“AI提高了我的生产力，但我更累了”

Core Viewpoint - The article discusses the phenomenon of "AI fatigue," where increased productivity through AI tools leads to greater stress and exhaustion among developers, rather than the anticipated efficiency gains [1][42]. Group 1: AI's Impact on Productivity - AI has the potential to significantly enhance productivity, allowing tasks that previously took a day to be completed in an hour [9]. - However, this efficiency often results in an increased workload, as developers are expected to handle multiple tasks simultaneously, leading to fragmented attention and higher energy consumption [10][9]. - The shift from a creator role to a quality control role means developers spend more time evaluating and correcting AI-generated outputs, which is more mentally taxing than traditional coding [12][14]. Group 2: Psychological and Emotional Effects - The unpredictability of AI outputs creates anxiety, as developers cannot rely on consistent results, leading to a constant state of alertness [18][20]. - The rapid evolution of AI tools requires continuous learning, which can lead to feelings of inadequacy and pressure to keep up with peers, exacerbating stress levels [23][39]. - Over-reliance on AI can result in cognitive decline, as critical thinking skills may diminish when individuals do not engage in independent problem-solving [33]. Group 3: Strategies for Managing AI Fatigue - The author suggests implementing time limits for AI tasks, distinguishing between thinking and execution time, and accepting that AI outputs do not need to be perfect [43][45]. - Developers are encouraged to focus on foundational concepts rather than chasing every new tool, and to document the efficiency of AI usage to determine when to rely on it [43][45]. - Emphasizing the importance of mental breaks and allowing for downtime can help maintain overall well-being and productivity in the AI-driven work environment [47].