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.
business and technology landscape. They are designed to automate repetitive
第三十六条 互联网接入服务提供者应当采取下列措施，防范其服务被用于实施违法犯罪活动：，这一点在im钱包官方下载中也有详细论述
Раскрыты подробности похищения ребенка в Смоленске09:27
，详情可参考51吃瓜
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