ai-regression-testing

Testing patterns specifically designed for AI-assisted development, where the same model writes code and reviews it — creating systematic blind spots that only automated tests can catch. When an AI writes code and then reviews its own work, it carries the same assumptions into both steps. This creates a predictable failure pattern: Real-world example (observed in production): The pattern: sandbox/production path inconsistency is the #1 AI-introduced regression. Most projects with AI-friendly architecture have a sandbox/mock mode. This is the key to fast, DB-free API testing. The key principle: write tests for bugs that were found, not for code that works . The most common AI regression: fixing production path but forgetting sandbox path (or vice versa). Frequency : Most common (observed in 3 out of 4 regressions) Test to catch it : Frequency : Common with Supabase/Prisma when adding new columns Frequency : Moderate — when adding error handling to existing components Don't aim for 100% coverage.