I recently started collecting email addresses using MailChimp for those readers who want to receive email updates when I post here. Given my relatively low frequency of posts these days, especially compared to my heyday when I posted almost daily, and given the death of RSS, such an email list may have more value than it once did. You can sign up for that list from my About page.
I've yet to send an email to the list successfully yet, but let's hope this post will be the first to go out that route. Given this would be the first post to that list, with perhaps some new readers, I thought it would be worth compiling some of my more popular posts in one place.
Determining what those are proved difficult, however. I never checked my analytics before, since this is just a hobby, and I realized when I went to the popular content panel on Squarespace that their data only goes back a month. I also don't have data from the Blogger or Movable Type eras of my blog stashed anywhere, and I never hooked up Google Analytics here.
A month's worth of data was better than nothing, as some of the more popular posts still get a noticeable flow of traffic each month, at least by my modest standards. I also ran a search on Twitter for my URL and used that as a proxy for social media popularity of my posts (and in the process, found some mentions I'd never seen before since they didn't include my Twitter handle; is there a way on Twitter to get a notification every time your domain is referenced?).
In compiling the list, I went back and reread these posts for the first time in ages added a few thoughts on each.
- Compress to Impress — my most recent post is the one that probably attracted most of the recent subscribers to my mailing list. I regret not including one of the most famous cinematic examples of rhetorical compression, from The Social Network, when Justin Timberlake's Sean Parker tells Jesse Eisenberg, "Drop the "The." Just Facebook. It's cleaner." Like much of the movie, probably made up (and also, why wasn't the movie titled just Social Network?), but still a good example how movies almost always compress the information to be visually compact scenes. The reason people tend to like the book better than the movie adaptation in almost every case is that, like Jeff Bezos and his dislike of Powerpoint, people who see both original and compressed information flows feel condescended and lied to by the latter. On the other hand, I could only make it through one and a half of the Game of Thrones novels so I much prefer the TV show's compression of that story, even as I watch every episode with super fans who can spend hours explaining what I've missed, so it feels like I have read the books after all.
- Amazon, Apple, and the beauty of low margins — one of the great things about Apple is it attracts many strong, independent critics online (one of my favorites being John Siracusa). The other of the FAMGA tech giants (Facebook, Amazon, Microsoft, Google) don't seem to have as many dedicated fans/analysts/critics online. Perhaps it was that void that helped this post on Amazon from 2012 to go broad (again, by my modest standards). Being able to operate with low margins is not, in and of itself, enough to be a moat. Anyone can lower their prices, and more generally, any company should be wary of imitating any company's high variance strategy, lest they forget all the others who did and went extinct (i.e., a unicorn is a unicorn because it's a unicorn, right?). Being able to operate with low margins with unparalleled operational efficiency, at massive scale globally, while delivering more SKUs in more shipments with more reliability and greater speed than any other retailer is a competitive moat. Not much has changed, by the way. Apple just entered the home voice-controlled speaker market with its announcement of the HomePod and is coming in from above, as expected, at $349, as the room under Amazon's price umbrella isn't attractive.
- Amazon and the profitless business model fallacy — the second of my posts on Amazon to get a traffic spike. It's amusing to read some of the user comments on this piece and recall a time when every time I said anything positive about Amazon I'd be inundated with comments from Amazon shorts and haters. Which is the point of the post, that people outside of Amazon really misunderstood the business model. The skeptics have largely quieted down nowadays, and maybe the shorts lost so much money that they finally went in search of weaker prey, but in some ways I don't blame the naysayers. Much of their misreading of Amazon is the result of GAAP rules which really don't reveal enough to discern how much of a company's losses are due to investments in future businesses or just aggressive depreciation of assets. GAAP rules leave a lot of wiggle room to manipulate your numbers to mask underlying profitability, especially when you have a broad portfolio of businesses munged together into single line items on the income statement and balance sheet. This doesn't absolve professional analysts who should know better than to ignore unit economics, however. Deep economic analysis isn't a strength of your typical tech beat reporter, which may explain the rise of tech pundits who can fill that gap. I concluded the post by saying that Amazon's string of quarterly losses at the time should worry its competitors more than it should assure them. That seems to have come to fruition. Amazon went through a long transition period from having a few very large fulfillment centers to having many many more smaller ones distributed more broadly, but generally located near major metropolitan areas, to improve its ability to ship to customers more quickly and cheaply. Now that the shift has been completed for much of the U.S., you're seeing the power of the fully operational Death Star, or many tiny ones, so to speak.
- Facebook hosting doesn't change things, the world already changed — the title feels clunky, but the analysis still holds up. I got beat up by some journalists over this piece for offering a banal recommendation for their malady (focus on offering differentiated content), but if the problem were so tractable it wouldn't be a problem.
- The network's the thing — this is from 2015, and two things come to mind since I wrote it.
- As back then, Instagram has continued to evolve and grow, and Twitter largely has not and has not. Twitter did stop counting user handles against character limits and tried to alter its conversation UI to be more comprehensible, but the UI's still inscrutable to most. The biggest change, to an algorithmic rather than reverse chronological timeline, was an improvement, but of course Instagram had beat them to that move as well. The broader point is still that the strength of any network lies most in the composition of its network, and in that, Twitter and other networks that have seened flattening growth, like Snapchat or Pinterest, can take solace. Twitter is the social network for infovores like journalists, technorati, academics, and intellectual introverts, and that's a unique and influential group. Snapchat has great market share among U.S. millennials and teens, Pinterest among women. It may be hard for them to break out of those audiences, but those are wonderfully differentiated audiences, and it's also not easy for a giant like Facebook to cater to particular audiences when its network is so massive. Network scaling requires that a network reduce the surface area of its network to each individual user using strategies like algorithmic timelines, graph subdivision (e.g., subreddits), and personalization, otherwise networks run into reverse economies of scale in their user experience.
- The other point that this post recalls is the danger of relying on any feature as a network moat. People give Instagram, Messenger, FB, and WhatsApp grief for copying Stories from Snapchat, but if any social network has to pin its future on any single feature, all of which are trivial to replicate in this software age, that company has a dim future. The differentiator for a network is how its network uses a features to strengthen the bonds of that network, not the feature itself. Be wary of hanging your hat on an overnight success of a feature the same way predators should be wary of mutations that offer temporary advantages over their prey. The Red Queen effect is real and relentless.
- Tower of Babel — From earlier this year, and written at a time when I was quite depressed about a reversal in the quality of discourse online, and how the promise of connecting everyone via the internet had quickly seemed to lead us all into a local maximum (minimum?) of public interaction. I'm still bullish on the future, but when the utopian dreams of global connection run into the reality of human's coalitional instincts and the resentment from global inequality, we've seen which is the more immovable object. Perhaps nothing expresses the state of modern discourse like waking up to see so many of my followers posting snarky responses to one of Trump's tweets. Feels good, accomplishes nothing, let's all settle for the catharsis of value signaling. I've been guilty of this, and we can do better.
- Thermodynamic theory of evolution — actually, this isn't one of my most popular posts, but I'm obsessed with the second law of thermodynamics and exceptions to it in the universe. Modeling the world as information feels like something from the Matrix but it has reinvigorated my interest in the physical universe.
- Cuisine and empire — on the elevation of food as scarce cultural signal over music. I'll always remember this post because Tyler Cowen linked to it from Marginal Revolution. Signalling theory is perhaps one of the three most influential ideas to have changed my thinking in the past decade. I would not underestimate its explanatory power in the rise of Tesla. Elon Musk and team made the first car that allowed wealthy people to signal their environmental values without having to also send a conflicting signal about their taste in cars. It's one example where actually driving one of the uglier, less expensive EV's probably would send the stronger signal, whereas generally the more expensive and useless a signal the more effective it is.
- Your site has a self-describing cadence — I'm fond of this one, though Hunter Walk has done so much more to point to this post than anyone that I feel like I should grant him a perpetual license to call it his own. It still holds true, almost every service and product I use online trains me how often to return. The only unpleasant part of rereading this is realizing how my low posting frequency has likely trained my readers to never visit my blog anymore.
- Learning curves sloping up and down — probably ranks highly only because I have such a short window of data from Squarespace to examine, but I do think that companies built for the long run have to come to maintain a sense of the slope of their organization's learning curve all the time, especially in technology where the pace of evolution and thus the frequency of existential decisions is heightened.
- The paradox of loss aversion — more tech markets than ever are winner-take-all because the internet is the most powerful and scalable multiplier of network effects in the history of the world. Optimal strategy in winner-take-all contests differs quite a bit from much conventional business strategy, so best recognize when you're playing in one.
- Federer and the Paradox of Skill — the paradox of skill is a term I first learned from Michael Mauboussin's great book The Success Equation. This post applied it to Roger Federer, and if he seems more at peace recently, now that he's older and more evenly matched in skill to other top players, it may be that he no longer feels subject to the outsized influence of luck as he did when he was a better player. In Silicon Valley, with all its high achieving, brilliant people, understanding the paradox of skill may be essential to feeling jealous of every random person around you who fell into a pool of money. The Paradox of Skill is a cousin to The Red Queen effect, which I referenced above and which tech workers of the Bay Area should familiarize themselves with. It explains so much of the tech sector but also just living in the Bay Area. Every week I get a Curbed newsletter, and it always has a post titled "What $X will get you in San Francisco" with a walkthrough of a recent listing that you could afford on that amount of monthly rent. Over time they've had to elevate the dollar amount just to keep things interesting, or perhaps because what $2900 can rent in you in SF was depressing its readers.
Having had this blog going off and on since 2001, I only skimmed through through a fraction of the archives, but perhaps at some point I'll cringe and crawl back further to find other pieces that still seem relevant.