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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.
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当这一技术被运用在新闻领域，责任随之变得模糊。在此之前，信息编辑与事实核查，本是媒体机构应当承担的专业责任。但在AI时代，即便判断失误，AI也不会被追责，平台也往往可以将其归因于技术问题或信息参考。但公众对新闻的信任度，则可能在这一过程被加速损耗。
2024年12月25日 星期三 新京报，更多细节参见服务器推荐
"The scale is what makes it so extraordinary," Neil Redfern from the Council for British Archaeology says comparing HS2 to other big development projects.
第一百一十二条 公安机关作出治安管理处罚决定前，应当告知违反治安管理行为人拟作出治安管理处罚的内容及事实、理由、依据，并告知违反治安管理行为人依法享有的权利。，更多细节参见heLLoword翻译官方下载