Interviews in the software industry have long been a flawed process, typically relying on algorithmic questions that don’t reflect real-world problem-solving. Candidates often train for these interviews by memorizing patterns, which creates an artificial pressure to perform. The arrival of AI has disrupted this system completely, allowing candidates to access perfect answers instantly. This has blurred the line between genuine skill and AI-assisted responses, making it nearly impossible for interviewers to trust what they see in a candidate. Many candidates now present flawless solutions without demonstrating any intermediate thought processes. They bypass the messy, iterative nature of real problem-solving, leading to suspicions about their authenticity. Interviewers are noticing changes in candidate behavior, such as jumping straight to polished answers or pausing awkwardly while waiting for AI-generated responses. This shift has led companies to reconsider remote interview formats, with some returning to in-person meetings in an attempt to regain trust and gauge true human reasoning. The article highlights the industry's struggle to adapt to these changes. With AI providing easy access to perfectly crafted responses, interviews are no longer effective at assessing a candidate's problem-solving abilities. Companies are grappling with how to rebuild a reliable interview process that accurately measures candidates without falling victim to AI's influence. The challenge lies in finding a way to differentiate genuine talent from those simply leveraging AI tools for an advantage.