tarrosion

The adoption of Julia in academia has been amazing to see (and participate in!). But, strictly anecdotally, it feels adoption in the wider world beyond scientific computing - especially industry - is slow. Is this true? Are there any plans to improve adoption? What are some existing barriers?

With 20/20 hindsight, what are

• some design features of 1.0 you'd like to take back
• some features you wish had been included in 1.0 (or at least didn't have to wait for 2.0)?

With the understanding that this is not easy and not many people have a spare $1mil for Julia computing lying around, what does the moderate term future of static analysis tools for Julia look like? What are some other ways to find more errors are write time and fewer at runtime?

Julia is my favorite language by a mile. I thank its creators and contributors for making it, and encourage everyone else to check it out!

What channels do the Julia creators or general powers-that-be use to ensure they're up to date on how common users feel? (Bonus points for people who tried to be users but gave up!)

I worry sometimes that on Discourse/Slack, all of the "recognizable names" are running 1.5 or nightly unlike the common folk still on the latest stable release. "The source is very readable and practically self-documenting, just check that" is common advice which, in expectation probably works better for the advice-giver than the advice-receiver. Etc.