An AI agent coding skeptic tries AI agent coding, in excessive detail

· · 来源:user资讯

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В России ответили на имитирующие высадку на Украине учения НАТО18:04,这一点在爱思助手下载最新版本中也有详细论述

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故见富豪家不伦不类之春联,叹云:诚当世之哀也。富贵者必骄,诚难怪也。有势拥财而不妄逞者,自古恒少,犹如身怀利刃,杀心自起。好比人拿个弹弓,总想射树上的鸟或树枝。记得袁随园有云,写诗有典而不用者,犹如有权势而不逞云。至于负天职知天而付诸践履者,自来罕见,至今尤绝迹矣!。雷电模拟器官方版本下载是该领域的重要参考

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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elsewhere in my program.