Ask HN: 在 AI 辅助编程时代招聘：什么有效？
5 分•作者: nitramm•4 个月前
我看到了 HackerRank (YC S11) 的招聘帖子（https://news.ycombinator.com/item?id=47667011），这让我意识到我不再理解如何有效地评估候选人了。
具体来说，我们正在从三个方面改变招聘：
> 任务：代码库上的真实世界任务，而不是标准的算法风格难题
> 评估：AI 流畅度、编排技能，而不是功能正确性
> 候选人体验：Agentic IDE（智能 IDE） vs 简单的代码编辑器
在“旧世界”中，你可以问多个问题，并通过答案来三角定位技能。现在看来，评估严重依赖于不断变化的工具和模型，这些工具和模型每个月都在变化。
所以我很好奇：
> 如今，哪些信号实际上与优秀的工程师相关？
> 如何设计不会随着下一个模型发布而过时的面试？
> 算法面试现在还有用吗？
很想听听最近改变了招聘流程或使用这种新方法接受过面试的人的意见。
查看原文
I saw the HackerRank (YC S11) hiring post (https://news.ycombinator.com/item?id=47667011) and it made me realize I no longer understand how to evaluate candidates effectively.<p>Specifically, we are changing hiring across 3 dimensions:
> Tasks: Real-world tasks on code repositories vs standard algorithmic-style puzzles
> Evaluation: AI fluency, orchestration skills vs functional correctness
> Candidate experience: Agentic IDE vs a simple code editor<p>In the “old world,” you could ask multiple questions and triangulate skill from answers. Now it seems like evaluation depends heavily on tools and models that keep changing month to month.<p>So I’m curious:
> What signals actually correlate with strong engineers today?
> How do you design interviews that don’t become obsolete with the next model release?
> Are algorithmic interviews still useful at all?<p>Would love to hear from people who have recently changed their hiring process or have been interviewed using this new approach.