SKDMy little systems lab / 2026
Open to work · probably building something
Game-playing agents · policy/value learning · native systems

I build agents that
learn, compete & ship.

Genseki is the main quest: a Hive engine lab where neural research has to survive real rules, real opponents, and evidence I can reproduce.

skd://research/system-map
LIVE
01 / GENSEKI02 / SELF-PLAY03 / NATIVE PORTS04 / EVIDENCE
GENSEKIHIVE + POLICY/VALUE
64DS-DXNATIVE PORT / #2
MK7 / ELOI#3 / #4 PAUSED
LAB / VERY ACTIVE43 PUBLIC REPOS4-ITEM QUEUE
Scroll for the rabbit holes
ACTIVE THOUGHT_01 — What if a Hive agent learned the position instead of memorizing it?

01 Current priority queue

Neural systems
with something to prove.

Four projects, in order. Genseki comes first; Eloi stays paused until its Kaggle program has an owner.

01B GitHub detour

More rabbit holes.

43public repos and countingSee the lab ↗
01

SM3DL-Recomp

A blunt future goal: recompile Super Mario 3D Land for native hardware. The repository is a marker, not fake progress.

Starts January 2027C++↗
02

HexQuoridor-3P

A recent experiment I keep around because “plan first” is still a technical result.

Useful failureJava↗
03

FIADA

A deterministic top-down racer with a recurrent neural driver. I learned from it; I am not pretending it is still active.

Completed chapterC++↗
04

TcSON

A configuration-language experiment that evaluated trusted source into deterministic JSON.

Archived toolingTypeScript↗
05

Synthiscape

A fast terrain generator with biomes, erosion, rivers, zoom, and pan in one Python file.

Procedural worldsPython↗
06

Short-Term Projects

The deliberately small builds I use to keep trying ideas without pretending each one is a startup.

Rapid experimentsSvelte↗
07

T_Caret

My earlier C++23 and Vulkan web-layout renderer experiment. Finished as a chapter, kept as evidence.

Archived rendererC++↗
08

Juliana

My archived attempt to rethink a few parts of Julia.

Archived languageRust↗
09

8j8k

I built an open-source multiplayer Svelte game around collaboration.

MultiplayerTypeScript↗
10

MSLASH

A tiny interpreter for a language I made up.

InterpreterPython↗
11

Flaky

What I built during OpenAI Build Week 2026.

Build weekTypeScript↗
12

Unspool

My Hack for Humanity 2026 project about mental wellbeing.

Civic techCSS↗
13

NORA

What I shipped for United Hacks V7.

HackathonJavaScript↗
14

Swordbattle Tweaks

My open collection of custom swordbattle.io mods.

Game modsTypeScript↗
15

Lordhank2

My multiplayer sword-fighting playground for quick experiments.

Game systemsJavaScript↗

02 Neural work, zoomed in

Questions I keep
losing sleep over.

3 rabbit holes open
R/01

Can an agent learn Hive instead of faking it?

Rho is my policy/value track: rules-grounded state, self-play evidence, training data, and experiments that stay separate from the Alpha engine.

Policy / value / self-play
R/02

A score is not an explanation.

I care about controlled opponents, frozen inputs, reproducible runs, honest failures, and knowing exactly why a model was promoted.

Evaluation / evidence
R/03

Can research survive contact with the whole system?

The model still has to meet a rules engine, search, a GUI, performance limits, packaging, and users. I like owning that entire path.

Research engineering

03 A little about me

Curious by default.
Way too into the details.

I started with Python, got curious about what was underneath it, and ended up in C++ and Rust building game engines, neural agents, native ports, and the infrastructure around them.

I will apply to Google DeepMind. Until then, I’m turning the gap between curiosity and research engineering into public, reproducible work.

01

Neural
agents

02

Engine
systems

03

Native
ports

04

Evidence &
reproducibility