I’d boil it down thusly:
What do agents provide? Asynchronous work output, decoupled from human time.
That’s super valuable in a lot of use cases! Especially because it’s a prerequisite for parallelizing “AI” use (1 human : many AI).
But the key insight from TFA (which I 100% agree with) is that the tyranny of sub-100% reliability compounded across multiple independent steps is brutal.
Practical agent folks should be engineering risk / reliability, instead of happy path.
And there are patterns and approaches to do that (bounded inputs, pre-classification into workable / not-workable, human in the loop), but many teams aren’t looking at the right problem (risk/reliability) and therefore aren’t architecting to those methods.
And there’s fundamentally no way to compose 2 sequential 99% reliable steps into a 99% reliable system with a risk-naive approach.