Longreads + Open Thread

Longreads

• Katie Baker reflects on Caroline Ellison's testimony in the FTX trial. This piece is a good entry in the genre of "Try to understand someone by reading everything they've ever written, and then read the things they say influenced them." In this case, the framing is looking at how the book Reminiscences of a Stock Operator influencer Ellison. The book gets recommended to beginning traders frequently, and does have some wisdom to share. On the other hand, the subject of the book, Jesse Livermore, ultimately lost all of his money and shot himself.
• Evan Osnos writes about the slow decline of China. The average level of optimism in an organization or a country is a leading indicator, since it determines whether the most effective people will be looking for upside or security. China had magnificent source of upside for the ambitious in the last few decades, but that's rapidly petering out. The article abounds with statistical and anecdotal evidence for both. On the anecdotal side, it's a bad time to be an independent bookstore owner or comedian in China. On the statistical side: "[I]n 2023, 1.5 million people sat for China’s national civil-service exam, up by half in two years." And more ominously "The popularity of securing a state job... has fuelled an unlikely fashion trend, in which young men display their aspirations with sombre suits, windbreakers, and even Communist Party badges, a vogue known as "cadre style.""
• Mathias Döpfner, CEO of Axel Springer, interviews Microsoft's Satya Nadella. (Disclosure: long MSFT.) This interview is a little bit more guarded than Nadella was earlier in the year on AI's potential to disrupt Google; Bing was briefly far ahead with inline AI answers, but now that's just a feature search engine users tend to expect. But the interview is also useful for its thoughts on corporate politics: Nadella talks about how his CEO tenure marked Microsoft's true switch from a founder-led company to more of an institution, and he is willing to say that the Ballmer years laid the groundwork for what Microsoft is today.
• Rafael Guthmann argues that the "Malthusian Trap" never existed. This is partly a definitional question—there was a correlation between fertility and crop yields up to the point where Malthus wrote his book—but there are plenty of other variables in the model. What this piece essentially proposes is something closer to a political Malthusian dynamic: there were areas where urbanization rose and GDP per capita was implicitly rising, too, but those were temporary. So perhaps escaping Malthus meant creating civilizations that could both build wealth and protect it.
• Rohit Krishnan reviews Brad DeLong's Slouching Towards Utopia. (The Diff also briefly reviewed it earlier this year.). DeLong's claim is that economic growth accelerated from 1870 through 2010 because of globalization, the joint-stock corporation, and corporate R&D labs. But wait! As Krishnan points out, all of those are much, much older than 1870, at least in some form, and it's hard to draw a dividing line where they suddenly reached peak effectiveness. (Corporations are a very interesting case here, because one of the big changes was accepting limited liability as a good norm. One reading of this is that the corporate form makes the most sense when it's ultimately backstopped by the state. "Limited liability" means there's someone who limits angry creditors from getting paid back by taking equity holders' personal assets.) The story is more complicated than this model, but the DeLong thesis is a great starting point.
• In this week's Capital Gains, we write about the seeming dichotomy between "real money" and "fast money" investors. They use different strategies, but fast traders are fundamentally trying to predict what slower-moving traders will do. Paradoxically, the easiest way for them to predict these psychological shifts is to understand changes in underlying fundamentals.

Books

• From The Bronx To Wall Street: My Fifty Years in Finance and Philanthropy: Leon Cooperman was Goldman's head of research and went on to run a successful hedge fund, Omega Advisors. He's also a very frequent CNBC guest, and has apparently gotten his urge to share stock picks out of his system through that venue; the book is fairly light on investment advice and case studies (though it does have a nice checklist for what make a good analyst, and spends time on one disastrous investment deal where his fund backed someone who, unbeknownst to them, planned to pay a massive bribe, but stole the money instead). The book is a good reminder that if you make a ton of money, towards the end of your life you'll be less worried about the incremental billion, and more worried about explaining your legacy.

Diff Jobs

Companies in the Diff network are actively looking for talent. A sampling of current open roles:

• A fund that backs growth companies in public and private markets  is looking for a senior engineer with experience building data pipelines. Experience with data science and/or experience developing frontends to display the results of models is a plus (SF).
• A company building the new pension of the 21st century and building universal basic capital is looking for fullstack engineers with prior experience in fintech. (NYC)
• A vertically integrated PE-backed cannabis company is looking for a data analyst with visualization experience. Excel wizards only! (Remote)
• An early-stage startup aiming to reduce labor costs by over 80% in a $100bn+ industry is looking for a part-time technical advisor with robotics experience; this has the potential to evolve into a full-time role. (NYC)
• A data consultancy is looking for a senior data scientist with prior experience in marketing data science and e-commerce. (NYC)

Even if you don't see an exact match for your skills and interests right now, we're happy to talk early so we can let you know if a good opportunity comes up.

If you’re at a company that's looking for talent, we should talk! Diff Jobs works with companies across fintech, hard tech, consumer software, enterprise software, and other areas—any company where finding unusually effective people is a top priority.

Open Thread

• Drop in any links or comments of interest to Diff readers.
• A theme in a few of these posts has been the specific question of what cause the industrial revolution and subsequent developments, and the meta question of how much this can be described as a single cause versus a complex process with multiple causes. What are some other historical shifts whose causes are misattributed?