Plain English
AI Glossary
The AI and automation terms you keep running into, explained simply — with enough real-world context to actually make sense of them.
AI Agent
An AI agent is a system that can take actions to accomplish a goal — not just answer questions, but plan steps, use tools, and carry out tasks across apps with limited human input.
LLM (Large Language Model)
A large language model is an AI system trained on vast amounts of text to understand and generate human-like language — the technology behind tools like ChatGPT, Claude, and Gemini.
MCP (Model Context Protocol)
MCP is an open standard that lets AI assistants connect to external tools, data sources, and apps in a consistent way — so one model can securely read from or act on many different systems.
Prompt Engineering
Prompt engineering is the practice of writing clear, well-structured instructions for an AI model to get more accurate, useful, and consistent results.
RAG (Retrieval-Augmented Generation)
RAG is a technique that lets an AI model pull in relevant information from an external source before answering, so its responses are grounded in your data rather than only what it learned during training.
Vector Database
A vector database stores information as numerical representations of meaning, so an AI can find results by similarity — retrieving text that's conceptually related to a query, not just an exact keyword match.