Also AI does not benefit from abstractions such as ORMs - you are far better to have your AI write SQL.
That goes for all abstractions including CSS JavaScript and everything else Rails has wrapped.
Golang with raw SQL CSS JavaScript works really well cause it avoids many abstractions and affordances that Rails makes to humanize programming.
Strictly speaking, if codebase A is doing the same thing as codebase B, but is 5-10x the LoC, you will be limited in how broadly you can effectively prompt the LLM. Queries will take longer, more technical debt+anti-patterns will creep in.
Anyone building large projects from scratch with LLMs will see plainly that they start to perform worse and slow down meaningfully as the codebase grows if you aren't pruning and compartmentalizing the code as you go.
Agree that abstractions which have a large performance cost are net-net not so worthwhile anymore. But many abstractions can be done with minimal performance hit (e.g. Rust)
And it can benefit from ORMs, because it means less tokens.
The biggest advantage of Rails is convention over configuration. Standardisation means AI is trained on lots of standardised codebases. So that still pays in AI land. The question to me is whether that’s such a big upside that it gives a real edge. Not sure on that; Python has way more code overall.
I agree on ORMs, but that would apply with or without AI for me personally. ORMs and ActiveRecord are an obvious and well documented anti-pattern at this point in time.