Aging of Prompt Engineering Techniques Across LLM Versions
It is shown that prompt engineering "ages" in a model-family-specific way: Newer GPT models exhibit diminishing or even negative marginal gains from structured prompting, suggesting that instruction-following and reasoning scaffolds are increasingly internalized, whereas Qwen models continue to benefit substantially from Few-Shot and CCoT.