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I recently noticed a paradox among a team of developers. With AI, engineers started writing code faster and getting answers in seconds, yet they also reported feeling more exhausted than before.<\/p>\n<\/div>\n
AI hasn\u2019t actually reduced the amount of work that needs to be done. Instead, it has fundamentally changed its nature. We can now run multiple tasks in parallel and perceive this as productivity. Up to a point, it is. But eventually, managing tools and constantly switching between them becomes more draining than performing the original tasks themselves. In some cases, it even slows down the process of finding a solution.<\/p>\n
I\u2019ve been managing developer teams for over 15 years, and I\u2019ve spent the past year trying to understand why AI tools\u2014designed to make work easier\u2014sometimes have the opposite effect. Here are the causes behind this phenomenon and what we can do about it.<\/p>\n
Take a developer\u2019s workflow as an example. In the past, when faced with a complex problem, developers would search Google, use Stack Overflow (before ChatGPT arrived), and ask colleagues for help. Each step and decision was separated by reflection time.<\/p>\n<\/div>\n Now, they start using Cursor or GitHub Copilot\u2014AI tools that suggest code in real time. The path to an answer gets shorter. But instead of searching, they\u2019re now engaged in continuous evaluation of AI suggestions: Accept the autocomplete or reject it, rewrite the prompt or regenerate the output. Dozens of micro-decisions with no pauses between them.<\/p>\n Each of these carries a cognitive \u201ccost.\u201d Even the smallest choice demands attention and mental effort. The more decisions a person makes daily, the worse the quality of each subsequent one. This happens because of what psychologists call decision fatigue<\/a>. AI has amplified this problem by dramatically increasing the number of decisions a person must make while completing a single task.<\/p>\n Researchers at Boston Consulting Group<\/a> (BCG) surveyed nearly 1,500 U.S.-based workers. They found that 14% of people who use AI at work, needing a high amount oversight, experience \u201cAI brain fry\u201d\u2014a feeling of mental fog and an inability to focus. And this has consequences: Workers experiencing it are more likely to consider changing jobs and make more mistakes.<\/p>\n<\/div>\n I\u2019ve seen it repeatedly: Managers begin implementing AI with the same question: How can we use these tools to help the team get more done? Then they start adding AI services.<\/p>\n One or two AI tools genuinely do boost productivity, per BCG, but at three tools, productivity peaks. With the fourth, it drops. Each new tool means new settings, prompts, and workflows. At some point, the team spends more effort managing tools than doing the actual work.<\/p>\n The worker stops being the doer and becomes the one checking, comparing, and choosing. Meanwhile, people remain convinced that AI makes them faster. But according to METR data<\/a>, the opposite was true: Experienced developers using AI tools actually worked more slowly\u2014even while believing their task completion time decreased by nearly a quarter.<\/p>\n<\/div>\n