"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."
Prompt engineering and context engineering focus on crafting inputs so large language models produce useful outputs, but those skills alone do not deliver full value. Real value emerges when employees integrate generative AI into their everyday roles to improve work outcomes. Effective integration requires identifying valuable problems inside existing workflows, assessing and comparing possible AI-enabled solutions, running rapid experiments to validate approaches, and embedding successful practices into routine work disciplines. Sustainable adoption emphasizes changes that align with core responsibilities, especially for product managers whose workflows can be reshaped through iterative experimentation and workflow-driven problem definition.
Read at Harvard Business Review
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