An Anthropic hiring manager says he stopped giving coding interviews because Claude is better at them and tells junior engineers that "hunger beats tenure"

Coding interviews are no longer an effective hiring tool for assessing candidate capabilities.

Felix Rieseberg, a hiring manager at Anthropic, announced he has discontinued traditional coding interviews for candidates. Rieseberg stated that AI models like Claude are now more proficient at coding tasks than human candidates, making the interviews redundant. He observed that successful engineers, regardless of their tenure, are those who can deliver impact, and that AI has shifted the landscape where "hunger beats tenure." Rieseberg advises junior engineers to focus on business impact, develop radical ideas, build prototypes quickly over a weekend, concentrate on one strong concept, and leverage their fresh perspectives. He noted that AI tools enable engineers with less experience to bypass traditional organizational hurdles and achieve significant results, citing an example where two new engineers at Anthropic rapidly developed a functional prototype for Claude Code's graphical interface, which shipped within eight days.

The obsolescence of coding interviews signals a fundamental shift in how technical talent is evaluated, moving away from rote problem-solving to a demonstration of AI-assisted productivity and business impact. Companies will need to develop new assessment methods that prioritize an engineer's ability to leverage AI tools for innovation and rapid prototyping, potentially favoring candidates with strong conceptual thinking and domain knowledge over those with deep algorithmic expertise. This change impacts how individuals prepare for and seek technical roles, emphasizing the need to cultivate skills in prompt engineering, AI integration, and a proactive approach to identifying and solving business problems.

This evolution in hiring practices suggests a broader market trend where AI's capabilities are reshaping job functions and required skill sets across the tech industry. Organizations that fail to adapt their recruitment strategies risk missing out on a new generation of engineers who can achieve significant output with AI augmentation. Consequently, educational institutions and training programs may need to reorient their curricula to equip students with the competencies needed to thrive in an AI-enhanced development environment, ensuring they can contribute effectively to companies that prioritize speed, impact, and innovation over traditional coding proficiency.