No Ideas, but in Things

"No ideas, but in things" – by William Carlos Williams expresses an idea around learning that's only recently crystallized in my head.

I'm an auto-didact; most of what I know about programming is self-taught. One of the biggest challenges I face as a self-taught programmer is to gauge the depth of understanding I've built on a subject. Do I actually understand things, or just think I do?

Learning about both the Dunning-Kruger effect and impostor syndrome hasn't helped in the least: how do I distinguish between the two?

I have to admit that I don't believe most college exams – or MOOC assignments and tests – meaningfully measure understanding beyond a very superficial level ¹. Looking backwards at attempts at learning: android, systems programming, neural networks, databases, programming languages… the knowledge that's stuck around in my head is the knowledge that I directly applied and built something with.

Which brings me to the point of this note: I only trust that I've mastered a topic once I can apply it to build something tangible.²

Accordingly, here's a list of projects I'm over-optimistically planning to work on over the next several years to feel reasonably competent as a programmer (along with some resources as I accumulate them over time).

This is obviously incomplete, and also very loosely structured; I'll prioritize based on what complements my professional work, and simply follow my nose on other occasions.

The idea is to build something more robust than a toy, but not necessarily something optimized for millions of computers and performance. I'll open source parts of these, write about them in others; and possibly simply publish the end products of the rest.