问HN：这是一个常见的LLM辅助开发工作流程吗？
我通常会为代理框架一个问题，并提出几个解决方案，然后询问它是否能列出这些解决方案的优缺点。我阅读输出结果，并根据这些结果做出最佳方案的决策。
接着，我会告诉大型语言模型（LLM）我认为的最佳逐步方法。它可能会提出一些修改意见，我会阅读这些意见，并选择同意或说“不要，我们就按照我提议的方式进行”。然后，我会要求LLM执行第一步。它生成代码，我会进行审核，最终我要么接受它，要么在接受的基础上进行修改，要么拒绝并告诉LLM我认为它没有走在正确的道路上。
我会这样反复迭代，直到问题得到我满意的解决。
我看到很多人谈论“氛围编码”，但我无法理解为何会完全接受模型的输出。不过，这种工作流程对我来说似乎非常有效。我可以说，我交付的代码质量很高，速度可能比以前快了10倍。
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I generally frame a problem for the agent and present a few solutions and ask if it can come up with some pros and cons of the solutions. I read the output and make a decision on the best approach based on that output.<p>Then, I'll tell the LLM what I think the best step-by-step approach will be. It may have some tweaks that I'll read and either agree with or say "no let's keep it how I proposed." Then I ask the LLM to execute the first step. It generates code, which I review, and I either accept it, accept it but make tweaks, or reject it and tell the LLM why I don't think it's going down the right path.<p>I iterate like this until the problem is solved to my liking.<p>I see a bunch of people writing about vibe-coding and I can't fathom wholesale accepting model output. But this workflow seems to work really well for me. I would say I ship high-quality code and maybe 10x faster than I used to.