I’m wrapping up The Warren Buffett Way by Robert Hagstrom for the second time. The first time I read it last year, I got a ton of information about the mechanics of how Warren Buffett invests. This time, I’ve gotten just as much, but more around psychology and mindset. It’s interesting how the book hasn’t changed, but what I got from it changed because what I’m interested in has changed.

The book helped me understand how a rational temperament is Buffett’s main competitive advantage. Here’s a passage that stuck with me:

The cornerstone of rationality is the ability to see past the present and analyze several possible scenarios, eventually making a deliberate choice. That, in a nutshell, is Warren Buffett.

Speaking to students at the University of Seattle, Buffett was asked how he got where he is and how he amassed such a large fortune. His response was thought provoking:

Buffett took a deep breath and began:

How I got here is pretty simple in my case. It is not IQ, I’m sure you will be glad to hear. The big thing is rationality. I always look at IQ and talent as representing the horsepower of the motor, but that the output—the efficiency with which the motor works—depends on rationality. A lot of people start out with 400-horsepower motors but only get 100 horsepower of output. It’s way better to have a 200-horsepower motor and get it all into output.

So why do smart people do things that interfere with getting the output they’re entitled to? It gets into the habits and character and temperament, and behaving in a rational manner. Not getting in your own way. As I have said, everybody here has the ability absolutely to do anything I do and much beyond. Some of you will, and some of you won’t. For those who won’t, it will be because you get in your own way, not because the world doesn’t allow you.

I’ve always thought high IQ is an edge. High mental acuity is genetic—you were either born with it or weren’t. But Buffett makes a great point about the efficiency with which someone uses their mental acuity materially impacting their output. You don’t have to be the smartest to win; you just need to avoid acting illogically.

You can’t change your IQ, but you can learn to think and act more rationally. This is a superpower hiding in plain sight. It’s something that everyone can do, but as with many superpowers hiding in plain sight, many people won’t.

Buffett built a fortune buying and overseeing businesses by being rational (he’s also pretty sharp). Entrepreneurs of all IQ levels should take note of his simple, but not easy, strategy and borrow a page from the Buffett playbook. Being rational and not shooting yourself in the foot is something everyone can do. It trumps intelligence in the long run and can lead to outsize success.

I’m finishing up The Warren Buffett Way by Robert Hagstrom. I’m interested in learning more about psychology to improve my decision-making. Hagstrom addresses the psychology of Warren Buffett throughout the book but also dives into broader psychological concepts. One that resonated with me was rationality. Here are a few passages I highlighted:

Rationalism, according to the Oxford American Dictionary, is a belief that one’s opinions or actions should be based on reason and knowledge rather than emotions. A rational person thinks clearly, sensibly, and logically.

The first thing to understand is that rationality is not the same as intelligence. Smart people can do dumb things.

In Keith Stanovich’s book What Intelligence Tests Miss: The Psychology of Rational Thought, Stanovich coined the term dysrationalia: the inability to think and behave rationally despite high intelligence. Research in cognitive psychology suggests there are two principal causes of dysrationalia. The first is a processing problem. The second is a content problem. Let’s look at them closely, one at a time.

Stanovich believes we humans process poorly. When solving a problem, he says, people have different cognitive mechanisms to choose from. At one end of the thinking spectrum are mechanisms that have great computational power. But they come with a cost. They require slower thinking and a great deal of concentration. At the opposite end of the thinking spectrum are mechanisms with very little computational power; they require very little concentration and permit quick decisions. “Humans are cognitive misers,” wrote Stanovich, “because our basic tendency is to default to the processing mechanisms that require less computational effort, even if they are less accurate.” In a word, humans are lazy thinkers. They take the easy way out when solving problems; as a result, their solutions are often illogical.

I’ve never considered the processing power it takes to think rationally, but this framing makes sense. When solving a complex problem, I’ve found that quick decisions usually aren’t the right decisions. I must sit back and focus on the problem. Think a few layers deep. When I’ve done this, I’ve often come up with some of my best ideas.

I like this framing of rational thinking: It’s the result of concentration and deep thought. If you try to solve a hard problem without them, you aren’t being rational; you’re being a lazy thinker and increasing your odds of making illogical decisions.

Some passages in The Warren Buffett Way by Robert Hagstrom reminded me of this post from a few months ago. I shared that taxes are a successful entrepreneur’s biggest expense. Allocating appropriate time to optimizing that expense, just as entrepreneurs do with all other major expenses, can have a material impact on a company’s ability to reinvest in growth opportunities. Here are the passages:

Except in the case of nontaxable accounts, taxes are the biggest expense that investors face—higher than brokerage commissions and often higher than the expense ratio of running a fund.

In a nutshell, the key strategy involves another of those commonsense notions that is often underappreciated: the enormous value of the unrealized gain. When a stock appreciates in price but is not sold, the increase in value is an unrealized gain. No capital gains tax is owed until the stock is sold. If you leave the gain in place, your money compounds more forcefully.

Overall, investors have too often underestimated the enormous value of this unrealized gain—what Buffett calls an “interest-free loan from the Treasury.” To make his point, Buffett asks us to imagine what happens if you buy a $1 investment that doubles in price each year. If you sell the investment at the end of the first year, you would have a net gain of $0.66 (assuming you’re in the 34 percent tax bracket). Let’s say you reinvest the $1.66 and it doubles in value by the second year-end. If the investment continues to double each year, and you continue to sell, pay the tax, and reinvest the proceeds, at the end of 20 years you have a net gain of $25,200 after paying taxes of $13,000. If, instead, you purchase a $1 investment that doubles each year and is not sold until the end of 20 years, you would gain $692,000 after paying taxes of approximately $356,000.

This is a great mathematical example demonstrating the power of compounding and the impact taxes can have on investment returns over a long period. It reminded me that playing the long game in investing gives you twin tailwinds, which can lead to explosive results.

I’m rereading The Warren Buffett Way by Robert Hagstrom. I enjoyed this book last year, and I decided to read it again after reading Hagstrom’s book Warren Buffett: Inside the Ultimate Money Mind.

The book contains lots of insightful information about Buffett’s investing approach and how he thinks about capital allocations as the CEO of Berkshire Hathaway. One part of the book I found invaluable was the chapter called “Common Stock Purchases.” In this chapter, Hagstrom walks through Buffett’s process to analyze and value nine of his biggest investments: GEICO, Capital Cities/ABC, Coca-Cola, and others.

Many people are familiar with Buffett’s investing strategy, but how he applied it when making investment decisions isn’t always clear. Hagstrom explains how Buffett valued each company and compares his valuations to the prices he paid. He walks through the math and shows how Buffett’s investments were made for prices below the intrinsic values that Buffett calculated. Buying for less than intrinsic value is core to his strategy of investing only when there’s a margin of safety.

I noticed that Buffett sometimes broke his own rules, such as when he invested in GEICO. Buffett usually invests only in companies with a consistent operating history that are generating increased free cash flow. However, when he invested significantly in GEICO in 1976, the company was on the verge of bankruptcy, had zero earnings, and needed a turnaround. Over several years, Buffett bought roughly 33% of the company. Hagstrom does a great job of detailing why he made this seemingly risky investment. Needless to say, Buffett was right, as GEICO is now a household name. This example reinforces that rules sometimes need to be broken when great investing opportunities present themselves. It also shows how Buffett spent decades preparing for this investment by reading and learning about insurance, and how that preparation positioned him to act swiftly when he needed to.

Last week, I shared that I want to learn more about psychology to improve my decision-making and because it seems like a fun topic. Charlie Munger famously studied the failures of others to understand thinking errors. That approach resonates with me, and I decided it’s best to start by regularly analyzing my own failures. I wasn’t sure how, though, so I started looking for ways others have done this.

I started rereading The Warren Buffett Way by Robert Hagstrom and found a great idea. Hagstrom says that Buffett included in his Berkshire Hathaway annual shareholder letter a section called Mistake Du Jour. In it, he “confessed not only mistakes made but opportunities lost because he failed to act appropriately.” He was transparent about his mistakes and shared them broadly.

I’m a huge fan of update emails (see here, here, and here). But I can’t recall ever seeing an update email with a section dedicated to the founder's mistakes. The more I thought about it, the more I thought it’s brilliant. It’s a great way to make a habit of analyzing your own mistakes—and also to build trust with others and maybe even get unexpected advice based on how other people navigated similar mistakes.

My weekly update blog posts are inspired by update emails. Including a mistake du jour–type section in them would be cool. It would check the box regarding forming a habit to analyze my mistakes and force me to crystallize and communicate them concisely. If I also force myself to include the lesson learned, this could be even better. I’m not sure about some things and need to think about them (e.g., will I have enough to do this weekly, or should I do it monthly?). But I like this idea and want to add my mistakes to my 2025 weekly updates.

Current Project: Reading books about entrepreneurs and sharing what I learned from them

Mission: Create a library of wisdom from notable entrepreneurs that current entrepreneurs can leverage to increase their chances of success

Cumulative metrics (since 4/1/24):

• Total books read: 40
• Total book digests created: 15
• Total blog posts published: 245
• Total audio recordings published: 103

This week’s metrics:

• Books read: 1
• Book digests created: 0
• Blog posts published: 7
• Audio recordings published: 0

What I completed this week (link to last week’s commitments):

• Read Warren Buffett: Inside the Ultimate Money Mind, a biography by Robert Hagstrom about Warren Buffett’s mentality
• Tested populating a database with data (my developer friend led this effort)
• Created sketch of UI
• Refined database tables and fields based on the test run
• Created idea bank for growth strategies
• Added to feature list based on idea bank
• Identified what I believe are the main reasons book-related applications have struggled to become part of users' daily habits and developed features to address these challenges

What I’ll do next week:

• Read a framework book or a biography or autobiography
• Update personal blog to link posts about the same book
• Get input from developers who’ve worked on similar projects
• Identify potential technologies for challenging features
• Ponder ways to communicate a founder’s journey more effectively
• Create a list of potential metrics for weekly updates that better reflect this project
• Share taxonomy drafts with one person

Asks:

• None

Week two hundred forty-five was another week of learning. Looking forward to next week!

Current Project: Reading books about entrepreneurs and sharing what I learned from them

Mission: Create a library of wisdom from notable entrepreneurs that current entrepreneurs can leverage to increase their chances of success

What I struggled with:

• I struggle to keep up with everything I’m learning about databases and AI. I’ll keep asking questions and researching to enhance my conceptual understanding. The joys of being a nontechnical founder! :)

What I learned:

• Using one AI model for the “book library” MVP likely won’t work. We’ll need to pick the best model for each specific task and devise a process to chain the tasks together to get the desired result.
• If the context is too large (i.e., I feed AI too much data), the quality of the results plummets. We’ve broken information down into smaller chunks that still turned out to be too large. We had to break the information down into even smaller chunks, which drastically improved AI’s output quality.
• When running an iterative addition loop with AI, we must store the results (i.e., keep snapshots along the way) to avoid results from a bad loop wiping out all the data from previous loops.  
• I can improve my AI response by asking AI to write prompts. More here.
• Launching with decent data is more important than launching when the data is perfect. More here.
• My blog posts have a much wider reach than I realized. When my blog posts are valuable, readers share them readily. I need to get this MVP launched so I can begin writing detailed posts and creating podcast episodes about what I’m learning from books.
• The vision for this project is starting to become clear: Create a world where more people can readily access and apply entrepreneurial wisdom to achieve economic mobility. See more here.
• I get excited sometimes and start thinking about cool features and the potential of this project. But creating this MVP isn’t easy. I must stay focused and get the minimum required features built and working first.

Those are my struggles and learnings from the week!

This week, I was talking to my engineering friend, and he mentioned that he’d figured out a way to improve the output of his AI responses. He showed me how changing the prompt had resulted in a significantly improved response on something he was working on. But his insight was about how he improved the prompt. He asked AI to write the prompt for him! It returned a better prompt, which resulted in a better response. It was akin to him saying, Show me how to ask you questions in a way you understand best. Later in the week, I tuned in to a webinar in which the presenter used a similar technique to generate his prompts. I was hearing the same technique from two credible people in the same week.

I’ve been trying to improve my prompts for a few months, but I never considered this approach. I tried it today while I was using AI to help me with some tasks, and the results were much better. I’ve read and listened to a lot of stuff about prompting over the last few months, but this is probably the one thing that’s improved my prompting the most.

Going forward, I’ll ask AI to write or edit my prompts for me.

One thing that resonated with me in Warren Buffett: Inside the Ultimate Money Mind was the idea of studying failure. The book mentions that Charlie Munger studied failure to improve his decision-making. Munger studied the failures of others as a way of understanding thinking errors, which is studying psychology.

This got me thinking. I want to be more intentional about studying failure. I get excited about hearing what worked from entrepreneurs, but I need to be equally (or more) excited to learn about their failures and the why behind them. I’m really curious about psychology and want to keep improving my own decision-making, so this approach is appealing.

I think the first step is to regularly analyze my own failures and mistakes. I’m going to put some thought into ways I can make this a habit and see if I can adopt strategies others have used successfully.

In a post last week, I shared an unexpected data issue with the “book library” MVP project. The book databases we planned to use have quality issues. Lots of other companies use the data, so it’s not terrible, but it’s not ideal. I initially saw two paths: we can use data with flaws, or we can build a pristine data set from scratch.

I thought about it, and I decided to do both. I want to keep things moving, so we’ll start with the data from the existing book databases. That will allow us to launch the MVP’s next version faster. The data won’t be 100% accurate and might limit what features can be built. But the starting database will have a limited number of records, and we’ll start with a small number of early users. It won’t be perfect (and doesn’t need to be), but we can get something out and start the feedback loop sooner, which will lead to improvements.

After that phase, we can tackle creating a pristine database (if it’s needed). The learnings from the prior phase should also help us figure out what features to build or, more importantly, not build, around the pristine data.