Juhee Dubey makes a thoughtful case that AI works best in UX research when teams are intentional about where it fits. Some parts of research benefit from automation and pattern detection, while others still depend on human judgment, empathy, and context. Her framework helps teams separate what should move faster from what still needs deeper human attention. 

DEEP CUT: The teams getting the most value from AI right now are creating better space for humans to focus on the moments that actually require interpretation, nuance, and care.

Bryan Zmijewski explains that UX metrics help teams stay connected to user needs as AI changes how products behave. Metrics like trust, comprehension, and satisfaction help teams understand if the experience is actually working, not just producing output. 

DEEP CUT: Without UX metrics it gets harder to tell if users are gaining clarity or frustration. The fastest learning teams right now are measuring human signals, not just system activity.

The ZURB team created the Glare AI Skills package that turns the Glare framework into installable AI workflows teams can run inside tools like ChatGPT, Cursor, and Claude. The skills help teams connect product decisions to outcomes, run clearer design reviews, and measure what design work actually changed.

DEEP CUT: Skills create repeatable ways to turn messy feedback, opinions, and hunches into signals teams can actually act on before more work piles up.

READER BONUS 

QUICK ACTIONS