什么是上下文工程及其在实际系统中的应用

An AI code assistant generated a function to handle user uploads, which appeared correct, compiled successfully, and passed all tests. However, two days after merging, a high-priority bug was reported where files from premium plan users were being processed by the standard, slower queue. The generated code invoked the generic function `enqueue_job()` because it was unaware of the existence of a utility function `priority_enqueue_job()` for specific user roles. While the code was syntactically correct, it was contextually wrong for the system. This situation illustrates the ceiling that most teams hit when working with large language models (LLMs), where the model's reasoning ability is strong, yet it remains largely ignorant of the specific context of the system.