I agree with you that for most software, verification was historically less of the requirement, however some software always needed to have abstract, mathematical correctness -- think military, medical, industrial automation.
While these areas were main premise of an article when it was written, I think the article really aged well into current time of mass AI/LLM deployment. It shows fundamental limitations of token based systems / symbolic reasoning that LLM espouses internally, while writing correct software. These limitations also apply to humans, however humans mental modelling, being not fully based on symbolic processing, have been historically shown capable of writing correct software systems, while AI/LLM systems have not been proven to be able to do that, and as article shows that with current token based technology it's unlikely they will ever be.
> however some software always needed to have abstract, mathematical correctness -- think military, medical, industrial automation.
I think those domains has more stringent requirement and a more focused usage, making the classes of inout narrower. A lot of software for B2B and B2C tries to be a kitchen sink and in the result get turned into a ball of mud. Some stuff should just be separate software.