Andrew Ng lays out a hierarchy of engineering talent — including who's in trouble and who he refuses to hire (www.businessinsider.com)

Andrew Ng told the 20VC podcast that the AI era is exposing a clear hierarchy of engineering talent and that he now refuses to hire some types of engineers. At the top, he places seasoned engineers (10–20+ years) who adopted AI early and use it to dramatically accelerate productivity. Next are fresh grads who learned AI tooling through online and social communities — a scarce, highly sought-after cohort. Below them are experienced developers who haven’t updated their workflows and “code like it’s 2022,” whom Ng avoids hiring, and at the bottom are new CS graduates who never learned core AI building blocks — a group he says is “in trouble.” The remarks underscore a broader shift: AI tool proficiency (including AI-assisted coding and cloud/ML fundamentals) is becoming a baseline expectation, reshaping hiring, curricula and workforce risk. Ng’s view echoes wider industry moves — CEOs pushing mandatory AI adoption and debates about which age cohorts will adapt — and implies concrete technical requirements: familiarity with ML primitives, model-assisted development workflows, and cloud/AI infrastructure. The practical takeaway for employers, universities and engineers is urgent: update curricula and upskill teams to include core AI technologies or risk obsolescence as software engineering performance benchmarks rapidly change.