Forecasting the Generative AI Skills Product Teams Will Need Most in the Coming Year

Which generative AI skills do you expect to become critical over the next year, and why? ```hint Tie each skill to a shift For every skill you name, point to a visible change in how generative AI products are built or used that makes the skill matter more a year from now than it does today. ``` ### Clarifying Questions - Whose skills should the answer address: product managers building AI features, the engineers who build them, or knowledge workers who use AI tools every day? - Is the interviewer after hands-on skills such as evaluating model outputs and building agents, judgment skills such as deciding where AI fits, or both? - Should the answer cover the skills the candidate plans to build personally, or what a team should hire and train for? ### What a Strong Answer Covers - A clear choice of audience and a short, prioritized list rather than an inventory of buzzwords. - A reason for each skill grounded in a concrete trend in how generative AI is built, deployed or attacked. - Attention to what production AI demands beyond building features: measuring quality, security and safety. - The business view: where generative AI creates real value, and its cost, latency and reliability trade-offs. - Evidence of practice: how the candidate is building these skills and where they show up in product work. ### Follow-up Questions - Which skill on your list are you weakest in today, and what are you doing about it? - If models keep getting better at following plain instructions, which skill on your list loses value and which gains? - How would you test a PM candidate for your top skill in an interview?