Generative AIA new study finds that certain patterns of AI use are driving cognitive fatigue, while others can help reduce burnout. by Julie Bedard, Matthew Kropp, Megan Hsu, Olivia T. Karaman, Jason Hawes and Gabriella Rosen KellermanMarch 5, 2026HBR Staff/Runstudio/Getty ImagesSummary. Leer en españolLer em portuguêsPostBuy CopiesOn New Year’s Day, programmer Steve Yegge launched Gas Town, an open-source platform that lets users orchestrate swarms of Claude Code agents simultaneously, assembling software at blistering speed. The results were impressive, but also dizzying. “[T]here’s really too much going on for you to reasonably comprehend,” wrote one early user. “I had a palpable sense of stress watching it. Gas Town was moving too fast for me.”Read more on Generative AI or related topics AI and machine learning, Technology and analytics, Analytics and data science and AutomationPostBuy CopiesRead more on Generative AI or related topics AI and machine learning, Technology and analytics, Analytics and data science and Automation
When Using AI Leads to “Brain Fry”
As firms increasingly incentivize employees to build and oversee complex teams of agents—for example, by measuring and rewarding token consumption as a proxy for performance—people are finding themselves pushed to their cognitive limits. Participants in a recent study described a “buzzing” feeling or a mental fog with difficulty focusing, slower decision-making, and headaches. The authors call this phenomenon “AI brain fry,” defined as mental fatigue from excessive use or oversight of AI tools beyond one’s cognitive capacity. This AI-associated mental strain carries significant costs in the form of increased employee errors, decision fatigue, and intention to quit. The findings also show how AI-driven workflows can be designed to diminish burnout and point toward specific manager, team, and organizational practices to avoid mental fatigue even as AI work intensifies.
