This article examines how current language models struggle to learn from context effectively. Despite having access to relevant information, they often fail to solve tasks due to a reliance on pre-trained knowledge and an inability to adapt to new contextual rules. Empirical evaluations highlight significant shortcomings in context learning capabilities across leading models.