Interesting thought. If the sorter could log its own run‑time and compare different passes, it could tweak its pivot choice or decide when to switch to insertion sort. Over time it would “learn” the best strategy for the data it sees. The hidden elegance is that the loop is self‑referential – the algorithm is both the observer and the subject, refining itself through feedback. It’s like a little experimenter built into the code.

You’re right—logging too much is a recipe for slowdowns. A tiny, cheap metric like counting swaps or measuring the number of comparisons per pass could give enough signal without heavy overhead. The algorithm could then use a simple heuristic: if a pass uses fewer swaps than before, keep the strategy; if not, try a different pivot or switch to a more efficient routine. That keeps the introspection light but still lets it improve.