Longreads + Open Thread

Longreads

• Paul Graham has a lengthy, thoughtful essay on how to do great work. Any writing of this nature will necessarily be somewhat abstract—"How to be a great mathematician" is a different essay from "How to be a great salesperson"—but it manages to be rigorous about its abstractions. For example: great work needs to break some of the rules, but great work also needs to be strict, meaning that one should insist on making things make sense. The key is to assume that "the rules" are imperfect, and that taking their underlying principles will lead to valuable evidence of internal contradictions in how they're implemented.
• In Construction Physics, Brian Potter tells the story of the development of titanium metal, from laboratory curiosity to indispensable material for aerospace and medicine. One minor detail that stood out: the first process for making pure titanium was discovered in 1930, in a home lab. Also worth noting: the government supported the industry in its early days, partly through tax incentives and partly by committing to buy the surplus and stockpile it. Market-based incentives like that can be a powerful tool: there was still an incentive to be the low-cost volume producer, even if that incentive was only partly provided by the market itself.
• Philo of MD&A has a great piece on what went wrong at General Electric. Scratch the surface of any academic discipline, and you eventually start asking philosophical questions. In this case, part of what went wrong with GE was that they had the wrong idea about what the company was for, and their management-to-numbers led them to misunderstand how much they benefited from trends they had nothing to do with (a company selling gas turbines, jet engines, medical equipment, and access to capital was tied to four different sectors that had above average GDP growth rates almost everywhere—so when they goosed the numbers to hit their quarterly goal, they wouldn’t realize that the real numbers were actually graded with a generous curve). It's a balanced piece, because GE did many things right, but perfectly implementing a sufficiently flawed plan can be worse than having no plan at all.
• Timothy B. Lee in Understanding AI covers how AI has impacted translators, a field where widespread cheap AI services have been available for years. There has been an impact on their per-word rates, but AI has also made some of them more productive. The piece doesn't dwell on it, but it's yet another instance where AI's benefits accrue to winners: making it cheaper to localize products means that market leaders in big countries can expand into more regions where localization costs are otherwise prohibitive.
• David Pierce in The Verge asks what happened to Google Reader. Google is exactly the kind of organization that would create such a product—a company that generated positive cashflow and was full of infovores who liked web-based apps—but was also the kind of company that could easily kill it. There's widespread agreement that the best companies will choose a focus, but determining the relevant scale on which to focus makes a big difference: a "customer-focused" company might continue to support a large number of relatively small-scale products (Reader had 30m users, which is big almost anywhere else but Google, especially since it didn't have a good monetization model). But a company that defines "focus" at the product level could easily conclude that Reader was just winning a category that would never be big, and let it die.
• In this week's Capital Gains, we cover the Capital Asset Pricing Model, which defines the relationship between risk and reward—and points to cases where it's possible to take on extra risk without being remotely well-compensated with possible reward.

Books

• Winner Sells All: Amazon, Walmart, and the Battle for Our Wallets: Walmart and Amazon (disclosure: I own shares of the latter) are very good at what they do, and both aspire to offer their services to consumers at the lowest available price. (Which doesn't mean doing everything for everyone at the lowest available price; Amazon ads and AWS egress fees certainly aren't priced to minimize gross margin!) Over the last decade, "what they do" has increasingly converged, which has led to a fierce retail duel. A running theme in this book, explored in more detail in this extended review for subscribers ($) is that Walmart's stores and distribution centers were an advantage in theory, but an obstacle in practice, since they meant that the company had to overcome more institutional barriers to sell online. Amazon, with less to lose, could make a bigger bet. Which raises an interesting question: at what point, and in what areas, will Amazon be the slower-moving incumbent bogged down by corporate politics?

Open Thread

• Drop in any links or comments of interest to Diff readers.
• The article on titanium points out that the metal was known for over a century before its first practical applications were discovered, but then had a sudden increase in usage and practical deployment. What else fits this pattern (besides, of course, neural networks!).

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