The abstract of a new arXiv paper reports that agentic large language models have been documented to lose reasoning capability when placed inside a harness—the software that mediates their observations and actions. This is presented as a known problem for LLM agents operating within structured environments.
To address this, the authors introduce AutoOnboarder, a system designed to reconcile these losses. The available abstract text does not specify the method or results, only that the system is introduced for this purpose.
The paper is listed as a new announcement on arXiv under identifier 2610.21218, indicating a recent submission. Further details would require access to the full manuscript.