AI-Generated Code Is Building Tech Debt You Can't See

Your team shipped more features last quarter than any quarter before. The AI coding tools are working. Everyone feels faster. Then you look at the codebase six months later and nothing makes sense. GitClear analyzed 211 million changed lines of code across repositories from Google, Microsoft, and Meta between 2020 and 2024. Their finding: copy-pasted code rose from 8.3% to 12.3% of all changes, while refactored code dropped from 25% to under 10%. Code duplication blocks increased eightfold. The codebase is growing, but the architecture is rotting. This is not traditional tech debt. Traditional debt comes from shortcuts under deadline pressure. AI-generated tech debt comes from code that works, passes tests, and reads fine — but lacks architectural judgment. The Measurement Problem Ox Security analyzed 300 repositories and found 10 recurring anti-patterns in 80-100% of AI-generated code. The top offenders: excessive commenting (90-100% of repos), avoidance of refactoring (80-90%), and d