The Adaptability Quotient asserts that success in the next human era will belong to those who can revise their thinking under pressure. Why was this an important book for you to write?

Over more than three decades in investing, I kept seeing the same pattern. The people and organizations that performed best over time were not always the smartest or most experienced. They were the ones who recognized when reality had changed and revised their thinking fastest.

IQ describes our capacity to reason. EQ helps us understand and work with other people. AQ — the Adaptability Quotient — is our capacity to update when the terrain changes.

That matters urgently now because AI is becoming a general-purpose partner in cognition — what I call the Second Cognitive Revolution. It can research, interpret, generate hypotheses, argue a case, and produce answers with extraordinary fluency. Used well, it can expand human capability. Used passively, it can let us outsource the difficult work through which judgment and agency are built.

I am private by nature, so writing this book required stepping outside my usual world. I did it because adaptability is learnable — and because the difference between using AI to sharpen our thinking and letting it replace our thinking may be one of the defining choices of this era.

You argue that success belongs to people who can revise their thinking under pressure. Why is changing our minds so difficult?

Because most of us make being right part of our identity. You form a differentiated view, the world proves you correct, and over time that view becomes who you are. Then the environment changes, and the model that just won stops working. Updating it now feels like losing yourself, so you defend it instead.

That’s the trap. If being right is your identity, every disconfirming fact feels like an attack. If the process is your identity, every disconfirming fact is useful. The strongest decision-makers I know hold their views with real conviction and stay willing to abandon them the moment reality stops matching the model. Strong opinion, weakly held. You’re in possession of the opinion. Reality is in possession of the answer. The aim is never weaker conviction. It’s to hold the view strongly — and update before circumstances force you to.

Which example in the book surprised you the most while researching or writing it?

Ernest Shackleton — which surprised me, because I thought I knew the story. It may be the most-told leadership story there is. What startled me when I went deep was how absolute the failure was. By every measure of traditional exploration, the Endurance expedition was a catastrophe: the ship was crushed by the ice before the crew ever set foot on the continent. And Shackleton updated overnight. At what he later admitted was his lowest moment, the goal of crossing Antarctica simply ceased to exist for him, and a new definition of success — every man home alive — replaced it, with no visible mourning of the old one. Everything after that was reclassified. Setbacks became feedback. Small wins became steps. The only failure that counted was losing a man, and he never lost one.

There’s a detail that stays with me. Photographs from that golden age of polar exploration usually have a haunted quality — men who vanished into the snow. The pictures of Shackleton’s crew are different: they show men who grew old and told the story. That’s what adaptability buys. Not the original prize — the ability to redefine the prize, and still win it.

What is one thing you hope readers take away from The Adaptability Quotient?

I hope readers come away with a different relationship to uncertainty — and with one idea in particular: when knowledge becomes abundant, what becomes scarce is agency.

AI gives us access to extraordinary amounts of intelligence. We should use it enthusiastically: to challenge assumptions, widen the possibilities we consider, and move faster. But we should not confuse receiving an intelligent answer with developing judgment. Judgment is built through the difficult human work of deciding what matters, interpreting ambiguous evidence, making choices under consequences, and updating when reality proves us wrong. AI can assist in that work, but it cannot own the consequences or preserve our agency for us.

If you build the capacity to update as the world changes, uncertainty stops being something to fear and becomes something you can navigate — and sometimes use. Being wrong is not the central problem. Staying wrong is.

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