UX research should be optimized not around studies and methods, but around reducing uncertainty in product decisions. AI makes generating hypotheses cheaper, which increases the value of researcher judgment about when existing evidence is enough and when reality still needs to be tested with users

Empathy maps organize what users say, think, do, and feel to create a shared understanding and expose gaps in research. NN/g also warns against filling them with assumptions or letting AI invent evidence that cannot be traced back to real user data

ChatGPT-5.6 matched human coders on open-ended survey responses and showed near-perfect consistency across repeated runs. Compared with GPT-4, it also produced more granular themes while maintaining strong agreement with human researchers

Product teams are getting faster at designing and building, but not always better at understanding whether users actually need what they create. The article argues for grounding product decisions in research, analytics, and observed behavior instead of assumptions, stakeholder opinions, and competitor copying

A tiny “Continue” button exposed a much bigger UX problem: users often hesitate not because of the control itself, but because they don’t understand what will happen next. The article reframes UX as designing a sequence of decisions, where each step gives users enough context, feedback, and reassurance to keep moving