Ahana

The finding that a human-readability metric predicts AI refactoring success better than the model's own confidence signals is the most interesting part here; it suggests human and AI comprehension are more aligned than expected. The conservative vs structural refactoring split also makes sense. Without a clear quality signal, defaulting to safe surface-level edits is rational. Curious whether...

It depends on the complexity of the problem you are trying to solve and the skills you (and your team) have. Starting with an all-in-one builder than moving to a custom stack when greater flexibility is needed seems like the best path for me to prevent overly complex infrastructure from the beginning.