夜雨聆风我在使用大语言模型（LLM）进行编程的时间越多，就越不为自己的职业担忧——即便它们的编码能力还在不断提升。
将 LLM 纳入我的工作流程，让我更清楚地意识到：我的工作远不只是机械地写代码。
我的工作是：识别那些可以用代码解决的问题，然后解决它们，再验证解决方案是否有效、是否真正解决了问题。
更先进的 LLM 也许最终能够完全处理“中间这一步”。它们可以在问题识别和结果验证这两端提供帮助，但前提是由一个既理解待解决问题、又懂得如何与 LLM 交互以推动问题解决的人来操作。
无论这些技术变得多么强大，它们仍然需要有人为它们找到要解决的问题、定义这些问题，并确认问题已经被解决。这本身就是一项工作——而其他人也很乐意把这项工作外包给专业的实践者。
而这，其实已经占据了我作为软件开发者大约 80% 的工作内容。
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原文：
The more time I spend using LLMs for code, the less I worry for my career - even as their coding capabilities continue to improve.
Using LLMs as part of my process helps me understand how much of my job isn't just bashing out code.
My job is to identify problems that can be solved with code, then solve them, then verify that the solution works and has actually addressed the problem.
A more advanced LLM may eventually be able to completely handle the middle piece. It can help with the first and last pieces, but only when operated by someone who understands both the problems to be solved and how to interact with the LLM to help solve them.
No matter how good these things get, they will still need someone to find problems for them to solve, define those problems and confirm that they are solved. That's a job - one that other humans will be happy to outsource to an expert practitioner.
It's also about 80% of what I do as a software developer already.
勇于拥抱未来是人类进步的赞歌
原文地址：https://simonwillison.net/2025/Jul/4/identify-solve-verify/
作者：Simons Willison
