Only if your idea of using AI is to write a single prompt to generate everything you need. That's a terrible way of using AI though, because it doesn't work.

If you approach AI as an iterative process where you're architecting an application just as you would without AI, but using the tool to speed up parts of the process like writing one method or writing just the tests for the part you're building right now, then AI becomes a genuinely useful tool.

For example, I've been using AI today to build some metrics tooling, and most of what I did with it was using it to assist in writing code to access an ancient version of a build tool that I can't find the documentation for because it's about 30 versions out of date. The API is wildly different to the modern one. Claude knows it though, so I just prompt it for methods to access data from the API that I need and only that. The rest of the app is my terrible Python code. Without AI this would take me 4 or 5 times longer if I could even do it at all.