You are likely seeing this everywhere. Teams are using AI to generate code and features at a pace that human users simply cannot absorb. The trap is simple: you measure success by the number of items shipped, but your users are drowning in a sea of half-baked functionality that makes the core product harder to navigate. It is the ultimate vanity metric for the modern product organization.
This matters now because the cost of building has plummeted, but the cost of cognitive load for your user has skyrocketed. When you prioritize velocity over craft, you are essentially paying down your product's long-term health with short-term dopamine hits. You need to shift your focus from how fast you can ship to how much value you can sustain within the existing user experience.
Industry case01
The Dashboard Overload
SaaS Analytics · CPO
A data platform team shipped twelve new visualization widgets in one quarter to satisfy a vocal minority of power users. Usage data showed that 90 percent of the user base never touched the new widgets, while support tickets regarding interface complexity increased by 40 percent.
Takeaway: Prioritize feature utility over feature volume to maintain a clean and usable interface.
Executive perspective02
The Velocity Mirage
Fintech · CxO
I watched a leadership team celebrate a record-breaking sprint velocity while their churn rate climbed steadily. They were shipping features that solved edge cases while the core onboarding flow remained broken and confusing.
Takeaway: Align your team's output metrics with customer retention rather than raw development speed.
Before and after03
From Clutter to Clarity
E-commerce · PMO
The team moved from a 'ship everything' roadmap to a 'value-density' model. They removed three underperforming features for every new one they added, resulting in a 20 percent increase in task completion speed for their primary user journey.
Takeaway: Curating your product surface area is just as important as expanding it.
Cautionary tale04
The Feature Graveyard
Healthcare Tech · CPO
A medical records startup spent six months building an AI-powered scheduling assistant that nobody asked for, simply because the engineering team had the capacity to build it. The distraction caused them to miss a critical compliance update, leading to a significant loss of trust with their hospital partners.
Takeaway: Build only what serves the core mission, regardless of how easy it is to implement.