Overreliance on intellisense does worsen your abilities, though, especially when dealing with complex packages and APIs. So does stack overflow. In my domain of data science and finance, it is VERY noticeable when someone doesn't actually understand how Pandas and Numpy work, for example, and how to write good vectorized solutions to their problems
Pandas is a very difficult api to use correctly and a huge swath of programs that the AIs have trained on was "programmed by accident" meaning people just typed stuff at it until they got the output they wanted.
To offset all the bad code, you would have to make a Pandas fine tune and/or ablate the bad Pandas from the weights.
I felt the same - have to relearn/lookup everything every time I went back to a project or wanted to do some operations that are simple to describe in SQL but I couldn't wrap my mind around e.g. using multi-indexed dataframes & aggregations properly. These days, I always jump to Polars instead of Pandas - much more intuitive and consistent API. Tons of props to Pandas for all that they did (and continue to do) in the data space, but their API did not evolve very well IMO.
I've also been wanting to play with Ibis[1] recently, but Polars has been sufficient for me.
What helped me with Pandas was a (very) short stint with array programming, specifically uiua. It gave me a good understanding of the possible operations on arrays.
You might be right that intellisense is to blame, but my suspicion is that some people are just worse at writing code and it isn't really about the available tools.
