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This article discusses a method for debugging AI agents by identifying which specific layer in the agent's architecture produced an incorrect answer, rather than immediately tweaking the prompt.
A reflection on how AI agents fail in production due to accumulated state issues (stale context, expired tokens, conflicting memory) rather than reasoning flaws, emphasizing the need for better state management.