We've using auto-research for harnesses and it's surprisingly powerful. It's amazing how many problems are easy to spot and fix from traces.

Few key things were required to get it working well: 1) let it read a heap of prod traces to spot real issues. 2) let it write it's own tools (example "loading context" goes from 20k tokens across 15 tool calls to 800 tokens and 1 call to session_context tool). 3) you need evals and val/test splits, it will reward hack. 4) you need proper tooling (synthetic users, synthetic tools) for it to be able to crunch for 12 hours and produce something. 5) you need the optimization target to be a reasonable size: not your 1M line codebase, but a lighter agent harness (pi harness, skill only, Kiln harness).