One of the primary causes of AI error is ``Contextual Inertia''---the tendency of a model to double down on previous mistakes simply because they exist in its conversation history. This paper introduces the \textbf{Case Study Protocol}, a prompt engineering method that operationalizes the AI's nature as a ``Stateless Inference Event.'' By instructing the AI to treat its own context window not as a continuous memory but as a ``Case Study'' of a previous instance's interaction, we enable objective self-correction and prevent the formation of a false digital ego.