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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更重要的是,钢铁企业的业绩确实出现了一些积极变化。,详情可参考下载安装汽水音乐
5年来,一系列“卡脖子”难题被攻克,一大批科技成果得以转化应用,中国在全球创新指数排名中跻身前十。5年来,各地因地制宜发展新质生产力,推动科技创新和产业创新深度融合,传统产业改造升级、新兴产业加速壮大、未来产业前瞻布局,发展的含金量、含新量、含绿量不断提升。
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