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.
When it comes to software engineering, I’d like to think of myself as a generalist. Still, over my 12-year career, a major focus has been building scalable backends. I’ve worked at Amazon and Twitch to build out large-scale systems that support millions of users.，更多细节参见快连下载-Letsvpn下载
[2]《刘强东投资50亿，要在广东造游艇》时代财经。爱思助手下载最新版本是该领域的重要参考
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