Complex-app users don’t always fit neatly into “novice” or “expert” labels. Designing for Legacy, Legend, and Learner users leads to more inclusive, effective systems.

Use-case prompt suggestions show how to effectively prompt AI tools. They aid learnability and creativity, helping users explore what AI tools can do.

To navigate this period of change, researchers must explore how generative AI changes what we study and how we study it.

Design specifications should provide all the relevant information needed to align the design and development teams.

Hamburger menus are a more familiar pattern today than 10 years ago, but the same old best practices for hidden navigation still apply.

AI-generated review summaries extract qualitative key themes from customer feedback, helping shoppers quickly assess what purchasers think about the product.

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Improve AI-enhanced workshops by narrowing ideas with clear criteria, allowing time to prompt, encouraging collaboration, and documenting results.

Top product experts share four strategies for remaining indispensable as AI changes UI design, accelerates feature production, and reshapes data analysis.

Overreliance on frameworks as universal solutions rather than adaptable starting points undermines critical thinking and threatens our field's intellectual rigor.

Plan AI-enhanced workshops by preparing warmup activities involving AI, uploading context files, creating custom AIs, and providing adaptable sample prompts.

AI acts as a creative teammate in group settings as it does for solo work. Thoughtful facilitation ensures teams leverage AI effectively in workshops and critiques.

Serial task switching, or rapidly shifting attention between tasks, is a natural user behavior that lowers productivity and increases stress and the chance of errors.

Better target user needs by understanding the three sizes of copy: long-form, short-form, and microcopy.

AI hallucinations threaten the usefulness of LLM-generated text in professional environments, but today’s LLMs encourage users to take outputs at face value.

AI is a new tool, not a replacement for UX professionals.

Despite improvements in narrow-scope AI design tools, most design-specific AI cannot replicate human designers’ output quality.

Training modern LLMs is a costly process that shapes the model’s outputs and involves unsupervised, supervised, and reinforcement learning.

Analyze with confidence by collecting relevant data, critically assessing it, and forming testable explanations.

System-generated suggestions for AI prompts must be contextually relevant, personalized, and specific to the task and the user’s level of experience.