Self-directed rabbit holes (rather than reading All The Topics)
Tyler Cowen: go down self-directed rabbit holes rather than reading the “definitive tomes” on broad-ish topics you’re curious about:
Let’s say you want to read some books on Venice, maybe because you are traveling there, or you are just curious about the Renaissance, or about the history of the visual arts.
…
I instead suggest a “rabbit holes” strategy, a term coined in this context by Devon Zuegel. Come up with a bunch of questions about Venice you want answered, and then simply do whatever you must to pursue them.
Current obsession: the Porsche 962 racecar. A spacecar GT/LeMans design. Bubble-esque cockpit, ground-effect body. It won some races. A great shape with the body panels on or off.
Personal choices outperform technology choices
This dinger at the end of Mattt’s WWDC wrap-up is everything:
Taking care of yourself — sleeping enough, eating right, exercising regularly — will do more to improve your productivity than any language or framework out there. Your ability to communicate and collaborate with others will always be a better predictor of success than your choice of technology stack. Your relationships with others are the most significant factors of success and happiness in life.
Problem solvers
We could be problem-solving technologists. We could avoid getting wrapped up in programmer elitism and tribal competition.
We might solve more problems that way!
We can still find joy in certain technologies. We can still ply our trade in solving meta-problems with those technologies while solving increasingly interesting problems with the technology.
We might have more fun and worry less about the hype treadmill!
We’d have more mental space to consider how we’re solving problems. We could communicate better with our teammates and customers.
We might consider whether the thing we’re building is right for the world we live in!
TIL that codemod is a (Python, target language agnostic) thing for doing large-scale find/replace refactorings in code bases, react-codemod is a tool for doing the same specifically for React APIs and idioms, based on jscodeshift for doing large-scale refactorings specifically on JS codebases. All come from Facebook. This is not at all confusing.
Craig Mod, on returning to the internet after forty days without:
Strong net connection burbling up above, smartphone in hand, put the right apps on the thing and we are all Odysseuses. Except we didn’t strap ourselves to the mast of our ship, we walked straight up to those beautiful singing bird-women and handcuffed ourselves to Thelxinoe’s silken leg.
zDog is 3-D rendering and animation with ~2k lines of JavaScript and only rectangles/spheres. I’m extremely impressed. This is the kind of playful but compelling technology I wish was more prevalent in the world.
If time is money, investing time in your tests can save money
Sam Saffron - Tests that sometimes fail. Fantastic advice on maintaining a test suite over time. A test suite is either an albatross or an asset, depending on the quality of effort your team invests. Via Ben Bailey.
“I don’t know everything, but I can learn anything.”
Rachel McQuater, On Becoming a Wizard: Strategies for Keeping Up as a New Developer:
The difference was that wizard developers perceived problems as artifacts of error by rational humans in otherwise rational systems, whereas I perceived them as mysteries beyond my control.
The damn dumbest smart kid I know
Partial explanation for smart folks, like Paul Graham or Mark Zuckerberg, making consistently bad predictions - The Peculiar Blindness of Experts:
In Tetlock’s 20-year study, both the broad foxes and the narrow hedgehogs were quick to let a successful prediction reinforce their beliefs. But when an outcome took them by surprise, foxes were much more likely to adjust their ideas. Hedgehogs barely budged. Some made authoritative predictions that turned out to be wildly wrong—then updated their theories in the wrong direction. They became even more convinced of the original beliefs that had led them astray. The best forecasters, by contrast, view their own ideas as hypotheses in need of testing. If they make a bet and lose, they embrace the logic of a loss just as they would the reinforcement of a win. This is called, in a word, learning.