Ask HN: Is post-training make AI models dumber?

An Ask HN post asks whether post-training, which improves benchmark performance and coding consistency, is making models worse in other ways. The author lists three observations, mostly about Claude: agents write vague natural language to avoid technical terms, produce spaghetti code that ignores encapsulation, and add workaround code rather than restructuring existing code. They ask whether this has always been the case or whether post-training is compressing outputs into predictable failure modes.