AI speeds up the labor of building, but not the training, testing, and QA that make software trustworthy; that's exactly where the saved money should go, and where the "cheap because AI" crowd cuts corners.

Every tech cycle runs the same play of euphoria and overspend; what's genuinely different about AI is the speed and cost collapse, but what's unchanged is that the winners adopt the right thing and make it pay, not the most.

Custom software used to be a bet too big for small businesses; AI killed the price barrier and proof-first killed the risk barrier, putting enterprise-caliber work within their reach.

When you tell owners the price dropped, the sharp ones don't take the savings, they ask what more they can build for the same budget; the story of AI isn't cheaper, it's more value for the same spend.

A proof of concept should answer one question (will this make money?) on a hard, few-day effort cap; if it can't be proven cheaply and fast, the scope is wrong, so you never pay to build on a hunch.

AI didn't make code cheaper, it deleted the coordination overhead that made big projects expensive, which is why the savings compound the larger the project used to be.