
HUSBAND,FATHER PASSIONATE ABOUT THINKING AND INVESTING IN AFRICAN BUSINESSES|BIBLIOPHILE|TECHIE@ HEART|SERVANT LEADER cc @ValueVest
kenya
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Halfway through Bob Iger's book and it is a gem. Highly recommended. A snapshot of relentless pursuit of perfection, diplomacy and humility.
Reminds me of Shoe Dog.
Expect a thread on excellence soon.
One of the founders sat me down for some homely advice. In his broad Scottish accent he said, “well, young Nick”, there was then a long pause and he began to smile “this job is the best fun you can have with your clothes on”. Zak and I love running Nomad.
“RULES
Are for INFANTS, INCOMPETENTS,
INCARCERATED CRIMINALS and IMBECILES
- NONE of WHOM should have any place in the
ERIE FAMILY.” 👏🏿👏🏿🫵🏿👍🏿
And now you can preorder the NOMAD LETTERS (out December 1!): press.stripe.com/nomad-lette…
For years these letters have circulated (at first, unofficially) among investors, acquiring a devoted readership. We wanted to give them a permanent home in print.
Nick and his partner Qais Zakaria’s record is extraordinary. The letters are the account of how they got there, featuring everything from studying Amazon and Costco (Nomad’s defining investments)—to visiting cement plants in Zimbabwe, and beyond.
They’re candid about their mistakes and curious about the forces that shape investors’ behavior: incentives, psychology, and the wisdom (or foolishness!) of the crowd.
Since closing the fund, they’ve devoted their time to philanthropy, a journey Nick recounts in the lovely foreword he wrote for this edition.
I’m thrilled to continue adding to the investing corner of our catalogue, and I can’t think of a better work to follow Poor Charlie’s Almanack. ❣️
youtube.com/shorts/s2TUZn4gW…
Eka kwa lungs.
Daystar valley road. @DaystarAlumniDU
Franklin Miswa retweeted
I joined IFC, part of WB group in Jan 2011, after a short stint in KNBS.
Well, where do I start? Perhaps at if you are a father, be very present in your SONS' lives.
Anyway, by the time my contract was ending sometimes in 2013, I couldn't find an employer who could
Franklin Miswa retweeted
Brothers Karamazov was Einstein’s favorite novel, a verdict he shared with Freud, Hillary Clinton, and Murakami. Dostoyevsky was Pope Francis’s favorite author. Indeed, he approvingly quoted Elder Zosima; perhaps an interesting case of art molding life. At the risk of betraying my relative shallowness and inferiority, I confess that I did not love it.
Written in the shadow of the death of Dostoyevsky’s son (also Alyosha), and, more broadly, after a life of repeated tragedy, Karamazov attempts most of all to address the problem of evil in Christianity. Ivan presents a trenchant argument, asking how the suffering of children may possibly be explained given the existence of a supposedly benevolent God (Dostoyevsky collected real court cases for Ivan), culminating in Ivan’s famous return of the ticket.
The book gives some sense for how dislocating the nineteenth century must have been. The ascendant authority of science, the spread of materialist philosophy, the doctrine of evolution, the aftermath of the French revolution and its supposedly enlightened empiricism: in Karamazov, we get the feeling that finding some kind of consilience wasn’t just an abstract philosophical challenge, but a source of intense spiritual torment. If inherited tradition is no longer an adequate basis for faith, why would we rationally cleave to an apparently irrational theology? All of this was in the air: it was only two years later that Nietzsche declared God to be dead.
Perhaps demonstrating the utility of the novel as a medium, Dostoyevsky does not even attempt to solve the problem, but merely to illustrate a response, showing how individuals (Alyosha, Elder Zosima) may in the face of the inherent injustice present in the world nonetheless pursue lives of benevolence and charity: theodicy-by-example. In so doing, Dostoyevsky tacitly concedes that none of the teetering justifications expounded over the centuries can actually survive critical pressure and be defended through pure logic.
Ultimately, though, I don’t find myself being fully compelled by Dostoyevsky’s characterization of the problem or his proposed solution. As another sprawling confrontation with and attempt to reconcile the problem of evil, Grossman’s Life and Fate is maybe a useful counterpoint. Unlike Karamazov, Life and Fate shows actual people confronting great wickedness. Ikonnikov, a small but important figure, is ordered to help in the construction of a gas chamber. He refuses, with full awareness of the consequences that will ensue. The Karamazovs, by contrast, live middle class lives unvisited by greater events. Ivan has money, education, and leisure; his torment is the invention of his own mind and thus a kind of self-indulgence. Even Alyosha, the novel’s most sympathetic character, is never tested. His crisis is spiritual: there is a slightly comic kerfuffle about Zosima’s noisome corpse, which challenges his faith, but no circumstance requires him to stake his life or even his comfort.
Thus, a fundamental issue with Karamazov is that the problems of the book are on some level fake: they’re the self-inflicted derangements of febrile and dysregulated men. How much can or should we learn from the insane?
To be charitable to Dostoyevsky, we might say that he understood the spiritual dislocation of the era that later gives rise to the larger evils of totalitarianism in the twentieth, even prefiguring them in the Grand Inquisitor. (Dostoyevsky explored this theme in greater detail a few years earlier in Demons.) Camus in 1959: “The real nineteenth century prophet was Dostoevsky, not Karl Marx.” In this interpretation, the problems in Karamazov set the stage for those in Life and Fate.
Maybe. At least as a work of art, I’m not sure that this anticipation is enough to make the book stand on its own. In Karamazov, one continually wonders why the brothers don’t just pull it together. Dostoyevsky seems to transpose his own inner depths and spiritual torment onto his characters, but most people are not tortured writers, and it does not feel that the unhingedness of the characters is ever fully earned.
In attempting to address evil, Grossman’s conclusion is ostensibly similar to Dostoyevsky’s: the only resolution lies in senseless kindness. For Dostoyevsky, this message is embodied in Alyosha, who represents a kind of fervent innocence. For me, however, it’s not clear that Alyosha ever fathoms the realities and extremities of evil, and hence he’s not fully persuasive: does he even reckon with the misdeeds of his brothers?
Grossman is willing to engage head on. Far beyond gruesome newspaper anecdotes or neurotic and volatile siblings, Ikonnikov directly experiences the Holodomor in Ukraine and then the murders of the Jews. He has no patience for the kind of revolutionary ideas that animated Ivan’s contemporaries: “whenever we see [the dawn of an eternal good], the blood of old people and children is always shed.”
Alyosha believes in the Church and is willing to set aside its failures to address suffering. The book closes on his declaration that all shall rise again. That is, Alyosha does not accept the tragedy of Ilyusha, an innocent boy’s death, but rather seeks to deny and escape it. “We shall see each other and shall tell each other with joy and gladness all that has happened.”
Life and Fate flatly rejects providential resolution. The heavens may be empty, and there is no greater meaning in evil. We can simply choose (freedom the other great theme of Life and Fate) to pursue acts of charity, generosity, and comfort:
“Yes, as well as this terrible Good with a capital ‘G’, there is everyday human kindness. The kindness of an old woman carrying a piece of bread to a prisoner, the kindness of a soldier allowing a wounded enemy to drink from his water-flask, the kindness of youth towards age, the kindness of a peasant hiding an old Jew in his loft. The kindness of a prison guard who risks his own liberty to pass on letters written by a prisoner not to his ideological comrades, but to his wife and mother.”
These acts don’t ennoble the suffering but are instead justified on their own terms. Such altruism cannot become a catechism, as clearly lies in Alyosha’s destiny (and Karamazov was planned before Dostoyevsky's death as the first of two works); instead, our kindness must be senseless. And we should presume no salvation in adherence: Alyosha imagines a kind of sacred tutelage, but Ikonnikov is unceremoniously shot.
Karamazov doesn’t show true evil, and Dostoyevsky’s solution, such as it is, involves a kind of denial, or at least evasion through metaphysics. Grossman saw it directly, and instead argues, humanistically, that we should be kind just because.
—
If Dostoyevsky came to his works by trying to understand and depict Russian society, they in turn became tapestries for others to understand national souls.
In the aftermath of WWI, Russia was the great power defined in opposition to the West. As Germany tried to rediscover its own soul in the wreckage of defeat, it looked east to Russia, and frequently to Dostoyevsky himself.
Carl Jung thought that the German people had a kind of Karamazovian quality. In particular, he believed that Christianity had disciplined them without fully transforming the impulses beneath their ostensibly civilized conduct: the “Germanic barbarian” was divided into upper and lower halves. Religion had domesticated the former while leaving the latter untamed. Waning faith consequently threatened to release forces that its authority had long restrained: “As the Christian view of the world loses its authority, the more menacingly will the ‘blond beast’ be heard prowling about in its underground prison, ready at any moment to burst out with devastating consequences. When this happens in the individual it brings about a psychological revolution, but it can also take a social form.”
Dostoyevsky was reputedly invoked on a weekly basis at Max Weber’s Sunday gatherings. At the beginning of Reflections of a Nonpolitical Man, Thomas Mann’s later-repudiated 1918 nationalist polemic, he quotes approvingly Dostoyevsky’s characterization of Germany as the “protesting Western empire”, never quite adopting or feeling at home with the inheritance of Rome. In the same year, Spengler wrote Decline of the West, and explicitly perceived in Russia a youthful vigor, primitiveness, and irrationality that contrasted with the senile high culture of the German and Western worlds. In Magic Mountain, Mann later used Clavdia Chauchat to personify the seductive dangers of Eastern (i.e. Russian) illogic.
Hermann Hesse declared that, for all their differences, Fyodor, Dmitri, Ivan, and Alyosha are actually all of one type; the Russian man. In them, he perceived that “the ideal of the Karamazov, primeval, Asiatic, and occult, is already beginning to consume the European soul”, which was leading to the downfall of Europe. In Hesse’s conception, the Russian man rejects inherited ethics and morals, and even beneficent Alyosha represents an “amoral impartiality.” Man is, Hesse says, halfway between animals and higher consciousness; the former restrained through the process of civilization and domestication. The Karamazovs represent the fraying of the ties.
Hesse proceeds, ominously, to notice that the Germans in particular are more vulnerable than any European people to the temptations of “all those evils which one may regard in different ways, but which collectively signify the Karamazov.” While he was prescient in anticipating some of what would follow, he was in the end too sanguine in his hope that the spiritual dislocation could remain limited to that. “It is possible that the whole Downfall of Europe will play itself out only inwardly, only in the souls of a generation, only in changing the meaning of worn-out symbols, in the dis-valuation of spiritual values.” Alas!
In general, it is interesting to trace the mutual obsession between Russia and Germany: how preoccupied each was with the respective supposedly corrupting influences; how urgent the question of the national soul was felt to be. Many of the analyses seem a bit contradictory—Hesse actually inverts Dostoyevsky, for whom “everything is permitted” nihilism is a Western import for which Russian Orthodoxy is the cure—but there’s a striking intensity in the attempts to apprehend.
Most of all, I’m struck by how anachronistic it all feels today: a country’s writers investigating the national soul and the nation’s fate through the lens of foreign literature.
Which novels or works of art do we use to understand our contemporary issues? Should we be using such works? Do they inform or do they mislead? Today, the US worries a lot about China, but this mostly manifests at the level of trade balances, AI policy, and military prowess. We don’t seem to worry much about the spiritual force of Chinese ideals, and for all of the policy fractiousness, China continues to import and absorb American culture with enthusiasm that is mostly undimmed. There is a genre of jeremiad and cultural analysis in the US that rhymes a little with early twentieth century German criticism, but it today tends to be much more clinical, hinging around PISA scores, smartphones, lower fertility, and not around higher aspirations and ideals as such. So, to what extent should there be analyses of the national soul? And to what extent should they connect with major novels and works of art?
Franklin Miswa retweeted
Assorted things I've been mulling over regarding agents in the economy:
• Companies are in some sense the original superintelligence. It's often the case that they can use their amortized cognitive surplus to advance their interests against those of certain consumers: relative to the optimization capacity of companies, consumers can be inattentive, underinformed, irrational, etc. (Think, say, of some of the classic insurance upsells at the end of a booking process, which is typically priced substantially above what a regular policy would cost.) Herbert Simon introduced the idea of bounded rationality, and firms often end up benefiting from it. Thanks to personal agents, we will probably get somewhat more rational in how we engage with companies.
• How exactly will outcomes change? Well, certain kinds of price discrimination will work less well (how do coupons work if every agent hunts fastidiously for them?), and certain kinds of customer cross-subsidy will change (today, people who forget to cancel subscriptions subsidize those who don't). Taken across the economy as a whole, I'm not sure what the incidence of all of this will be.
• In corporate strategy, people have long debated the relative importance of distribution and product quality. Perhaps you've made something better, but does anyone know about it? Won't people just continue to buy the ACME Corp Mousetraps? Personal agents will, I think, act as a kind of structural subsidy for product quality. How would markets look different if individuals always spent at least 10 hours researching their purchases? On the margin, focusing on making a product better is, I think, going to become a more effective strategy for companies. This is good!
• It true, a corollary is that information about product quality will become more important and impactful. Today, most people have very limited ability to aggregate and integrate such data, but agents will have insatiable thirst for such signals. (It's often said that data is becoming more valuable because it helps in the training of models. That's obviously true, but I think there's a secondary way in which it's more valuable simply as a complement to cheaper intelligence.)
• A big question is whether agents will increase superstar effects (rational agents all settle on the same product) or increase dispersion (because everyone has slightly different tastes and preferences, which agents are good at eliciting, finally overcoming the artificial clustering we've been subjected to).
• Many internet companies have monetized demand routing, which is in turn often predicated on short attention spans. "I'll click on the first thing I see." This has led to some amount of inefficiency, as companies try to propitiate capricious ranking algorithms and incur various placement fees. It's not all deadweight loss (willingness to pay is itself a kind of signal, which is valuable to buyers), but it's not great. How will the nature and value of this routing change in a world of personal agents? I don't know the answer, but I think that the effects might be pretty big.
• Much of what I'm writing hinges on the assumption that personal agents will be on the consumer's side. I suspect that that will be the winning strategy, but whether it's true, and what it means to be true, involves a lot of other questions.
Taken as a whole, the market is a massively parallelized, decentralized, and highly imperfect value attribution machine, and, taking stock of all of the effects, it seems to me that the quality point may well be the biggest: that agents will change the nature of the backpropagation such that the rewards for better products increase. Maybe this is too optimistic, but I suspect (and hope) that companies that make things that they're proud of will feel that the universe is a little more partisan in their favor.
Every man is responsible for everything he does and for everything everyone else does.
My reco has always been #Thug Notes on YT.
Franklin Miswa retweeted
Li Lu at Columbia Business School's 36th Graham & Dodd event (Oct 5) 🎧
Value investing's six principles, AI as a tool not a god, a market split between a few hot names and many neglected ones, and compounding in markets and in life.
Full talk: youtu.be/FwDKCNfHHtY ❄️
Franklin Miswa retweeted
There are massive startup opportunities hiding in plain sight : every layer of the computing stack will need to be rebuilt for agents.
For the last few years, most of the focus has been on making enterprise software agent-ready: APIs, connectors, MCPs.
Now personal agents are forcing the same conversation for consumer products - e-commerce is an early example.
This is just the tip of the iceberg.
Now think about the rest of the stack:
Desktop and mobile OSes where agents are first-class users
Cloud infra built for agents to operate directly.
identity, permissions and security designed for thousands of agents acting on our behalf.
Interfaces designed for agent and human users or both working together.
If you’re looking for startup ideas, go through each layer of the computing stack and ask: what has to change when the primary user is an agent?
Franklin Miswa retweeted
Interesting report on Kenya pulse markets - declining production , growing demand and now importing (was wondering why there’s a US bean council in Kenya), plus missed opportunities for export. We play too much. #ProteinAgenda apps.fas.usda.gov/newgainapi…
Franklin Miswa retweeted
It is untenable for Kenyans to shoulder a 1.5% Housing Levy, 2.75% SHIF contribution, 6% NSSF contribution and PAYE that can reach 35% while still facing exorbitant school fees, soaring rents, high fuel prices and endless medical fundraisers.
If citizens are taxed more but must continue paying privately for basic services, then the fundamental question is: what exactly are their taxes delivering?
Taxation must translate into tangible public services, not simply a heavier burden on working families.
Genius. You get a follow. 🤣👍🏿👍🏿👏🏿👏🏿
Of course, that’s your contention. You’re a first-year machine-learning engineer. You just got finished readin' Attention Is All You Need, probably watched a Karpathy video too. So now you’re convinced everything is just transformers and scaling laws.
That's gonna last until next month when you discover convolution, and then you're gonna be talkin' about inductive biases and locality and how CNNs were actually incredibly compute-efficient for vision.
Then you're gonna read the FlashAttention paper, and suddenly everything's about IO complexity and SRAM and how FLOPs don't matter because the whole goddamn thing is memory-bandwidth bound.
That'll last until somebody shows you an MoE model, and then you're gonna be in here regurgitating DeepSeek, talkin' about expert parallelism and active parameters and how dense models are economically obsolete.
Then six months from now you'll write one shitty Triton kernel, look at an Nsight trace for the first time, and start telling everybody Python isn't actually the bottleneck because the GPU is asynchronous.
And by next year you're gonna be standing right here explaining to me that your 400-billion-parameter model is fast because you turned on CUDA graphs.
Franklin Miswa retweeted
Of course, that’s your contention. You’re a first-year machine-learning engineer. You just got finished readin' Attention Is All You Need, probably watched a Karpathy video too. So now you’re convinced everything is just transformers and scaling laws.
That's gonna last until next month when you discover convolution, and then you're gonna be talkin' about inductive biases and locality and how CNNs were actually incredibly compute-efficient for vision.
Then you're gonna read the FlashAttention paper, and suddenly everything's about IO complexity and SRAM and how FLOPs don't matter because the whole goddamn thing is memory-bandwidth bound.
That'll last until somebody shows you an MoE model, and then you're gonna be in here regurgitating DeepSeek, talkin' about expert parallelism and active parameters and how dense models are economically obsolete.
Then six months from now you'll write one shitty Triton kernel, look at an Nsight trace for the first time, and start telling everybody Python isn't actually the bottleneck because the GPU is asynchronous.
And by next year you're gonna be standing right here explaining to me that your 400-billion-parameter model is fast because you turned on CUDA graphs.
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models
“I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that.
“With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor.
“You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something.
“That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’
“I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
Franklin Miswa retweeted
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:
Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:
Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!
In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.
What Klopp achieved at Liverpool deserves to be remembered as one of the great managerial accomplishments of modern English football. 👏🏿👏🏿👏🏿

































