According to a Business Insider report on July 8, 2026, software-engineering interviews are shifting from memorized algorithm drills toward AI fluency, project reasoning, and workflow evidence. Companies including Dropbox, Cisco, and AI startups are asking candidates how they use AI, while some recruiters look at GitHub and X to find engineers with visible proof of work. Some interview formats now allow AI tools or web search where older processes tried to block them. The shift matches a broader pattern where employers evaluate whether candidates can debug, validate, and integrate AI-generated work. HackerRank's 2025 Developer Skills Report says 74% of developers still struggle to land roles and 66% prefer practical coding challenges over abstract algorithmic tests. Candidates should treat AI usage as a skill to demonstrate, with stronger interview evidence including a clean GitHub project, a concise explanation of where AI helped or failed, validation steps for generated code, and trade-offs around testing, security, and maintainability. For data and ML roles, the same logic applies to notebooks, evaluation scripts, model cards, and deployment notes.