Business: Product Management

Over the last several years, I’ve noticed a shift in the adoption of User Experience within organizations. This is encouraging, but might also require UX professionals to consider the skills and the roles that we bring to product teams. There are two key factors that are now impacting the way UX professionals work with product teams.

First is the adoption of new project-management methods, as well as the integration of UX deliverables into those methods. Early in my career, most software and Web projects followed a waterfall methodology, which is still common in manufacturing industries. The difficulty I frequently encountered with this approach was that it rarely allowed sufficient time for the integration of new knowledge. UX research often got squeezed out because it didn’t directly add business value. Often, from the beginning of a project, a product team essentially had to know exactly what they would deliver at the end of the project. The team’s inability to deviate from the original plan undermined the iterative nature of most UX design approaches. Read More

Some have hailed the introduction of artificial intelligence (AI) as a seismic shift, an epochal change, and having the most powerful impact on business since the Internet. However, this article might disappoint you. In truth, AI is not meant to do everything, all the time.

In the face of technological hype, product teams and UX professionals risk falling into the “AI-for-everything” trap. They often pursue agentic AI solutions because the technology is novel, not because it represents the most efficient or high-value answer to a user painpoint. The outcome is predictable: wasted resources, unnecessary complexity, and user frustration with a product that fails to solve the right problem. Therefore, the most effective AI strategy involves mastering the power of no. UX designers must move the conversation from Can we build this with AI? to this more responsible and strategic question: Should we build this with AI?

Answering this question requires a rigorous, data-informed tool for governance. Therefore, I have developed the AI Value Rubric to force a structured conversation balancing user needs, business objectives, and technical aptitude to help product teams separate high-impact AI opportunities from technical vanity projects. Read More

As software products have expanded over the decades, companies have had to apply a fair amount of effort to managing their customers’ experience. Since companies have added more and more features and functions to their software products, customer engagement has begun to fluctuate. Managing customers’ expectations had become complicated. These products have continued to grow because customers desired more features and the software companies wanted to offer more value—for a nominal fee, of course. Now, these companies confront the challenge not only of how to design and build the new features but also how to manage and release them.

Several companies—for example, Google—have managed these changes fairly well, but many have a lot of room for improvement. The days are over when we can honestly say, “If we build it, they will come.” We must do the work necessary to truly understand our customers’ needs. If we understood our customers, we would understand that we can’t just jam new features or functions into our software and expect customers joyfully to accept them. Read More