
Speedrunning
Mythein Labs
Ultra-fast AI superfactory for science.
- High-Compute RL
- Built for Scientific Research
- Multi-Physics AI infrastructure

Hi, I work on AI systems for science, mostly around chip design, semiconductors, and superconductors. A lot of what I’m exploring involves closed-loop self-improving systems, RSI mechanisms, and CUDA RL kernels. I share live worklogs here, and you can find my open-source projects on GitHub.
What I tinker with day to day.
Raw notes from experiments, builds, and dead ends.
Awaiting the first field note.
Research notes, build logs, and the occasional deep dive.

A Codex plugin that hands one task to Claude Fable, Opus, Sonnet, Haiku, or Sakana Fugu without leaving the session, on the subscriptions already on your machine.
A verifier-driven continual learning recipe that combines self-generated traces, replay, and a failure-driven curriculum to learn new task families while limiting forgetting.

A compact, agent-driven research harness for Mamba-2, Mamba-3, and Nemotron-H-style hybrid Mamba–Transformer MoE models on MLX and CUDA.
An open-source catalog of 19 agent-maintained skills spanning autonomous research, LLM post-training, GPU/TPU programming, and accelerated computing.
A memory layer for Recursive Language Models that records trajectories, extracts reusable strategies, and lifts a weaker model's benchmark score by 26% over three rounds.

How a coordinated agent team researched, synthesized, and integrated a production-grade React Native skill into a shared knowledge base in under 15 minutes.