AI Amplifies the ‘Build Trap,’ Warns Product Strategist Melissa Perri

In a recent LinkedIn post, product strategy expert Melissa Perri warns that the advent of artificial intelligence, while promising increased efficiency, may inadvertently exacerbate a critical pitfall for many development teams: the “build trap.” Perri, author of “Escaping the Build Trap,” argues that AI’s ability to significantly accelerate production could lead organizations further astray if not managed with strategic discipline.

Perri highlights the core issue of the build trap, which she defines as a pervasive organizational tendency to measure success by the sheer volume of features shipped, rather than the actual value those features deliver to customers or the business. This often results in busy roadmaps and teams that appear productive, yet fail to achieve meaningful business outcomes.

“That is the build trap. Mistaking output for outcome. Confusing motion for progress.”

The AI Acceleration of the Build Trap

Traditionally, the inherent effort and cost associated with building products served as a natural brake on unchecked development. Teams had to be somewhat selective about what they chose to build, forcing a consideration of value. However, Perri points out that AI is rapidly removing this constraint.

“AI just removed that brake,” Perri writes. “When shipping a feature costs almost nothing, the discipline of asking ‘should we build this at all’ gets quietly skipped. Why argue about value when you can just build it and find out? So teams produce more, faster, and call it progress.”

This acceleration, according to Perri, means that the gains from AI are often realized in the engineering process itself, rather than translating into tangible benefits felt by customers or the business. Her recent survey findings underscore this observation, indicating that “the measurable wins from AI are landing where engineers build, not where customers feel it.”

The Enduring Importance of Saying ‘No’

Perri contends that the teams poised for success in the coming years will not be those that simply leverage AI to build more, but those that retain the crucial discipline of strategic selection. The ability to discern and prioritize valuable work, and to refuse the wrong work, becomes even more critical when the cost of building is no longer a significant deterrent.

Discipline Over Speed

In Perri’s view, the build trap has always been fundamentally a problem of discipline, masquerading as a speed issue. AI, by drastically reducing the speed bottleneck, has effectively raised the stakes for this underlying discipline problem.

“The build trap was always a discipline problem dressed up as a speed problem. AI just raised the stakes.”

The challenge for organizations, therefore, is not merely to adopt AI for faster development, but to reinforce the strategic thinking and prioritization processes that ensure this increased speed serves genuine business objectives. Perri’s analysis suggests that without this focus on outcome over output, AI-driven efficiency could lead to a more severe and widespread build trap.

Concluding her post, Perri poses a reflective question to her audience: “What is one feature your team shipped this year that you would take back if you could?” This prompts a broader conversation about the value-driven decisions that should guide product development, even in an era of unprecedented building speed.