Are coding agents making Go more attractive for production ML stacks?

I recently read Google’s post arguing that Go may be particularly well suited for AI-assisted software engineering: https://developers.googleblog.com/why-go-is-an-ideal-language-for-ai-assisted-software-engineering/ Their argument is that as coding agents generate more code, the bottleneck shifts from writing code to reviewing, validating and maintaining it. That made me think specifically about MLOps and production ML systems. Python is still the obvious choice for training, experimentation and most of the ML ecosystem. But a lot of production ML code lives around the model itself: serving, A