Peter Ludwig: evaluation

Transcript context

…Another thing I was thinking about is just in terms of, like, AI, adoption, does it change your hiring at least a little bit, or how do you, how do you sort of manage engineers, differently? Yeah. absolutely, it does. we, I think like every company in the Valley right now, are evolving our hiring practices because the skills required to be effective are changing so fast, right? you used to really select for just rote implementation ability and now it is more the AI engineer skill set, right? Where it’s like, yeah, how to implement, but actually-Just banging out code is no longer the core job, right? It’s, it’s actually knowing what questions to ask, knowing how to tie, how to tie together these different AI tools. And so the interviews that we give now I think are way harder than they’ve ever been. But we also allow, right, selective use of AI tools to solve the problems. And I think in that you start to see more of a bimodal distribution of engineers, right? You start to see like wow, there’s, there’s this subset of people that they really get it. Like they’re, they’re all in and they’ve, they’ve clearly invested the hours needed to learn these tools and how to be effective. And then there’s sort of the group of people that haven’t done that, and that the productivity gap is just enormous. And so we’re, we’re trying to obviously select for the people that are really into this. I first wrote the my AI engineer piece three years ago, and when I first wrote about it, I was like, “Actually, not everyone should be an AI engineer,” ‘cause I think there’s a there’s an extremist stance where well, every software is an engineer is an AI engineer. And my actual example of people who should not be adopting AI was embedded systems and operating systems, and database people. Are they adopting AI?…

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