I read about this notion often and the deeper truth behind it seems to be that abstractions are hard and they tend to be harmful if done wrong.
At the same time there are clear, obvious benefits of abstraction, which is why we don't typically write in machine code. This means that the goal is to create the right abstractions and not just throw our hands up in despair.
Using the popularity of Go as a metric is interesting, because it is a language that was designed in an environment with very large amounts of code and high fluctuation. It was targeted at the programmers that are replaceable cogs in a very large system, so it has to accommodate the lowest common denominator. One of the great features of the language is how easy it is to learn. (But they went too far, leaving out parametric polymorphism which is a feature they are now working on for years.)
Something that is easy to use and understand typically has a broader appeal. However, other environments want different things from programming languages. The appeal of a Lisp for example is its expressive power, programming expertise scales with the language more strongly. At the other end of the spectrum we have languages like Rust and statically typed functional languages that have very strong guardrails, stronger runtime guarantees can be made in exchange for agility. Again, certain types of programmers who face certain problems are drawn to these.
So creating good abstractions is both hard and desirable and programming languages are itself abstractions and facilitate the creation of abstractions. But what is a "good" abstraction depends entirely on perspective, which includes problems, domains and people. This is why languages like Lisp are not going away, languages like Go are popular and why there is plenty of diversity in language design.