> What do you think is being measured? In a leetcode style interview? I think they are attempting to measure aptitude at solving algorithmic-style problems on

> What do you think is being measured? In a leetcode style interview? I think they are attempting to measure aptitude at solving algorithmic-style problems on a white board. I think they are indirectly measuring ability to perform under pressure, ability to vocalize while thinking, ability to function in unnatural environments, and either time since graduation from a CS major, or time spent practicing / gaming the system on leetcode (the premium feature even lets you see which questions your employer will likely ask). I think they should be measuring things like: ability to select good frameworks for a solution, ability to reason about how such frameworks are implemented at an algorithmic level, when and where to add an index or avoid a shuffle, how to debug, ability to write readable code, ability to coach more JR devs, ability to learn from more SR devs, etc. > Can you describe a utility function they are applying to that measurement? I'm not sure I can. I see this as a very multi-dimensional problem, so I think the utility of given skills would have to be considered in regards to the existing skills within the team. Honestly, I feel like "software engineer" has been split in two: R&D is done within the FAANGs (and maybe a few universities) and the results are open-sourced. Outside the FAANGs, something more like "software development" happens: FAANG libraries are glued together. _Very_ occasionally, you get a smaller company that has a legitimate business reason to write their own library or database or whatever, and an engineer is lucky enough to convince them of that. I'm also not trying to be snarky - I've been stuck on the latter side for most of my career, because I prefer to work in smaller companies, and as such have not had as much opportunity to practice "interesting code" as I would have liked. Perhaps this is due to my market (Denver), but I've also worked with companies in the bay, and I've seen a tremendous amount of over-engineering when off the shelf parts would have worked. So I'm legitimately curious: 1. Am I interpreting your questions correctly in that you think the ds & algo whiteboard interview selects well for desired attributes? 2. Do you solve those kinds of problems on a day to day basis? 3. If so, do you work at a FAANG? I don't mean to pry, so feel free to disregard any of those questions if your are uncomfortable answering them on a public forum, or message me privately. Thanks!