Comment by phillipcarter

Oh, I completely agree with using tools like this. For example, the latest models are very good at being passed a description of a problem and its inputs, expected outputs, and some sample test cases, and then generating a very diverse set of additional cases that likely account for some edge cases you might have missed. Hugely productive for things like that.

However, these same coding assistants lack so much! For example, I can't have a CSV co-located in my directory as a jupyter notebook file, then start prompting+coding without having also done a call to df.head to get those results burned into the notebook file. The CSV is sitting right there! These tools should be able to detect that kind of context, but they can't right now. That's the sort of thing I mean when we have a long way to go.