Stop AI code sprawl before it destroys your software design

The New Stack · 1 month ago · 39 ● 8 sources

The article argues that AI code generators can create architecturally wrong but functionally correct code, causing a growing gap between what gets written and what humans understand about the system. It highlights a concrete example where a Python AI agent could exceed boundaries like billing importing from shipping, which is blocked by running pytest-archon in CI with rules such as “billing*” should_not_import “shipping*” after installing it via pip. It recommends shifting from documentation to “executable architecture” by adding automated boundary tests (and complexity/interface checks) so CI fails and feeds results back to the AI for fixes without relying on human reviewers.