> The same modularity that keeps a system inside a human’s head keeps each change inside a well-defined boundary the agent can reason about reliably.

Not only that. Good modularity also:

- improves code reusability, reduces unnecessary code duplication

- helps agents and engineers make better data model, data structure, design pattern, naming, and algorithm choices

- surfaces incorrect irregularities or outdated exceptions to a rule

- enables clean, independent upgrades of parts of a system to improve performance

- reduces stale references in code and comments (and the confusion that results, both from agents and humans)

Bad modularity is basically a summary of what usually constitutes pathological code in general, but AI systems seem particularly disposed to sling lots of it (at least humans are constrained in their output rate). How often have you tried to grok an AI-built project and found trivially unreusable code, unnecessary duplication (everywhere!), bad data structure and algorithm choices, and stale references?