Measuring and evolving AI projects

Learning goal

What matters after launch - metrics, spotting quality drift, when to retire a tool, and how to systematically evolve AI solutions in ongoing operation.

5 modules

Why the launch is only the beginning

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The metrics that actually matter after launch

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Why an AI solution quietly gets worse: quality drift

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When a tool should be retired

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The improvement loop: learning from ongoing operation

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