The original title is about AI auditing and systematic layer-by-layer review. Let me rewrite this as a punchy mobile feed headline.

Short summary

Spot-checking AI systems misses failure modes that live in edge cases and cross-layer interactions. A thorough audit moves systematically through every layer—data pipeline, model behavior, agent decisions, downstream effects, and rollback paths—documenting failure modes before production traffic finds them. The author argues audits require patience and method over intelligence, and that checklists should evolve into institutional knowledge.

• •Spot checks miss failures in edge cases and multi-step interactions
• •Full audits cover data pipeline, model behavior, agent decisions, downstream effects, and rollback paths
• •Audit checklists become institutional knowledge over time

Generated with AI, which can make mistakes.