I loved reading this article. It was reasonably short to not make the reader lose interest. It jumped around in different domains to make a core point at the end about SREs managing complex systems. This gets even more difficult with the rate of change each of those systems has with coding agents. I don't know if I agree with the terms "synthesis" and "analysis" as the equivalent of global and local respectively, but it was a great read.
Thank you for taking the time to detail the differences - very educational and easy to read.
Congrats on the launch! I work in this space, and fwiw I strongly agree with the idea of A/B testing + continuous improvement. I have found that it is relatively easy to setup A/B tests, much harder for stakeholders to draw the right conclusions.
I have programmed in many languages over a 2 decade long career. C / C++/ C# / Java / Scala / Python / Rust / Go / lisp / JavaScript, and probably more that I have forgotten.
I agree with the framing that scaling a language is about scaling to more engineers easily.
Having said that, you can write scalably in any language, and write unscalably elsewhere. This is a bigger factor on scalability overall by far, than the language itself.
For example, I can make unmaintainable macro magic in rust. I can avoid dynamic pitfalls by using pydantic effectively in python.
Anyway, my 2c is speed to delivery of features matters more than scalability as defined here. Again, that depends more on technical components that have been invested in, rather than the selected language.
I am curious about your use case. Was it full text search? Did you get the database in wiki format, which you transformed to text?
The goal of my library is to enable quick data mining on wikipedia. Search is just one use case. As an example, you might want to build a content classifier to automatically categorize web pages into wikipedia categories (like politics, sports, etc). To go about doing this, you would need to parse wiki pages and extract features (like n-grams) for a particular category. The C library transforms plain wiki text to a parsed object, that you can use to extract what information you want. The only advantage is that it does this incredibly fast.
Yes I have, and that project would be a great fit. They already have a scala regex based lib though. My library is likely a faster and lighter alternative.