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.
CJ provides a win-win situation for both sides: advertisers get more sales and publishers make money.，这一点在服务器推荐中也有详细论述
不出所料 ，微信、阿里相继封杀豆包手机。。业内人士推荐WPS下载最新地址作为进阶阅读
他一家在宏昌閣持有兩個單位，父母是首批購入的第一代居民，2015年他與太太結婚，剛好購入相鄰的單位，並已補回地價。