The simple answer would be AI. That’s been the major change in the past year. I find it odd that everyone thinks Uber’s end game is automated cars, but no one seems to be talking about how tech companies end game is automated coders. LLMs are not even close, but what’s to say internally, they don’t have something that works. Or they have enough data to show they need fewer workers since they can leverage AI now.
I work at a FAANG, I can't speak for all companies divisions but I can pretty comfortably say that I have seen next to no evidence that AI tooling has become so productive that we "need" less engineers.
Actually it's somehow kind of the inverse, any AI related code has been subpar which has been putting a lot of stress on the core systems in terms of reviews and performance.
From my personal perspective, things overall seemed more productive pre ChatGPT for FAANG level companies.
Whats interesting is I think there might be a disconnect between AI capabilities and tech executives. I'm guessing executives believe AI will catch up to be good enough to multiply engineers productivity say 120% within the next few years - hence the 20% layoffs everywhere.
Maybe this will be the case. But for me on the ground its producing a lot more work. I now have to code review everything starting at a very high level working my way down and there's just so much MORE code now.
> Actually it's somehow kind of the inverse, any AI related code has been subpar which has been putting a lot of stress on the core systems in terms of reviews and performance.
My experience is that AI tooling just means engineers can do more, which means product managers want more… resulting in more work with the same engineering team…
We already had a revolution of automating coders, when Fortran first appeared. And a revolution of automating accountants, when a spreadsheet first appeared.
If anything, these revolutions increased the demand for programmers and specialists in finance. A person wielding a right automation tool is producing much more revenue, while demanding nearly the same salary; it makes sense to hire more of such people, as long as there is a market for the product or service your company provides.
The layoffs are a signal of this not happening. The AI is not helping enough to increase production and revenue per worker. Companies are out of new and efficacious business ideas. The companies don't know where to apply the intellectual / productive capability they have, so they are cutting it down, to save on its (substantial) upkeep.
A counterpoint would be: if you kept the same number of engineers and increased their productivity with AI, rather than keeping output the same and reducing the number of engineers, wouldn't you be producing more value overall?
