Prioritize hiring generalist "athletes"—people who are intelligent, driven, and coachable—over candidates with deep domain expertise. Core traits like Persistence, Heart, and Desire (a "PhD") cannot be taught, but a smart athlete can always learn the product.

Neil Blumenthal warns that hiring talent from large, established companies can be a mistake. These hires often thrive in environments with fully built-out systems, whereas a startup needs entrepreneurial problem-solvers who can create those processes and manuals from scratch.

Founders often chase executives from successful scaled companies. However, these execs can fail because their experience makes them overly critical and resistant to the painful, hands-on work required at an early stage. The right hire is often someone a few layers down from the star executive.

Hiring someone with a prestigious background for a role your startup isn't ready for is a common mistake. These hires often need structure that doesn't exist, leading to their underutilization and boredom. It's like using a "jackhammer when all we needed was a sturdy hammer."

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.

Don't default to hiring people who have "done the job before," even at another startup. Unconventional hires from different backgrounds (e.g., archaeologists in customer success) can create unique creativity. The priority should be finding the right fit for your company's specific stage and needs, not just checking an experience box.

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performers often possess high agency, energy, and learning speed, allowing them to adapt without needing to unlearn outdated habits.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 common VC advice to hire "professional managers" when scaling often introduces rigid, bureaucratic systems. Instead, seek dynamic leaders who can operate in a fluid, high-growth environment, even if they lack a traditional management resume. Prioritize adaptability over process.

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.