I prefer work simulation questions to leet code questions for tech interviews. I like to ask interviewees to write code that is similar to what we actually did was better than, for example, finding a successor node in a BST. At Trello, our tech interview would have you refactoring code in a way that is very common in iOS or implementing a UI from a spec. At Atalasoft, we had a lot of image processing algorithms in our code base, so I wanted to see you do something simple with pixels.

The other day I was thinking about my career and trying to remember if I ever did have to code a custom algorithm given a specification, and I did come up with a few examples. I’ve written before that my career happened to have a lot of math in it, and those same jobs sometimes also needed me to implement algorithms.

But more often, I chose algorithms (or knew that I needed to). I think that’s a more universally useful skill. It’s often the case that something just isn’t fast enough. A lot of published and common implementations of algorithms work well for the general case, but you may be able to make some assumptions in your specific application that allow you to do something better. Or your particular workloads might make a different set of trade-offs more appropriate.

To do this, it’s good to have broad knowledge of a bunch of choices, just so you know what techniques might be possible. These days, I think AI can help you a lot with this, but it helps to know what to ask for and when to ask for it.