Why showing the model examples changes what it's actually doing — not just how much it knows.
It's tempting to think of zero-shot and few-shot prompting as points on the same dial — few-shot is just zero-shot with "more stuff" added to the prompt. That framing misses the actual mechanism. A zero-shot prompt asks the model to interpret a natural-language instruction and infer, on its own, exactly what output is wanted. A few-shot prompt instead demonstrates the desired output through concrete worked examples, letting the model extend a pattern rather than guess at an abstract description. Those are two genuinely different ways of getting a model to do what you want — and the difference shows up hardest exactly where it matters most: getting a consistent, specific output format every single time.