Every AI conversation follows specific patterns that shape how users interact with the system. These patterns guide expectations and create structured experiences:

• Query-response pattern: Users ask questions and the AI provides direct answers. Works well for information retrieval but can feel mechanical over time.
• Guided dialogue pattern: The AI proactively suggests next steps or asks clarifying questions to narrow down options. Creates more engaging interactions.
• Task-completion pattern: Breaks interactions into clear stages with confirmation points, giving users a sense of progress through complex processes.
• Mixed-initiative pattern: users and AI can steer the dialogue naturally, creating more human-like exchanges that flow in multiple directions.

The pattern choice should match user goals and context. Information-seeking benefits from direct query-response, while complex decision-making works better with guided dialogues. Shopping experiences often combine patterns, starting with open exploration before shifting to task completion during checkout. Pattern consistency builds user confidence by making interactions predictable while allowing for natural variations within the established framework.