The Owner’s Memo is on vacation this week and will return next week with another case study.
In lieu of a regular article, I’d like to highlight four pieces of reading that have stuck with me over the past year or so. None of them have to do with investing per se, but they do by extension. The pieces discuss work and performance, and, as such, they contain lessons applicable to the work of investing (and other work).
I hope you find them interesting.
The Mundanity of Excellence by Daniel F. Chambliss
Daniel Chambliss is a professor of sociology and was an amateur swim coach. In the 1980s, he conducted research to discover what made the most elite athletes in the sport of swimming different from other swimmers. He spent one and a half years attending national and international swim meets, including the 1984 Olympic Games. The result of his work was this journal article published in 1989.
In it, Chambliss makes a few interesting and unintuitive points:
“Talent” is a meaningless description. Chambliss argues that the common refrain, that great athletes are “talented”, is meaningless and circular because we only call an athlete “talented” after they achieve success, like winning competitions or performing some great feat.
Excellence in swimming requires qualitative difference. Top swimmers do things differently than the rest, and there are step-change differences at each of the higher levels of the sport. The styles of strokes, dives, and turns are dramatically different at each level.
Excellence is much more mundane than we think. Motivation is too. From the article:
“People don’t know how ordinary success is,” said Mary T. Meagher, winner of 3 gold medals in the Los Angeles Olympics.
…
”When Mary T. Meagher was 13 years old and had qualified for the National Championships, she decided to try to break the world record in the 200 Meter Butterfly race. She made two immediate qualitative changes in her routine: first, she began coming on time to all practices. She recalls now, years later, being picked up at school by her mother and driving (rather quickly) through the streets of Louisville, Kentucky trying desperately to make it to the pool on time. That habit, that discipline, she now says, gave her the sense that every minute of practice time counted. And second, she began doing all of her turns, during those practices, correctly, in strict accordance with the competitive rules. Most swimmers don’t do this; they turn rather casually, and tend to touch with one hand instead of two (in the butterfly, Meagher’s stroke). This, she says, accustomed her to doing things one step better than those around her—always. Those are the two major changes she made in her training, as she remembers it.”
…Within a year Meagher had broken the world record in the butterfly.
Beyond nature and nurture by David Bessis
This article by mathematician and writer David Bessis pairs well with Chambliss’s work. Bessis makes the argument that mathematical talent isn’t primarily the result of genetics, and he provides commentary from elite mathematicians to support his claim.
It is popular to debate whether someone’s achievements in a given field are the result of “nature” or “nurture”. Bessis, citing geneticist Eric Turkheimer, discusses a third factor that he calls “idiosyncratic cognitive development”, which is his attempt to grasp at the vague factors in one’s life not covered by genetic makeup nor by the family environment. What is it that happened to some of the greats that was different from the rest?
He tells a brief story about Bill Thurston, a celebrated mathematician and Fields Medal winner, who was able to visualize geometric structures in 4 and 5 dimensions. How did he gain this unimaginable skill? Thurston had a congenital squint that deprived him of the ability to see the world in three dimensions. To rectify it, he had to practice imagining “stitching” together the 2D images he saw to form the 3D world around him.
As a first-grader he made the decision “to practice visualization every day.” Asked how he saw in four or five dimensions he said it is the same as in three dimensions: reconstruct things from two-dimensional projections.
Thurston practiced his way to elite performance, and the anecdote squares with Bessis’s own experience in learning elite mathematics.
Since reading this article, I’ve become enamored with Bessis’s writing. You can find other articles on his website. I recommend also reading Attention is all we have and Writing is hard - and it should be.
What’s the next physical action? by Oliver Burkeman
This is a short article that I come back to regularly. While the Chambliss and Bessis pieces are helpful and inspirational, giving an “ordinary” person hope that deliberate practice can bring about excellence, Burkeman’s article is a nice reminder of some of the basics of good work.
Namely, Burkeman reviews some popular and classic work, and recalls the advice pioneered by David Allen and written about by Cal Newport that, in order to get something done, it helps immensely to break it into chunks that are tangible, even physical.
Cal Newport makes the excellent suggestion (also explored in his book Deep Work) to set targets for focused work in terms of tangible products. If you aim to spend the morning planning a given project, aim to produce, say, a two-page strategic plan which you can print out and hold in your hands. Then print it out, and hold it in your hands.
Burkeman’s advice is especially valuable in a world in which so much information resides online. It’s easy to have good intentions about your work but get dragged into a vortex of online information and emerge feeling like you didn’t actually do the work you intended.
I’m constantly creating to-do lists for myself, and constantly needing to remind myself of Burkeman’s counsel. Work goes much better when it is broken into concrete steps rather than vague ones.
After Automation by Dan Shipper
This piece is a bit different from the prior three, but I include it here because it relates to the work we do, and it tries to tackle the question that so many of us are wrestling with as AI continues to advance: “does AI progress mean that human work will be redundant or replaced?”
Dan Shipper is the CEO of Every, a media and software company. The article he wrote discusses how his company is using AI today (or at least as of May 2026, when it was written). It is replete with examples, which makes it especially enjoyable and useful. Much of Shipper’s discussion describes agentic-style work at Every, and he offers a balanced view of the quality; the agents help the team, but it cannot yet completely replace most work.
Because everyone has access to the same models, and the models are all based on yesterday’s competence, by default the models end up creating work that ranges from “a decent start” to “it’s just plain slop.”
I’ll leave you with Shipper’s commentary about whether humans might be replaced.
And yet, the paradox remains. If you talk to anyone in the AI industry—or to early adopters outside of it—you’ll hear the same thing we’ve noticed internally: There’s more work to do than ever.
The big question, within the industry and without, is: Is this just a temporary state of affairs? Will the next model drop be the one to replace everyone? We watch the benchmarks and sweat, wondering if there’s a tipping point around the corner where all of the jobs go away.
There’s no tipping point coming where things flip and the jobs are gone. The new reality is the opposite—the more we automate, the more expert human work there is to do.
Thanks for this. I haven’t read Burkeman’s article. Cal’s book, Deep Work, completely transformed my approach to my work when I ran a fund. We began to break the tasks into chunks and both productivity and enjoyment increased. Anyway, great collection of articles.