| I run engineering for a venture backed AI-first startup and we use Ruby/Rails. For us, it made sense to leverage one of the best domain modeling and ORM frameworks out there. Most of our inference is http calls to foundational models, but we can still fine tune and host models on GPUs using Python. Inference matters, but part of building an effective user platform are the same old SaaS problems we’ve had before, and Rails just works. Inbound and outbound email done in a day. Turning an OCR’d title from ALL CAPS into Title Case is one method call and not a whole custom algorithm, etc. A lot of people seem to think Ruby is slow for some reason but it’s as fast as Python, and with falcon as fast as node for async behavior. Safe to say the application language taking 0.03 seconds instead of 0.003 seconds when you have to wait 3 seconds for first token is absolutely not the bottleneck with LLM heavy workflows, anyway. And yes, metaprogramming is a powerful tool with which you can easily shoot yourself in the foot. We culturally just don’t write any code that’s not greppable so don’t use method_missing kinds of things unless it’s in a robust gem like active record. Pretty trivial problem to solve really. PS - We’re hiring, if that philosophy aligns with you! |
I played with Ruby when I was a teenager (~2015 or so), and I definitely remember enjoying it. I know there's still a vocal group of users who love it, so I would be interested in digging in again.