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原始链接: https://news.ycombinator.com/item?id=43519938
在Hacker News关于“氛围编程”(vibe coding)和大型语言模型(LLM)在编程中应用的讨论中,用户分享了他们的经验和观点。 caust1c 发现LLM在编程方面已经超越了“恐怖谷”,在提供清晰的问题描述、约束条件和语言规范时,可以提高生产力。他们强调要审查所有LLM生成的代码。 bicx 询问了开发工具,提到了用于代码库分析的Windsurf。jawns 描述了一种有用的“树状”编程方法(树干、树枝、树叶),用于指导LLM并保持专注,同时将“氛围编程”与“心流”的感觉联系起来。 ashishb 将“氛围编程”比作社交媒体信息流,认为它结构较少,但需要更少的脑力,这可能会导致更广泛的采用。anthk 建议Prolog和Lisp非常适合代码重构和单元测试创建。 mattmcegg 认为理解AI生成的代码至关重要,将其比作过去理解从Stack Overflow复制的代码。
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I've personally found LLMs to have recently crossed the "uncanny valley" of programming for me, meaning that I'm much much more productive than without them.
I find that if you're really good at describing a problem and the constraints you want to solve, using a language it knows well (like Go) and following well known patterns in that language, you can describe thousands of lines of code and get accurate results.
Maybe this isn't vibe coding speicfically, but I actually review every line of code that the LLM puts out. It doesn't take long if you know what you're reading, and the LLM make a weird solution to the problem. Usually if I'm specific about how I want it solved, it does it well.
I also found it useful to say "Please tell me your plan to implement the solutions and ask me about any ambiguities that need clarification." In other words, don't make your own assumptions.
The results are incredible. Thousands of lines of code that maybe not stylistically like mine, but are structurally very accurate to what I'm looking for. Giving function/interface signatures and code examples works wonders.
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