Few-shot learning is a model's ability to perform a new task after seeing only a handful of examples, typically two to five, without retraining. Large language models excel at this: show the model a few input-output pairs and it infers the pattern. An HR team can classify CVs as junior or senior by providing three labeled examples in the prompt. Few-shot capability is what makes modern LLMs flexible enough for thousands of business use cases without building custom models.