We're going to have a bunch of hardly used libraries/frameworks that might converge on a single one. Similar to the surge in JS frameworks/libraries from a few years back and where we are now.

Is squeezing a lot more performance beneficial to a business? or is it a small amount of VPS cost per month difference?

It helps to be clear, at least with yourself, about if you're doing something because you can/want to or if there are actual business reasons.

This is my first attempt at a AI framework and I'm pretty happy with it

https://pricklypear.rocks/

This is a question I have been circling around. The agents are good at Ruby/Rails. It’s probably a confluence of things, but whether the L in LLM benefits from Ruby’s emphasis on human readability is something I’d love to see a study on. Or more generally, how key is (human) language itself in the performance ceiling of LLMs. A machine specific coding language/framework/process could obviously be more efficient, but if language itself is the hard limit, those would be dead in the water with LLMs. Or put another way: if language wasn’t the ceiling, why didn’t we see machine first coding implementations before LLMs?