Codex‑driven auto‑research slashes QR kernel time 232×
In GPU Mode’s auto‑research contest, I used OpenAI Codex to generate a batched Householder QR factorization kernel that outperformed the baseline by 232×. The workflow combined automated code synthesis, iterative prompting, and targeted profiling, turning what was a research‑grade bottleneck into a production‑ready speedup.