Conversational AI Patterns and Sequencing

This unit guides students to synthesize prior learning into practical conversational AI designs by extracting key takeaways, sequencing reusable patterns, and producing clear implementation notes. Learners prototype patterns in action, evaluate effectiveness and ethical implications, and produce documented artifacts to inform further development in AI and automation pathways.

Learning Objectives

• Analyze key takeaways from prior units and lesson materials to define design goals, constraints, and success criteria for conversational AI systems
• Apply established conversational AI patterns and sequencing techniques to design and prototype multi-turn dialogue flows that handle intent, context, and error recovery
• Demonstrate organized documentation practices by producing structured notes that record chosen patterns, prompt structures, test cases, edge cases, and implementation rationale
• Evaluate pattern effectiveness and ethical considerations by testing conversational flows against measurable performance criteria, identifying failure modes, and recommending refinements