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I share what I learn each day about entrepreneurship—from a biography or my own experience. Always a 2-min read or less.
How Warren Buffett Avoids Impetuosity, the Casino Mentality
This weekend, I shared with a friend what I learned about psychology from rereading The Warren Buffett Way by Robert Hagstrom. One of the things he found interesting was the concept of impetuosity and how it negatively impacts investors.
Impetuosity is the tendency to act quickly, without thinking about the consequences. It can be considered a casino mentality—an itch to go into action. You get caught up in what other people are doing and place a bet or make an investment without taking time to think it through.
Impetuosity can result in investors making bets when the probabilities are against them, upsides are low, and downside risks are high.
This section of the book reminded me of 2020 and 2021. ZIRP made investors comfortable paying high valuations for a growth company. Early-stage venture capital deals were getting done in a few days with limited diligence. In 2022 and 2023, companies that raised at these high valuations and didn’t grow into them struggled to raise capital. Some raised down rounds with brutal terms. Some didn’t make it.
Looking back, it was a period of impetuosity. Investors were doing deals they otherwise wouldn’t have because of what other investors were doing. Founders were raising at sky-high valuations because other founders were. Many didn’t think about the long-term consequences. They were caught up in the hype, doing what seemed normal.
Some founders and investors were aware of impetuosity and recognized what was happening. They took note and acted differently. The shrewd investors were selling assets at peak prices, not buying. And the shrewd founders were raising reasonable sums at valuations that wouldn’t hinder future fundraising, or they were selling their companies outright at peak multiples.
Hagstrom details how Warren Buffett and Charlie Munger avoided impetuosity. The most important thing they did before making an investment was calculate the probability that it would be favorable for them. If it wasn’t favorable, they continually took in more information and monitored the situation. They had the patience to wait until the odds were in their favor, which reduced their risk of losing money. And if the odds tilted in their favor, their research and calculated probability gave them the confidence to bet big even when others were doing the opposite.
Their use of facts and probabilities helped them act counter to the crowd and overcome impetuosity.
Weekly Update: Week Two Hundred Forty-Six
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: 41
- Total book digests created: 15
- Total blog posts published: 252
- 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):
- Finished rereading Robert Hagstrom’s The Warren Buffett Way, a biography about Warren Buffett’s investing framework and psychology
- Linked popular blog posts written about the same book using related lists
- Updated descriptions of popular blog posts
- Identified a method to compile a founder’s journey from multiple sources and communicate it digestibly
- Received feedback on my draft taxonomy
- Received input and ideas from a developer who built a project like the “book library” MVP
- Identified technologies that can help with building challenging features
- Completed code to parse data according to a schema and populate database fields (my developer friend led this effort)
What I’ll do next week:
- Read a biography, autobiography, or framework book
- Create a list of potential metrics for weekly updates that better reflect this project
- Review data set in Looker Studio
- Experiment with ways to visualize data in Looker Studio
- Identify root cause and fixes for data set quality issues
- Evaluate NoteBookLM Plus
- Update UI sketches based on learnings
- Share taxonomy draft with one person
- Continue linking blog posts about the same book
- Continue updating descriptions for blog posts about the same book
- Generate ideas for a methodology for creating blog post titles using data from Google on top-performing posts
Asks:
- None
Week two hundred forty-six was another week of learning. Looking forward to next week!
Last Week’s Struggles and Lessons (Week Ending 12/15/24)
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:
- No struggles this week.
What I learned:
- Matching to existing data sets that have unique identifiers is a good way to start building a database about people and companies from scratch. It reduces the number of duplicate records.
- This summer I published 100 podcast episodes about autobiographies and biographies I was reading. To learn, I wanted to get reps quickly. To prepare for those episodes, I distilled the books into a series of blog posts. Analytics show that my series on Ted Turner, Henry Singleton, Ed Thorp, and Jim Simons are the most popular. I have 1700+ blog posts, but most visitors are for the blog post series I did this summer. I need to do more of this kind of post.
- Looker Studio is a good business intelligence tool to easily display data, especially from a database.
- Many of the AI thinkers are open to chatting about new projects. I cold emailed one of them, and we chatted this week. He was open to sharing how he built his latest project and even showed me his database. Builders like connecting with other builders and sharing their projects. Cold outreach works. I’ll do more of this going forward.
- Some AI models trained on books without permission by using the infamous Books3 data set (article).
- NoteBookLM released a paid tier and an enterprise version this week via NoteBookLM Plus (article). This could be game changing and get people more comfortable using their own source documents with AI, especially for learning.
- NoteBookLM also released the audio interactivity feature. You can listen to a podcast generated using the source documents you uploaded and interrupt the podcast mid-play to ask it questions (article).
Those are my struggles and learnings from the week!
Warren Buffett: Your IQ Isn’t How You Get Rich
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.
Rational vs. Lazy Thinking
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.
Warren Buffett’s Twin Tailwinds: Unrealized Gains and Compounding
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.
Unpacking Warren Buffett’s Big Public Market Investments
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.
Warren Buffett’s Mistake du Jour
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.
Weekly Update: Week Two Hundred Forty-Five
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!
Last Week’s Struggles and Lessons (Week Ending 12/8/24)
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!