I enjoy the paper as a starting point for discussions. However, given the varying definitions of technical debt, I think it is important to see additional elabo

I enjoy the paper as a starting point for discussions. However, given the varying definitions of technical debt, I think it is important to see additional elaborations and examples of real-world trade offs in production systems. Perhaps the best overall wisdom this paper tries to impart is this: build awareness, culture, and tooling around your ML systems, both upstream and downstream. Never stop exploring and improving. Relentlessly try to slim down your models, simplify your pipelines, and bring people together to talk about all kinds of dependencies.