Working deeply with AI creates a mental crash I'm learning to navigate.

Working deeply with AI creates a mental crash I'm learning to navigate. Pre-AI, a solid 6-hour sesh meant 1-2 meaningful cycles of work. A cold start + a messy middle + the dopamine hit of finishing something. Done. Now I'm running 50-100 of those cycles a day. Each one has the same emotional weight: ramp up, grind through the hard part, feel the rush when it works. Repeat. That's 100x the tax on your nervous system. Huberman talks about the pain of learning - how the brain actually experiences cognitive load as discomfort. Working with AI stacks that discomfort 100 times by dinner. The end-of-day crash is real. I'm still figuring out what "deep rest" means when you've compressed a month of mental cycles into a single afternoon. AI And Machine Learning Competing LLMs Were Asked to Pick Stocks. Their Choices Revealed AI's Limitations. 7 Factors That Drive Returns on AI Investments, According to a New Survey Researchers Asked LLMs for Strategic Advice. They Got Research: Using AI Can Stifle Innovation. But It Doesn't Have To. LLMs Are Overtaking Search. Here's How to Adjust Your Online Presence How Gen AI Can Turn Reams of Text into Actionable Insights When Using AI Leads to "Brain Fry" The Business Cost of AI Brain Fry AI brain fry is more than just uncomforable. Our data reveals that the cognitive strain created by intensive AI use carries several critically significant business costs as well. The first is decision fatigue. Perhaps unsurprisingly, when we exhaust our brains with the cognitive load of intense AI work, we have fewer mental resources available for making high-quality decisions. Workers in our study who endorsed AI brain fry experience 33% more decision fatigue than those who did not. One 2018 study estimated the cost of suboptimal decision making for a $5B revenue firm at $150M per year. A 33% increase in worker decision fatigue could increase that cost by millions of dollars per year. Likely due to a similar mechanism, we found consistent predictive phenomena in terms of AI brain fry and self-reports of both major and minor errors on the job. AI Doesn't Reduce Work—It Intensifies It AI And Machine Learning February 9, 2026 AI Doesn't Reduce Work—It Intensifies It by Aruna Ranganathan and Xingqi Maggie Ye February 9, 2026 Workers in our study who endorsed AI brain fry experience 33% more decision fatigue than those who did not. Blurred boundaries between work and non-work. Because AI made beginning a task so easy—it reduced the friction of facing a blank page or unknown starting point—workers slipped small amounts of work into moments that had previously been breaks. Many prompted AI during lunch, in meetings, or while waiting for a file to load. Some described sending a "quick last prompt" right before leaving their desk so that the AI could work while they stepped away. These actions rarely felt like doing more work, yet over time they produced a workday with fewer natural pauses and a more continuous involvement with work. The conversational style of prompting further softened the experience; typing a line to an AI system felt closer to chatting than to undertaking a formal task, making it easy for work to bleed into lunch, meetings, or even evenings. But our research reveals the risks of letting work informally expand and accelerate: What looks like higher productivity in the short run can mask silent workload creep and growing cognitive strain as employees juggle multiple AI-enabled workflows. Because the extra effort is voluntary and often framed as enjoyable experimentation, it is easy for leaders to overlook how much additional load workers are carrying. Over time, overwork can impair judgment, increase the likelihood of errors, and make it harder for organizations to distinguish genuine productivity gains from unsustainable intensity. For workers, the cumulative effect is fatigue, burnout, and a growing sense that work is harder to step away from, especially as organizational expectations for speed and responsiveness rise.