Comment by jdmichal

I was part of an ACM programming team in college. We would review classes of problems based on the type of solution necessary, and learn those techniques for solving them. We were permitted a notebook, and ours was full of the general outline of each of these classes and techniques. Along with specific examples of the more common algorithms we might encounter.

As a concrete example, there is a class of problems that are well served by dynamic programming. So we would review specific examples like Dijkstra's algorithm for shortest path. Or Wagner–Fischer algorithm for Levenshtein-style string editing. But we would also learn, often via these concrete examples, of how to classify and structure a problem into a dynamic programming solution.

I have no idea if this is what is meant by "l33t code solutions", but I thought it would be a helpful response anyway. But the bottom line is that these are not common in industry, because hard computer science is not necessary for typical business problems. The same way you don't require material sciences advancements to build a typical house. Instead it flows the other way, where advancements in materials sciences will trickle down to changing what the typical house build looks like.