The world of AI is full of jargon that’s scarier than it should be. Here are the 2026 key terms explained simply, with no unnecessary tech-speak, so you can follow any conversation or article about artificial intelligence. Bookmark this page: it’s your cheat sheet.
The basics
- AI (Artificial Intelligence): programs that perform tasks we associate with human intelligence, like understanding language or recognising images.
- Machine Learning: the machine learning from examples instead of following hand-written rules.
- Deep Learning: a type of machine learning with large neural networks; it’s what powers today’s AI.
- LLM (Large Language Model): the “brain” behind ChatGPT or Claude. It predicts the next word from enormous amounts of text.
How you talk to AI
- Prompt: the instruction or question you give it. The better the prompt, the better the answer.
- Token: the chunk of text the model processes (roughly a syllable or word). Prices and limits are measured in tokens.
- Context (context window): how much text the model can “remember” at once. The bigger it is, the more documents it can handle.
- Hallucination: when AI invents information with total confidence. The reason you must always verify.
Terms you’ll hear in 2026
- AI agent: an AI that doesn’t just answer, but runs tasks and uses tools for you.
- MCP (Model Context Protocol): the standard that connects AI to your data and tools; the “USB-C of AI”.
- RAG: a technique to make AI answer from your documents, reducing hallucinations.
- Multimodal: an AI that understands and combines text, images, audio and video.
- Fine-tuning: retraining a model with your data to specialise it for your task.
- Open source: open models (Llama, Qwen, Mistral) you can run or adapt yourself.
- Reasoning (thinking models): models that “think” more before answering, better at complex problems.
- Prompt engineering: the art of writing good instructions; less and less a “trick” and more clear communication.
Our recommendation: which terms really matter
- If you only keep three: “hallucination” (why to verify), “context” (what it can handle) and “agent” (where it’s all going). With those three you understand 80% of conversations.
- The most practical day to day: “prompt”. Learning to give context completely changes the quality of what you get.
- The newest and most important: “MCP” and “agent”. That’s where 2026 is being decided.
Our advice: don’t try to memorise the whole glossary at once. Come back here when you hit a term and, above all, understand the ideas (not rote definitions). That’s what really lets you find your way around.
Frequently asked questions
What’s the minimum I should understand to use AI?
That it predicts plausible text (hence hallucinations), that the context you give it rules, and that it’s a copilot, not an oracle. With that you already use it wisely.
Do I need to understand how it works inside?
To use it, no. But the idea of “it predicts the next word” helps you understand why it sometimes nails it brilliantly and other times makes things up.
Conclusion
With these terms you can follow any AI conversation without getting lost. What matters isn’t the vocabulary, but the judgement: understand the ideas and always verify. To go deeper, start with what MCP is and AI agents, the concepts of the moment.
Want more than 20 terms? We have the complete AI glossary with 50 entries explained in plain language.
And mind the tricky pairs: 7 concepts everyone confuses.
