AI Vocabulary · 03 Working with AI
What is Few-Shot Prompting?
Showing the model a few examples of what you want, so it can copy the pattern instead of guessing it.
Few-shot prompting means including a handful of worked examples in your prompt: two or three inputs together with the output you would want for each. The model picks up the pattern, such as tone, length, format and level of detail, and applies it to the new case. "Zero-shot" means asking without any examples.
It is one of the simplest and most reliable ways to improve results, especially for formats that are hard to describe in words, like your house style or a specific way of tagging data. Good examples also make structured output more consistent.
Why it matters for you
If you find yourself writing long descriptions of the style you want, show it instead. Two real examples usually beat a paragraph of adjectives.
Own it
Your best examples are a reusable asset. Collect them in a prompt library so the whole team gets the same quality, with any tool.
Where it comes from
The phrase became famous with OpenAI's 2020 GPT-3 paper, titled Language Models are Few-Shot Learners. It showed that a large model could pick up a new task from just a handful of examples placed in the prompt, with no retraining. "Zero-shot" and "one-shot" come from the same research vocabulary, describing tasks with no or one example.
Related
Your AI Learning Hub
Learn the whole AI Vocabulary, step by step, and build with it. Build it. Own it.