工程面试过程存在问题，人工智能作弊正在加速暴露这一问题。
我一直在思考，技术面试在过去十年几乎没有演变，而人工智能正在加速其崩溃。
我们仍在使用Leetcode风格的问题，这些问题几乎无法反映工程师的实际工作。候选人被期望刷50道以上的算法题才能获得面试机会，即使这份工作与算法毫无关系。现在，AI工具被用来完成家庭作业、进行现场编码环节，甚至撰写能够绕过ATS筛选的简历。
问题在于，这甚至不是传统意义上的作弊——这只是人们在利用可用的工具。更深层次的问题是：我们在评估错误的东西。既然他们在工作中也会使用AI，难道我们还需要在意他们是否使用AI来解决家庭作业吗？我们真的应该根据工程师在压力下是否记得如何反转链表来评判他们的能力吗？
我们陷入了一个容易被操控且难以辩解的系统中。有没有人看到公司在这方面做得更好？在人工智能时代，你们如何调整招聘流程？
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I've been thinking a lot about how technical interviews have hardly evolved in the last decade, and how AI is accelerating their collapse.<p>We're still using Leetcode-style problems that barely reflect the actual work engineers do. Candidates are expected to grind 50+ algorithm questions just to get a shot—even if the job has nothing to do with algorithms. Now, AI tools are being used to pass take-home assignments, do live coding rounds, or even write resumes that bypass ATS filters.<p>And the thing is, it's not even cheating in the traditional sense—it's just people using the tools available to them. The problem is deeper: we’re assessing the wrong things in the first place. Should we care if someone uses AI to solve a take-home if they’ll use AI on the job anyway? Should we really be judging an engineer’s ability based on whether they remember how to reverse a linked list under pressure?<p>We’re stuck in a system that’s easy to game and hard to justify. Has anyone seen companies doing this better? How are you adjusting your hiring process in the age of AI?