The discourse around algorithms/data structures coding interviews (as opposed to domain-relevant pair programming coding challenges) does seem to be universally

The discourse around algorithms/data structures coding interviews (as opposed to domain-relevant pair programming coding challenges) does seem to be universally either about abolishing them or keeping the status quo. Then what about keeping those topics but improving the process? How about reducing other pain points? Such as: * Transparent rubrics about how an applicant is to be judged * Disclosure of what specific topics are to be tested or not, e.g. avoiding candidates stressing over dynamic programming problems only to be stumped by simple string manipulation * Actual training of interviewers so that they can be more collaborative and helpful during the interview * Disclosing to candidates just how many questions they are expected to answer during a round Companies want to keep their Leetcode question banks, fine. But the coding interview process are painful and scary to candidates not only because of any difficulty in problem content, but because of the apparent subjectivity and opaqueness of everything involved. Maybe the current process can be reformed and systemized a bit so neither party wastes their time. And another subject worth considering: how could current algorithmic pedagogy be improved? How do you take the teaching of runtime costs and complexity, specific data structures, and general principles like dynamic programming, and be able to solve specific problems like, say, merge intervals, without having seen such problems previously? Maybe there’s a layer of “now that you have a toolset, this is a good set of heuristics for matching your methods to actual problems.”