Software developer. I care about clear docs, typed systems, and browser-heavy apps (maps, dashboards, long-lived sessions) where performance is as much architecture as hot loops.
Architecture notes for dense web UIs—Bonsai vs Leptos vs vibe.d, client/server split for auth and databases, creative-stack interop, and why some integrated suites feel faster than others—are in Dev-Centr docs: UI-heavy web applications (source).
GitHub orgs I own:
- antora-supplemental
- Cook-Systems-Team-Blue-Feb-2021-Ryan
- dev-centr
- dlang-supplemental
- FoodTruckNerdz
- formatte
- Linx-Photos
- openshellorg
Opinions are defaults, not absolutes—they keep my own projects consistent.
Systems programming
- Prefer D (or Rust) over C for new systems work: modules and safer patterns beat C’s global namespace and header friction.
- C vs D (Gemini share)
Scientific and numerical computing
- Prefer Julia over Python for serious numerical / ML work when you control the stack; Julia and D vs Java (Gemini share).
- I avoid leaning on Java for that space when the bloat and fragmentation in the ecosystem outweighs the gain.
Application and systems scripting
- Prefer D over C++ for application code; C++ vs D (Gemini share). C++ rant (YouTube) — same thesis, louder volume.
- For scripting-shaped tools that still talk to the OS, D is my default over Python when I want readable syntax without dragging a huge runtime (see scientific section for why Python is a weak default for me).
Math-heavy / functional style
Programming is math. Lisp and Haskell are the usual on-ramps if you want lambda-calculus-shaped thinking in performant languages.
I fork on the first date and commit to main.