Susan Ripley
Product Leader & Artist

As AI becomes part of everyday software, designing experiences that feel intuitive is only part of our responsibility. We also need to help people recognize when to question the system.

Features are often defined as collections of user stories. Reframing them around Jobs to Be Done creates a clearer connection between scope, customer value, measurement, and meaningful outcomes.

Photography has changed how I pay attention—and reminded me that strong product discovery often starts by slowing down, noticing workarounds, changing the frame, and staying curious long enough to find the better question.

AI is making product development faster. That makes product discovery, evidence, validation, and human judgment more important when deciding what deserves to be built.

Great UX extends beyond a single screen. End-to-end experience design connects touchpoints, transitions, context, teams, and technology around the customer's journey.

Involving product teams early builds ownership, judgment, and better decisions. The key is knowing when to tell, teach, or invite cross-functional problem-solving.

UX and CX operate at different altitudes, but customers experience one journey. Connecting product interactions, customer evidence, and cross-functional touchpoints creates a more coherent end-to-end experience.

Personas, journey maps, prototypes, and other UX artifacts create value when they build shared understanding and help teams make better product decisions—not simply when they are completed.

Healthy leadership sometimes requires necessary endings. Pruning projects, processes, priorities, and roles can redirect limited energy toward the work and people with the greatest potential to grow.

AI empowers fast, high-quality, and innovative results, but its true potential is unlocked when guided by experienced, creative minds

VUCA and the Stacey Matrix help leaders diagnose uncertainty and choose the right operating mode: execute, align, experiment, make smaller bets, or stabilize first.

The Kano Model can do more than rank features. Used with Jobs to Be Done, research, and pull-based planning, it helps teams align on customer expectations and the experience they intend to create.

Generative AI is making UX production faster, but designers remain responsible for judgment, craft, problem framing, customer evidence, and the quality of the experiences they direct AI to create.

Great product ecosystems don't make every experience identical. They create consistency where familiarity reduces friction and purposeful variation where context and customer jobs require it.

A brand promise isn't created by marketing alone. Customers learn what a company stands for through the product, service, support, and every interaction across the journey.

Data-driven product teams start with a baseline, define the outcome before the solution, combine analytics with research, and measure what changes after launch.

Adopting a human-centered design (HCD) approach is not just a trend but a necessity for creating products that resonate deeply with users.

As a design leader, staying ahead means anticipating future needs through continuous research, embracing new technologies, and fostering cur

Systems thinking helps product teams see dependencies, feedback loops, downstream effects, and local optimizations that can turn a reasonable feature decision into a poor overall customer outcome.

Fostering continuous learning and a growth mindset transforms your design team into a hub of discovery and innovation.