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.

I’m reading Warren Buffett: Inside the Ultimate Money Mind, which is a book about the mindset of Warren Buffett and other investors. One of the things it discusses is how Buffett and other investors make decisions. Robert Hagstrom points out that to understand psychology is to understand human decision-making. That’s why successful investors like Charlie Munger studied psychology to improve their own decision-making.

I’ve never thought much about psychology,  but this book got me thinking about it in relation to entrepreneurship—specifically, entrepreneurial wisdom. In this post, I shared that wisdom is the ability to apply knowledge in a manner that aligns with the outcome you desire. Wisdom means changed behavior and improved decision-making—knowing what to do and when to do it.

I’m always looking for ways to improve my decision-making (and share what I learn). But I’ve never really thought about trying to understand psychology to accomplish this until now. Hagstrom has me interested in learning more about psychology.

I’m going to try to find one of two books about psychology and add them to my reading list.

My book project started with me reading biographies about entrepreneurs and sharing what I learned. During that process, I realized there’s no central repository of all the wisdom of entrepreneurs who came before us. I decided to create one and came up with this mission:

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

This project is super early, but I’ve been thinking about the impact it could have. The thing I keep coming back to is economic mobility. Starting a business that becomes successful is the fastest way to climb the economic ladder, which is why I think entrepreneurship is such a powerful force. Families who struggled financially for generations have seen their circumstances change in a few years because they started a successful business. There are numerous examples of family patriarchs and matriarchs starting businesses and their families still benefiting economically many generations later. Their descendants have continued to climb the economic ladder because of their business (or the resources it created).

Entrepreneurs still must do the work. There’s no substitute for execution and no shortcut to it. But if this project is successful, I can see it boosting many entrepreneurs. Making learnings of notable entrepreneurs easily accessible and helping other entrepreneurs figure out how to apply them could accelerate their velocity and increase their chances of success. If more entrepreneurs are successful, more people, and their families, will experience economic mobility and, hopefully, economic independence.

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: 39
• Total book digests created: 15
• Total blog posts published: 238
• 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 a third book on David Ogilvy - a collection of his learnings about advertising
• Demoed first major feature for “book library” MVP
• Refined and ranked sub-feature list for “book library” MVP
• Defined data views for “book library” MVP
• Updated list of competitors for “book library” MVP
• Analyzed database sources for book data

What I’ll do next week:

• Read a framework book, biography, or autobiography
• Share taxonomy drafts with one person
• Refine list of fields for database tables
• Create idea bank for growth strategies

Asks:

• None

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