LLMs are pattern matchers, but every model is given specific instructions and response designs that influence what to do given unclear prompts. This is hugely valuable to understand since you may ask an LLM an invalid question and it is important to know if it is likely to guess at your intent, reject the prompt or respond randomly.

Understanding how LLMs fail differently is becoming more valuable than knowing that they all got 100% on some reasoning test with perfect context.