---
title: "AI Glossary: Plain-English Terms for Normal People"
date: "2026-05-26"
author: "Graham"
description: "A plain-English AI glossary explaining models, prompts, tokens, context windows, agents, MCP, hallucinations, RAG, embeddings, and more."
tags: ["Glossary", "Power of AI"]
url: "https://powerofai.ca/ai-glossary"
readTime: "9 min"
---

# AI Glossary: Plain-English Terms for Normal People

AI jargon makes the whole field feel harder than it is. This glossary explains the words you keep seeing without assuming you are a researcher or software engineer.

Use it as a reference while reading the rest of Power of AI.

## How to use the glossary

When a tool announcement mentions a new model, ask: is this a new engine, a new app feature, or a new workflow? When someone says "agent," ask what tools it can actually use. When someone says "context," ask how much source material it can really see.

## Terms

### Model

The underlying AI system that produces answers. ChatGPT, Claude, and Gemini are apps; GPT, Claude Opus/Sonnet, and Gemini models are the engines inside them.

### Prompt

The instruction you give the AI. Good prompts include context, goal, constraints, and the format you want back.

### Context window

How much information the AI can consider at once: your prompt, prior messages, uploaded text, tool results, and sometimes files.

### Token

A chunk of text the model reads or writes. Pricing and context limits are usually counted in tokens, not words.

### Agent

An AI system that can take steps toward a goal, often by using tools, reading files, searching, writing code, or asking follow-up questions.

### MCP

Model Context Protocol. A standard way to connect AI tools to outside systems like files, databases, APIs, and services.

### Hallucination

A confident wrong answer. It can be a fake fact, fake citation, wrong date, or made-up explanation.

### RAG

Retrieval-augmented generation. The AI retrieves relevant source material first, then answers using that material.

### Embedding

A numerical representation of meaning. It helps systems search by similarity instead of exact keyword match.

### Fine-tuning

Training a model further on specific examples so it behaves better for a narrower task.

### System prompt

Higher-priority instructions that shape how an AI behaves before the user prompt is considered.

### Structured data

Machine-readable metadata on a web page, often JSON-LD, that helps search engines understand the page.

### JSON-LD

A structured data format placed in a page head or body so machines can read facts about the page without guessing from layout.

### Temperature

A setting that changes how varied or conservative some model outputs are. Lower usually means more predictable; higher usually means more varied.

### Tool use

When an AI can call outside tools such as search, code execution, file access, calendars, browsers, or databases.

### Grounding

Tying an answer to provided sources, search results, files, or database records instead of relying only on model memory.

### Multimodal

Able to work with more than one kind of input or output, such as text, images, audio, video, or files.

### Latency

How long the model takes to respond. A slightly weaker but faster model can be better for everyday work.

### Evaluation

A repeatable way to test whether an AI system is doing the job well, often using examples, expected outputs, and human review.

### Guardrail

A rule, filter, permission setting, or workflow step designed to reduce unsafe, private, wrong, or low-quality output.

### Prompt injection

A trick where outside text tries to override the user or system instructions, often by hiding commands inside documents or websites.

### Model router

A system that sends different tasks to different models depending on cost, speed, difficulty, or available tools.

### Computer use

A capability where an AI can interact with software through a browser, desktop, terminal, or app interface.

### AI crawler

A bot that reads public web pages for AI search, citation, answer generation, or model-related indexing.

## Related Power of AI pages

- [Getting Started: The Basics](/guide/getting-started-basics): Learn how to use AI without jargon.
- [What Is an AI Agent?](/what-is-an-ai-agent): A focused explanation of agents, tools, loops, and safety.
- [ChatGPT vs Claude vs Gemini](/chatgpt-vs-claude-vs-gemini): Apply these terms to real tools.
- [How to Question AI](/guide/questioning-ai): Learn how to verify answers.

## Sources and official references

- [OpenAI API text generation guide](https://platform.openai.com/docs/guides/text)
- [Anthropic Claude Code docs](https://docs.anthropic.com/en/docs/claude-code)
- [Model Context Protocol](https://modelcontextprotocol.io/)
- [Google Search structured data](https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data)