For people: When a few people make most changes, the knowledge sits with them: their absence slows everyone, and reviews and onboarding depend on them.

For AI agents: Not in the AI rating by default: an agent reads the code, not people's memory, though it gains when that knowledge is written down.

For people: A fix in one copy must be repeated in all the others; a missed copy becomes a bug.

For AI agents: Agents copy the patterns they find, so duplicates multiply; a change to one copy misses the others, and every copy costs context.

For people: A test suite documents the intended behaviour and makes changes safe. Counted is whether there is one of reasonable size, not its coverage.

For AI agents: Tests let an agent check its own work; without them its mistakes surface later, in review or in production.

For people: More code is more to learn, search and keep in mind; onboarding and judging a change's impact slow down as it grows.

For AI agents: An agent sees only a slice at a time: the bigger the code base, the more it searches, and the likelier it misses relevant code or rewrites an existing helper.

For people: Large files are hard to navigate, mix responsibilities and attract merge conflicts.

For AI agents: Agents read whole files into their context: every change to a large file costs many tokens and crowds out other relevant code.

For AI agents: Agents copy the patterns they find, so duplicates multiply; a change to one copy misses the others, and every copy costs context.

For people: A fix in one copy must be repeated in all the others; a missed copy becomes a bug.

For AI agents: Tests let an agent check its own work; without them its mistakes surface later, in review or in production.

For people: A test suite documents the intended behaviour and makes changes safe. Counted is whether there is one of reasonable size, not its coverage.

For AI agents: An agent sees only a slice at a time: the bigger the code base, the more it searches, and the likelier it misses relevant code or rewrites an existing helper.

For people: More code is more to learn, search and keep in mind; onboarding and judging a change's impact slow down as it grows.

For AI agents: Agents read whole files into their context: every change to a large file costs many tokens and crowds out other relevant code.

For people: Large files are hard to navigate, mix responsibilities and attract merge conflicts.