Instead of focusing solely on a candidate's current skills, Figma's CEO looks for their 'slope,' or their trajectory of rapid learning and improvement. This is assessed by analyzing their history of decision-making and growth mindset, betting on their future potential rather than just their present abilities.

A key to OpenAI's innovation is hiring young talent who grew up thinking natively about AI. These individuals "hold the model weights in their brains," enabling creative breakthroughs. The team behind the video model Sora, for instance, has a median age in the low twenties.

As AI agents handle technical execution, the most valuable human skill becomes ideation. Replit CEO Amjad Massad predicts this will dissolve rigid corporate hierarchies in favor of adaptable teams of generalists who collaborate with autonomous AI tools to bring ideas to life.

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.

In a fast-moving environment, rigid job descriptions are a hindrance. Instead of hiring for a specific role, recruit versatile "athletes" with high general aptitude. A single great person can fluidly move between delivery, sales, and product leadership, making them far more valuable than a specialist.

A surprising Replit user base is CEOs who feel disempowered and delegated. They use the platform to quickly build and prototype their own ideas, which they can then bring to meetings to demonstrate feasibility and challenge the timelines of their engineering departments.

In rapidly evolving fields like AI, pre-existing experience can be a liability. The highest performers often possess high agency, energy, and learning speed, allowing them to adapt without needing to unlearn outdated habits.

The objective, high-pressure environment of competitive math contests cultivates a first-principles problem-solving mindset and intense competitive drive. This background proves to be a powerful, if unconventional, training ground for founders navigating the hyper-competitive AI startup landscape.

For cutting-edge AI problems, innate curiosity and learning speed ("velocity") are more important than existing domain knowledge. Echoing Karpathy, a candidate with a track record of diving deep into complex topics, regardless of field, will outperform a skilled but less-driven specialist.