Armed with a solid example for something that I thought I could work with, I got to work.
The problem
In general, property delivers value to people by doing something. It can do all sorts of things, but my first pass was to try to figure out the relationship between buildings and parking lots. Eventually I realized I needed to be able to “tag”:
parking lots
buildings
green space (useful)
legally required but otherwise useless green space (building setbacks)
streets
and maybe more some day.
I’ve got a working hypothesis that we’ve built our cities based off of some insane rules, one of which being “lets put surface parking lots everywhere.”
I contend that a surface parking lot close to an economically productive stretch of property (like a walkable downtown) is a very poor use of resources.
Lets look at a quick example from my home town, Golden, CO:
Hm. Doesn’t reveal too much, does it?
Maybe it would be nice if we could color-code the map by land use?
The solution
Lets take another look, through the lens of crowd-sourced GIS data:
In no particular order, I’m throwing down thoughts in three general categories:
What went well
What didn’t go well
What I might have done differently, were I to do it again
I believe there is a narrow window for me to capture this information well. As soon as I get a job, I’ll probably forget everything that didn’t go well, and if I were to never get a job, I’d forget anything that went well.
Went well
Learning
I’ve learned a ton, and my pace of learning has steadily climbed through Turing, as I build a more and more robust mental for existing information. It’s easier to add new information when the framework for the old stuff is strong.
I use Anki (a flashcard app) every day, so even on days when I don’t write any code, I’m still getting reps in of practice, and strengthening mental pathways. I’ve used Anki every day since Turing started, and have almost 1000 cards in my programming deck.
This is not meant to be read in isolation. Memorization is almost useless without doing work ahead of time to grasp the material. For the full context, start with Learning how to Learn
As a student at Turing, I’ve recently been thinking about learning how to learn, specifically in the context of software development.
I am a bit hyperactive when it comes to trying to learn new things. Over the years, I’ve done plenty of ineffective learning, and at least a little bit of effective learning. The good news is that even as I’ve not learned most of the topics I’ve originally set out to learn, I have learned a bit about learning. (Does this make it “metalearning”?)
I’m defining “learning” or “learning a topic” as to be able to rearrange or reorganize or reuse the idea or pieces of the idea in new ways to resolve unstructured problems I face.
I’m a huge fan of “a good workflow”. Makes you think better.
This is still under construction, but I’m fleshing out all the tools, tidbits, and other things that serve me well every day as I build my skills as a developer. It will always be a work in progress, but will hopefully serve others.
Last updated 06/02/17. If you’re curious, version history here
