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As someone who interviews and hires engineers I'm not even remotely convinced live code exercises lead to better hiring than any other signal such as a CS degre

As someone who interviews and hires engineers I'm not even remotely convinced live code exercises lead to better hiring than any other signal such as a CS degree. I remember when the the coding horror fizz buzz article came out and honestly things have just gotten worse since then. I always like to link the talk where the speaker mentions google hiring committee refused to hire themselves [0]. I suggest that this outcome isn't rare. [0] https://youtu.be/r8RxkpUvxK0?t=531 https://youtu.be/r8RxkpUvxK0?t=531

CharlieDigital 2y ago
Indeed; there are a wealth of better ways to find signals. One is look at any available public work (GitHub repos, OSS contributions), public writing (blog, Medium, etc.), past projects for fun or profit. I have hired candidates that ended up failing almost all of my technical assessment that turned out to be great engineers to work with because I could see in their responses a self-awareness and a curiosity about the question. These were engineers that were easy to train and bring up to speed. I saw a post on LinkedIn recently that really summarizes this sort of "intangible" in a more concrete way: https://imgur.com/a/l9Wql7A https://imgur.com/a/l9Wql7A My take is that low ego, curiosity, tenacity, humbleness, focus -- these tend to be better predictors of success in most cases. (But I can certainly appreciate that there are cases where you really want deep expertise in a very technically challenging aspect of a system). Conversely, I've seen many average and below average engineers end up in FAANG by dedicating time to studying leetcode challenges. The system is perversely broken when selection biases towards those that actively seek to game the system.
- gregors 2y ago
  Completely agree. This seems to me like common sense reasoning to me so I'm curious how the best companies in the world just seem to phone it in with leetcode.

CharlieDigital 2y ago

Indeed; there are a wealth of better ways to find signals. One is look at any available public work (GitHub repos, OSS contributions), public writing (blog, Medium, etc.), past projects for fun or profit. I have hired candidates that ended up failing almost all of my technical assessment that turned out to be great engineers to work with because I could see in their responses a self-awareness and a curiosity about the question. These were engineers that were easy to train and bring up to speed. I saw a post on LinkedIn recently that really summarizes this sort of "intangible" in a more concrete way: https://imgur.com/a/l9Wql7A https://imgur.com/a/l9Wql7A My take is that low ego, curiosity, tenacity, humbleness, focus -- these tend to be better predictors of success in most cases. (But I can certainly appreciate that there are cases where you really want deep expertise in a very technically challenging aspect of a system). Conversely, I've seen many average and below average engineers end up in FAANG by dedicating time to studying leetcode challenges. The system is perversely broken when selection biases towards those that actively seek to game the system.

gregors 2y ago
Completely agree. This seems to me like common sense reasoning to me so I'm curious how the best companies in the world just seem to phone it in with leetcode.