[mpalczewski]

and it's wrong. a 6000 line class is not easier for a model to understand. the same things that help humans also help agents. I find myself adding linters that must pass and the agent muss fix that limit file size, function length, function complexity, how many files in a directory. a little more work for the agent, but the codebase is healthier and the agents write fewer bugs.

[lukevdp]

I don't think the same things that help humans help agents. Simplicity helps humans, for agents parsing complexity is a breeze.

Not saying code quality isn't important - it is. But I think what is described as quality code will change.

[cjbgkagh]

Agents still pay a penalty for complexity even if it is a smaller one.

[digitaltrees]

Parsing single file is easier than navigating a file system for an LLM. Until the models have context windows large enough to hold the entire codebase in one shot, single files will beat multiple files every time.

[bossyTeacher]

This. I suspect the codebases in the future will be made of a small number of gigantic source files. These will be able to be transpiled into a more human friendly that produces multiple smaller files per big file in human-debug mode.

[cjbgkagh]

As a human who typically uses large files, 10k to 30K lines of code files are pretty common, I find the agents don’t read the whole file after the first time, they almost always do a range select for the bit they are interested in.

[digitaltrees]

But you wouldn’t argue that a 30k line file is good code would you?

Humans write bad code to. For me the litmus test is: will someone read this in the future. If yes, then write good code.

I don’t think we are in the era when a human will never read the code again in human history. So we should still strive for human intelligibility.