Yes, and brownfield is where the discipline shows. How a factory reads an existing architecture, works inside its conventions, and what to do first when the system is legacy and has no tests.
Outsourcing sells hours; a factory sells verified changes. What actually differs between handing a backlog to a vendor team and running it through a production line on your own codebase.
The honest answer is that quality becomes a verification problem. AI can produce code and tests faster than teams can review them, so the control structure, not the generation, is where quality is won or lost.
The pipeline from a product specification to a merged change: how the factory reads your architecture, derives tests from acceptance criteria, verifies its own output, and stops at a human gate inside your pull request process.
An AI software factory is a production line for software changes. It takes specifications the way product writes them, produces the code and the tests, verifies its own work with an independent check, and stops for human approval before anything merges.