Zero‑LLM Benchmark Shows Loop Engineering Isolates Failures
The author builds a tiny, deterministic Python benchmark that replaces the LLM with simple rules to isolate the contribution of the loop architecture. Across 300 random seeds the loop‑engineered controller completes an average of 3.3 of 10.3 branches, versus 0.4 for a linear baseline, proving that loop engineering can contain failures without any model involvement.