The current interaction with AI agents is often limited to simple input fields, hindering their evolution into true partners. We expect AI to be intuitive and understanding, but vague questions yield generic answers, forcing frustrating refinement cycles. True partnership emerges from dialogues where intent is co-constructed through clarification and confirmation, not just rapid question-and-answer exchanges. Bridging the "Gulf of Execution" and "Gulf of Evaluation" has historically improved human-computer interaction, but speed doesn't equate to understanding. While AI excels at tasks with clear goals, it struggles with complex, ambiguous real-life challenges. The single input box model forces users to cram details or simplify, leading to a "slot machine" experience with unpredictable results. This interaction model is ill-suited for expressing complex thoughts and leads to information dumps rather than helpful guidance. Designing AI interactions to facilitate exploration of vague impulses is crucial for a more coherent dialogue. Human conversations involve co-discovering and shaping ideas through back-and-forth exchanges, a process of "Intent Co-construction." Future AI partners should leverage multimodal inputs and subtle cues to understand unspoken intentions and provide truly insightful support.