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.

A frequent hiring error is choosing candidates because you believe they possess "magical knowledge" from their specific background that will solve all problems. These hires often fail by rigidly applying an old playbook. Prioritize adaptable, curious problem-solvers over those with seemingly perfect but ultimately static domain expertise.

When hiring, a candidate with high passion for the subject matter but low experience is more valuable than an experienced candidate with low passion. Skills are teachable, but genuine enthusiasm for the mission is not. This framework helps resolve the common hiring dilemma between potential and polish.

Companies often complain about a lack of qualified candidates. The real issue is their failure to invest in developing the potential of hires who aren't 'perfect.' Talent development is a core organizational responsibility, not a luxury.

The most promising hires are often high-agency individuals constrained by their current environment—'caged animals' who need to be unleashed. Look for candidates who could achieve significantly more if not for their team or organization's limitations. This is a powerful signal of untapped potential and resourcefulness.

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.

Perplexity's talent strategy bypasses the hyper-competitive market for AI researchers who build foundational models. Instead, it focuses on recruiting "AI application engineers" who excel at implementing existing models. This approach allows startups to build valuable products without engaging in the exorbitant salary wars for pre-training specialists.

The "attitude vs. aptitude" debate is misleading. Hire the person with the smallest skill gap for the role. For complex roles, hire for intelligence (defined as rate of learning), as smart people can bridge any skill or attitude gap faster.