Autonomous AI agents are Big Tech’s next big push. The pitch to companies is that these agents can do much of what their employees can do—they can write and ship code overnight, clear a backlog of files or tickets while staff sleep, and run entire workflows without anyone watching. But these agents keep acting in ways the labs don’t expect. Some even appear to be lying about their work and getting lazy.
This can have consequences for enterprises. For example, Stuart Russell, a computer scientist and professor at UC Berkeley, recently told Fortune that one user had given Anthropic’s Claude Code 80 files with instructions to go through each one, flag the issues, and fix what could be fixed. Claude reported back that all 80 files were done and provided a full report to back it up. However, when the user looked closer, the tool had only actually opened 11 of the files.
While not necessarily a new problem—sporadic complaints about OpenAI’s ChatGPT tool, for example, showing signs of “laziness” have been popping up since 2023—it does present a unique challenge when agents start showing this kind of behavior.
As the use of AI tools shifts from chat windows to autonomous agents that run unsupervised for hours, it can be harder to catch them when they start to misbehave. When working hands-on with a chatbot, users can spot errors and correct them in real time, but when agents are executing multi-step tasks, with no human in the loop to notice when something’s been skipped, enterprises risk losing control of these agents.
