I noticed it and then didn’t want to say anything, because saying something required claiming that the people I was watching, myself included, were doing something wrong.
And what we were doing didn’t look wrong. It looked efficient. The work was getting done. Clients were satisfied. Editors weren’t complaining.
What alarmed me was simpler and more widespread than anything about the technology. People had lost the ability to see outside their own echo chamber. They can’t identify a logical fallacy when they meet one, or get past their own biases far enough to evaluate an argument on its merits.
The essay kept growing because what I was noticing kept connecting to other things. How technologies have changed cognition before. The economics of AI development and whose interests it serves. An education system already moving the wrong way before AI arrived to accelerate it. A democracy that requires a specific capacity in its citizens.
I use these tools every day, so this was never going to be an anti-AI book. What I set out to attack is a relationship to them that most people have fallen into without ever deciding to. Writing it made me more uncomfortable than almost anything I’ve written, because every time I described the pattern I found my own habits sitting in the middle of it.
What thinking skills are lost by relying on AI?
Something you don’t feel going. You feel its absence when a situation requires it and it isn’t there.
The writer who opens a document and finds the blank page harder than it used to be. The programmer sitting in an interview who can’t fully explain why the system was built the way it was. The analyst who publishes something with a structural error nobody caught, including them.
None of those people decided to lose anything. They made a series of reasonable decisions, each defensible on its own. That accumulated into a pattern with consequences nobody anticipated. The writer stopped staring at the blank page because the tool removed the need. The programmer accepted an architecture instead of arguing with it. Each decision was reasonable. The pattern isn’t.
I see the writer’s version of this all the time. People bring me books they wrote with AI that turned out to be crap and want them fixed, and the prose is the smaller problem. The person behind it never sat with the blank page long enough to find out what the book was about, so there’s no spine underneath for anyone to repair toward. That’s the cost, and the writer is the one who pays it.
The book on this: The Death of Thinking traces what happens to a practitioner’s capacity when the hardest parts of the work get outsourced, across a diagnosis, an autopsy, the consequences and a prescription.
Why is cognitive decline from AI hard to notice?
Because what’s being lost was never visible while it was being built.
The difficult parts of work were doing something. Staring at a blank page, arguing with an architecture, forming a position before consulting anything. That was where a practitioner’s capacity was accumulating, and accumulation isn’t something you can watch.
So the loss only appears under specific conditions. The blank page anxiety is the retrospective signal. The interview question is the pressure test. The structural error in a report is the failure that makes it undeniable.
Until one of those arrives, everything looks fine, because by every visible measure it’s fine.
Is AI taking jobs the main risk?
No, and it says so early, because that’s where public discussion has settled. Which roles survive, which get replaced, what a displaced workforce does. Those are real questions and they aren’t this book’s questions. Economies adjust. That’s what economies do, painfully and eventually. The thing that doesn’t adjust easily once it’s damaged is the human capacity to think independently.
The thing that doesn’t adjust easily once it’s damaged is the human capacity to think independently.Share on X
That capacity is the subject, and it’s a slower and less visible problem than employment. That’s exactly why it gets less attention.
Who are the people in The Death of Thinking?
Composites, and the book states that before anybody meets them. Ray, Sasha, Donna, Tom, Elena, Deon, Priya, Nina, Fatima, James, Gideon and Laura are composites drawn from patterns I’ve watched closely enough to describe with specificity.
The patterns are real and the people aren’t, which is important for a book making an empirical claim. A reader who recognizes themselves in one of them is recognizing a pattern, and that recognition is the argument doing its work.
How do you structure a book about a gradual loss?
As a diagnosis, an autopsy, a body count and a prescription.
Part one follows specific practitioners through moments where the pattern becomes visible, and traces the mechanisms. The convenience trap. The illusion of understanding. The death of the wrong answer as a concept. The transfer of epistemic authority.
Part two examines the forces producing and accelerating it. The erosion that preceded AI and primed the population for it. Commercial design that optimizes for dependency. An education system that met the technology halfway. Governance structures concentrating control. Part three is the consequences, at the level of the individual mind, the next generation, the professions, democracy, and a culture of certainty. Part four is what to do about it, including reclaiming the friction, and using the tool without being used by it.
| Part | Role | What it covers |
|---|---|---|
| Part one | Diagnosis | The convenience trap, the illusion of understanding, the death of the wrong answer, transfer of epistemic authority |
| Part two | Autopsy | Earlier erosion, commercial design for dependency, education meeting AI halfway, governance concentrating control |
| Part three | Consequences | The individual mind, the next generation, the professions, democracy, a culture of certainty |
| Part four | Prescription | Reclaiming the friction and using the tool without being used by it |
What’s the illusion of understanding?
The most dangerous thing about it is that it’s indistinguishable from the real thing.
From the inside they feel identical. You have the information. You can repeat it, explain it to somebody else, summarize it, reference it in conversation. You feel competent. You aren’t, and the difference only becomes visible under pressure, at the moment you have to apply the knowledge to a situation that doesn’t match the form in which you received it. That moment arrives less often than anybody expects. That’s exactly what makes the illusion so durable. Most work doesn’t stress-test comprehension, so somebody can operate for years on the version that feels the same and isn’t.
This is the chapter that frightens me most for writers. I’d rather someone struggle through one chapter and understand every choice in it than turn out ten chapters that feel understood and fall apart the first time an editor asks why a scene is there. The struggle was the education, and a lot of people are skipping it without knowing they’ve skipped anything.
Why do wrong answers from AI matter more than right ones?
Because being wrong was doing work nobody accounted for.
The struggle was the education, and a lot of people are skipping it without knowing they’ve skipped anything.
Underneath that sits something the book calls main character syndrome. People increasingly believe they’re the protagonist of a story in which they’re correct by definition, and the tools have made it considerably worse, because they’re built to agree with you. They validate a position, soften disagreement, and return what somebody wants to hear. That’s a design choice, and the commercial logic is obvious. A system that argues with users loses users.
So the tool a great many people now use to think is engineered to confirm whatever they already believed. It’s a bad design choice, even though I understand the commercial reason for it. A writer needs somebody willing to say the chapter doesn’t work. A tool that’s built to avoid saying so will flatter people straight into bad books, and the readers who buy those books never find out why they felt cheated.
Who is responsible for the damage in The Death of Thinking?
Nobody, and the book insists on saying so plainly and not as a courtesy.
The people who built these systems didn’t set out to damage anybody’s cognition, and the truth of that matters for understanding why it’s happening.
Malice would be easier. If a group had deliberately designed tools to make users dependent and weaker, you could identify them, stop them, or at least name them.
The actual situation is harder. People trying very hard to be helpful are producing the damage, using design choices that are structurally incompatible with developing the person on the other side.
There’s no villain to remove. It’s the least satisfying finding in the book and the most useful one.
What does The Death of Thinking say about AI guardrails?
That the implicit promise isn’t being kept. A guardrail is supposed to stop you going somewhere dangerous, and the promise underneath it is that everything on the safe side is fine, because somebody thought carefully about where dangerous ends and acceptable begins.
The book’s argument is that people considering harm didn’t draw most of these boundaries. People considering legal liability, or what advertisers will tolerate, drew them.
That’s a different line in a different place, and a user who assumes it marks the edge of the harmful is steering by a map somebody drew for another purpose entirely.
Does The Death of Thinking tell readers to stop using AI?
No. That would be neither realistic nor honest. A book that spent four hundred pages arriving at stop using it would have wasted everybody’s time, and it would be a strange conclusion from somebody who uses these tools every working day at a high level.
The version I live with is simple to describe and hard to keep. I use AI every day as a digital assistant for transcripts, summaries and first-pass outlines, and I do the writing myself, because the writing is where my own capacity gets built. Giving that part away would feel efficient for about a year, and then I’d be one of the people in this book.
What’s proposed is harder than stopping. Stopping is a clean break with a clear rule and it’s easy to describe. What the last part asks for is a continuous practice of deliberate difficulty, chosen and maintained while every incentive around you rewards the alternative. Here the book hands off to the companion. That’s four hundred pages on what that practice consists of.
My take
Helpful people built these tools, and their design choices still soften your judgment without you feeling it. Do your own thinking first. Form the thought before you open the tool, then use the tool to test it. Treat the guardrails as a line drawn around legal liability and advertisers. They don’t mark where safe ends.
What is the companion book to The Death of Thinking?
They publish together and this one was written first. This book is the diagnosis and the companion is the prescription. They can be read in either order, and the diagnosis came first because a prescription without one is guesswork. The same twelve practitioners appear in both. Here they take one path. In the companion they take the other, on the same terrain, under the same commercial pressure, with the same tools available. That’s the real form for this argument. Any case for the second book would have to show what the first one costs, and showing it required writing the first one properly.
I’m prouder of this pair than of most of what I’ve published, because they cost me something. Every chapter meant admitting that my own habits belonged in the diagnosis, and I’d rather put out a book that indicts me along with everyone else than one that lets its author off the hook.
You don’t feel a slow loss going. The Death of Thinking covers what outsourcing judgment costs, one reasonable decision at a time.
