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The article argues that AI defensibility comes from owning the full feedback loop—custom models post-trained on proprietary data, tuned to specific workflows, and evaluated by user-defined standards—rather than renting frontier APIs from suppliers who can change terms. It emphasizes model customization as key to differentiation and margin control.