Core Viewpoint - The article argues that the prevalent use of chat interfaces in AI products is a result of laziness in design, leading to a failure in user experience and interaction efficiency [4][5][8]. Group 1: Chat Interface as a Design Flaw - Chat interfaces are described as a lazy product of design, which fails to adapt to user needs and instead forces users to learn the system [5][12]. - The uniformity of AI product interfaces is alarming, indicating a lack of user-centered design [7][8]. - Nearly 50% of potential users are deterred by chat-based AI tools due to usability issues, which require users to act as "prompt engineers" [12][28]. Group 2: Inefficiency in User Interaction - Users spend 11% to 27% of their time in inefficient interactions with AI, with 26% of their questions remaining unresolved [11][12]. - The complexity of AI collaboration is compared to cooking with a sous-chef, requiring iterative work rather than simple queries like Google Search [13][14]. - Heavy users of AI tools experience cognitive overload due to the need to explain context repeatedly and transfer outputs manually [13][14]. Group 3: Successful AI Product Design Examples - Companies like GitHub and Microsoft have successfully integrated AI into existing workflows, enhancing productivity by 56% through seamless integration rather than isolated chat windows [16][17]. - The design of these products emphasizes the role of AI in empowering existing workflows rather than replacing them with inferior interaction modes [16][17]. Group 4: Proposed Design Framework - A new design framework called "Hybrid Workspace" is proposed, which includes a work environment and an intelligent layer that integrates AI capabilities contextually [17][18]. - This framework aims to reduce the cognitive load on users by eliminating the barrier between thinking and acting, thus maintaining user flow [22][27]. Group 5: Future of AI UX Design - By 2025, companies that continue to prioritize chat-first models will struggle against those that create workflow-native AI experiences [28][29]. - The industry faces a choice between refining chat interfaces or leading the way in creating valuable AI experiences that respect user intelligence and workflow [29][30].