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Understanding a (complex) system wholly is a fantasy. We might pride ourselves in having a strong grip on how a whole stack of things work, but there are always layers of abstraction that we are relying, that we’d be lost without.

This is the fundamental nature of complex technologies: our knowledge of these systems will always be partial, at best. Yes, AI will make this situation worse. But it’s a situation that we’ve been in for a long time.

Potential interview tip embedded in this post — often an interviewer is looking for more than the “correct” answer to their question. They want to see your thought process or how you respond when you reach something like the edge of your understanding.

I remember talking to Brendan Gregg about how he conducted technical interviews, back when we both worked at Netflix. He told me that he was interested in identifying the limits of a candidate’s knowledge, and how they reacted when they reached that limit. So, he’d keep asking deeper questions about their area of knowledge until they reached a point where they didn’t know anymore. And then he’d see whether they would actually admit “I don’t know the answer to that”, or whether they would bluff. He knew that nobody understood the system all of the way down.