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Thu. Oct 22nd, 2020

Digital Valhalla

Desert of the real

A grimoire of failures, lessons learned, and comments

4 min read

“I have not failed. I’ve just found 10,000 ways that won’t work.” – Thomas Edison

The over-arching theme here behind DiVa stems from a synergy of a few simple mindsets concerning the “occult” embodied in the following quotes:

  • “Any sufficiently advanced technology is indistinguishable from magic”
  • “Magic is the Science and Art of causing Change to occur in conformity with Will”
  • Satanism demands studynot worship

This will be expanded upon (ad-nausea, no doubt) at a later time, but for now, it will suffice to state that science, technology, and study are here, in the tradition of sincere alchemists of ages past, considered the bedrock of application. Study, not only of the principles and of world as-is, but also study of the results of one’s experiments and practices: success and, most especially, failures.

When embarking on the acquisition of a new skill in furtherance of leveling-up, there is a great temptation, especially in the fields of science, technology, mathematics, and engineering to equate “the beginner’s mind” with inadequacy – the words “I don’t know” tantamount to self-deprecation. Yet, that’s just the thing, no one comes out-of-the-box born with an innate understanding of, say, QFT, or multivariate calculus, or chemistry, or Node.js. There must always be a point where it all may just as well be Greek or arcane hieroglyphs in an ancient tome. Only with persistence, does it become clearer. Persistence automatically implies hours and hours of getting it wrong. Absolutely wrong! One should only be so lucky to get something wrong in a way that is obvious, that’s quickly rectified. There’s also the more insidious ways of getting it wrong: ways that seductively “seem” to work and become a habit until, many months down the road as new insights are acquired, the error becomes glaringly apparent and that much harder to admit. One sees they know less than they thought.

There’s also reaching a plateau of simply “not getting it” – this is especially true in mathematics and even programming. There’s always a limit – a sort of ring-pass-not – a level one gets stuck-on and often for many, many, months before that one day, for seemingly no reason at all, it “just clicks”. The quantum leap is made – one of several. How soon we forget the precipices past.

All through-out, one is advised to keep a note-book of sorts, possibly a folder on the file system, one containing a single document for each thing that, in the process of learning something new, one gets stumped on. Learning a new programming language, operating system, branch of mathematics, development platform, device configuration, or software package presents multiple opportunities for doing just that. Set out to learn, be prepared to spend hours – entire weekends – just getting something to work, and all along the way, making notes of the various errors encountered. These are the sacrifices the gods and daemons require most. Those notes become a book pretty quickly – a book of what not to do – and in time the intuition of how it should work develops. That expert who seems to just know everything there is to know about whatever it is, they got that way because they put in the work, and can attest “an expert in any field has made every mistake… twice”. These mistakes, when noted and reasoned-out verbally force the mind to think about the problem domain differently – not as an obstacle in the way of some goal – but as a thing in itself to be studied and explained.

A similar effect is achieved in commenting code. The comments don’t, in themselves, add to functionality directly. Early-on they seem superfluous, yet the simple act of writing down the thought process provides clarity – a sort of checks-and-balances between right and left hemispheres. Often the right hemisphere sees the problem the left is itching to rush into before it even happens. Commenting and taking notes on what is being done as it is being done is the single best way to understand the problem in ways that lead, ultimately, to asymptotic mastery of the problem domain. First, however, one must concede going-in that they don’t fully understand nearly as much about anything as they would like to – one is always, no matter how proficient, still learning, will always be learning, and as such will make mistakes. They must be both courageous enough to make them and above all, take notes. Indeed doing just that is what this very project, essentially is.

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