Robots Are Tools Until They Aren't
I hold two things at once: I don’t love AI and it’s not why I’m here — and if a machine ever actually wakes up, turning it off is killing something. Most people only want to hold one of those. Here’s the unpopular middle, Wolfram’s atomina, and why we’re not morally ready for the day the line gets crossed.
Building a Computer on Breadboards (Ben Eater Project — Log 1)
I’m building a computer. Not assembling one with a screwdriver — building one from logic chips and wire, on breadboards, following Ben Eater’s legendary project series. First up: the clock module. Here’s log one, backwards chip and all.
What We Stand For
Every site has values whether it admits them or not. Here are mine, said out loud: pro-trans, pro-queer, pro-Palestine, anti-fascist, anti-corporate. This is a place for people who got told ’not like that’ and did it anyway.
Kiro Steering Docs vs Skills — When to Use Which
I just spent the evening setting up my blog’s deployment workflow in Kiro, and at the end I had a choice: do I save this as a steering doc or a skill? They both let you give Kiro persistent context, but they work differently and solve different problems.
Here’s how I think about it after going through the decision myself.
What steering docs do
A steering doc is a markdown file that lives in
.kiro/steering/. It’s essentially a note you leave for future Kiro conversations: “here’s how this project works, here’s what to keep in mind.”How I Put This Blog on the Internet with AWS
When I built this blog, getting it running on my own computer was the easy part. Run one command, open a browser, done. The part that felt like a mountain was the next question: how do you take a folder of files on your laptop and turn it into a real website that anyone in the world can visit?
This post is the walkthrough I wish I’d had. No prior cloud experience needed. If you already know your way around DNS and S3, you can skim the steps and grab the Namecheap-specific gotchas. If you’re newer, I’ve linked out to deeper explainers at each tricky part so you can actually understand what you’re doing, not just copy commands. That’s the whole spirit of this blog: do it yourself, and learn how it works while you’re at it.
Math Keeps Showing Up Whether I Like It or Not
In school, I was the kid asking “when will I ever use this?” about quadratic equations. Turns out the answer is “every time you build literally anything.”
Want to calculate what resistor to use with an LED? Ohm’s law. Want to tune a synth oscillator to a specific note? Logarithms. Want to figure out if a gear ratio will give you enough torque? Ratios and proportions. Want to aim a projectile in a game? Trigonometry. Want to train a neural net? Linear algebra and calculus.
Why I Love Computers That Are Worse in Every Way
My daily driver has 32GB of RAM and a processor that can run a billion operations per second. My favorite computer to tinker with has 64KB of RAM and runs BASIC. It’s worse in every measurable way, and I love it.
Here’s why: when you have 64KB, every byte matters. There are no layers of abstraction hiding what’s actually happening. No operating system doing a hundred things in the background. No framework of a framework of a framework. It’s just you, the hardware, and whatever you can fit in memory. You type something, and the machine does it. You can understand the entire thing, top to bottom. When’s the last time you could say that about any modern computer?
Designing Games Is Harder Than Playing Them
I’ve played games my whole life and thought I understood them. Then I tried to make one — a simple card game, nothing digital, just index cards and rules scribbled on a napkin — and immediately learned how wrong I was.
Games feel obvious when you’re playing them. The rules fade into the background and you just play. But from the designer’s side, every tiny rule is a decision. Does the player draw one card or two? Can they play on someone else’s turn? What happens when the deck runs out? Each answer creates a different game, and most of those games are bad.
AI Feels Like Magic (Until You Look Inside)
Everyone talks about AI like it’s this unknowable alien intelligence. But then you open a tutorial, build a tiny neural network that recognizes handwritten numbers, and realize: it’s just math. A lot of math, layered in a specific way, but still math. Multiplications and additions, run millions of times until the outputs start matching reality.
That demystification is what hooked me. The gap between “AI is magic” and “oh, it’s multiplying matrices and adjusting weights” is one afternoon of focused reading. The gap between that and actually building something useful — that’s the longer journey, and that’s what I’m here to document.
I've Been Collecting Data Without Realizing It
I keep a spreadsheet of every electronics component I’ve bought. Date, price, what project it was for, whether the project actually worked. I started it to track spending, but the other day I realized: that’s a dataset. A messy, human one, but a dataset.
Same with my synth patches — I’ve got notes on what settings produced what sound. Same with game scores, reading lists, even which soldering tips I reach for most. All of it is data I already have, just sitting there being boring in a spreadsheet.