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.
如果说当初Sora的出现，让世界看到了AI“无中生有”的魔力，那么Seedance 2.0则将讨论的焦点，从“能生成什么”拉回到了“如何精确地生成我想要的”。
，详情可参考Line官方版本下载
（四）核反应堆，是指为了利用核反应产生的能量、中子、核素等建设的装置。
# user = "pixel" # default