SEA Architecture Guarantees Safety for Self‑Modifying AI Agents
The SEA framework limits an agent’s self‑modifications to a tiny steering adapter and a versioned harness around a frozen base model. Each change must pass an anytime‑valid gate that issues an auditable certificate within a fixed error budget, preventing regressions. Experiments on a 52‑instance SWE‑bench subset show performance lifts of +4 to +5 points on strong base models while guaranteeing safety.