Much of the conversation about how to work effectively with generative AI has focused on prompt engineering or, more recently, context engineering: the semi-technical skill of crafting inputs so that large language models produce useful outputs. These skills are helpful, but they are only part of the story. The real payoff comes when employees learn how to apply generative AI in their day jobs in a way that improves how they work. This requires defining valuable problems within workflows, evaluating possible solutions, rapidly experimenting, and integrating new practices sustainably into day-to-day work—disciplines that are core to the work of product managers.
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