Debugging AI failures requires asking 'which layer' broke, not just 'where'

Software engineer Derek Wang argues that when an AI system fails, the instinct to pinpoint a single broken location is a fundamental debugging trap. He proposes a three-layer analysis framework: L1 (the visible phenomenon), L2 (structural flaws in the code), and L3 (flawed design assumptions underlying the system). A key rule in his approach forbids labelling something a 'data problem' as a root cause, since that label merely restates the symptom without explaining why the data went wrong. Wang also warns that fixing only the identified layer often triggers failures elsewhere, as engineering systems are deeply interconnected. The framework functions as a mandatory gate — no fix is permitted until all three layers have been examined and documented.