AI-assisted development works better when the work is separated into roles. One capable, economical model can handle a large share of implementation. A stronger model—or simply a fresh review pass—can then inspect the result with a different goal: find mistakes, risks, and missing requirements.
That is not very different from a well-run human team. Development and review ask different questions. The first pass is trying to make the feature work; the second is trying to prove where it does not.
In one small web-export project, a review pass exposed three problems that the implementation pass had not emphasized: secrets belonged outside source code, untrusted input needed validation, and the generated output needed a clearer contract. Those were not failures of the idea. They were the normal kinds of issues that become visible when someone reviews from another perspective.
The human remains the project lead. I choose the requirements, decide when the evidence is sufficient, and take responsibility for what ships. AI gives that lead more leverage, but it does not remove the need for review.
Using different tools and roles deliberately is one way to get better quality without treating the most expensive option as the answer to every task.