plourens

My optimistic take on literature, compared to code, is that what writers produce is what is exactly consumed. The medium stays the same. The implementation choices of writers, like syntax, matter deeply to how the text resonates with a reader.

Code, on the other hand, is not consumed by end users in the same way. It compiles and turns into applications, which are then used. So users of applications are less scrupulous about what the code looks like, what language was used, and so on.

Indeed there are people who don't contribute to the community. Or maybe they can't find a publisher. I'm sure there are brilliant things written which will never find an audience.

But the broader point, in agreement with the article, is that the existence of fiction depends in part on extrinsic motivation (e.g. publishing, finding readers) and a community of intellectuals engaging with one another through their work. If everyone decided to stop seeking readers all of a sudden, the field would die and become a museum (mausoleum?) of former thinkers.

"Private intellectual activity that is sustained, complex, and long-term requires an external intellectual community to provide material and motivation, like fuel and oxidizer."

Aside from programming, one of my main interests is reading and writing. I think that literary fiction proves what the author is saying above. Even the most reclusive, private authors (Thomas Pynchon, Cormac McCarthy, etc.) actually published their work. They contributed to the community and took part as readers. Literature is always in conversation with itself. And although literary fiction may seem not to have the sway it once did in society, it is flourishing among the people who care about it (like me).

My thoughts aren't fully formed, but I find it interesting to situate technical pursuits like software engineering with humanities. And anyway, I've always felt that programming is both a science and art.

Former teacher here. Your example of the USSR is a good one to demonstrate the importance of a broad base of knowledge. In order to actually understand what "the Soviet Union collapsed" means, you need to know facts about what precipitated the Cold War. What communism means, what democracy means, and so on. Where Russia is on a map, and what "satellite" countries are. These are all concepts, too, but more atomic that build to the bigger idea.

Any "concept" is composed of interrelated facts, all the way down.

You hit the nail on the head. It sounds silly to say, but it simply is useful to know things. And to know things, you "memorize" them. More specifically, you build neural pathways as the information becomes better known to you, and which can be activated quickly. This is why I maintain a massive Anki deck for anything I find curious and want to remember, inspired by Michael Nielsen (https://augmentingcognition.com/ltm.html) and others.

Even if AI is very powerful, it is very obvious that someone actually knowledgable in a given domain can leverage AI more usefully than someone without that base of knowledge. And to be actually knowledgeable, as opposed to vaguely familiar with terms, takes significant effort over time. Luckily we have tools like spaced repetition that make that effort easier.

The last thing I'd add is that it's useful to know lots of things in various domains. Much like an LLM, our brains draw connections between disparate things which we know well, in the process of diffuse mode thinking.

If I recall correctly, in The Pragmatic Engineer, this was described simply as "provide options, not excuses" and is a critical way of building credibility.

Sounds right to me. As AI has picked up, I have found myself drawn to resources that (I hope) help improve my taste and judgment not only of code but also of overall software design. The lessons in Code Complete, for example, have been helpful to me in thinking about managing the complexity of a codebase. It was useful before, too, but perhaps even more so now.