Preference Engineering: Marketing in the Agentic Economy

We describes a fundamental transition from the Attention Economy to an Agentic Economy, where autonomous AI agents increasingly handle market transactions. In this new landscape, **marketing** is reimagined as a technical discipline called **Data Source Engineering**, focusing on the rigorous collection of human preference data rather than simple brand persuasion. This evolution prioritizes **Preference Alignment** and **Active Learning**, using consumer interactions to refine the AI models that drive decision-making. The report highlights emerging **infrastructure protocols** and **elicitation frameworks** that allow brands to communicate directly with digital assistants. Ultimately, the role of the marketer shifts toward managing a **"Digital Twin"** of the market to ensure business agents accurately reflect and serve user intent. These sources argue that firms must master **technical signaling** and data integrity to remain visible to the algorithmic buyers of the future.