Full Explanation
When AI gives a wrong answer, the instinct is to blame intelligence or memory. But if we narrow down to missing knowledge, there are only three structured causes: a training gap (the information was never part of the dataset), an injection gap (the information exists but was never added to the model's system), or a visibility limit (the conversation grew long enough that earlier context fell outside the context window). In all three cases, the model is not being stupid — it is operating within structural constraints.
Understanding which cause applies changes how you respond. For a training gap, provide the information explicitly in the chat. For a knowledge cutoff, use browsing, retrieval, or re-injection. For a visibility limit, restate the critical information in the current conversation. Before blaming intelligence or memory, ask a simpler question: where would this knowledge have come from?
