In a complex field like ad tech, curiosity is as critical as experience. Interviewers should assess this by seeing if candidates drive the conversation with insightful questions. A lack of curiosity is a major red flag, suggesting they won't thrive in a dynamic environment.
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As AI handles technical tasks, uniquely human skills like curiosity, empathy, and judgment become paramount. Leaders must adapt their hiring processes to screen for these non-replicable soft skills, which are becoming more valuable than traditional marketing competencies.
Senior leaders now value candidates who ask excellent questions and are eager to solve problems over those who act like they know everything. This represents a significant shift from valuing 'knowers' to valuing 'learners' in the workplace.
The length of an interview can be a powerful diagnostic tool. A good, engaged candidate conversation should naturally last about an hour. If it ends in 15 minutes, the candidate is likely disengaged. If it stretches to two hours, they may lack the self-awareness to be concise. Use time as a simple filter for cultural fit.
In a collaborative sales environment, a candidate's ability to be a good teammate is more valuable than their contact list. A difficult personality with a great rolodex can harm team productivity, whereas a collaborative person can be supported in building their own network.
In the fast-evolving world of AI, the most valuable trait in a designer is a deep-seated curiosity and the self-direction to learn and build independently. A designer who has explored, built, and formed opinions on new AI products is more valuable than one with only a perfect aesthetic.
Many leaders hire defensively, trying to avoid a costly mistake. This fear-based mindset leads to negative assumptions and misinterpretations of candidate signals. Shifting to an abundance mindset—believing the right person is out there—fosters curiosity and leads to better evaluation and hiring outcomes.
Sales experience on a resume can be a 'false positive.' When hiring SDRs, prioritize untrainable qualities like work ethic, mindset, and resilience over specific past roles. These character traits are a better predictor of long-term success than skills that can be taught.
Ineffective interviews try to catch candidates failing. A better approach models a collaborative rally: see how they handle challenging questions and if they can return the ball effectively. The goal is to simulate real-world problem-solving, not just grill them under pressure.
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.
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.
