What's troubling to me is that it doesn't seem to have much account for "drift" -- it sort-of just goes down a single path and tries to improve as it goes. Wha

What's troubling to me is that it doesn't seem to have much account for "drift" -- it sort-of just goes down a single path and tries to improve as it goes. What about structuring the agentic loop to do a simple genetic algorithm -- generate N children (probably 2 or 3), choose the best of the N+1 options (original vs. child A vs. child B vs. child C, and so-on) and then iterate again?