I work in machine learning research: training loops and loss functions are incredibly repetitive and pattern filled, highly represented in the code the LLMs are trained on, and typically short. They are exactly my intuition of simple code that LLMs would work well on.
With respect, having trialed these tools on pretty large ML codebases it's very much most folks' experiences that they're not very good across the board.
Training loops, sure... those are pretty much straight pattern recognition w/ well-represented APIs. But more broadly? Not so much.
I didn't say it cannot work well on anything other than greenfield web projects. I said it would probably be best at those as those have the most training data available. It can work well for your use case and still fit the pattern I laid out