Lesson 1 of 8 · Generative AI Foundations You Can Explain
In this lesson. Separate useful generation from search, rules, and hype.
What you will learn
- Generation versus retrieval versus rules
- Typical failure modes you should expect
- A one-sentence definition you can reuse
Walkthrough
Generative models predict the next piece of content from a prompt. They do not look up a private source of truth unless you connect one. This lesson names what the model is good at — drafting, transforming, exploring — and where it fails: citations, live facts, and anything you cannot verify. You will finish able to tell a teammate when generation helps and when a spreadsheet or a search box is the better tool.
Work through the ideas in order. After each point, pause and connect it to a task you already do — a document, a workflow, or a feature you own. The goal of Generative AI Foundations You Can Explain is usable skill, not a pile of notes.
If something is unclear, rewrite it in your own words before you continue. Teaching the step back to yourself is the fastest way to see gaps.
Practice
Write two columns: three tasks you would give a generative model this week, and three you would not.
Keep the first attempt small. A finished example you can reuse beats a perfect plan you never run.
Check your understanding
- Can you explain the goal of this lesson in one sentence to a teammate?
- Where would you apply “Generation versus retrieval versus rules” in your own work this week?
- What would you change on a second pass of the practice?
Next. Continue to the following lesson when the practice has a real artifact, even a rough one.