I‘m not sure I believe that when just yesterday, I ran a bunch of data analysis, simulation, and visualization based on a single csv and produced 5-10 decent matplotlib plots in a 90 minute back and forth between OpenAI canvas, vscode, python and jupyter. I didn’t believe some of my results and then discovered some problems of the dataset itself, so there was some „real work“ done in those 90mins.

I can say with certainty that I wouldn’t know how to wield matplotlib and pandas with such fluency in an hour, even though I am perfectly able to read the implementation and query for some relevant intermediate results to check my mental model.

Granted this is not the world’s most complex problem, but that is a good example of the domains where these tools are incredibly useful and productive already (I didn’t have to consult the docs even once). So in a way I think of LLMs as very good interfaces to the docs :)

I often feel that the UI aspect of new technologies is underappreciated. All our computers (even grep) are turing complete. This means software engineering is fundamentally a discipline of building better user interfaces that allow us to do whatever we want more easily.

I am always curious how other people experience these things as so useless :)