Coding interviews are completely different now (here's why)
AI Summary
Marina Wyss discusses how coding interviews have drastically changed in the era of AI, moving away from a single standardized format to a fractured landscape. She highlights insights gathered from a roundtable with 20 hiring managers at the Pragmatic Summit, revealing that the industry lacks consensus on AI's role in interviews, with some companies banning it, others allowing it, and many deciding case-by-case. Traditional LeetCode-style algorithmic questions are still common in 43% of assessments, yet a significant majority of developers find them irrelevant to real-world work. The video breaks down four distinct interview modes: the 'AI arms race' where companies ban AI and implement intense proctoring due to issues like AI-generated resumes and even different people showing up for work; 'AI-native' interviews where AI use is expected, often involving take-home assignments followed by live pair programming to assess a candidate's understanding and ability to verify AI output; 'project-based' interviews where a candidate's GitHub portfolio becomes the primary focus; and 'ML from scratch' interviews, specific to machine learning and data science roles, which still require implementing algorithms from the ground up. Wyss emphasizes that hiring managers are universally looking for 'T-shaped engineers' with product thinking, comfort with ambiguity, and strong communication skills. She concludes by recommending that job seekers directly ask recruiters about the specific interview format to avoid wasted preparation time and advises building real projects with AI while maintaining a baseline knowledge of data structures and algorithms.
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