In 2025, AI agents hit the mainstream, transforming how consumers interact with technology. People became familiar with chat interfaces, which evolved from simple question-and-answer formats to more complex tasks like shopping and coding. However, a significant limitation emerged: while these agents can perform actions, they still rely heavily on user input for context. Most users struggle with this, lacking the skills to ask the right questions or provide necessary context. The real advancement needed for consumer AI isn't just better execution; it's a deeper understanding of user intent before they even articulate it. Google's personal intelligence exemplifies the challenge of intent capture. It can analyze your behavior, like frequent food delivery orders, but fails to understand the underlying reasons—whether it's stress, convenience, or something else. This gap between actions and the motivations behind them affects the quality of AI interventions. The same issue arises across various AI platforms, including OpenAI and Apple's Siri. Reactive AI waits for commands, while proactive AI can anticipate needs and engage users more effectively. To build effective consumer AI that captures intent, several strategies are essential. Start with data that offers initial insights, be proactive in surfacing relevant information, and simplify user interactions by limiting the number of questions. It's also vital to make sharing personal context feel rewarding, turning data collection into a collaborative process rather than a chore. Lastly, every interaction should contribute to a growing understanding of the user, enhancing future engagements. Companies that master these elements will likely outpace general-purpose platforms in delivering genuine value.