A Practical AI Reference Guide

A Whole Lot
of AI Terms!

AI has enough acronyms, buzzwords, and technical language to make a smart person feel like everybody else got the memo. This guide fixes that.

Get 127 AI terms explained in plain English, organized A to Z so you can quickly understand the language behind LLMs, RAG, MCP, AI agents, prompting, automation, governance, security, and more.

Read the AI Glossary See What Is Inside
Built by 28 Foot Systems. Plain English. Practical use. No technical degree required.
28 FOOT SYSTEMS

A Whole Lot
of AI Terms!

THE A-TO-Z EDITION
LLM RAG MCP AGENTS TOKENS HITL EVALS API VECTOR GUARDRAILS
127 AI terms explained
A–Z Alphabetical reference format
Plain English Built for actual humans
2026 Current AI terminology
The Problem

AI is moving fast.
The vocabulary is moving faster.

You should not need to stop a conversation every 30 seconds to figure out what somebody means by vector database, MCP server, model router, prompt injection, or agentic AI.

01

Too Many Acronyms

LLM. RAG. RLHF. MCP. HITL. STT. TTS. API. Knowing the letters does not mean you understand the concept.

02

Too Much Tech Language

Many definitions are written for developers when the people making purchasing and operational decisions are not developers.

03

Too Much AI Hype

New terminology can make old ideas sound mysterious. Understanding the words makes it easier to separate capability from marketing.

Inside the Guide

Stop pretending you know what they mean. Look it up.

Every entry gives you a straightforward definition plus a practical explanation of why the term matters.

AI Agent Understand systems that can pursue goals and use tools across multiple steps.
Context Window Learn how much information a model can consider during one interaction.
Embedding Understand how AI represents meaning numerically for retrieval and search.
Guardrail Learn how boundaries and controls help keep AI systems within acceptable limits.
Hallucination Understand why AI can generate convincing information that is still wrong.
HITL Human in the Loop. Learn why people still matter inside AI workflows.
MCP Understand the Model Context Protocol and how AI connects with external tools and resources.
RAG Learn how AI retrieves external information before generating an answer.
Token Understand the units language models actually process instead of simply counting words.
Vector Database Learn why semantic search and AI knowledge systems often depend on vectors.
Prompt Injection Understand one of the major security risks facing AI systems and agents.
Model Router Learn how systems can select different AI models based on cost, speed, or capability.
Who This Is For

You do not need to become an AI engineer.

You need enough understanding to ask better questions, recognize what a tool is actually doing, and make smarter decisions.

  • Business owners evaluating AI tools
  • Teams adopting AI and automation
  • Consultants and agency owners
  • Educators and trainers explaining AI
  • Leaders responsible for AI governance or risk
  • Creators using generative AI
  • People who keep hearing AI terms and finally want them explained
The 28 Foot Systems Approach

Learn enough AI to make better decisions.

You do not need to memorize 127 definitions. You need a reference you can return to when the terminology starts getting in the way of the work.

UNDERSTAND

Know What They Are Talking About

Build enough AI literacy to follow conversations without getting buried under terminology.

QUESTION

Ask Better Questions

Better vocabulary helps you challenge vendors, developers, consultants, and AI-generated recommendations.

APPLY

Connect Terms to Real Work

Move beyond definitions and start understanding how the terms relate to workflows, websites, automation, security, and operations.

Your AI Reference Guide

You are going to hear these terms anyway. You might as well know what they mean.

Open A Whole Lot of AI Terms! and get a practical A-to-Z reference you can keep coming back to as AI continues to evolve.

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