AI glossary, in plain English

The jargon, minus the jargon.

Agent: An AI that doesn't just answer but takes steps for you, like browsing, using apps or running tasks, often asking before acting. Read the beginner's guide to AI agents.
AI (artificial intelligence): Software that does things we usually think need human smarts, like understanding language, recognizing images or making decisions.
API: A way for one piece of software to talk to another. Builders use APIs to put AI inside their own apps.
API key: A secret password that lets your app use a service's API. Keep it private, like a credit card number.
Automation: Setting things up so a task happens on its own, like 'when an email arrives, save the attachment'.
Chatbot / AI assistant: An app you talk to in plain language, like ChatGPT, Claude or Gemini. You type or speak, it answers.
Context window: How much text a model can 'keep in mind' at once, including your conversation and any files.
Credits: A tool's in-app currency for usage. Each generation spends some, and free plans give you a small amount.
Deep research: A mode where the AI searches many sources and writes a longer, cited report.
Fine-tuning: Extra training that teaches a model a specific style or task.
Free tier / free plan: The no-cost version of a tool, usually with limits on how much you can use it.
Generative AI: AI that creates new things (text, images, music, video or code) instead of just sorting or labeling existing ones.
Hallucination: When an AI states something false with confidence. Always double-check important facts.
IDE / code editor: The app programmers write code in, like VS Code or Cursor.
LLM (large language model): A model trained on huge amounts of text so it can read and write language. It's what powers chat assistants.
MCP (Model Context Protocol): An open standard that lets AI assistants connect to outside tools and data, like a universal plug.
Model: The trained 'brain' behind an AI tool. One app can offer several models, some faster and some smarter.
Multimodal: An AI that understands more than one kind of input, like text plus images, audio or video.
Open source: Software whose code is public so anyone can inspect, run or modify it, within its license.
Prompt: What you type to tell the AI what you want. Clear, specific prompts get better results.
Self-hosting: Running software on your own computer or server instead of the company's cloud.
Text-to-speech (TTS): Turning written text into spoken audio.
Token: A small chunk of text (roughly ¾ of a word) that AI tools count to measure usage and limits.
Vibe coding: Building software by describing what you want in plain English and letting AI write the code.
Workflow: A series of automated steps connected together, as in Zapier, Make or n8n.