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.
Что думаешь? Оцени!，详情可参考Line官方版本下载
。旺商聊官方下载是该领域的重要参考
We learned last year that Block had developed an AI agent called "codename goose" for interacting with LLMs. Leadership is clearly putting high expectations on that project and any other in-house tools to fill the shoes of thousands. "intelligence will be at the core of how the entire company works. How we make decisions, how we build trust and manage risk, how we build products, and how we serve customers," the shareholder letter states.，更多细节参见safew官方版本下载
（五）主动投案，向公安机关如实陈述自己的违法行为的；