AI & LLMs
Few-Shot Prompting
Showing an LLM a few labelled examples in the prompt instead of describing what you want in prose.
Reviewed by the RadarTrek editorial team · June 2026
Few-shot prompting includes one or more example input-output pairs directly in the prompt before the real input, so the model can pattern-match rather than infer your intent from a written description. A single well-chosen example often communicates a format or classification scheme more reliably than several paragraphs of instructions.
Why it matters
- —Examples are usually faster and more reliable than written instructions for formatting, tone, and classification tasks.
- —Few-shot examples anchor the model to your specific categories instead of its own generalised assumptions.
- —A small change to one example can noticeably shift the model's output — examples are a real lever, not decoration.
Where to learn this
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Few-Shot Prompting
AI Prompt Engineering course
This is the exact lesson that covers this term in depth — with examples, diagrams, and a hands-on exercise.