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.
Continue reading...
，更多细节参见Safew下载
Go to worldnews
* @param arr 待排序数组。业内人士推荐im钱包官方下载作为进阶阅读
和我预想的被动式接受AI不同，我身边的很多银发族是主动寻求AI的一代。。业内人士推荐搜狗输入法2026作为进阶阅读
Зарина Дзагоева