He is probably comparing R to SAS (which are the two most popular statistical programming languages). SAS doesn't really have libraries, instead you buy additional packages from SAS, which are very reliable and well supported, but expensive.
My company shuns R (although I personally like it), primarily because of this issue. If we need to run a rare or uncommon statistical procedure, it is a lot easier to trust the SAS procedure, rather than an open source R package written by some grad student.
True,
Though if you need to run a rare or uncommon stat procedure, SAS is not likely to have it in the core, and then you are back to using what "some grad student wrote".
I am shunning SciPy and to a less extent NumPy for the same reason. I have reason to believe the developers are not experts in numerical linear algebra and some of the documentation also do not lend confidence.
My company shuns R (although I personally like it), primarily because of this issue. If we need to run a rare or uncommon statistical procedure, it is a lot easier to trust the SAS procedure, rather than an open source R package written by some grad student.