on creating outcomes, using AI as a force multiplier throughout the process.
Product builders won’t simply launch products. They’ll also be responsible for continually reinventing them. “If the current rate of innovation stays at this high level, your risk as a company or product builder is high that somebody is going to disrupt you, unless you do it yourself,” Moatti says. “Product is going to become a culture of cannibalization because that’s the only way you survive if you’re constantly at risk that somebody can disrupt you. You just have to reinvent your own product over and over again.”
What Leaders Should Do Now
The challenge for leaders is that most organizations are still structured around functions. Product, design and engineering report into different leaders, operate on different metrics and follow different workflows. As AI collapses the work, those organizational boundaries become harder to justify. Leaders may find that their greatest obstacle isn’t technology but rather an outdated structure built for a pre-AI workflow.
The deeper question is the same one raised by the Products That Count report: What happens when capabilities matter more than functions? Product builders may simply be the first example of a broader workforce transformation that’s already underway.
The rise of the product builder doesn’t mean organizations should eliminate product managers, designers or engineers. Specialized expertise will remain essential. What is changing is how those capabilities come together.
We’re entering an era where the cost of building software is falling dramatically. That won’t reduce the need for people who create products; rather, it will increase the need for people who can combine product thinking, technical fluency, design judgment and business understanding into a single capability.
AI is shifting the competitive edge from team size and model quality to talent — specifically, builders who can pair human judgment with AI-powered execution.
Product builders may be the first example of this shift. They almost certainly won’t be the last. As AI continues to merge traditional boundaries between functions, leaders will need to rethink not only how work gets done, but how work is organized.
