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.
Мир Российская Премьер-лига|19-й тур
，这一点在搜狗输入法2026中也有详细论述
当需求不稳定、价格下探、技术迭代叠加在一起时，这门生意的风险结构就变得复杂。
"But now I've been staring at it a lot more, and I think others will be joining us and staring at the Moon a lot more as there will be humans flying around the far side and that is just good for humanity."
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