AI Glossary · 23 terms · last reviewed August 2026

Plain-English AI definitions, written by humans.

Every entry is hand-written, tied to the real tools that use the concept, and updated at least every six months. No auto-generated dictionary entries.

23Terms defined

100%Hand-written, no AI slop

LinkedTo the tools using each

August 2026Last full review

AI Agents

A program that takes goals and figures out the steps to reach them, calling external tools to act in the world.

AI Models

Artificial Intelligence Models

Pre-trained systems that process inputs like text, images or code and generate intelligent outputs based on patterns learned from large datasets.

API

Application Programming Interface

The way one piece of software talks to another.

Chain of Thought

A prompting technique where the model reasons out loud, step by step, before giving an answer.

Context Window

How much text a model can read at once.

Embeddings

Numeric fingerprints of text or images that let computers measure semantic similarity.

Few-shot Learning

Showing a model two to five examples in the prompt so it follows the pattern, without any retraining.

Fine-tuning

Training a pre-built model further on your own data, to make it better at a specific task or voice.

Hallucination

When a model confidently states something false.

Inference

Running a trained model to get a prediction or response.

Latency

Time-to-first-token: the delay between sending a request and seeing the first word.

LLM

Large Language Model

A neural network trained on huge amounts of text, capable of generating, summarising, and reasoning about language.

MCP

Model Context Protocol

An open standard that lets AI models connect to external tools, data sources and services in a consistent way.

Multimodal

A model that handles more than text, like image, audio or video.

Prompt Engineering

Writing the instructions to a model in a way that consistently produces useful output.

RAG

Retrieval-Augmented Generation

A method that fetches relevant documents at query time and feeds them to the model, so answers are grounded in real sources.

RLHF

Reinforcement Learning from Human Feedback

A training method where humans rank model outputs to teach the model what good looks like.

Semantic Search

Search that matches on meaning instead of exact words.

System Prompt

The hidden instruction that sets a model behaviour and constraints before a user message arrives.

Tokens

The chunks (usually word-pieces) that models read and produce.

Transformer

The neural network architecture behind almost every modern LLM.

Vector Database

A database optimized to store and search embeddings.

Zero-shot Learning

A model performing a task it was never explicitly trained on, just from instructions.

How we write these definitions

Hand-written, every entry
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Reviewed every 6 months
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Why it matters section
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