Computers Can Be Understood (2020)

I tried very hard to steer an old colleague away from their &quot;magical&quot; view of computers, because at some point I aggregated enough experiences and insights to agree with the article&#x27;s thesis. When working closely with hardware, there&#x27;s no way around breaking that magic. I would even flavor that how it all &quot;actually&quot; works physically is cool and magical (in a we can compose magic way).<p>It was interesting to connect some of the issues they asked for help with relate back to this magic-fication.

I had an experience similar to their Lambda one not that long ago. Needed somewhere to host a static Hugo site, went with Netlify, who marketed some vaguely specified special support and functionality for Hugo, and &quot;sync-to-git-repo&quot; functionality.<p>Ended up spending several hours digging through their docs and scattered code until it became clear to me that the hugo-stuff was just out-of-date and poorly stitched together tooling around hugo build that was made to run in CI, and there was no actual git functionality, just web hook APIs specific for GitHub&#x2F;GitLab&#x2F;Bitbucket.<p>Even leaving that aside and figuring out how to properly upload the ready-made static directory, which I got to in the process, would have taken its own fair share of detective work.<p>Whereas if I had treated it like magic, I could have just zipped it up and drag-and-dropped it in their web UI and be done in 2 minutes.<p>It still bothers me how they go to such great extents to make it as appealing and smooth as possible for the majority happy-path use case but end up making it extremely confusing to do what in the end turns out to be trivial. Even deliberately using technically incorrect terminology in documentation (which act as misdirection) just to align with common misconceptions.<p>I can&#x27;t seem to properly verbalize the eerie feeling I have but it relates to a trend leading to devs only using ready-made tools and APIs precisely on their abstraction level, dumbing down, total centralization of internet infrastructure, and an eventual ban on or unavailability of general computing for individuals.<p>&lt;&#x2F;rant&gt;

Perhaps I&#x27;m pretentious, but I&#x27;d question the quality of code written by someone who believes computers and software are magical mysterious systems.

At a fundamental level I understand that doping silicon turns rock into transistors upon which a computer is built. I still think it&#x27;s magic though.

I think this desire for understanding ultimately drives the resistance to systemd and the Linux&#x2F;BSD divide, and I think for good reason. There will always be friction between features and inherent simplicity&#x2F;ability to understand the system.

Haha, started thinking of Julia Evans while reading the post and then her name just popped up.

Strive to know as much as possible but delivery is different from achieving understanding. If your goal is to deliver knowledge is just another tool; it is not some magic answer to everything.<p>You have to find a balance where you know enough to know you have delivered.

Eh, sufficient complexity is indistinguishable from magic. No single human can understand the whole system of a modern computer in full detail. There is just too much stuff to learn for one lifetime. That&#x27;s why we build all those abstractions in the first place.

&quot;At core, computers are built on a set of (mostly) deterministic foundations, which follow strict rules at each tick of the clock. We built layers upon layers of abstractions upon those foundations, each of which, as well, behaves in a (mostly) reproducible and deterministic way based on the abstractions at the previous level.<p>There is no magic. There is no layer beyond which we leave the realm of logic and executing instructions and encounter unknowable demons making arbitrary and capricious decisions. Most behaviors in one layer are comprehensible in terms of the concepts of the next layer, and all behaviors can be understood by digging down through enough layers.&quot;<p>It is possible for deterministic systems to become so complex that they are unable to be understood. Physics and most natural sciences encountered this very dilemma early on, determinists posited that the world was a deterministic state machine and that for this reason the future could be predicted with enough study.<p>This philosophical and physical debate was resolved in the formation chaos theory, which proved that systems can become complex enough that this would be benefit of determinism vanished.<p><a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Chaos_theory" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Chaos_theory</a>