Dis correct — the defining feature offew-shot promptingis the inclusion ofmultiple input-output exampleswithin the prompt todemonstrate the desired behavior or output structureto the LLM.
In UiPath’s Agentic Prompting practices, few-shot examples help:
Anchor the model to a consistent format
Reduce ambiguity in task instructions
Improve performance in tasks like classification, transformation, or content generation
Example:
Input: “My password isn’t working.”
Output: “Category: Login Issue”
Input: “App won’t open.”
Output: “Category: Access Error”
This trains the model within the prompt — no fine-tuning required — making it apowerful design patternin building intelligent agents.
Option A describeschain-of-thought prompting.
B refers tozero-shot prompting.
C refers toprompt chaining, used in advanced orchestration, not few-shot logic.
