The Lindy effect is ultimately a kind of momentum. If that's the case, it seems like it's not the language itself, but rather the 'contracts,' 'interfaces,' and 'standards' that survive longer than the specific implementations a language provides.

Looking at the examples of Lindy that the OP mentioned, they're mostly at the infrastructure level. That's probably because many systems have been built on top of them, and the cost of replacing them is high.

On the flip side, things with weak Lindy effects are likely frontend frameworks or specific libraries. CSS methodologies are a good example of that.

In other words, the deeper something is, the harder it is to change, and as long as that deep language and its ecosystem aren't replaced, it will persist. As a counterexample, Fortran comes to mind—it's still being used today. Fortran has also evolved to exist beneath NumPy and Julia.

Ultimately, I think the core isn't the Lindy effect itself, but rather how many people you can attract commercially, and how many jobs you can create based on that.

In that sense, I think the next-generation language will succeed when it's used to build new infrastructure, and when the cost of refactoring becomes exponentially high. Right now, something that's growing similarly strong is CUDA. Personally, I'm always waiting to see what that language will be.