Agent watches training and rewrites optimizer source code live, matching hand-tuned recipes
cephaloform · x · 2026-10-23
A research thread introduces a "reactive optimizer": an agent observes training dynamics and rewrites the optimizer's source code mid-training. Across every language and image setting lacking a tuned recipe, it matches or beats the best one-shot recipe and self-guards against loss spikes and overfitting — suggesting optimization decisions may soon belong to agents. A reposter extrapolates: with Sol-level agents at 10k in/1k out tokens, how many processes get dynamically optimized? Will future software resemble biology — thousands of subagents living in Dockers — forcing us to hunt "cancerous Dockers" and micro-LLM viruses?
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