What you'll learn this week
By the end of Week 1 you will be able to:
- Explain in plain language what an LLM does well, does poorly, and why it hallucinates.
- Name the four main categories of AI tools and give one example of each.
- State three privacy rules you will follow when using AI with work or client data.
- Describe the three ways people realistically earn money with AI.
- Identify one personal income idea, backed by your own skills audit.
A prediction engine, not a database
An LLM (large language model) is a prediction engine trained on huge amounts of text. It predicts the most plausible next words — it does not "look things up" or "know" facts the way a database does. Understanding this one idea explains almost everything about when to trust it and when not to.
What it does well — try each of these now
Open your AI assistant and run these four prompts. Watch how quickly it handles each:
- Drafting:
Write a polite email declining a meeting but proposing two alternatives. - Summarizing: paste any long article and ask for 5 bullet points.
- Transforming:
Rewrite this paragraph for a 12-year-old.(paste any paragraph) - Analyzing: paste a pros/cons situation and ask for a structured recommendation.
Where it fails — see it for yourself
- Hallucination. Ask for citations on an obscure topic and look closely at the results — some will be confident but completely made up. Remember: fluency is not accuracy.
- Stale knowledge. Models have a training cutoff; anything recent may be missing or wrong unless the tool has web search.
- Math and counting. LLMs can slip on arithmetic. Always verify numbers.
The rule that governs this whole course
AI drafts, you decide. Anything with your name on it — or a client's money on it — gets verified by a human.
Write that somewhere you'll see it. Every week of this course builds on it.