Edge cases breaking system

Edge cases are where many AI systems reveal their weakest assumptions. The main flow looks solid, but unusual phrasing, unusual data, or unusual user behavior can break the experience in ways the team did not anticipate.

This happens because test coverage usually favors common cases. Real users, however, live in the long tail, and those rare patterns are often the ones that cause the most frustration.

The best defense is broad evaluation and thoughtful fallback design. If the system can survive edge cases gracefully, it becomes much more trustworthy in production.