The AI Glossary for Professionals

The AI industry has a jargon problem.

The people who built these tools named them for other engineers. You are a professional trying to use them effectively, not to write code or pass a computer science exam. That gap is not your problem to apologize for. But it is your problem to close.

This glossary is how you close it.

Every definition here is written for someone running a business or building a career. Not for developers. Not for academics. If you have sat through an AI conversation nodding along while tracking about forty percent of it, this is the resource you needed six months ago.

Use it as a reference guide. Jump to what is confusing you. Bookmark it. Come back when a new term surfaces. The industry is not going to slow down and explain itself. That is what this is for.

SECTION 1: THE BASICS

What AI is and how it works

Artificial Intelligence (AI)

Software that can perform tasks that used to require human judgment. Writing content, analyzing data, answering questions, recognizing images. The important word is "software." It is a tool. You are still the one deciding what to do with it.

Context Window

The amount of text an AI can hold in its working memory at one time. Your conversation history, uploaded files, and any background instructions all count toward this limit. When the context window fills, the AI begins losing track of earlier parts of the conversation. Think of it as a whiteboard with a fixed size. Once it is full, something has to come off to make room.

Hallucination

When an AI generates incorrect information and presents it confidently as fact. The AI is not lying. It is pattern-matching its way to a wrong answer, and it does not know the answer is wrong. This is why you verify anything consequential that AI tells you. Treat it like a knowledgeable colleague who occasionally gets things wrong with great confidence.

Knowledge Cutoff

The date when an AI stopped absorbing new information from the world. If a model has a knowledge cutoff of early 2025, it does not know what happened after that point. It is not a flaw in the technology. It is a known limitation. Always verify time-sensitive information from AI with a current search.

Large Language Model (LLM)

The technology behind most AI tools you will encounter as a professional. A large language model (LLM) is trained on massive amounts of text from books, websites, and other sources, and it learned patterns in language well enough to generate useful responses. Claude, ChatGPT, and Gemini are all LLMs. Think of it as a very well-read assistant who has absorbed a library's worth of information and can speak back to you in plain language.

Model

The specific version of an AI you are talking to. Claude Sonnet 4, GPT-4o, and Gemini 1.5 Pro are all models. Different models have different strengths, speeds, and costs. Choosing the right model is like picking the right tool from a toolbox. You would not use a sledgehammer to hang a picture frame.

Temperature

A setting that controls how predictable or creative an AI's responses are. Low temperature produces more consistent, factual outputs. High temperature produces more varied, creative ones. Most consumer applications handle this in the background. You rarely need to set it manually. Worth knowing it exists.

Tokens

The unit AI uses to measure and process text. Roughly speaking, one token equals about three-quarters of a word. Every AI model has a limit on how many tokens it can process in a single session. If you have ever pasted a long document into an AI and received a partial or confusing response, you may have hit that limit.

Training

How an AI learned what it knows. Before you ever opened the app, the AI was shown billions of examples of text and learned patterns from them. You are not training when you use it. You are using what it already knows.

SECTION 2: THE TOOLS

The apps, platforms, and services you will use

ChatGPT

AI assistant built by OpenAI. The most widely recognized AI tool on the market. Available at chat.openai.com. Runs on GPT models. A capable general-purpose assistant with free and paid tiers.

Claude

AI assistant built by Anthropic. Strong at writing, reasoning, and following complex, multi-step instructions. The primary AI tool Michael uses in his consulting and training work. Available at claude.ai. Free and paid tiers available.

Cowork / Claude Cowork

Anthropic's tool that allows Claude to work directly with your local files. Instead of just responding in chat, Claude can read, write, and organize files on your computer. Michael uses this as part of his content production system for clients. Think of it as giving Claude access to your filing cabinet.

ElevenLabs

An AI voice platform. It clones voices, generates realistic speech from text, and powers conversational AI agents capable of speaking in real time. Michael uses this in select client voice automation projects.

Gemini

AI assistant built by Google. Integrated with Google Workspace tools including Gmail, Docs, and Drive. A natural fit for professionals already working inside the Google ecosystem. Available at gemini.google.com.

GoHighLevel (GHL)

A marketing and customer relationship management (CRM) platform used heavily in the business and agency space. GoHighLevel (GHL) is not an AI tool on its own, but AI can be integrated into it to automate communications, follow-ups, and client workflows. Michael uses this platform in select client consulting builds.

Grok

AI assistant built by xAI, Elon Musk's company. Integrated with X, formerly known as Twitter. Has access to real-time information from the platform.

Manus

An AI agent platform. Not a standard chatbot. You give it a goal, and it determines the steps and executes them on its own. More on what agents are in Section 4.

Midjourney / DALL-E / Flux / Ideogram

AI image generators. You describe what you want in plain language, and they produce an image. Different tools have different strengths. Midjourney is widely regarded for artistic quality. DALL-E is built directly into ChatGPT. Flux and Ideogram are popular alternatives worth knowing.

NotebookLM

Google's AI research tool. You upload your own documents, and it becomes an AI that answers questions based only on what you provided. Useful for building a research assistant from your own material. It is far less likely to hallucinate information outside your documents because it is constrained to what you gave it.

Perplexity

An AI-powered search engine. Unlike ChatGPT or Claude, Perplexity is built specifically for research. It searches the web, synthesizes what it finds, and gives you source citations. Use it when you need current information or want to verify a claim.

Zapier / Make

Automation platforms. They connect apps together so that when something happens in one tool, it triggers an action in another. Neither is AI by default, but AI can be added to handle more complex decisions inside those workflows. Zapier is more beginner friendly. Make offers more flexibility for advanced builds.

SECTION 3: PROMPTING

How to talk to AI and get useful responses

Chain of Thought

Asking the AI to think through a problem step by step before giving you its final answer. "Walk me through your reasoning before you give me a recommendation" is a chain of thought prompt. It tends to produce better results on complex decisions because it forces the model to work through the problem rather than jump to a conclusion.

Context

The background information you give the AI so it can do its job accurately. Your business type, your audience, your goals, your tone. The more relevant context you provide, the more relevant the response will be. "Write a post" gives the AI almost nothing to work with. "Write a LinkedIn post for finance professionals evaluating AI tools, in a direct tone, under 200 words" gives it something useful.

Few-Shot Prompting

Giving the AI examples of what you want before asking it to produce something. Instead of only describing what you need, you show it two or three examples and say, "write something like these." AI learns quickly from examples. This technique consistently improves output quality.

Iteration

The process of refining an AI output through follow-up prompts. Your first response is rarely your final output. Prompting is a conversation, not a one-shot command. "Make this shorter," "shift the tone to be more direct," and "add a specific example here" are all iterations. Good results usually come after a few rounds.

Prompt

The instruction or message you send to an AI. Everything you type into the chat is a prompt. The quality of the output depends heavily on the quality of the input. A vague prompt produces a vague response. A specific, well-structured prompt produces a useful one.

Prompt Mastery Blueprint™

Michael's four-part framework for getting consistently useful responses from any AI tool. Step one: give the AI a defined expert role. Step two: provide the relevant background context. Step three: assign one specific task. Step four: end with "Ask me any questions you have." This structure works across every major AI platform.

Skill (in the Claude context)

A reusable set of instructions that tells Claude how to handle a specific, repeatable task. Michael has skills built for drafting client reports, repurposing content, running structured meeting debriefs, and dozens of other recurring workflows. Think of a skill as a trained employee who knows exactly how to handle one type of work, every time, without being re-trained from scratch.

System Prompt

Instructions given to the AI before a conversation begins. These define the role, tone, rules, and context the AI should follow for the entire session. When you use a custom AI tool or a Claude Project, there is almost always a system prompt running in the background, shaping how the AI behaves. You do not see it in the chat. But it is there.

SECTION 4: AGENTS AND AUTOMATION

The part everyone is talking about and almost no one explains clearly

Agentic AI

The broader category of AI that can act with some degree of autonomy. When you hear "agentic," it means the AI has can take sequential steps on its own, use tools, search the web, interact with apps, or execute a series of actions without being prompted at each step. This is where AI starts to feel less like a chat tool and more like an additional team member.

AI Agent

An AI that does more than respond. It takes actions, makes decisions, and completes tasks with minimal ongoing input from you. You give it a goal. It figures out the steps and carries them out. A standard chatbot waits for your next message. An agent works while you are not watching.

API (Application Programming Interface)

The technical connection that allows one piece of software to communicate with another. An application programming interface (API) is what makes integrations between tools work. You rarely interact with it directly. You see the result of it. "Connect via API" means two apps are sharing information through a direct, authorized link.

API Key

A private code that gives one app permission to access another. When you connect an automation platform to an AI tool, you typically use an API key to authorize that connection. Keep it private. It is essentially your identity and billing authorization for the service.

Automation

Any process that runs without you doing it manually every time. An automation might send a follow-up email, update a contact record, or publish content on a schedule. Automation handles the repetitive. You handle the strategic.

Cowork (as a concept)

The idea of Claude operating directly inside your file system, creating and editing documents, running tasks in sequence, without you being present in the conversation at every step. It is AI functioning as a background operator. Michael uses this model for batch content production and client deliverable workflows.

MCP (Model Context Protocol)

A technical standard that connects AI tools to external apps and data. If you want your AI to check your calendar, read your email, or search your file storage, model context protocol (MCP) is the bridge that makes those connections possible. Michael's AI systems use MCP to connect Claude to tools like Gmail, Google Drive, and calendar platforms.

Trigger

The event that starts a workflow or automation. A new form submission, an incoming email, a new sale, a calendar event: these are all triggers. "When X happens" is the trigger. "Do Y" is the action.

Workflow

A defined sequence of steps that runs automatically when triggered. "When a new lead fills out a form, send a welcome email, create a record in the CRM, and notify the team." That is a workflow. AI can be layered into a workflow to make judgment calls instead of only following fixed rules.

SECTION 5: BUILDING WITHOUT CODE

You do not need to be a developer to build with AI

Base44

An AI-powered application builder. You describe what you want to create, and it produces a working web application. No programming required. Useful for building internal tools, intake forms, calculators, and other focused business applications.

Fine-Tuning

Training an AI model on your specific data so it performs better on your specific use case. More technical and resource-intensive than prompt engineering. Not something most professionals need to worry about. The majority of practical AI work is done through prompting, not fine-tuning.

Lovable

Similar in purpose to Base44. An AI-powered web application builder designed for non-developers. You describe what you need and it generates functional software.

Micro-App

A small, purpose-built software tool designed to do one specific job. Not a full platform. An intake form with conditional logic, a pricing calculator, and a quiz that routes visitors to different offers. These can be built quickly using AI tools and solve real, specific business problems.

No-Code / Low-Code

Building tools, automations, or applications using visual interfaces instead of writing programming code. Zapier, Make, and GoHighLevel are no-code platforms. You configure instead of code. Most professionals and business owners work here, and that is completely appropriate.

PRD (Product Requirements Document)

A document that defines what a software tool needs to do before anyone starts building it. A product requirements document (PRD) answers the core questions: what is this, who is it for, what does it do, and what are the rules. If you are having AI build something for you, a PRD is what keeps the build from going sideways.

Prompt Engineering

The practice of crafting prompts deliberately to improve AI output quality. Less technical than it sounds. At the practical level, it means thinking carefully about how you frame your instructions, so the AI understands exactly what you need.

Vibe Coding

Describing what you want to build in plain English and having AI write the code for you. You are not a programmer in this process. You are the person who knows what the result should look like and can communicate it clearly. Tools like Base44, Lovable, and Claude make this increasingly accessible. You describe it. The AI builds it.

SECTION 6: THE STUFF YOUR TECH FRIEND TALKS ABOUT

Terms that come up in more advanced AI conversations

Conversational AI

AI designed to hold a natural, back-and-forth conversation, often with voice capability. Customer service assistants that understand context, voice agents that can handle inquiries, and automated intake systems that communicate like a person. The goal is an AI interaction that feels like a conversation rather than a form.

Embedding

The process of converting text into a numerical format that AI can compare and search. Embeddings are what make it possible to find documents related in meaning even when the exact wording is different. More background knowledge than hands-on skill for most professionals. Worth understanding the concept exists.

Inference

The moment an AI is actively generating a response. When you send a prompt and the AI starts writing back, that is inference. It is distinct from training (the original learning process) and fine-tuning (specialized additional learning). The terms are different because the underlying processes are fundamentally different.

Multimodal

An AI that can process more than just text. Images, audio, video, PDFs, spreadsheets. Claude, ChatGPT, and Gemini are all multimodal. You can upload a photo, a document, or a data file and ask the AI to analyze or work with it.

Open Source vs. Closed Source

Open source AI models have their underlying code published publicly. Anyone can examine, use, or modify them. Llama, from Meta, is a well-known example. Closed-source models are proprietary. Claude, ChatGPT, and Gemini are closed source. Open source models can be run on your own hardware, which matters in contexts where data privacy is a priority.

On-Premise / Local AI

Running an AI model on your own hardware instead of through a company's cloud servers. More private. No data leaves your system. More technically demanding to set up. Not a requirement for most professionals, but worth knowing the option exists.

RAG (Retrieval-Augmented Generation)

A method of giving an AI access to your specific documents and data when it generates a response. Instead of relying only on what it was trained on, the AI retrieves relevant information from a library you provide. Retrieval-augmented generation (RAG) is the concept behind tools like NotebookLM. You do not need to build one yourself. You need to know it exists so you understand what is possible.

Vector Database

Where information is stored so an AI can search it by meaning rather than exact word matches. When an AI pulls relevant context from your documents in response to a question, a vector database is often what makes that retrieval accurate. Background knowledge for most professionals. Worth knowing the term.

HOW TO USE THIS

Do not try to memorize it. That is not the point.

Use it as a reference. When a term surfaces in a meeting, a podcast, or a tool description and you are not sure what it means, come back here. When you are trying to describe something you want to build or automate, browse the sections until you find the language that fits.

Knowing the vocabulary does not make you a developer. It makes you a sharper buyer, a better collaborator, and a more confident user of the tools and people around you.

The professionals who move fastest with AI are not the ones who know the most code. They are the ones who ask better questions and give clearer instructions. This glossary is a step in both directions.

Want more like this?

Michael publishes practical AI for working professionals at AI Educational Solutions (AIES). Join the AI Edge: Tools and Skills for Professionals, Facebook Group. That is where you will find weekly content.