请问HN：人工智能在工作场所的效率
我工作单位的某个人花了三天时间给Claude写一个提示，以生成一份产品需求文档（PRD）。结果生成了12页精彩的Notion文档，里面有图表、架构定义、预期行为等等。我仔细阅读了所有内容，并对他选择的架构提出了一些问题，因为他走的方向与我们讨论的不同，这没关系。他的大部分回应都是“哦，那个可以忽略，Claude加上的”。
我们到底在做什么？这三天的时间本可以用来手动撰写PRD。虽然手写的可能没有前者那么精美，但至少是准确的！这正是我对大型语言模型（LLMs）的痛点，它们生成大量文本，看似高效，但真正的效率应该是用最少的文字来描述功能。
我真的不知道在这个领域该怎么办，这完全违背了撰写文档的初衷。
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Someone at my workplace took 3 days to write a PROMPT to Claude to write a PRD.
It generated magnificent 12 notion pages with graphs, schema defenitions, expected behaviors, what-have-you.
I read through all of them and raised some questions regrading the architecture he decided to go with, as he went on a different direction that what we discussed, and thats OK. Most of his responses where "oh just ignore that, claude added that".
What are we even doing here? The same 3 days could've been spent writing the PRD by hand. Sure, it might not have been so as polished looking as the former, but at least it was accurate! This is exactly my pain with LLMs, they make loads of text, where, they appear efficient. Where actual efficiency is having the least amount of text to describe the feature.<p>I truly don't know what to do in this area, this goes against the whole premise of writing things up.