Thanks. Reliable, to me, starts with not letting the same model review its own code. A model checking its own work tends to give itself a pass. Different models from different labs help: different training, different blind spots, they catch what each other misses. Same-model review alone isn't enough. And neither is skipping the deterministic checks layer.