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Eric Siu explains how to identify candidates who actually know AI. Ask to see their live work and projects in production, check their GitHub activity, and notice whether they use current models or outdated ones. Low usage is a red flag.
Eric Siu explains how to identify candidates who actually know AI. Ask to see their live work and projects in production, check their GitHub activity, and notice whether they use current models or outdated ones. Low usage is a red flag.
How do you screen for someone that's AI native, that's AI fluent? We ask people to show their work, whatever harness that they're using right now, but we want to see them work inside it. We want to see the projects that they have because once they open up their harness, you can see what their usage levels are. So are they maxing out on their usage? That's one signal that I look at. You can also ask them to open up their GitHub. I know it's not perfect, but you can see how active their GitHub is. I'll notice sometimes people aren't using the latest model or I'll ask them, hey, how come your usage of the latest model isn't there? And they'll be like, oh, you know, well, it just came out because it just came out. I'm just used to using like old model, which that reasoning doesn't make sense. My whole thing is how you do anything is how you do everything. If your usage is low and you're nothing you've built is in production right now and you're not using the latest models, that's how it's going to be working with you. And I don't know if I want to work with you if that's how you think.
