Can Agents Self‑Improve Their Harness? Designing a Self‑Harness Architecture
The article presents Self‑Harness, an engineering‑focused framework that lets AI agents analyze their execution traces, propose limited harness edits, and retain only those changes that pass regression tests, demonstrating measurable held‑out pass‑rate gains across three models while emphasizing reliable fact sources and staged adoption.
