Many of these are points I would agree with, except:
> [comparisons to] commenters in this submission
I wouldn’t make claims as to the level of accomplishment here, not least of which because I’m not willing to pick any one definition of accomplishment.
For example, I’ll avoid the temptation to conflate visibility and popularity with productivity.
> be cautious in criticizing their workflow unless I can demonstrate something better
Yes, making assessments based on comparisons against alternatives is important. And I’m inclined to give their approach attention and consideration, especially for people with their mindset and skillset. But generally, I’m not willing to grant any particular level of broader applicability for a given audience.
So I would reframe this discussion as a question: “Which of their practices are likely to work for [me/my team]?”
Like so many things in life, valid generalization is hard. Especially hard when no one knows the correct answer, so instead we assess better and worse. So, reinforcement learning. And RL in complex environments with large action spaces can be very data intensive!