That being said, I still think gp's argument is flawed. We don't have examples of complexity that an AI can't overcome. Up until 2016 Go was a great example that was far to complex for an AI. Now there is no problem that an AI isn't expected, in principle, to outperform humans in with engineering effort. It is just a question of figuring out which problems it needs to outperform us in.
Engineering effort is not in shortage. There are many capable people on hand and modern AI is going to be a perfect force multiplier for engineering work. We're going to figure it out. Complexity is maybe a good argument that we've got a few generations to go, but life for a 2nd tier intelligence is not a well-resourced one. It could easily be like this world except with humans displacing orangutans in 2nd place to the smart species.
The fact that AI today isn't superhuman in every aspect is no real comfort. Post-AlphaGo humans don't seem to have any advantage that can be pointed to apart from having existed for more time. And computers move forward quite quickly.
It is like the BSD Kernel vs Linux - in many ways the differences are minor but they are different projects.
Evolutionary goals are not something that has to be aligned. Evolution isn't specific to organic life, it's an intrinsic rule of self-organizing systems. Viruses aren't alive, but they evolve. A clever stitch of self-writing code on a Pi attached to someone's TV may evolve without knowing or intending to.
What makes this dangerous now is the vast amount of energy input toward specific systems. Saying "there's surely not enough energy available for it to..." is false comfort. It's underrating the process of evolution.
As a poker analogy, if you just called the guy across from you because you think he couldn't possibly have more than two pair, you're wrong. You've bet into a full house.
[edit: Upon review, I think I've unintentionally gone 100% Jeff Goldblum Jurassic Park in this response LOL]