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.
Депутат добавил, что в обеспеченных семьях наблюдаются проблемы с воспитанием. Он убежден, что «счастье мужчины в его деле, а счастье женщины — в семье».。关于这个话题，爱思助手下载最新版本提供了深入分析
，推荐阅读91视频获取更多信息
On top of this, I built a trivial state machine: a boolean flag representing whether the user was currently speaking or listening. When the system detected the end of speech, it played a pre-recorded WAV file back to the caller. When speech resumed, it sent a clear signal over the Twilio WebSocket to flush any buffered audio and stop playback immediately.，更多细节参见快连下载安装
但只要稍微理性分析，就会发现这根稻草，根本撑不起崩塌的大厦。
The regulations are always changing, as they differ from place to place.