I don't think it is such a surprise. The ecosystems around Rails (for Ruby) and numpy/pandas/etc (for python) are orders of magnitude larger than you get in the

I don't think it is such a surprise. The ecosystems around Rails (for Ruby) and numpy/pandas/etc (for python) are orders of magnitude larger than you get in the modern languages. In Rails for example, adding an entire user management system (including niceties like password reset mails and must-haves like proper security for obscure vulnerabilities most people will have never heard of) is literally a single extra line in the gemfile and two console commands. In python the ML and numerics ecosystem are completely beyond anything another language has to offer at the moment, even more so when you compare the time to get started. In addition, "real" performance is often tricky to measure and may be irrelevant compared to other parts of the system. Yes, Ruby is 10-100x slower than C. But if a user of my web service already has a latency of (say) 200ms to the server then it barely matters if the web service returns a response in 5 ms or in 0.5 ms. Similarly for rendering an email: no user will notice their email arriving half a second earlier. Similarly for a python notebook: if it takes 1 or 2 seconds to prepare some data for a GPU processing job that will take several hours, it doesn't really matter that the data preparation could have been done in 0.1 seconds instead if it had been done in Rust. Especially for startups where often you're not sure if you're building the right thing in the first place, a big ecosystem of prebuilt libraries is super important. If it turns out people actually want to buy what you've made in sufficient numbers that the inefficiency of Ruby/Python/JS/etc becomes a problem then you can always rewrite the most CPU intensive parts in another language. Most startup code will never have the problem of "too many users" though, so it makes no sense to optimize for that from the start.