A design paradox plagues AI products i.e. we obsess over improving model accuracy while underinvesting in how humans and AI interact to make meaningful decisions. Yet these interaction patterns may be our most consequential design choice, as fewer modality choices can limit human-AI collaboration and leave users uncertain about their role, AI’s capabilities, and where agency lies. This talk introduces the Dimension Framework which offers a systematic way to align interaction patterns with task complexity, reasoning depth, and autonomy expectations. Each pattern establishes a collaborative contract, positioning AI as co-creator, thought partner, expert, or validator, shaping trust, control, and user expectations in distinct ways. Attendees will learn how to evaluate and select modalities with intention, apply the Dimension Framework as a design tool, and guide organizations through paradigm shifts like conversation-first interfaces to build AI experiences that are trustworthy, adoptable, and transformative.