Prompt Engineering
The practice of designing inputs to elicit optimal outputs from language models.
Prompt engineering involves structuring instructions, examples, and context to maximize model accuracy and minimize token usage. Techniques include zero-shot instructions, few-shot examples, chain-of-thought reasoning, and role assignment via system prompts. Effective prompting can reduce costs by 30–60% by cutting redundant tokens and improving first-attempt accuracy.
İlgili Terimler
An instruction block sent before the conversation that configures model behavior.
Prompting a model to perform a task without providing any examples.
Providing a small number of input-output examples in the prompt to guide the model.
A prompting technique that instructs the model to reason step-by-step before answering.