Many say they are still struggling with the memory of that day.
Anthropic’s prompt suggestions are simple, but you can’t give an LLM an open-ended question like that and expect the results you want! You, the user, are likely subconsciously picky, and there are always functional requirements that the agent won’t magically apply because it cannot read minds and behaves as a literal genie. My approach to prompting is to write the potentially-very-large individual prompt in its own Markdown file (which can be tracked in git), then tag the agent with that prompt and tell it to implement that Markdown file. Once the work is completed and manually reviewed, I manually commit the work to git, with the message referencing the specific prompt file so I have good internal tracking.
。关于这个话题，同城约会提供了深入分析
“灵师”回忆，早期的小天才好友圈里，大家围绕人文历史、原生家庭等话题进行交流，纯粹是为了交友分享。但点赞功能推出后，隐形等级制度逐渐形成，点赞数量高的用户开始“歧视”低点赞用户，圈子氛围变得浮躁功利。“大家不再单纯交友，而是互相点赞、功利互换，只为提高名气。”
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