Eh, I’ve gotten over that. I’ve been using Claude recently on a personal project for a friend who wanted to take a known export file format and turn it into a list of good households for local political candidates to hit when knocking on doors. And I did that. But it’s been a while since I used pandas and numpy so I told Claude to swap out my loops for efficient code. And he did. Then, just for fun, I said, “Hey, since I am providing you with street lengths and long/ lats, use K means clustering to group high scoring houses into walkable routes and then plot the whole thing in a map from OpenStreetMap.” Five minutes later I had all of that. I could have done the latter, but doin any “real CS” thing would take me days. There’s not a bunch of value in me taking days to do something but there is value in knowing about K means clustering, knowing OpenStreetMap exists and having a feel for efficient code. Plus more high-level things like what good code does and doesn’t look like.
I 100% agree with you, but to play devils advocate, what would stop an LLM for telling you all about k means clustering and openstreetmap and everything when you ask about an efficient way to cluster deliveries on a map?
Also... One of the more dangerous things that can happen with Claude is this: it goes to implement your K means clustering (or whatever) and runs into difficulties, and actually builds something else, but calls it K-means, or slips it by you in a long conversation ("This is getting complicated, so I'll just..."). And it's only if you actually know the algorithm and review what it did that you can be confident in really publishing the work it produced into the public sphere.
