Editing Prompt Engineering (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Prompt''' — The text input provided to an LLM; the complete context from which the model generates a response.
* '''System prompt''' — A special instruction block (usually at the start of a conversation) that defines the model's role, persona, constraints, and output expectations.
* '''User prompt''' — The specific query or request provided by the human user at inference time.
* '''Few-shot prompting''' — Including a small number of input-output examples in the prompt to demonstrate the desired response format or reasoning style.
* '''Zero-shot prompting''' — Asking the model to perform a task without providing any examples, relying solely on its pre-trained knowledge.
* '''Chain-of-thought (CoT)''' — A prompting technique that asks the model to reason step by step before giving a final answer, improving accuracy on complex tasks.
* '''Self-consistency''' — Running the same prompt multiple times with high temperature, then taking a majority vote over the outputs to improve reliability.
* '''Role prompting''' — Assigning the model a persona or expert role ("You are a senior security engineer…") to anchor its reasoning style and vocabulary.
* '''Output format instruction''' — Explicitly specifying the structure of the desired output (JSON, markdown table, numbered list, etc.).
* '''Temperature''' — A sampling parameter controlling response randomness. Lower (0–0.3) for factual/deterministic tasks; higher (0.7–1.0) for creative tasks.
* '''Context window''' — The total number of tokens the model can process; prompts + conversation history must fit within this limit.
* '''Prompt injection''' — An attack where malicious input in the prompt attempts to override the model's original instructions.
* '''Hallucination''' — The model generating plausible-sounding but factually incorrect content; prompt techniques can mitigate but not fully eliminate this.
* '''Delimiters''' — Characters or tags (e.g., <code>triple backticks</code>, <tags>, ---) used to clearly separate sections of a prompt.
* '''ReAct''' — A prompting framework combining reasoning traces ("Thought:") and tool calls ("Action:") for agent-like behavior.
* '''Constitutional prompting''' — Including explicit rules or principles in the prompt to constrain the model's behavior.
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