AI has a jargon problem. Every tool, every salesperson, every LinkedIn post throws around words like "agent" and "LLM" and "RAG" as if you are supposed to already know them. You are not. The terms are simple once someone explains them without trying to sound smart.
So here is the whole vocabulary in plain English. No hype, no buzzwords defended with more buzzwords. Just what each term means and why a small business owner should care. Bookmark it. I will be linking back to it constantly.
LLM (Large Language Model)
The engine behind tools like ChatGPT. An LLM is a program trained on a huge amount of text that is very good at predicting the next word, which turns out to be enough to write emails, answer questions, and summarize documents. Why you care: when someone says "the AI," they almost always mean an LLM. It is the thing doing the writing and reasoning.
ChatGPT (and its cousins)
The most famous product built on an LLM. ChatGPT, Claude, and Gemini are all chat tools you type into and get answers back. Why you care: these are the on-ramps. If you have ever wondered how to actually use ChatGPT for your business, that is where most owners start.
Prompt
What you type to the AI, your instruction. A vague prompt gets a vague answer; a clear one gets a useful answer. Why you care: the single biggest difference between people who get value from AI and people who give up is how they write prompts. It is a learnable skill, not a talent.
AI Agent
A step up from a chatbot. A chatbot answers; an agent does. It can take a series of actions to finish a job, like reading an email, checking your calendar, and booking the appointment. Why you care: "agent" is the most overused word in AI right now. I wrote a whole no-BS guide to what AI agents really are because the gap between the marketing and the reality is wide.
Harness
The software wrapper around an AI model that gives it tools, memory, and a loop to take actions: the execution layer that turns a model that can only talk into something that can do. The model is the engine; the harness is the rest of the car. Why you care: the "agent" you actually use is built on a harness. A coding tool like Claude Code is the textbook example: it is "the agentic harness around Claude." (Assistants like OpenClaw, the open-source private assistant I set up for businesses, often get grouped with "harnesses" in the press, though technically the harness is the execution layer inside a tool like that.) When people compare "AI tools," they are usually comparing harnesses, not the models underneath.
Automation
The unglamorous workhorse. Automation is any "when this happens, do that" rule: when a job finishes, send a review request. It often does not involve AI at all, and that is fine. Why you care: most of the ROI small businesses get from "AI" is actually plain automation with a little AI sprinkled on top.
AI Voice Agent
An AI that answers your phone in a natural-sounding voice, qualifies the caller, and books the job, 24/7. Why you care: for service businesses that miss calls, this is often the highest-return tool there is. More on affordable AI voice agents.
Hallucination
When an AI states something false with total confidence: a made-up fact, a fake citation, a wrong number. Why you care: this is the real risk, not robots taking over. Never publish AI output about facts, prices, or law without checking it. It is also why I am careful about where I let AI run unsupervised, as I cover in the honest dangers of AI agents.
SEO vs. GEO
SEO (Search Engine Optimization) is getting found on Google's blue links. GEO (Generative Engine Optimization) is getting mentioned inside AI answers: the paragraph ChatGPT or Google's AI Overview writes when someone asks for a recommendation. Why you care: customers increasingly ask the AI instead of scrolling results. Here is the full breakdown of SEO vs. GEO for small business and what GEO actually is.
RAG (Retrieval-Augmented Generation)
A way to give an AI your specific information (your pricing, your FAQs, your past jobs) so its answers are about your business instead of generic internet knowledge. Why you care: this is what makes an AI assistant actually useful to you rather than a clever stranger.
API
The plumbing that lets two software tools talk to each other, like how your booking system can hand information to your AI, and back. Why you care: you will never touch one directly, but when a setup "connects" your tools, an API is usually how.
MCP (Model Context Protocol)
A newer, AI-specific standard for plugging tools and data into an AI. Think of it as a universal adapter built just for AI assistants. How it is different from an API: an API is the general-purpose plumbing between any two pieces of software; MCP is one agreed-upon shape of that plumbing, designed so any AI model can connect to any compatible tool without someone hand-wiring each connection. If an API is "a cable," MCP is "the USB-C standard for AI." Why you care: you will not configure it yourself, but MCP is fast becoming how modern AI assistants connect to your calendar, files, and apps, so when a tool says it "speaks MCP," it means it will plug into your AI cleanly instead of needing custom work.
Private / On-Prem AI
Running AI on your own hardware (like a Mac Mini in your office) instead of a big company's cloud, so your data never leaves the building. Why you care: if you handle sensitive customer info, this matters. I explain the setup in your own private AI assistant on a Mac Mini.
The bottom line
You do not need to memorize any of this. You need just enough to tell the difference between a tool that will help and a pitch that is mostly noise. Most of "AI for business" comes down to three of these words: an automation triggers, an LLM writes, and a little RAG makes it sound like you.
Confused about which of these your business actually needs? That is a free, 15-minute conversation, and you will leave knowing exactly which terms apply to you and which you can ignore. Book at aiguyjosh.com/contact.