Post by Shuo Zheng

Hello, World! Today, I wanted to revisit my Google NYC software engineering on-site interviews (detailed in a previous post). While I walked away very happy about having solved the problems optimally, I left the loop with a nagging intuition that something was fundamentally misaligned. Reflecting on my engineering interviews, I discovered that my biggest mistake was stating my assumptions rather than asking clarifying questions. Later, the Google recruiter call confirmed it, but the accompanying feedback gave a precise name to the exact cognitive gap I was feeling: Mathematical Maturity (Curry-Howard Isomorphism). In his recent guide on How to Land a Frontier Lab Job (heavily-recommended), Vlad Feinberg (Google DeepMind Pretraining Area Lead) notes that this engineering maturity is paramount to frontier computer science. While getting rejected sucks, the diagnostic clarity is an absolute win. It shifted my focus away from the surface-level "LeetCode grind" and pushed me back to building from my roots in mathematics. If you are interested in gaining mathematical maturity, then I recommend MIT OpenCourseWare starting with 18.100A Real Analysis (by Prof. Casey Rodriguez) or 6.1200J Mathematics for Computer Science (by Dr. Zachary Abel, Prof. Erik Demaine and Dr. Brynmor Chapman). #GoogleNYC #MITOpenCourseWare