nearly every dynamic language has trended towards this in the last 7-8 years. it's probably had the most profound effect in modern Javascript (typescript) and python. It's incredible how different production javascript and production python are compared to say, 2014 javascript or 2014 python.
JET.jl is a interesting project to do some error analysis through abstract interpretation: https://aviatesk.github.io/JET.jl/dev/jetanalysis/
more so than the goals of JET itself, the abstract interpretation framework it exposes should allow for TypeScript-like gradual typing.
This is important, imho, if Julia is ever to go out of a niche area because most of the rest of the world has already moved on to see the benefit that the improvement in application reliability that static analysis allows.
Not even close to "only thing". Dynamic language is a net loss of productivity once you reach a certain level of scale. Refactoring a codebase with millions of lines of code in a dynamic language is an absolute nightmare.
Opinions vary at what level of scale this happens. My personal experience is that once you hit just a few thousand lines of code that dynamic typing is a drag on productivity.
There's a reason things like TypeScript are increasingly popular.
I don't care what language first year CS students use. I care what languages I'm forced to deal with on a day-to-day basis!