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It's architecture dependent. A fairly functional modular monolith with good documentation can be accessible to LLMs at the million line scale, but a coupled monolith or poorly instrumented microservices can drive agents into the ground at 100k.

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I think it's definitely an interesting subject for Verification Engineering. the easier to task AI to do work more precisely, the easier we can check their work.

Yup. Codebase structure for agents is a rabbit hole I've spent a lot of time going down. The interesting thing is that it's mostly the same structure that humans tend to prefer, with a few tweaks: agents like smaller files/functions (more precise reads/edits), strongly typed functional programming, doc-comments with examples and hyperlinks to additional context, smaller directories with semantic subgroups, long/distinct variable names, etc.

Aren't those all things, humans also tend to prefer to read?

I like to read descriptive variable names, I just don't like to write them all the time.

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