AI terms, in plain English.

Prompt engineering

Prompt engineering is the practice of writing inputs (prompts) that get an AI model to produce the output you want.

Large language model (LLM)

A large language model (LLM) is an AI trained on huge amounts of text to predict and generate language.

AI agent

An AI agent is a system that uses a language model to take actions toward a goal, not just answer a question.

Retrieval augmented generation (RAG)

Retrieval augmented generation (RAG) is a technique where an AI model retrieves relevant documents from a knowledge source and uses them to ground its answer.

Token

A token is the small chunk of text an AI model reads and generates, roughly a word or part of a word.

Context window

A context window is the maximum amount of text (measured in tokens) an AI model can consider at once, including your prompt, any attached documents, and the conversation so far.

AI hallucination

An AI hallucination is when a model states something false as if it were true, for example inventing a citation, statistic, or fact.

Fine-tuning

Fine-tuning is further training an existing AI model on your own examples so it better fits a specific task, tone, or domain.

System prompt

A system prompt is an instruction that sets an AI model's role, rules, and behavior before the conversation starts.

Model Context Protocol (MCP)

The Model Context Protocol (MCP) is an open standard that lets AI assistants like Claude connect to external tools and data sources, such as apps, databases, and file systems, in a consistent way.