AI 410 - Agentic AI Application Development

5 CR

Previously ROBAI 410.
This project-based course teaches students to design and build AI-powered applications using specification-driven development and modern agentic frameworks. Students master AI development tools and workflows while working with the latest language models to create stateful, multi-agent systems. The course covers agentic frameworks and patterns for building systems with reasoning capabilities, tool use, and multi-step workflows. Emphasis is placed on human-centered AI interaction design principles, ensuring systems are intelligent, usable, and meaningful for end users. Students apply user-centered design theories, cognitive models, and usability evaluation methods. The course follows agile methodology with sprint projects, building toward a team-based final agentic system that demonstrates retrieval-augmented generation or multi-step reasoning capabilities with effective human-AI interfaces.

Prerequisite(s): ROBAI 240 or AI 240 and admission into the BAS Software Development Artificial Intelligence concentration, or permission of the instructor.

Course Outcomes

Design and implement specification-driven development workflows using AI-augmented tools to transform user requirements into executable technical plans.
Evaluate and select appropriate AI models and agentic frameworks based on task-specific requirements while implementing Responsible AI practices, including human-in-the-loop checkpoints and security considerations.
Build agentic applications using modern frameworks that demonstrate stateful reasoning, tool use, and multi-step workflows.
Implement retrieval-augmented generation patterns and data-centric AI architectures with proper data ingestion, indexing, and retrieval strategies.
Apply user-centered design principles, cognitive models, and usability evaluation methods to create intelligent, usable, and meaningful agentic systems.
Apply agile development practices to AI projects through iterative sprints, team collaboration, and stakeholder-driven refinement.

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