Domain-agnostic metric-driven improvement loop, generalizing Karpathy's autoresearch. Use when you want an agent to discover what to measure for a project/goal, then run a keep-or-revert experiment loop that proposes changes, measures them against an objective, keeps wins, discards regressions, and records implemented improvements. Adapts to code perf-auditing, codegen, bug-finding, ad optimization, or any artifact + measurable objective + trial. Trigger: 'autoresearch this', 'find and implement improvements to X', 'discover metrics and optimize'.