An AI agent speeds up work just as well on a healthy architecture as on a poor one; the difference is what it accelerates. GitClear research, based on 211 million lines of changes, recorded an eightfold rise in duplicated blocks of five or more lines in 2024; copy-paste grew from 8.3% to 12.3% of all changes, while refactoring fell from 25% to under 10%.
Practical takeaway: the agent tends to generate working snippets and copy them across modules without consolidating them. This creates a layer of technical debt that grows quietly and later shifts the team’s time from building new things to fixing old ones. That is why the AI-native approach works only on top of an engineering foundation, such as loose coupling, reusable components, and build checks, not instead of it.
