• This article is crossposted from IEEE Spectrum’s careers newsletter. • Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free! • We’d like to introduce Brian Jenney, a senior software engineer and owner of Parsity, an online education platform that helps people break into AI and modern software roles through hands-on training. • Brian will be sharing his advice on engineering careers with you in the coming weeks of Career Alert. • Here’s a note from Brian: “12 years ago, I learned to code at the age of 30. • Since then I’ve led engineering teams, worked at organizations ranging from five-person startups to Fortune 500 companies, and taught hundreds of others who want to break into tech.

Article Summaries:

  • The article discusses a growing trend in technical hiring: companies are now permitting and even encouraging the use of AI assistants during interview coding challenges. Major firms such as Meta, Rippling, and Google have adopted this approach, shifting evaluation from pure code correctness to how candidates interact with AI. Interviewers assess decision‑making-why a candidate accepts or rejects AI suggestions, how they balance AI help against potential errors, and how they explain their reasoning. The piece highlights that while AI can produce correct code quickly, it cannot articulate intent or take responsibility, making the interview harder for candidates who rely solely on AI. The article offers guidance on succeeding in these AI‑enabled interviews.
  • IEEE Spectrum’s careers newsletter highlights a growing trend in technical hiring: companies are now permitting candidates to use AI assistants during coding challenges. The article, featuring Brian Jenney of Parsity, notes that about 20 % of interviewees struggle to explain their code even when it runs correctly, underscoring the need for deeper understanding. Interviewers are shifting from judging correctness alone to assessing how candidates evaluate, modify, and trust AI‑generated suggestions. Major firms such as Meta, Rippling, and Google have adopted this approach, aiming to gauge a candidate’s decision‑making process rather than just their coding output.

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