I’ve been going to evening AI sessions hosted weekly at Georgia Tech. This week’s session was great, and I learned something new. I knew Meta had acquired or licensed the technology of several AI companies and incorporated their teams into Meta’s team over the last year or so. But what I didn’t know was that Meta has quietly built and significantly improved its own ChatGPT competitor. It’s agentic and, for now, 100% free.

If you’re interested in checking out this tool before it hits the mainstream, you can go to Meta.ai to play with it.

Last week, I was chatting with someone about books and how I think about reading. I used to pick up random books to read, but now I’m more intentional about why I read. Before I choose a book, I write down what problem I’m trying to solve or what roadblock I’m currently facing. The more painful the problem, the more motivated I am to solve it. I then go find books written by people who have solved the problem, often biographies or framework books.

I use a synoptical reading approach to consuming the books. I’m not looking for the answer in any single book. I’m looking for patterns, and I’m comparing and contrasting ideas in the various books. The idea is to understand the problem and possible solutions from different perspectives so I can come to my own conclusions about how to solve the problem.

I found out about synoptical reading when I read How to Read a Book in 2023. I synthesized what I learned from that book here. It took a little bit of effort to embrace this approach, but I’m glad I did. It’s one I hope I can keep up for many years.

Continuing with my new protocol, here I’m going to share content I consumed and learned from. This week, I spent time doing general learning about a variety of topics.

What I consumed this week and what I learned from it:

• Social media channels are information maps – YouTube interview with Chris Camillo, an investor who turned $80k into $50M by spotting trends early on social media. Camillo got on my radar when I read Jack Schwager’s latest book, Unknown Market Wizards. Chris thinks differently, and his insights are often thought-provoking. He’s made a career out of being ahead of the crowd. In this interview, he explains that social media platforms began as contained social grids, meaning you didn’t have access to what existed outside your “friends.” These platforms have evolved into open information maps where you can now see in real time what everyone in the world is talking about as they talk about it. He goes on to say that agentic AI will ultimately help people make sense of the growing amount of conversational data. This concept stuck with me and reinforced my belief that X is a valuable tool for bottom-up research. Later in the interview (see here), he reinforces what I’ve heard many entrepreneurs and investors say (in different ways): the biggest trap is making big decisions right after you have a big win. Your worst decision or investment comes right after you’ve had a massive win because you’re overconfident and you’re flush with cash, so you don’t adhere to the strict decision-making and execution process that led to your big win.
• Pace of insight to action determines success – Interview with Taylor Holiday, founder and CEO of ad agency Common Thread Collective. Holiday caught my attention when he said that the amount of time between an insight being identified and action being taken based on that insight is a critical component of achieving your goal. This ultimately determines the speed of course correction, which is important when you’re doing something that doesn’t have a clear path, especially if it’s hard. People who have superior decision-making skills act quickly when they learn new information that changes the situation or connect dots that lead to new insights.
• Customers care about their problems, not what you’re selling – Interview with Donald Miller, marketing entrepreneur and author of Building a StoryBrand 2.0. This is a great interview on the psychology of customers and how entrepreneurs should communicate to customers the reasons they should buy their product or service. The gist is that you should talk about the customer’s problem and how you’ll make them a hero by helping them solve their problem. His analogy is that if you go on a date with someone who talks about himself or herself the whole time, that’s a bad date. Customers have similar feelings about companies that talk about themselves instead of the customer’s problem.

That’s what I learned from what I consumed last week.

I’ve been looking into the current marketing landscape for selling physical products. From what I learned through my own research, things have changed considerably since I was selling physical products online. How companies reach customers has evolved materially.

After I felt like I had a high-level understanding of what’s changed, I reached out to an old friend who runs a marketing agency. He’s on the front lines every day buying ads on behalf of his clients. The conversation was great. He was able to give me a front-line perspective about what’s working and not working and share what he’s hearing from his peers who run agencies. It was also cool to hear his thoughtful approach to building his agency and structuring his team in a way that differentiates his services and better aligns his agency with his clients.

What I learned in a single call would have taken me tons of time to learn on my own (if I ever could have). Today was a reminder that when I’m trying to get up to speed on something fast, nothing beats talking with an entrepreneur who operates in the space. I just need to come to the meeting prepared so they don’t think I’m wasting their time.

Continuing with my new protocol, here I’m going to share content I consumed and learned from. This week, I spent time doing general learning about a variety of topics.

What I consumed this week and what I learned from it:

• How AppLovin CEO values his company: free cash flow minus stock-based compensation – YouTube interview with AppLovin CEO Adam Foroughi. I’ve been listening to different perspectives on how to account for stock-based compensation (see here). Foroughi shares an interesting perspective on why he thinks cash flow minus stock-based compensation is the best way to value a company. He also discusses his historic $6 billion stock buyback, which created $50 billion in value, and why his stock fell by 92% in 2022.
• How a billionaire runs his life with AI agents – YouTube interview with Andrew Wilkinson on how he uses AI agents to run his personal and professional life, including his health and his family office. Interesting details on the vertical SaaS app for psychological screening that he vibe-coded.
• Run toward ugly and misunderstood stuff – YouTube interview with Matt Schrager of TD Quant. Schrager explains his views on the best opportunities lying in messy or misunderstood opportunities. Those opportunities tend to have more upside potential because there’s more inefficiency. This reminds me of how Warren Buffett and Ed Thorp generated outsize returns, early in their investing career, in inefficient and misunderstood markets.

That’s what I learned from what I consumed last week.

A few weeks ago, I shared that I’d listened to a podcast presenter talk about how sound neural entrainment can reduce distractibility and help you get into your flow state. He mentioned Brain.fm, and I signed up for a free trial.

It’s been two weeks, and I really like the product. It’s hard to explain, but when I turn on the service, I definitely feel more in the zone and more productive. I focus faster than usual and knock out my to-do list like a champ.

I’ve noticed a few things, though. The first is that I need to remember to turn on the service! I don’t consistently remember, but when I do, I’m glad. I need to work toward making turning it on part of my normal work habits. The other thing I’ve noticed is that I get the most impact when I use earphones. When I let it play over the speakers on my computer, it doesn’t have the same effect. I think the earphones block out all other background noise so the rhythm of the music is all I hear.

Overall, I’m a fan so far. I’ll keep testing it for the rest of the month.

Continuing with my new protocol, here I’m going to share content I consumed and learned from. This week, I spent time trying to understand the brokerage and 3D gaming worlds. I listened to the perspectives of two seasoned public equity market investors.

What I consumed this week and what I learned from it:

• Building the YouTube of 3D worlds and video games – YouTube interview with Roblox cofounder and CEO David Baszucki. Interesting interview to understand the early days and what led Baszucki to found an ahead-of-its-time company after he sold another company for $20 million. He looked for a CEO job for two years before following his passion.
• Building an AI brokerage – YouTube interview with Public co-CEO and founder Leif Abraham. I’ve read biographies about the founders of Schwab, TD Ameritrade, and Vanguard (see here, here, and here). The brokerage business fascinates me. Public is building an AI-first brokerage platform. Learning more about the company and where the industry is going, as seen through Abraham’s eyes, was thought-provoking.
• The more risk you feel you’re taking, the less risk you’re taking – YouTube interview with Chris Davis of Davis Advisors. I read the biography of the Davis family (see here) and have followed Chris ever since. Lots of great nuggets in this interview about how he approaches investing in durable companies using a margin of safety. He shares wisdom about regretting selling great companies too early.
• Paul Tudor Jones on stock market cap-to-GDP – YouTube interview with Paul Tudor Jones, legendary trader and founder of Tudor Investment Corporation. Great insights from someone who’s seen multiple market cycles. His views on the total stock market cap–to-GDP ratio stuck with me. His daily routine is insane. His reflections on how long-term investing and Buffett’s approach are better were entertaining, especially coming from a multibillionaire who said the opposite years ago. Interesting story about how one small act of kindness to him in the 1950s sparked decades of philanthropic activities.

That’s what I consumed and learned from last week.

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I’ve been listening to a lot of friends discuss the amount of money that’s being spent to build data centers and related infrastructure for AI. Some of them are investors and others are entrepreneurs, so I hear varying perspectives on whether the current and proposed levels of spending make sense. And after listening to Kevin Koharki explain how stock-based compensation hits shareholders twice and reduces cash flow per share significantly (see here), I began thinking about it from that perspective as well.

I’m not sure what to make of this boom in spending on AI, but I want to understand it better because I think its impact on the economy and society will be massive. Luckily, this isn’t the first time we’ve had a massive spending boom driven by new technology. That being the case, I think the best thing for me to do is study history to understand what happened so I can better understand today’s reality. I have some historical books on this topic that I’m going to crack open.

I watched a few interviews where founders mentioned that physical AI and robotics are the next frontier in AI. I’m not very familiar with either, so I started digging. It’s early, but the more I learn, the more I can see why they believe that incorporating AI into robots and other devices that execute complex actions in the real world is a big deal. Especially when you consider repetitive, dangerous, or labor-intensive tasks being handled by machines or robots. That’s an enormous market.

I’m still learning, but so far I’m intrigued. I don’t have a deep enough understanding to share insights at this point, but anyone interested in finding out what physical AI is or why it’s important should check out a great article from Nvidia about generative physical AI here.

Yesterday I finished my second AI workshop at Georgia Tech. This session was focused on learning how to use the AI agent and workflow tool n8n. The person leading the session has built a sophisticated e-commerce company that’s automated on the n8n platform, so he was very knowledgeable.

n8n reminds me of workflow and conditional logic tools I’ve used in the past, but it’s way more powerful. The ability to connect it to foundational models like those from OpenAI (ChatGPT’s parent company) is huge. Last night, we linked our n8n workflow to OpenAI models via API, connected our n8n workflow to Telegram so we can give it written instructions, and built an OpenClaw-type setup in n8n.

Working with these tools hands-on with other people who are motivated to learn them makes for a wonderful environment. I met several great people last night, and I’m looking forward to the next session.