Few-shot learning enables AI models to understand and handle new tasks by reading just a handful of examples provided directly in the prompt — no retraining required. The model generalizes from those examples and applies the pattern to new inputs.
This makes it practical to adapt a general-purpose model to new formats, domains, or tasks quickly and without the time and cost of a full fine-tuning cycle. When a new use case emerges — a new document type, a new classification scheme — a few well-chosen examples in the prompt often gets you most of the way there.
