The AI Glossary

Demystifying the jargon. Simple explanations for the terms you'll hear in the world of Agentic AI.

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How It All Fits Together

Every term in this glossary is one part of a single chain — from your request to a verified result. The agent orchestrates everything except the thinking.

Flowchart: a human delegates an outcome to the agent. The agent orchestrates five steps — prompt, context plus RAG, reason by calling the model for inference, act via APIs and MCP against business systems, and verify against source data. If verified, the outcome is delivered with an audit log; if verification fails, no outcome is delivered.

AI (Artificial Intelligence)

Fundamental

Broadly, software that can perform tasks that typically require human intelligence—such as recognizing patterns, solving problems, or understanding language.

Prompt

Interaction

The specific instruction, question, or input you give to an AI. Think of it as the "assignment" you are giving your AI co-worker.

Context

Memory

The "background information" the AI is currently looking at. This includes the previous messages in your chat and any documents you have uploaded for it to read.

Model (LLM)

Fundamental

The "brain" of the operation (e.g., Llama, GPT, Claude). A Large Language Model (LLM) is a program trained on massive amounts of text to predict and generate human-like language.

Inference

Technical

The actual process of the AI "thinking." When you hit enter, the model performs "inference" to calculate the most likely next words in its response.

API (Application Programming Interface)

Technical

A digital bridge that allows two different software programs to talk to each other. For example, Hermes uses an API to "talk" to Telegram or Nextcloud.

MCP (Model Context Protocol)

Advanced

A standardized way for AI agents to connect to external tools and data. It ensures that different tools can be added to an agent without needing to write custom code for every single one.

Agent

Interaction

Unlike a basic chatbot that just talks, an Agent can actually *do* things—like searching the web, reading your files, or updating a calendar.

Hallucination

Caution

When an AI confidently provides an answer that is factually incorrect or completely made up. This is why "Trust but Verify" is a core rule of the Academy.

RAG (Retrieval-Augmented Generation)

Advanced

The process of giving the AI a specific document to read *before* it answers. It's like giving the AI an "open book test" instead of relying on its memory.

Sovereign AI

Principle

Running AI where you control the model, the data, the infrastructure, and the rules — instead of renting intelligence from a provider on their terms. See the Sovereign AI track for the full walkthrough.

ZDR (Zero Data Retention)

Privacy

A provider guarantee that nothing is kept after your prompt is processed. Important: this is often a setting you must enable or a contract you must sign — never assume it is the default.

Local Inference

Technical

Running the AI "brain" on hardware you own — a server in your office or a private cloud instance — instead of sending prompts to an outside service. Your prompts never leave your network.

Data Residency

Privacy

The answer to "where in the world is my data stored?" Some industries and contracts require data to stay in a specific region or building — a key reason organizations choose sovereign AI.

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