> - Do we have reasons to care about LOC in a world where we don't write code manually? What happens to token usage numbers when the codebase is significantly larger?

Yes, at least to the extent that we care about context windows and tokens consumed by coding agents processing code that is ultimately irrelevant to their assigned task.

Anecdotally, I've found keeping file sizes small has been important for agentic coding not just to maintain human readability, but also for optimizing agent performance, precisely because it limits the amount of incidental context they load while working a problem, because they generally load entire files rather than just parsing the part relevant to their current assignment as a human might. That smaller file size thus reduces input noise and the LLM generates a tighter solution, which in turn reduces input noise for future solutions. Or at least this strategy avoids a death spiral into exploding context length.

I expect (but cannot currently prove) that keeping overall LOC down yields similar benefits even when file sizes are kept small because it spares the LLM from parsing potentially relevant files that prove irrelevant to its current task.