If he's hiring new people they won't be engineers or the people that used to do engineering.
They'll be people that are better suited to writing English than code.
There is no fixed pie of work that AI is taking from us. In this circumstance, increased productivity caused the company to just make more stuff, not lay off people (or avoid planned hires).
It is a real world example of https://en.wikipedia.org/wiki/Jevons_paradox
It's that the benefits of that productivity won't go to the kinds of people that previously wanted to stay in engineering their whole career.
I'm not sure the Jevons Paradox applies because you're not just making engineering more efficient you're replacing it altogether with something much more commoditised.
People will gain from this but it won't be the same people.
It's an interesting example in that a switch from web/React -> native seems like Jevons paradox from the perspective a developer considering "amount of effort I'd need to put in"
But Jevon's paradox is about consumption of a resource increasing. The resource being "developer effort" but the new supply all running inside GPUs and dev machines. He actually says he decreased their server deployment by 90%.
So on net, did they basically deliver their users a much nicer but functionally equivalent app, which in total now consumes less resources / spends less $ into the economy? And then the $10T question is to what degree this is representative of AI's effect.