An AI agent is optimizing Elasticsearch. Engineers validate on improved performance
Coding agents are trained on tasks judged by LLMs and humans. Being convincing gets rewarded. That's a problem when the question is "did this get faster?"
One agent, two phases with different permissions. Exploration goes broad on a real workload and ranks opportunities; a human approves the benchmark and promotes one into a scoped exploitation task. A statistical acceptance rule the agent can't bypass decides whether it lands, and a human reviews before the PR.
All validated with Elasticsearch engineers in the loop