The AI cheat sheet
in plain business terms
AI jargon too often serves to impress rather than explain. Here are the terms that come up in meetings, decoded in one sentence — click a card to flip it. You'll never have to nod along without understanding again.
LLM
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A "large language model": trained to predict the next word over huge texts. It knows nothing, it generates plausible output — so we verify.
Prompt
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Your instruction to the AI. A good prompt is a brief: role, context, bounded task, expected format.
Hallucination
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When the AI invents a wrong-but-credible answer (a date, a source). Inevitable: hence verifying important facts.
RAG
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We plug the AI into YOUR documents so it answers from them, with sources — without retraining. Fixes "it doesn't know our docs".
Fine-tuning
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Retraining a model on your data to change its behavior or style. Heavier than RAG; useful when you want to change how it answers.
Agent
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An AI that doesn't wait: it chains actions, consults tools and reports back to reach a goal.
MCP
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The "universal plug" that connects an agent to your tools and data in a standardized, governable way.
Token
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The unit of text chunking for the AI (often part of a word). Billing and limits are in tokens: hence "context window".
Generative AI
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An AI that produces new content (text, image, code) rather than only classifying or predicting a value.
AI Act
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The European regulation that classifies AI uses by risk level and imposes obligations accordingly.
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The AI glossary as a 1-page PDF
All these terms (and a few bonuses) in an A4 cheat sheet, to print and keep at hand in meetings. Leave your email to receive it, or download directly.
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Frequently asked questions
What is an LLM?
A Large Language Model is a system trained to predict the next word from huge amounts of text. It doesn't "know" anything: it generates plausible answers. Hence the importance of checking facts.
What's the difference between RAG and fine-tuning?
RAG connects the model to your documents so it answers from them, without retraining. Fine-tuning retrains the model on your data to change its behavior. RAG answers "it doesn't know my documents"; fine-tuning answers "I want it to respond a certain way".
What is an AI agent?
An agent is an AI that doesn't just answer: it chains actions, consults tools and reports back, to achieve a goal. MCP is the "universal plug" that lets it connect to your tools in a governable way.
Vocabulary is the first step.
In IAPLC, each term becomes a reflex: you practice it on YOUR cases, through 30 levels generated for your IT role.
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