Sequencing Conversational AI Patterns

This unit synthesizes core conversational AI design patterns and shows how to sequence them into reliable multi-turn interactions. Students consolidate key takeaways, apply pattern sequencing in practice, and document notes and trade-offs to prepare prototypes for iterative development or capstone work.

Learning Objectives

• Analyze conversational AI design patterns and map them to a given use case by producing a documented sequence diagram or flowchart that identifies intents, states, and transitions
• Apply key pattern sequencing strategies to design a multi-turn dialogue prototype (storyboard, pseudocode, or runnable script) that manages context carryover, interruptions, and error recovery
• Demonstrate a pattern-in-action by implementing and testing a small conversational interaction (mock or live) and collecting metrics or qualitative observations on user flow behavior
• Evaluate design trade-offs and produce notes and key takeaways that justify pattern choices and outline concrete improvements for iterative development