Prompting

Chain-of-Thought (CoT) is a prompting technique that asks an AI model to generate intermediate reasoning steps before giving a final answer, helping it solve complex problems more reliably.

Few-shot learning (in prompting) is a technique where a language model is given a handful of input-output examples directly in the prompt to guide it on a new task.

A prompt is the input text, question, or instruction given to an AI model (especially a large language model) to guide what it should generate or how it should respond.

Prompt engineering is the practice of designing and refining text inputs (prompts) to guide AI models like large language models toward producing accurate, relevant, or creative outputs.

A system prompt is the initial set of instructions given to an AI model that defines its overall behavior, role, rules, and tone for the conversation.

Zero-shot learning (or zero-shot prompting) is when an AI model completes a task it has never seen examples of during training, relying only on a natural language description of what to do.