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The article argues that organizations outperform others by running rigorous engineering with mature CI/CD, automated testing, and a culture of trust but verify that catches AI-generated code errors before mistakes become incidents.

It notes that high-performing organizations already know how to govern probabilistic systems-banks have managed credit models, fraud models, and market risk models for decades, so governing a system that makes probabilistic decisions is not a new question for them.

While leaders often cite speed as the reason for investing in AI, the piece emphasizes that the first job of an AI strategy is to identify the actual throughput bottleneck rather than simply buying coding assistance tools.