Hyperautomation and Sequencing Patterns

This unit examines real-world practice and disruption caused by hyperautomation in conversational AI ecosystems, using a practitioner case study and focused notes to distill lessons. Students learn sequencing and orchestration patterns for building resilient, modular intelligent systems and prepare designs for integration and deployment in the next unit.

Learning Objectives

• Analyze the Josh Tyson case study to identify key architectural decisions, stakeholder roles, and trade-offs in operationalizing conversational AI systems
• Evaluate the technical, business, and societal risks and opportunities introduced by hyperautomation and hyperdisruption, and propose at least three mitigation or governance strategies
• Apply sequencing and orchestration patterns to design an end-to-end automation pipeline for a conversational AI feature, producing sequence diagrams and component interaction maps
• Demonstrate the ability to translate annotated notes and pattern selections into a modular ecosystem plan that specifies integration points, monitoring hooks, and rollback/continuity procedures