Words, sharpened

An agentic workflow is an AI system that executes a defined task using tools and data you provided, with enough judgment to handle the branches you didn't script.

An AI agent is a software system that pursues a goal by deciding its own steps, calling tools, and acting on the results without a human directing each move.

An AI assistant is a software tool that helps a person get work done by understanding requests in plain language and producing drafts, answers, or summaries on demand.

AI content optimization is the practice of writing and structuring your website content so AI answer engines can read it, understand it, and cite it accurately.

AI crawlers are automated bots that visit websites to collect content for AI companies, either to train models or to fetch live answers for tools like ChatGPT and Perplexity.

AI ethics is the practice of making sure the AI a business uses treats people fairly, respects their data, and produces decisions someone can stand behind.

AI keyword research is using AI tools to find the words, questions, and topics your customers actually search for, and to understand the intent behind them.

AI Overviews are the AI-generated summaries Google places at the top of many search results, answering a question directly instead of just listing links.

An AI plugin is an add-on that connects an AI model to an outside tool or data source so it can do things beyond just generating text.

AI safety is the practice of making sure an AI system behaves as intended and stays within limits you set, even when it faces inputs its builders never anticipated.

AI search is a way of finding information where a model reads your question, gathers relevant sources, and writes a direct answer instead of returning a list of links to sort through.

AI SEO is a set of content and technical practices that make your business easy for AI systems to find, understand, and cite when they answer a user's question.

AI slop is AI-enabled output released into circulation without the judgment — of idea or of execution — that would have filtered it out before.

Answer engine optimization (AEO) is the practice of structuring your content so tools that give direct answers, like AI assistants and voice search, pull the response from you.

An application programming interface (API) is a defined set of rules that lets two software systems request things from each other and exchange data in a predictable way.

Artificial general intelligence (AGI) is a hypothetical AI that could learn and perform any intellectual task a person can, across any domain, rather than being built for one narrow job.

Artificial intelligence is software that performs tasks normally requiring human judgment, such as understanding language, recognizing patterns, or making predictions from data.

Automation is the use of software to carry out a task or process on its own, so it runs reliably every time without a person doing the steps by hand.

Autonomous is the property of an AI system that self-reflects, researches beyond its inputs, builds its own tools, pushes back on wrong premises, and retains what it learns.

BERT is a language model from Google that reads a sentence in both directions at once to understand the meaning of each word from the words around it.

A chatbot is a software program that holds a text conversation with a person, answering questions and handling requests through a chat interface.

ChatGPT is a conversational AI assistant from OpenAI that answers questions, writes drafts, and helps with tasks through a chat interface powered by a large language model.

Conversational AI is technology that lets software understand and respond to natural human language, so people can interact by talking or typing the way they would with a person.

A copilot is an AI assistant embedded directly inside the software your team already uses, offering suggestions, drafts, and answers in the flow of work.

The cost of large language models is the total spend required to use them, spanning per-token usage fees, subscriptions, integration work, and the staff time to run them well.

Emergent behavior is a capability that appears in a large AI model without being explicitly programmed, arising from scale and training rather than a designed feature.

Enterprise AI is the practice of adopting AI tools with the controls a real business needs: data protection, access rules, vendor accountability, and clear ownership.

Fine-tuning is the process of taking an existing AI model and training it further on your own examples so it adopts a specific style, format, or task.

A foundation model is a large, general-purpose AI model trained on broad data that serves as the base other applications are built on top of.

Generative AI is a class of AI that produces new content, text, images, audio, or code, in response to a prompt rather than choosing from fixed options.

Generative engine optimization (GEO) is the practice of shaping your content so generative AI tools cite and recommend your business inside the answers they write.

Google Gemini is Google's family of foundation models and the assistant built on them, capable of working across text, images, audio, and video.

Guardrails are the rules and controls placed around an AI system to keep its behavior inside safe, approved boundaries.

A hallucination is a confident, plausible-sounding output from an AI model that is factually wrong or entirely made up.

A large language model (LLM) is an AI system trained on vast amounts of text to predict and generate language one piece at a time.

Machine learning is a type of AI in which a system learns patterns from data and uses them to make predictions, rather than following rules a person wrote by hand.

Manager — a simple broad definition of a manager is someone that is responsible for a process and the resources assigned to complete the process.

Multimodal AI is AI that can work with more than one type of input or output at once, such as text, images, audio, and video together.

Natural language processing (NLP) is the field of AI focused on getting computers to understand, interpret, and generate human language.

OpenAI is an AI research and product company that builds the GPT family of models and the ChatGPT assistant most people first meet AI through.

Perplexity AI is an answer engine that responds to a question by searching the live web and then writing a short, cited summary of what it found.

A prompt is the instruction you give an AI model that tells it what you want it to do or produce.

Prompt engineering is the practice of designing and refining the instructions you give an AI model so it reliably produces the output you need.

Quantum computing is a form of computing that uses the rules of quantum physics to represent and process information in ways a normal computer cannot.

Reasoning, in AI, is a model's ability to work through a problem in steps, weighing information and following a chain of logic, before it commits to an answer.

Responsible AI is the practice of building and using AI systems in ways that are fair, transparent, secure, and accountable to the people they affect.

Retrieval-augmented generation (RAG) is an AI method that looks up relevant documents before it answers, so the model responds from that retrieved material instead of memory alone.

Search intent is the actual goal behind a query: what the person typing it is really trying to find, do, or decide.

Self-reflection is the property of an AI system that evaluates its own output, detects when it's uncertain or wrong, and adjusts its behavior before returning the result.

Semantic search is a search method that matches on the meaning of a query rather than its exact words, returning results that fit your intent even when the wording differs.

A token is the small unit of text, a word, part of a word, or a character, that an AI language model reads and generates one piece at a time.

Token economy is an AI cost framework that quantifies how large language models price every unit of text — called a token — flowing into and out of a model.

Training data is the collection of text, images, or other examples an AI model learns from to build its abilities.

Unit of Work is an AI productivity metric that measures the value of a completed task divided by the token cost required to produce it.