AI basics for work
A practical baseline. Cuts through hype to get to honest capabilities and honest limits, then maps both onto the kinds of work most teams actually do.
What you will learn
- List three categories of work where current AI tools clearly help.
- List three where they reliably struggle.
- Decide whether one specific task in your week is a fit.
How you’ll learn this module
Built around evidence-informed learning methods. Designed to support retrieval practice, feedback, and spaced review.
Learn brieflyAttemptGet feedbackRetryReview laterApply in a workflow
Topics covered
What models do wellDrafting, summarizing, structuring.
Where they breakSources, numbers, judgment under pressure.
Tool vs. workflowA model is not a process.
Working with uncertaintyTreating outputs as drafts, not answers.
Suggested learning sequence
01
Watch
Capabilities overview. ~10 min.
02
Try
Run two prompts against one real task. ~15 min.
03
Compare
Mark what helped and what didn’t. ~10 min.
Practical exercises
- Take a draft you wrote last week. Have AI rewrite it. Note three honest gains and three honest losses.
- Identify one task you should NOT delegate to AI right now. Write why in one sentence.
Practice with the AI Tutor
Run this module on a real workflow
Bring one piece of work into the tutor. It turns this module’s topics into risk flags, a practice mission, an experiment, and an evidence record.
Open the AI Tutor for this module