If someone had told me three and a half years ago that there would be something called ChatGPT that could answer questions across almost any discipline, I would have called them a lunatic. And yet, here we are.That’s exactly what ChatGPT does today. I can ask it coding questions, ask it to improve my grammar, get a simple explanation of tariffs, or understand how amortization math works. For most things, I can just ask, and I get a usable answer.Most of the time, it gets things right. It’s a probabilistic system, so of course it makes mistakes. But the product is so good that sometimes it makes me wonder: should I even bother learning anything deeply if I can just ask it for answers?Thinking about this more carefully, I realized something important. I get the best answers from ChatGPT on topics where I already have some understanding. If I know nothing about a subject, how do I judge whether the answer I’m getting is correct? I simply don’t have any intuition yet.For example, if I already understand the basics of mortgages, I can quickly spot when an amortization explanation makes sense or when something feels off. If I’ve read a bit about geopolitics, I can tell whether an explanation of tariffs is shallow or nuanced. Without that base, everything sounds equally convincing.That led me to two ideas that really stuck.First, you need a broad understanding across multiple disciplines. Not deep expertise in everything, but enough to have intuition and context.Second, you need to know how to ask good questions. The world has always rewarded people who can ask better questions. With tools like ChatGPT, that skill becomes even more valuable. The quality of the output depends heavily on the quality of the input.So it really comes down to this:Build a broad base of understanding.Learn how to ask the right questions.If I were starting fresh today, knowing this, what would I read to build that kind of broad, first-principles understanding across disciplines?Below is a list of books and resources that helped me in this journey. I’m not an expert, and I certainly haven’t mastered all of this. These are simply things I’ve found useful over time.What I like about these books is that they don’t just dump facts on you. They slowly shape how you think, how you reason, and how you build intuition. They help you develop a calmer, clearer way of looking at the world, whether the topic is money, health, technology, or society.For me, this kind of learning isn’t just about being smarter. It’s about becoming a bit wiser, making better decisions, and staying mentally healthy in a noisy world. When you have that foundation, you can ask better questions, spot nonsense more easily, and use tools like ChatGPT in a much more thoughtful way, rather than just taking answers at face value.These books helped me build that base, one small step at a time. This isn’t meant to be read top to bottom. It’s more like browsing a bookstore or a library. Pick what catches your eye, ignore the rest, and come back when your curiosity changes.Arithmetic by Paul LockhartThe Disappearing Spoon by Sam KeanHow To Read Mathematics by Shai SimonsonThe Magic of Reality by Richard DawkinsCalculus Made Easy by Silvanus P. ThompsonSix Easy Pieces by Richard P. FeynmanProofs by Jay CummingsIllustrated Guide To Machine Learning by Josh StarmerA Short History of Nearly Everything by Bill BrysonThe Making of the Fittest by Sean B. CarrollHow to Lie with Statistics by Darrell HuffHow to Solve It by George PolyaThinking Clearly with Data by Ethan Bueno de MesquitaA Brief History of Intelligence by Max S. BennettModeling Life: The Mathematics of Biological Systems by Alan GarfinkelCalling Bullshit by Carl T. Bergstrom and Jevin D. WestThe spelled-out intro to neural networks by Andrej KarpathyFactfulness by Hans RoslingThe Lessons of History by Will Durant and Ariel DurantThinking in Systems by Donella H. MeadowsA Mathematician’s Lament by Paul LockhartBasic Economics by Thomas SowellA Concise Guide to Macroeconomics by David A. MossCode by Charles PetzoldDesigning Data-Intensive Applications by Martin KleppmannPython Distilled by David BeazleyDon’t Make Me Think by Krug SteveThe Craft of Research by Wayne C. BoothThe Mom Test by Rob FitzpatrickUnderstanding Michael Porter by Joan MagrettaThe Essays of Warren Buffett by Lawrence A. CunninghamPoor Charlie’s Almanack by Charles T. MungerSeeking Wisdom: From Darwin to Munger by Peter BevelinHow the World Really Works by Vaclav SmilSustainable Energy without the hot air by David MacKayHow to Read a Financial Report by Tage C. TracyAntifragile by Nassim Nicholas TalebMeasuring the moat by Michael J. MauboussinSuper 30 by Anand KumarInvisible Learning by David FranklinMake It Stick by Peter C. BrownGood Energy by Casey MeansTicker: Don’t Die of Heart Disease by Jared HechtThe Bhagavad Gita by Eknath EaswaranEarly Retirement Extreme by Jacob Lund FiskerWho Moved My Cheese? by Spencer JohnsonThe Psychology of Money by by Morgan HouselThe Little Book of Talent by Daniel CoyleThinking, Fast and Slow by Daniel KahnemanVantage Point by Sanjay BakshiThe Inner Game of Tennis by W. Timothy GallweyPlaying Socratic Solitaire by Sanjay BakshiThe Ultimate Guide to Blood Sugar by Robert LustigNon-Sleep Deep Rest with Andrew HubermanChip War by Chris MillerThe Day You Became a Better Writer by Scott AdamsHow the Internet Happened by Brian McCulloughAmericana by Bhu SrinivasanBreaking Down China’s Tech Surge by BG2Ikigai by Héctor García