In a recent LinkedIn post, product management expert Melissa Perri discusses a dangerous new iteration of the “Product Death Cycle” that she believes is being fueled by a misunderstanding of Artificial Intelligence (AI) implementation. Perri highlights how companies are falling into a trap of using AI to dictate product roadmaps, rather than focusing on genuine customer needs.
Perri, author of “Escaping the Build Trap,” shared an updated version of the “Product Death Cycle” originally conceived by her colleague David Bland. This new cycle, she explains, is particularly insidious because it masquercially appears data-driven.
“We’ve created a new version of the Product Death Cycle, and it’s even more dangerous than the original.”
The cycle, as described by Perri, begins with a product failing to gain traction, leading to the question posed to AI about what features are missing. The subsequent step involves building those AI-generated features, only to repeat the process without fundamental user validation. This creates a self-perpetuating loop of wasted development effort.
The Illusion of AI-Driven Strategy
Perri argues that the allure of AI makes this new cycle particularly perilous. Companies are under the impression that they are being innovative and strategic by leveraging AI to inform their product decisions. However, Perri contends that this approach often bypasses the critical work of understanding what actual users require.
“The irony is painful. Companies think they’re being strategic by using AI to inform their roadmaps, but they’re actually avoiding the fundamental work of understanding customer needs. It’s the build trap with a shiny AI wrapper.”
According to Perri, the perception of data-driven decision-making, facilitated by AI, masks the underlying issue. Instead of genuine customer discovery, teams are relying on AI prompts to generate feature ideas. This, she warns, leads to the creation of products and features that lack real user value.
The Danger of Shipping Useless AI Features
The ease and reduced cost of developing and shipping AI-powered features can exacerbate the problem, Perri points out. This technological advancement, while powerful, can enable companies to produce unwanted software at an accelerated rate, contributing to a growing graveyard of underutilized AI products.
“The technology makes it cheaper and easier to ship useless software, so we’re already seeing a graveyard of AI products and features that nobody wanted in the first place.”
Perri emphasizes that the solution to this problem does not lie in developing more sophisticated AI features. Instead, she advocates for a return to fundamental product management principles.
Prioritizing Customer Discovery Over AI Features
The core of Perri’s message is a call for prioritizing genuine customer discovery. She asserts that the path to successful product development, even with AI, must begin with deep engagement with users.
As Melissa Perri advises:
“The solution isn’t better AI features. It’s better customer discovery. Talk to users, understand their problems, then decide if AI can actually solve them.”
By focusing on understanding user problems first, organizations can then determine if AI is an appropriate and effective tool to address those validated needs. This approach, Perri suggests, is essential for avoiding the pitfalls of the AI-driven Product Death Cycle and building products that truly resonate with customers.
📝 About This Content
This article is based on insights shared by Melissa Perri on LinkedIn.
📅 Originally posted on June 27, 2026 | View original post on LinkedIn →