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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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

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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.

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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.

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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.

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

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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.

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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.

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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.

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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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

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

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

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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.

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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.

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

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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.

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

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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.

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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.

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

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

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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.

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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.

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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.

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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.

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

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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.

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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.

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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.

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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.

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

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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.

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