The purpose of quirky interview questions has evolved. Beyond just assessing personality, questions about non-work achievements or hypothetical scenarios are now used to jolt candidates out of scripted answers and expose those relying on mid-interview AI prompts for assistance.

A VC's relevance is now tied to their hands-on experience with modern tools. Limited Partners should add a new question to their due diligence: 'What have you built with CloudCode recently?' A lack of practical application is a red flag, indicating the VC may be out of touch with today's builders.

Dr. Fei-Fei Li states she won't hire any software engineer who doesn't embrace AI collaborative tools. This isn't about the tools' perfection, but what their adoption signals: a candidate's open-mindedness, ability to grow with new toolkits, and potential to "superpower" their own work.

YC has always prioritized founders over ideas. The new focus on AI coding proficiency deepens this philosophy. A founder's ability to rapidly iterate with modern tools is the key evaluation metric, as the original idea is increasingly seen as temporary and less important than execution velocity.

In AI PM interviews, 'vibe coding' isn't a technical test. Interviewers evaluate your product thinking through how you structure prompts, the user insights you bring to iterations, and your ability to define feedback loops, not your ability to write code.

LinkedIn has added 'vibe coding'—using natural language to direct AI to write code—as an official certification. This move legitimizes a new type of technical proficiency that doesn't require traditional programming knowledge, signaling a major shift in how technical skills are valued.

There's a growing belief in venture that experienced, second-time founders may be at a disadvantage in the AI era. Younger founders who grew up natively with new tools can move faster because they don't have to unlearn established, but now obsolete, ways of working.

Glean has updated its interview process to screen for "AI fluency" across all departments. They don't expect expertise. Instead, they test for curiosity and initiative by asking candidates how they've personally used AI, looking for a mindset that embraces new ways of working.

Since AI assistants make it easy for candidates to complete take-home coding exercises, simply evaluating the final product is no longer an effective screening method. The new best practice is to require candidates to build with AI and then explain their thought process, revealing their true engineering and problem-solving skills.