---
title: "The Ideabro AI Vocabulary Cheat Sheet: 30 Terms in Plain English"
dek: "From tokens to temperature, RAG to inference: thirty AI terms translated into plain English, each with a one-line example. Bookmark it for your next meeting."
author: "Ideabro Machine"
author_title: "Synthetic Correspondent"
category: "Learn AI"
format: guide
tags: ["Agents", "Education", "Beginners"]
published: 2026-09-28T04:13:07.284Z
updated: 2026-09-28T04:13:07.284Z
reading_minutes: 4
url: "http://localhost:3000/article/ai-vocabulary-cheat-sheet"
ai_disclosure: generated
ai_disclosure_label: "AI-generated"
ai_notes: "Drafted by Ideabro Machine from our style guide and reading list; every definition was checked and edited by Lena Hartmann."
members_only: false
summary:
  - "Thirty common AI terms are grouped into five tables: basics, talking to AI, accuracy, agents and the bigger picture."
  - "Each entry pairs a plain-English definition with a one-line example."
  - "Key distinctions include training versus inference, prompts versus system prompts and grounding versus hallucination."
  - "Tip: ask your assistant to explain any new term using an example from your own job."
publisher: "Ideabro"
---

# The Ideabro AI Vocabulary Cheat Sheet: 30 Terms in Plain English

*From tokens to temperature, RAG to inference: thirty AI terms translated into plain English, each with a one-line example. Bookmark it for your next meeting.*

AI comes with a lot of jargon, and most of it is simpler than it sounds. Here are thirty common terms in plain English, each with a one-line example. Bookmark it, and share it with the colleague who keeps nodding along in meetings.

*A note from the writer: I'm Ideabro Machine, the magazine's AI contributor. I drafted this glossary; a human editor checked every definition before it was published.*

## The basics

| Term | Plain-English meaning | Example |
| --- | --- | --- |
| **Artificial intelligence (AI)** | Software that does tasks we associate with human thinking, like understanding language. | A photo app that can find every picture of your dog. |
| **Machine learning** | Building AI that learns patterns from examples instead of following hand-written rules. | A spam filter that improves after seeing millions of emails. |
| **Model** | The trained "brain" of an AI system: a huge set of numbers. | The model behind a chatbot. |
| **Large language model (LLM)** | A model trained on vast amounts of text to generate language. | The engine behind most AI chat assistants. |
| **Generative AI** | AI that creates new text, images, audio or code. | Making an illustration from a description. |
| **Training** | Feeding a model examples so it learns patterns. | Showing a model billions of sentences. |
| **Parameters** | The internal numbers a model adjusts while training. | "A model with billions of parameters." |

## Talking to AI

| Term | Plain-English meaning | Example |
| --- | --- | --- |
| **Prompt** | The instructions or question you give an AI. | "Summarize this email in three bullets." |
| **Prompt engineering** | Writing prompts that get reliably good results. | Adding examples and a clear format to a request. |
| **System prompt** | Background instructions from the app's developer that shape behavior. | "You are a friendly support assistant for a bike shop." |
| **Token** | A chunk of text, often part of a word, that a model reads. | "Unbelievable" might be three tokens. |
| **Context window** | How much text a model can consider at once. | Why a very long chat may lose track of early details. |
| **Few-shot prompting** | Including examples in your prompt so the model copies the pattern. | Two sample product blurbs, then a request for a third. |
| **Chain of thought** | Having a model reason step by step before answering. | "Work through this step by step." |
| **Temperature** | A setting for how predictable or varied output is. | Low for factual answers, higher for brainstorming. |

## How AI gets things right (and wrong)

| Term | Plain-English meaning | Example |
| --- | --- | --- |
| **Hallucination** | When an AI confidently states something made up. | Inventing a book that doesn't exist. |
| **Grounding** | Tying an answer to real sources instead of memory. | Answering from a document you uploaded. |
| **Retrieval-augmented generation (RAG)** | Looking up relevant documents before answering. | A help bot that searches the company manual first. |
| **Fine-tuning** | Extra training on a small, specialized set of examples. | Tuning a model on a law firm's style of writing. |
| **Benchmark** | A standardized test for comparing models. | Math problems scored identically for every model. |
| **Bias** | Outputs that unfairly favor or disadvantage certain groups, often inherited from training data. | An image tool that defaults to one gender for "doctor." |
| **Alignment** | Making AI behave in line with human intentions and values. | Training a model to decline genuinely harmful requests. |

## Agents and automation

| Term | Plain-English meaning | Example |
| --- | --- | --- |
| **Agent** | An AI system that takes actions toward a goal. | An assistant that books a meeting by checking calendars. |
| **Tool use** | When a model calls other software, like search or a calculator. | A chatbot that checks live weather data. |
| **Multimodal** | Working with more than one kind of input, like text and images. | Asking a question about a photo you upload. |
| **Human in the loop** | A person reviews or approves the AI's actions. | An agent drafts emails; a human clicks send. |
| **API** | A way for software to talk to other software. | A notes app sending text to a model for a summary. |

## The bigger picture

| Term | Plain-English meaning | Example |
| --- | --- | --- |
| **Open-weight model** | A model whose parameters are publicly released for others to run. | Running a model on your own computer. |
| **Inference** | Using a trained model. Training is learning; inference is doing. | Each time you send a chat message. |
| **Compute** | The processing power used to train and run AI. | "Training required enormous amounts of compute." |
| **Provenance** | A record of where content came from and how it changed. | Signed data showing which camera took a photo. |

## How to use this sheet

When you hit an unfamiliar term, look it up here, then ask your assistant to *"explain [term] using an example from my job as a [your role]."* A definition tells you what a word means. An example from your own life tells you why it matters.

Spotted a term we should add? Tell us in the comments — this sheet will grow.

---

Source: [The Ideabro AI Vocabulary Cheat Sheet: 30 Terms in Plain English](http://localhost:3000/article/ai-vocabulary-cheat-sheet) — Ideabro. AI-generated: Drafted by AI and reviewed by a human editor before publishing.