To differentiate hype from reality, seed investors should practice "vibe coding": daily, hands-on experimentation with new developer tools. This provides an intuitive understanding of current technological capabilities, leading to better investment decisions and inoculating them against unrealistic expectations.

Theoretical knowledge is now just a prerequisite, not the key to getting hired in AI. Companies demand candidates who can demonstrate practical, day-one skills in building, deploying, and maintaining real, scalable AI systems. The ability to build is the new currency.

YC's new optional application question is not just a technical test but a 'Rorschach test' for a founder's modernity. It assesses how deeply they've embraced AI coding tools like CloudCode, filtering for advanced, creative users over those with only basic prompting skills.

An AI-native VC firm operates like a product company, developing in-house intelligence platforms to amplify human judgment. This is a fundamental shift from simply using tools like Affinity or Harmonics, creating a defensible operational advantage in sourcing, screening, and winning deals.

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.

To build an AI-native team, shift the hiring process from reviewing resumes to evaluating portfolios of work. Ask candidates to demonstrate what they've built with AI, their favorite prompt techniques, and apps they wish they could create. This reveals practical skill over credentialism.

As AI makes the act of writing code a commodity, the primary challenge is no longer execution but discovery. The most valuable work becomes prototyping and exploring to determine *what* should be built, increasing the strategic importance of the design function.

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.

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.