I disagree. Right now, feedback on correctness is a major practical limitation on the usefulness of AI coding agents. They can fix compile errors on their own, they can _sometimes_ fix test errors on their own, but fixing functionality / architecture errors takes human intervention. Formal verification basically turns (a subset of) functionality errors into compile errors, making the feedback loop much stronger. "Come up with what software we need better than us in the first place" is much higher on the ladder than that.
TL;DR: We don't need to be radically agnostic about the capabilities of AI-- we have enough experience already with the software value chain (with and without AI) for formal verification to be an appealing next step, for the reasons this author lays out.
It's getting better every day, though, at "closing the loop."
When I recently booted up Google Antigravity and had it make a change to a backend routine for a web site, I was quite surprised when it opened Chrome, navigated to the page, and started trying out the changes to see if they had worked. It was janky as hell, but a year from now it won't be.
I completely agree it's appealing, I just don't see a reason to assume that an agent will be able to succeed at it and at the same time fail at other things that could make the whole exercise redundant. In other words, I also want agents to be able to consistently prove software correct, but if they're actually able to accomplish that, then they could just as likely be able to do everything else in the production of that software (including gathering requirements and writing the spec) without me in the loop.