No, this post is not about a Burnout game. It’s about generative AI. Well, not strictly gen-AI, but Large Language Models. Well, not necessarily LLMs, but internet buzz around both of them. At first, I wanted to write a post on my thoughts about LLMs, constant deem of disclosure1, and how it affected me in the past year or so.

Earlier this year I published a guide on how to implement slopes in AABB collision resolution using bump.lua. The resulting system worked, but was a bit hard to use in-game and had a few issues, so I wouldn’t consider it a viable solution.

This year I decided to participate in the Spring Lisp Game Jam. It’s an annual event, where you have to make a game in any kind of lisp in a limited time, usually a week. I’ve been putting this away for several years, because every time the jam started I wasn’t ready to spend time on it, because of work or other duties I had at the time.

Recently (again, bored on a vacation), I started working on a game I’ve planned for a long time. I wasn’t satisfied with my existing implementations of a player controller1, so I started working on a new one. After a bit of fiddling around, I came to something I’m satisfied with, for now, at least, but while working on it, I wanted to add something I haven’t done in any of my projects yet - I decided to add slopes to my game.

This sure was a long year. Work stuff January began with bad news - the product I worked on was about to be closed. We weren’t sure how things would go, and a lot of people started to worry about their job security.

A sequel to Linux Music Players. I’ve been using Linux for the past 15 years and managed to solve almost all my problems with it during that time. But I had to switch to a Mac due to reasons related both to my work and my hobbies, so now I have to solve the same kind of problems, but in macOS.

Recently, I bought my first-ever MacBook. I’ve spent some time with it, and I gotta say - despite all that hot garbage that is thrown at GNOME for being an OSX clone, GNOME does the job better than I’ve expected, and certainly better than Apple. In some areas, that is.

I’ve been programming in Clojure for the last five years. I don’t write much about it here, largely because I use Clojure at work and rarely for hobby projects, so I don’t have much to share. Even today, the post will be more about Clojure tooling, rather than Clojure itself.

Some time ago, I was working on an HTTP library for Fennel. As a proof of concept, I added a module that implements a simple web server and wanted to experiment with it. The server can serve files from a directory using this simple handler:

Modern-day computing is fast. Incredibly fast! For most tasks, the feedback can be considered instantaneous. Even the slowest languages used in production, like Python, are considered fast enough for the majority of tasks, and if not, there are almost always faster alternatives you could choose from.