[mechagodzilla]

Interns and new grads have always been a net-negative productivity-wise in my experience, it's just that eventually (after a small number of months/years) they turn into extremely productive more-senior employees. And interns and new grads can use AI too. This feels like asking "Why hire junior programmers now that we have compilers? We don't need people to write boring assembly anymore." If AI was genuinely a big productivity enhancer, we would just convert that into more software/features/optimizations/etc, just like people have been doing with productivity improvements in computers and software for the last 75 years.

[lokar]

Where I have worked new grads (and interns) were explicitly negative.

This is part of why some companies have minimum terminal levels (often 5/Sr) before which a failure to improve means getting fired.

[0xpgm]

Isn't that every new employee? The first few months you are not expected to be firing on all cylinders as you catch up and adjust to company norms

An intern is much more valuable than AI in the sense that everyone makes micro decisions that contribute to the business. An Intern can remember what they heard in a meeting a month ago or some important water-cooler conversation and incorporate that in their work. AI cannot do that

[alephnerd]

It's a monetary issue at the end of the day.

AI/ML and Offshoring/GCCs are both side effects of the fact that American new grad salaries in tech are now in the $110-140k range.

At $70-80k the math for a new grad works out, but not at almost double that.

Also, going remote first during COVID for extended periods proved that operations can work in a remote first manner, so at that point the argument was made that you can hire top talent at American new grad salaries abroad, and plenty of employees on visas were given the option to take a pay cut and "remigrate" to help start a GCC in their home country or get fired and try to find a job in 60 days around early-mid 2020.

The skills aspect also played a role to a certain extent - by the late 2010s it was getting hard to find new grads who actually understood systems internals and OS/architecture concepts, so a lot of jobs adjacent to those ended up moving abroad to Israel, India, and Eastern Europe where universities still treat CS as engineering instead of an applied math disciple - I don't care if you can prove Dixon's factorization method using induction if you can't tell me how threading works or the rings in the Linux kernel.

The Japan example mentioned above only works because Japanese salaries in Japan have remained extremely low and Japanese is not an extremely mainstream language (making it harder for Japanese firms to offshore en masse - though they have done so in plenty of industries where they used to hold a lead like Battery Chemistry).

[sarchertech]

> by the late 2010s it was getting hard to find new grads who actually understood systems internals and OS/architecture concepts, so a lot of jobs adjacent to those ended up moving abroad to Israel, India, and Eastern Europe where universities still treat CS as engineering instead of an applied math disciple

That doesn’t fit my experience at all. The applied math vs engineering continuum is mostly dependent on whether a CS program at a given school came out of the engineering department or the math apartment. I haven’t noticed any shift on that spectrum coming from CS departments except that people are more likely to start out programming in higher level languages where they are more insulated from the hardware.

That’s the same across countries though. I certainly haven’t noticed that Indian or Eastern European CS grads have a better understanding of the OS or the underlying hardware.