A brilliant post from the GLM-5.3 team on RSI (recursive self-improvement).

GLM-5.3 was already used to optimize the infrastructure that runs GLM itself, including production kernel and concurrency fixes. It helped triple GLM-5.3-Flash throughput on 100,000+ accelerators.

Their early self-improvement loop: the model improves its serving system, that system runs the model, and the engineering knowledge accumulates for the next optimization cycle.

Engineers still set objectives and boundaries, while the agent handled analysis, hypotheses, code changes, and experiments.

In one test, Prefill plus KV Transfer lagged Prefill alone by over 20%, and the agent traced the slowdown to the Python GIL, and releasing that lock cut the gap below 1%

Another kernel change reached a 1.71x speedup over the prior version by eliminating repeated FP32 normalization and gating work.