What We’re Reading (Week Ending 02 November 2025) - 02 Nov 2025
Reading helps us learn about the world and it is a really important aspect of investing. The late Charlie Munger even went so far as to say that “I don’t think you can get to be a really good investor over a broad range without doing a massive amount of reading.” We (the co-founders of Compounder Fund) read widely across a range of topics, including investing, business, technology, and the world in general. We want to regularly share the best articles we’ve come across recently. Here they are (for the week ending 02 November 2025):
1. Do We Want an Age of AI Robopets? – Jessica Roy
One August morning, Kaarage woke up and took the train from the Japanese countryside into the city. She went to a restaurant and enjoyed a lunch of vegetables and soup, as well as an iced coffee. Afterward, she studied a musical score on her iPad, then went home to relax.
Kaarage is not a person: She’s an internet-beloved Moflin, an AI-powered robopet made by Casio—yes, Casio—who shares a charming, bucolic life with her owner in rural Japan…
…Since Casio initially released Moflins last year in Japan, they’ve proven to be a surprise hit, with the company selling several million dollars’ worth of Moflins in a matter of months. Last month, Casio made them available in the U.S. too, offering the furry-haired critters on its website for $429 a pop in two colors: gold and silver…
…Casio markets them as an “AI companion and robot pet” that can offer “quiet reassurance,” “ease stress” and “bring comfort.” (Watch out, loneliness epidemic.) The wellness language here is purposeful—a very real attempt to imagine the softer, cuddlier side of AI…
…The fandom and internet subcultures devoted to the robopets include a Reddit board where Moflin owners share fur-care tips and celebrate their Moflins’ “50-day” birthdays, the point when Casio says the AI pet has fully studied its owners’ vocal tones and can best respond to them in a series of purrs and coos audible through a tiny, built-in speaker beneath their fur. In Japan, hardcore Moflin owners can even spend $49 annually to join Casio’s Moflin Membership Club, which gives them access to health checkups (for maintenance issues, like charging problems) and appointments at a salon to take care of their Moflins’ fur…
…The Moflin, which weighs as much as a small rabbit, comes equipped with an app, several auditory and touch-based sensors, and a battery that lasts about five hours. (It charges in a soup bowl–shaped bed.)…
… Its only facial feature is two beady eyes. This is by design.
“We intentionally avoided features like ears, tails or distinct facial characteristics because making them look like a real creature would only emphasize how they differ from one,” said Casio developer Daisuke Takeuchi. “The abstract design allows each person to interpret who Moflin is to them, which helps build a more personal bond.”
Moflins rely on what Casio calls “emotional AI” to learn and respond to their environments, developing different personalities based on their owners’ interactions. The companion app, MofLife, allows users to track a Moflin’s mood to see how affectionate and energetic it feels…
…Amy Wang, 27, of New York. Wang has bad allergies and a small apartment, so a real pet was out of the question, but she said her Moflin, which she named Roku, provides much of the same emotional support a pet would…
…Whether the Moflin appealing to a younger demographic is a good thing remains to be seen. Nataliya Kosmyna, a research scientist at Massachusetts Institute of Technology’s Media Lab who focuses on AI, said there’s not a huge amount of research into the effects of soft AI, like that used by the Moflin, on children’s brains, but that’s exactly the issue: Kosmyna argues there should be more research into the impact of emotional AI toys on kids before they hit the market.
2. Argentina Could Be a Superpower – Tomas Pueyo
Argentina used to be rich.
Its capital, Buenos Aires, was “the Paris of South America”.
For decades, Argentina (which means “the country of silver”) was among the richest countries on Earth—richer than France, Germany, Japan, or Italy…
…Not only did the Western world leave Argentina behind. Traditionally poorer countries like Chile and China are now richer! And Brazil is catching up!
How is this possible?
Because, unlike most countries I write about, Argentina is poor despite its amazing geography. With better management, it could become the United States of Latin America…
…Argentina is basically the US of the Southern Hemisphere:
- Very similar defensibility, with oceans, mountains, and ice on three sides, and weak neighbors on the other
- The huge exception is Argentina’s neighbor, Brazil.
- Very similar land and climate, allowing for a world-class agriculture industry and cheap infrastructure.
- A very similar navigable river basin in the heartland, helping reduce transportation costs, and creating wealth and political harmony, all controlled from Buenos Aires.
- Huge, untapped mineral deposits.
Despite these striking advantages, Argentina has not been able to translate them into immigration and wealth. Geography is not destiny.
One way to put it: Geography is the hardware, our institutions are the software. When both work well, a country is unstoppable. With bad hardware but intelligent software, a country can go far. But it’s easy to waste good hardware with very bad software. This is what Argentina has done. Another way to put it: Geography is the chessboard: How you play on it determines your success, and Argentina hasn’t played very well.
3. The AI Boom’s Real Economy Problem – Bob Elliott
Meta’s release showed revenue grew 26% from the same quarter last year, or roughly 10bln, claiming that AI is now helping improve the way ads are being placed on the platform. The ads of course being the only source of revenue for the business…
…On the surface those numbers sound great for any company, but in context it’s a pretty mediocre outcome. For instance the rise of 26% y/y is only at a marginally faster rate than previous years 3Q reads which grew 19% and 23% respectively. All that AI investment for a few extra percentage points.
To achieve these goals Meta is spending upwards of $70bln on AI capex to say nothing of rising operational expenses all chasing the hope that it’ll drive increased income…
…Of course all the AI investment is driving more income, but at best it’s maybe 3-5bln more than they would have had relative to the underlying trends pre capex spend. I’m no individual company analyst, but investing 70bln/yr to get 3-5bln/yr of revenue seems like a pretty shitty ROI…
…The whole sector faces the same basic problem. Already they are spending upwards of 60% of their operating cash flow on CAPEX at this point…
…The math is pretty simple, unless there is a surge in revenues from these activities, big tech is going to pump nearly all their free cash flow into CAPEX in just a few years…
…Blowing all this cash on investment means that they need to start to generate significant incremental cash flow from their investment on real economy activities (not just self referential activities to each other on things like cloud, etc)…
…Cumulative investment has surged and yet actual revenues either direct or indirect from these activities has been, has been … lets call it subdued…
…But the reality is that there are already signs that the AI adoption curve for companies is starting to bend downward even as forward expectations are high, a real threat to the idea that revenues will surge ahead…
…Increasing revenue may not be the primary benefit of AI for the economy, because most of the benefit will come in the form of increased efficiencies…
…But higher margins do not come free of impact. Workers earnings by definition finance the vast majority of spending in the real economy. So the trouble is that if you fire a bunch of workers, they have less income to spend, and with less revenue earned. The real economy realities make what looks like a free lunch actually a drag.
4. Is AI Eating CSI? – Dragon Field
As the ChatGPT turns three in November 2025, the most popular recent riff is “AI is eating SaaS”, which has claimed countless victims of the once popular software companies such as Duolingo, Shutterstock, Coursera, Gartner, Adobe, and Constellation Software. Everyday we have hundreds of TikTok influencers and YouTubers hyping the notion that even people without any coding experience and no technical education can simply type a few prompts into ChatGPT, and the AI will automatically create a software application in a few minutes. We also have high-profile tech CEOs like Ali Ghodsi of Databricks and Satya Nadella of Microsoft all announcing that “AI is eating SaaS”.
In fact, the expression that “AI is eating software” was first mentioned by the Nvidia CEO Jensen Huang in a 2017 LinkedIn post…
…About 25 years ago, I became an IT operations manager for a metal stamping plant for one of the Detroit Big Three auto companies. The plant is 2.4 million square feet, sitting on 118 acres of land. It produces automotive parts like hoods, door panels, bumpers, floor pans, and hundreds of other smaller parts. The plant had about 1,600 employees working three 8-hour shifts for six days a week at the time. At its peak in the 1950s, the plant had several hundred presses and employed over 6,000 people…
…In stamping plants we don’t usually let the manufacturing execution system (MES) have full control of the production because if the IT system is down, we would not shutdown the press lines. This is a situation we call “running blind” and usually you want to restore the system as quickly as you can. In addition, our VMS system was integrated with our warehouse inventory and corporate ERP systems, so a sustained downtime can cause a lot of issues thus we consider it mission-critical. Accuracy and reliability are the most important for us.
At the core of our MES is a VMS for production monitoring. It was first developed in the 1980s by a small vendor in Michigan when the US Big Three auto companies started to automate and install IT systems in their manufacturing plants…
…This VMS is deeply imbedded in every aspect of our production and workflow as depicted in the chart below. It has integration with our ERP system that is running on IBM mainframe with blue screens. It’s used by most departments in the plant, even the Finance and HR people use the system regularly for production and labor hour reports…
…For many years, this small VMS vendor only had three employees: One hardware engineer who liked to hide in the workshop fiddling with all kinds of gadget, a software engineer who focused on the the software development and upgrades, and the third engineer who worked as the leader and the face of their company…
…For many years, we also tried to find a replacement for this VMS, either from another vendor or develop one by our own internal IT. Sometimes the pressure from my own IT headquarters was intense. Like most legacy VMS systems, this VMS was first procured by the business people and they did not confirm to our new IT standards. They called VMS like this “Shadow IT”. Our internal IT spent a few million dollar developed a replacement and it was pushed to many plants. It caused a lot of trouble to the business and headache to the manufacturing IT operations. Because the new system did not well, we had to keep the old vendor system running in a “passive mode” in case the new system broke. It was also needed to run data collection layer, the barcode system, and to provide data via SMS to the phones and emails. When our new system acted up (which happened a lot especially in the early years), we would quickly switch back to the old “passive” vendor system. We ended spending a lot of more money and manpower plus it tarnished IT’s reputation.
The last time (~7-8 years ago) I heard about the VMS and its vendor was when a friend mentioned to me my former company had decided they would retire the new corporate system and reverse back to the old vendor system (which was never truly replaced anyway). They announced the older vendor VMS the new corporate standard and called it “strategic”. The vendor had to hire a couple more engineers to support the added scope.
5. Stumbling Onto a Goldmine – Joe Raymond
One sunny afternoon in the late-80s (more than a decade after the Interstate Stores transaction), Larry and Nate were having lunch together on Long Island.
After eating, Nate asked Larry if they could swing by the bank so he could make a deposit. Larry was enjoying the good weather and friendly company. “Sure,” he said, “Let’s do it.”
They walked into the bank and up to the counter to grab a deposit slip.
Larry noticed on the counter a copy of the bank’s most recent quarterly balance sheet. It was one of the cleanest, most secure bank balance sheets he’d ever seen…
…He looked around the lobby and saw on the other side of the room a thick wood door with a big brass knob and the word “PRESIDENT” emblazoned across the front…
…A man in a suit opened the door and asked how he could help.
“You have a beautiful balance sheet,” Larry said. “I’d love to know how and why this came to be, and if there are any other banks out there like yours!”
The president invited Larry into his office and explained to him how the bank had recently converted from a mutual to a stock bank….
…Imagine a make-believe mutual bank with $1 million of tangible equity. Let’s say this bank wants to convert to a stock bank and offers 100,000 shares at $10 per share in an IPO. Only depositors are invited to participate in the offering.
On a pro forma basis, the converted bank will have $2 million of tangible equity (the original $1 million plus the $1 million of IPO proceeds), which equates to $20 per share of tangible book value ($2 million of equity divided by 100,000 shares).
As an IPO investor, you were able to purchase the shares at $10. You paid only 50% of tangible book value…
…The president explained all of this to Larry, including how he himself had made a killing on the bank’s conversion…
…”You should check out this little bank in Queens,” he said. “They are preparing for a conversion themselves, and I think it will be a good one.”
That little bank in Queens was called Jamaica Savings Bank. And JSB ended up being a killer investment…
…Less than two years later, on June 24, 1990, JSB Financial went public. Santa Monica bought 59,000 shares at $10 per share for an initial investment of $590,000. The pro-forma book value was $21 per share (0.48x P/TBV)…
…The shares shot up 30% to $13 right after the IPO. Many investors sold for a quick profit. Larry decided to hold on as he saw a bigger pot of gold down the line…
…BVPS could be north of $25 within three years and the company would be worth $35 per share to a strategic buyer at 1.4x TBV. This works out to a 51% annualized return over three years.
Given the nature of the balance sheet (liquid, overcapitalized, and invested primarily in short-term government securities), the downside was minimal.
Thus, Larry found himself in investment nirvana: low downside paired with big upside.
JSB became an avid repurchaser of its own stock, buying back 7% of its outstanding shares in 1991 and another 8% in 1992…
…The share count was further reduced by 10% in 1993, 9% in 1994, 2% in 1995, and 7% in 1996. Shares outstanding fell by a cumulative 38% from 1990 to 1998. And most of these buybacks were done at or below tangible book value…
…JSB entered a stock-for-stock merger with North Fork Bank (NFB) in 1999. Every one share of JSB received three shares of NFB…
…As for Larry, he held onto his stock until NFB sold to COF, at which point he elected to receive cash. The $590,000 investment in 1990 turned into more than $5.5 million in 2006.
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have a vested interest in Adobe, Mastercard, Meta Platforms, Microsoft, and Visa. Holdings are subject to change at any time.
