AI Tools Help Grads Build Impressive Projects, But Can They Explain Them?
A hiring manager noticed a troubling pattern while interviewing fresh graduates: their resumes featured polished projects with modern tech stacks and AI-powered features, yet many candidates struggled to explain their own work when questioned. When asked about architectural decisions, API functionality, or failure scenarios, several applicants could not provide clear answers. The observation has sparked a broader debate about whether traditional project-based evaluation is still an effective measure of developer competence in the AI era. The author argues that fundamentals, problem-solving ability, debugging skills, and ownership of work should now take center stage in technical interviews. The post invites hiring managers and developers to share how they are adapting their evaluation processes as AI tools become more accessible to entry-level candidates.
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