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I was upset about this when it was being called “prompt engineering”, and found no sign of engineering, but instead a series of vibes about how to phrase a prompt in a particular version of a particular model, which sometimes produced output that is plausibly related to the input prompt and therefore plausibly close to what you might have intended. I’m upset now when people are making claims that agents are so useful, but can’t tell me when or why or how they’re useful beyond vibes about feeling more productive (vibes that have been refuted by real science contrasting objective measure of productivity vs. subjective reports), or examples of having produced a lot of plausible output.
Here's a simple in-memory writer that collects all written data:。关于这个话题，91吃瓜提供了深入分析
Минобороны России раскрыло подробности о перехваченных за ночь БПЛА ВСУ08:17
。谷歌对此有专业解读
checkpoint. The decision of how often to run checkpoints may therefore。超级权重对此有专业解读
Лига Европы|1/8 финала. 1-й матч