Last week, I read a post on X that caught my eye. I shared it with a few folks, which sparked some great dialogue. The post was based on this article. The gist of the post and the article is that the venture capital industry has increasingly focused on coordinating capital across multiple funding rounds for the start-ups it invests in. Therefore, investors focus on fundability—the likelihood they can attract later investors—when making investment decisions. This is a form of consensus seeking. The more capital a company requires from VCs, the more consensus is needed.

For several reasons, it’s harder for smaller VC firms to play and win this game. They need to play a different game if they want to generate alpha (i.e., outsize returns for their investors). Instead of focusing on the fundability of a company, here’s what they should be looking for:

• Companies that are capital efficient and don’t require insane amounts of growth capital to build a great business with a moat. For example, Ho Nam and his firm Altos Ventures invested in Roblox early. He says (see here) that Roblox needed only $10 million total from investors to become cash-flow positive. Roblox has a market cap today, as of this writing, of roughly $50 billion and generated over $1.3 billion in operating cash flow in the last 12 months.
• Companies that don’t need hype or investor consensus to prove they work. With very little capital, they can show in their data that customers demonstrate strong demand for the product because of how well it solves a problem for them.

Interestingly, Ho Nam commented “Agree 100%” below this post.

I’m glad I found this post. It got me thinking about how, going forward, outsize returns can be generated by the smaller funds, especially those that aren’t feeder funds to the big boys.

I tend to still think that founders (and small VC funds that back them) create a lot more optionality for themselves when they focus on providing a good product that customers will pay for (which provides growth capital) instead of on giving the VCs the story they want to invest in. Ironically, if customers love and pay for your product, VCs will love you too. The inverse isn’t always true.  

Last week, I reread Felix Dennis’s book How to Get Rich. Dennis was the founder of Dennis Publishing, Maxim magazine, and Micro Warehouse, a mail-order computer parts company. He was a colorful person who lived an extreme lifestyle, but his thoughts on creating wealth through entrepreneurship were based on his experiences and, in my opinion, spot on.

After reading this book in 2024, I wrote a blog series that captured its main ideas. You can read them:

• Felix Dennis Part 1: Getting Going as a Founder
• Felix Dennis Part 2: Succeeding as a Founder
• Felix Dennis Part 3: Winning and Walking Away

Today I read those posts again, and even after a second reading of the book, I think they capture its essence in a concise way.

His lessons on getting started as a founder got me thinking, especially his advice to find new industries that are growing fast. Lots of people are doing this with AI. His advice to never think small and to act big also resonated with me. He’s right that people stop doing the things that led to their success once they become successful, or they think small and don’t embrace new ideas and ways of doing things.

I’m glad I read this book again. It was a nice refresher.

Side note: I read Dennis’s biography More Lives Than One too. You can learn more about his life journey  here, in the blog post series I wrote based on this biography.

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: 99
• Total blog posts published: 658

This week’s metrics:

• Books read: 1
• Blog posts published: 7

What I completed in the week ending 1/25/26 (link to the previous week’s commitments):

• Reread How to Get Rich, a framework for creating wealth through entrepreneurship written by publishing magnate and founder of Maxim magazine Felix Dennis  

What I’ll do next week:

• Read a biography, autobiography, or framework book
• Write a post sharing what I learned from synthesizing The Art of Execution

Asks:

• No ask this week

Week three hundred four 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:

• Same as last week: I had trouble getting started on synthesizing another book.

What I learned:

• ·Going back to synthesize a book I’ve read after I’ve begun reading another one is hard. Might make sense to synthesize as I read.

That’s what I learned and struggled with last week.

The forecast is calling for bad weather to hit most of the country this weekend. An ice storm is expected in Atlanta. I hate feeling trapped, but I’m going to try to use this time to catch up. Specifically, I want to write a post about what I learned from synthesizing The Art of Execution.

Wish me luck!

Today I had a conversation with a friend and entrepreneur about how he works. He described his system, which relies heavily on an AI assistant that he chats with daily. He graciously showed me what he built and how it all works.

I won’t get into all the specifics, but a few things stuck with me:

• MCP – He’s using model context protocol (MCP) to connect all his various tools to Claude’s AI assistant so the assistant has proper context around what’s important to him.
• Database – He stores everything—contacts, goals, etc.—in a Notion database, which Claude accesses via MCP.
• 10 items max – In any given day, Claude gives him no more than 10 action items to focus on getting done.
• Specialization – He built a different AI assistant for each part of his life (work, personal, etc.). Each acts according to specific instructions and accesses the appropriate data in a Notion database.
• Update permissions – He gives Claude update permissions so it can update his calendar, his Notion database, and other systems it has access to.

I was impressed with his setup. He’s leveraging AI to manage various aspects of his life and help him pinpoint what to focus on every day.

Today I read a blog post (see here) that had caught my eye. It was supposed to be about how to create a personal customer relationship management (CRM) system. Like a lot of people, I struggle to maintain relationships, so I gave it a read. The article turned out to be more than I expected. It’s a great read for anyone trying to understand how to use AI to help with manual tasks and how AI can connect with various tools you already use.

It presents a high-level overview of how you can use AI to talk to the tools you commonly use (Slack, Calendar, Gmail, Google Sheets, Notion, etc.) using the model context protocol (MCP). It describes how MCP works, who created it (Anthorpic), and how the average person can easily download and use it. MCP is powerful because most manual tasks involve shifting between systems. MCP connects all those systems to an AI assistant like Claude, empowering the AI to see the same data you do and execute on it just as you would. You can have an AI assistant complete tasks that would have taken you tons of time or energy, or you can have it do 90% of the work so you have to do only 10%.

The author then takes it a step further and shows you, pretty much step by step, how to use MCP to connect to Gmail and Calendar. It then provides example prompts for instructing AI to do tasks that you’d normally have to manage manually in a CRM. For instance, the author has AI prepare a list of names, using specified criteria, of people he needs to follow up with. He also has AI analyze his calendar for the past week and summarize all his meetings so he can report to his cofounder on Monday what he’d done that week.

I found this post helpful and will be sharing it. Not everyone needs a personal CRM, but the post does a great job of showing how anyone can use MCP and AI assistants to become more efficient and also explaining how to set it up.

Last week I was working on a data project. I needed to get information from a website and manually enter it into a spreadsheet. In the past, I’ve used Upwork to find data entry resources to help with this sort of thing, and I did that again this time. But as they worked (I have them do tests before I give them the full project), I soon realized that at the rate they were working, it would take someone weeks to build the spreadsheet and cost several times more than I wanted to pay.

I wanted to be frugal and get this task done faster, so I reached out to a developer friend for suggestions. He showed me how to extract the data using the website’s API instead of the user interface (i.e., webpage). All I had to do was figure out how to parse and store the data. Normally, I’d have a developer do this for me, too, but I turned to AI instead. I cracked open Google Gemini and explained the project. Within minutes, it had written a Google Apps script that I could run. It would take the data returned by the API, parse it, and store the data in Google Sheets. The script required one manual step, too, but I was happy to do that. It was very efficient and way less prone to error as compared to someone manually doing it over a few weeks. So, I spent the weekend using the script, Gemini, and the website’s API to build a large data set.

In the end, a project that was projected to take weeks, cost a significant amount, and require me to manage another resource was instead completed by me (with help from Gemini) in several hours over the weekend.

Once people realize they don’t need developers to write code and can build things on their own with AI tools, we’ll see an explosion of people building tools to solve their own problems (and do their jobs more efficiently).

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Last week, I shared (see here) that I was curious about how entrepreneurs learn to work. My thesis is that many don’t know how to work, and the ones who do are self-taught out of necessity. In the last few days, I’ve talked to a few entrepreneurs and asked these point-blank questions:

• How do you decide what to work on each day?
• What did your last workday look like?
• What did your last workweek look like?  
• How did you learn how to work as a founder?

The first three questions are to understand how they work. The last question is the most important one.

I’ve done only a handful of these sessions, but so far, the answer is that they learned over time by piecing together what people shared with them. Also, the forcing function was stress and anxiety, which made them realize that how they were working was a big problem.

It’s early days, and I’m curious. I’ll have more of these conversations with entrepreneurs. This might be an overlooked problem that many entrepreneurs face.

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: 98
• Total blog posts published: 651

This week’s metrics:

• Books read: 1
• Blog posts published: 7

What I completed in the week ending 1/18/26 (link to the previous week’s commitments):

• Read The PARA Method, a framework for implementing the PARA Method from Building a Second Brain

What I’ll do next week:

• Read a biography, autobiography, or framework book
• Write a post sharing what I learned from synthesizing The Art of Execution

Asks:

• No ask this week

Week three hundred three was another week of learning. Looking forward to next week!

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