请问HN：如何在大型代码库中提升人工智能的编码/调试能力？
我主要使用Github Copilot（公司支付费用）。在调试大型代码库时，有哪些特别有效的技巧吗？到目前为止，我只有一个MD文件，里面包含了一些关于我们代码库的一般信息，然后我就让它搜索特定的函数或文件，从那里开始。对于更大的代码库，还有其他特别有效的想法吗？特别是考虑到这个领域似乎在快速变化。
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I mostly use Github Copilot(paid by the company). Are there any particular techniques that are helpful in debugging large codebases?
So far I just have a MD file, with some general details about our codebase, and then I just ask it to search for a particular function/file and start from there.
Are there other ideas that are particularly helpful for larger codebases, especially since this area seems to be changing rapidly?