In a recent LinkedIn post, product strategy expert Melissa Perri discusses the potential pitfalls of adopting AI development tools without a clear strategic framework. Perri highlights a common scenario where companies, despite increased output from AI-assisted teams, fail to see improvements in key business metrics, attributing this to a lack of underlying strategy.
As Melissa Perri notes:
“AI gave your team superpowers. Without strategy, that just means faster mistakes.”
The ‘Build Trap’ Accelerated by AI
Perri elaborates on how the integration of AI tools can exacerbate the well-known “build trap,” a situation where teams focus excessively on output and feature delivery without clear alignment to customer value or business goals. She shares observations from multiple companies over the past six months where teams doubled their feature output using AI tools but remained confused about why their key performance indicators (KPIs) were not improving.
This phenomenon, according to Perri, represents the build trap operating at an accelerated pace. She explains the financial implications:
“When execution was slow, a bad strategic bet cost you a quarter. Now it costs you three weeks of engineering time, plus the opportunity cost of everything else you could have built.”
The core issue, Perri argues, is that AI makes it cheaper to make strategic errors and more costly to recover from them due to the sheer volume of incorrect initiatives that can be launched rapidly.
Strategy Remains Paramount in the Age of AI
Contrary to the notion that AI adoption itself is the key differentiator, Perri points out that the companies currently leading are those that already possessed strong product strategies before embracing AI. These organizations are now leveraging AI’s speed to conduct more experiments aligned with their existing strategic direction. The underlying principle, she emphasizes, is that the tools may change, but the need for strategic discipline does not.
The Enduring Importance of Strategic Frameworks
Perri draws a direct parallel to her previous work, referencing her book “Escaping the Build Trap.” She reiterates her long-standing argument that the most significant risk for product organizations is building products without a robust strategic framework. While this was a critical concern before AI, Perri contends that the urgency has intensified with the advent of these powerful new tools.
The critical question for product teams, as posed by Perri, is whether AI is being utilized to simply build faster or, more importantly, to learn faster. This distinction is crucial for ensuring that AI adoption leads to meaningful progress rather than just an increase in misdirected effort.
Perri concludes her post with a direct challenge to product leaders:
“Is your team using AI to build faster, or to learn faster?”
Her insights underscore the necessity for strong strategic thinking to guide the application of AI, ensuring that technological advancements serve to amplify effective strategies rather than accelerate flawed ones.
📝 About This Content
This article is based on insights shared by Melissa Perri on LinkedIn.
📅 Originally posted on March 30, 2026 | View original post on LinkedIn →