This has the side benefit of likely being easier to navigate for humans too. The less I need to keep in my head to figure something out the better.
The app I work on is fairly highly modular, to the point that we split the app in half and unwinding the two halves of the code only took about 2 weeks.
> The LLM codebase 'navigation' becomes near-free with good naming and structure
I have not found this to be true. They seem to break badly if you have a lot of files with similar-ish names even if they're descriptive.
I run LLMs against a 500k LoC poker engine and they do well because the engine is modularized into many small parts with a focus on good naming schemes and DRY.
If it doesn't require a lot of context for an LLM to figure out how to direct effort then the codebase size is irrelevant -- what becomes relevant in those scenarios is module size and the amount of modules implicated with any change or problem-solving. The LLM codebase 'navigation' becomes near-free with good naming and structure. If you code in a style that allows an LLM to navigate the codebase via just an `ls` output it can handle things deftly.
The LLMification of things has definitely made me embrace the concept of program-as-plugin-loader more-so than ever before.