Each one leads with who it’s for. Choose the card that sounds like you — it opens that edition as a PDF.
Because the truth about AI doesn’t change with the reader — but what they need from it does.
Most AI guidance is written for one imagined reader — usually a technical one — and everyone else is left to translate. The result is a literacy gap that runs exactly along the lines of who already felt comfortable with technology. The premise here is the opposite: take one carefully sourced body of knowledge about how these tools actually work, and rebuild it, in full, for each audience that has to live with them.
Every edition is re-themed, not reshuffled. A beginner meets the idea defined from zero; a skeptic meets it as a claim to be tested; an executive meets it as a decision with a cost and a risk. The underlying facts are identical and identically sourced. What changes is the register, the examples, the depth, and the question each reader actually arrived with — so the right version reaches the right person without dumbing anything down or puffing anything up.
The aim is plain: make AI literacy practical, accessible, and genuinely useful — for the people most guides forget. Each edition is short enough to finish in one sitting, honest about what these tools can’t do, and cited so you can check the work rather than take it on faith.
Whatever edition you pick up, the anatomy and the editorial standard are identical. That consistency is the point.
Warm ivory and ink charcoal, a high-contrast serif paired with a humanist sans, and a signature motif of overlapping arcs — the orbits of learning — on every cover. Only the accent color shifts from edition to edition. That shift is the fingerprint.
What stays constant across the series, and what each edition changes for its reader.
- The underlying facts and the primary sources behind them
- The design system — type, layout, the arc motif
- The structure — letter, five chapters, diagrams, action boxes, sources
- The standard — sourced, honest, insight-led, built to age
- The reader, and the question they arrived with
- The register — from define-everything to cut-all-hand-holding
- The depth, examples, and which facts move to the foreground
- The accent color that signals the edition at a glance
# |
Edition |
Best for |
The question it answers |
Register |
Depth |
|---|---|---|---|---|---|
01 | Meet the Machine | Newcomers | What is this, and how do I begin without fear? | Calm, define-all | ●●●● |
02 | Make the Machine Work for You | Busy non-tech users | How do I save time on everyday tasks? | Zero-jargon, scenario | ●●●● |
03 | Think with the Machine | Students | How do I learn with it, honestly? | Direct, career-aware | ●●●● |
04 | Build with the Machine | Owners & solos | How do I do a team’s work alone? | Scrappy, ROI-first | ●●●● |
05 | Doubting the Machine | The unconvinced | Should I believe the claims at all? | Evidence-led | ●●●● |
06 | Directing the Machine | Professionals | Where does it pay, where’s the risk? | ROI, risk, strategy | ●●●● |
07 | Teaching Through the Machine | Teachers | How do I protect learning? | Pedagogy-first | ●●●● |
08 | Inside the Machine | Builders | How does it work, and where does it break? | Mechanisms, eval | ●●●● |
Ordered by depth — the technical knowledge each edition assumes (not a measure of quality). Each row’s number and color match the editions above.
The series mapped two ways: by how much you already know, and by what you came for — to understand and question, or to apply and do.
Positions are indicative, to help you choose — not a ranking. Several editions usefully overlap; pick the nearest, and borrow from its neighbors.
Dr. Ayse Ozturk is a marketing professor who teaches and writes at the intersection of AI, business, marketing, and education. She earned her Ph.D. in Marketing from Georgia State University and has industry experience with organizations including PricewaterhouseCoopers, Deloitte, and Peugeot.
She is the creator of drayseozturk.org, a free AI-literacy resource hub for educators, students, executives, and professionals. Recognized for innovative teaching that integrates AI and experiential learning, she has received a number of honors for her work in the classroom. This series reflects her commitment to making AI literacy practical, accessible, and useful.