The author discusses the conditions under which maximizing a proxy utility function can lead to harmful outcomes. This analysis suggests that such scenarios pose significant problems for the application of standard decision theory. The text highlights specific circumstances where optimizing for a surrogate goal diverges from intended results. These findings challenge the robustness of current theoretical frameworks used in artificial intelligence and economics. By identifying these failure modes, the work aims to refine how agents should be designed to avoid unintended consequences.