As LLM chat patterns become more widespread, making them accessible is essential to ensuring everyone can access the information, tools, and opportunities they offer. Drawing on his work improving these interfaces, Eric Bailey shares practical ways to make chat-based experiences on the web more accessible and usable for people who rely on assistive technology.
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What can digital transformation teach us about AI adoption? Paul Boag revisits his book Digital Adaptation to show how lessons from the past can help organizations navigate the challenges of AI today.
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The web is evolving beyond menus, forms, and endless clicks toward experiences shaped around human intent. For UX designers, understanding this shift means re-evaluating their role, moving from designing visible interfaces to guiding transparent, intent-driven AI experiences.
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Every website peaks on launch day and slowly drifts from there, not because it breaks, but because nobody has time to keep it current. Autonomous websites, continuously optimized by agents after launch, aim to change that. Pierre Burgy shares what they learned building for full website autonomy and the deeper design problem they uncovered along the way.
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New EU guidelines, why AI sparkles aren’t enough, when AI labels are required, and what the rules mean for AI-powered features and products.
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As AI reshapes product design, it could give designers greater autonomy or expose the gaps that autonomy makes harder to hide. Exploring both the bull and bear cases, Andy Budd examines what happens when designers need less permission to act.
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Many of the AI tools we interact with take the form of text boxes. But what if there was a different way to interact with AI? Oleksii Hrzhehorzhevskyi explores a different approach to creating a new AI assistant and how designers can navigate the field as AI continues to change it.
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Many companies assume everyone craves new AI features. But the reality is that most people don’t want more AI — at least not in the way most AI leaders envision it. Brought to you by Design Patterns For AI Interfaces, friendly video courses on UX and design patterns by Vitaly.
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A closer look at why users don’t need more tools in their daily lives. What they need are seamless integrations of useful features to match already existing, established mental models. Brought to you by Design Patterns For AI Interfaces, friendly video course on UX and design patterns by Vitaly.
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We’ve fallen into conversational tunnel vision, defaulting every AI capability into a chat-based interface simply because LLMs are trained on dialogue data. But great UX is about matching modality to users’ context, intent, and cognitive load, so the interface adapts to the user, not the other way around.
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