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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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Not the day you're after? Here's the solution to yesterday's Connections.
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但也有很多人觉得近几年绿联飘了，质量不如以前好，价格却比以前贵了的声音。2024 年 1 月，绿联有批充电器不符合国标，还被龙华监管局罚了三千多。
:first-child]:h-full [&:first-child]:w-full [&:first-child]:mb-0 [&:first-child]:rounded-[inherit] h-full w-full。关于这个话题，爱思助手下载最新版本提供了深入分析