What is AI?
Artificial Intelligence is a broad term for systems that can perform tasks normally requiring human intelligence — recognising patterns, understanding language, making decisions, generating content.
For most of its history, AI was rule-based: programmers wrote explicit instructions for every situation. These systems were useful but brittle — anything outside the rules broke them. Modern AI is different: instead of writing rules, we train systems on enormous amounts of data and let them discover patterns themselves.
The key shift: we went from telling computers how to do things, to showing them millions of examples and letting them figure it out.
Quick check — for each scenario, decide: Is this AI?
Smart Thermostat
Turns on heating at 7am every weekday, exactly as programmed.
Spam Filter
Improves over time based on what you mark as spam or not-spam.
AI Chatbot
Reads your question and generates a helpful, human-sounding reply.
Calculator
Computes 2 + 2 = 4. Always. Exactly as programmed.
What is an LLM?
A Large Language Model is AI trained on massive amounts of text. Claude, ChatGPT, Gemini — all LLMs. They can read, write, summarise, translate, explain, and reason in natural language.
❌ Rule-based system
→ mark as spam
IF sender is in contacts
→ mark as safe
ELSE → ??
Breaks as soon as spammers change tactics
✅ Machine learning
labelled spam / not-spam
Model learns patterns
automatically
Adapts to new tactics
Gets better as it sees more data
How LLMs work
You don't need to understand the maths — but a solid mental model makes you a far better AI user. Here's the full picture, step by step.
The full pipeline — watch each stage light up as you read.
Tokens — the basic unit
LLMs don't process text word by word. They use tokens — chunks of text roughly ¾ the size of a word. The word unbelievable might be 3 tokens; cat is 1. Punctuation and spaces are often separate tokens too.
This matters because models have a context window — a maximum number of tokens they can hold in "memory" at once. Think of it as a desk: once it's full, things start falling off the edge.
Token visualiser — pick an example to see how it breaks into tokens.
Generation — one token at a time
When you send a message, the model doesn't write the whole reply at once. It predicts one token, appends it, predicts the next, and so on — that's why responses stream in. Each token is the statistically most likely continuation given everything before it.
This is also why hallucinations happen: the model is always generating the most plausible-sounding continuation, not necessarily the true one.
Prompt
"Explain what a token is in one sentence."
Model response — token by token
Temperature — precision vs creativity
Temperature is a setting that controls how random the model's outputs are. Low temperature = focused and predictable. High temperature = creative and varied.
Drag the slider to see how temperature changes the same response.
Prompt: "Describe the speed of light."
Key vocabulary
Know these terms and you'll be able to follow any AI conversation. Click each card to reveal the definition.
Token
tap to reveal
The basic unit of text an LLM processes. Roughly ¾ of a word on average.
Context window
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The max amount of text (in tokens) the model can "see" at once — its working memory.
Temperature
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Controls randomness. Low (≈0) = focused. High (≈1) = creative and varied.
Hallucination
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When a model confidently produces information that is incorrect or made up.
Embedding
tap to reveal
A numerical representation of text that captures semantic meaning. Powers search and RAG.
Fine-tuning
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Training a pre-existing model further on a specific dataset to specialise its behaviour.
System prompt
tap to reveal
Instructions given to the model before the conversation — sets its behaviour and persona.
Parameters
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The numerical values inside a model encoding everything it learned during training.
What AI can (and can't) do
Click each card to reveal the verdict. Some answers might surprise you.
Write code
click to reveal
✅ Strong
Excellent at generating, explaining, and debugging code across most languages.
Know today's news
click to reveal
❌ Can't
Has a training cutoff. Doesn't know recent events without web-search tools.
Translate language
click to reveal
✅ Excellent
High quality across major languages, including nuance and tone.
Complex maths
click to reveal
⚠️ Unreliable
Can handle simple maths but makes errors on multi-step calculations. Always verify.
Remember last week
click to reveal
❌ Can't
No memory across sessions by default. Each conversation starts fresh.
Summarise documents
click to reveal
✅ Strong
One of its best use cases — extract key points from long text at any scale.
Guarantee accuracy
click to reveal
❌ Never
Models hallucinate. Confident ≠ correct. Always verify important facts.
Brainstorm ideas
click to reveal
✅ Excellent
Generates diverse ideas quickly. Great for overcoming blank-page paralysis.
You're ready for Level 02
You now understand what AI is, how LLMs work, what tokens are, and what to realistically expect. The next level teaches you how to communicate with AI effectively — which is where most of the practical value comes from.