But, I think Julia is the closest thing to an honest-to-goodness lisp that has a prayer of mainstream adoption. I quite like Julia and think the community has leveraged the meta programming strengths of the language well enough to convince me to relinquish my love of minimalist lisp syntax.
I do wonder if the biggest risk to Julia isn’t that it’s not extreme / superlative in any dimension. If you want raw performance, Rust seems to be capturing the lion’s share of excitement among “new” languages. If you want meta programming, Julia still feels like a compromise compared to Scheme/Racket/Clojure/Common Lisp. If you want libraries, Python is still king. If you want stats libraries, R is still king. Julia is impressively good at all of those things... but it’s not good enough to be the most compelling of any of them.
Still, it makes me think that it may be time to dive in head first rather than dabble my toes as I've been doing for the past few years. I guess my main barrier at the moment is compiler / deployment story—it still seems hard to build a deployable binary that fits in, say, a Lambda layer as far as I can tell.
I guess the selling point is that being good at many things means you don't have to keep switching between all these languages, or glueing them together. Others have mentioned the composability benefits of this. But it also has a learning advantage, I think. You can incrementally learn to speed up the crucial piece of something. You can learn just enough metaprogramming to solve some problem you have.