Advanced AI & Agentic Design

Learn how LLMs, multimodal models, and fine-tuned systems differ in capability and how these differences shape user experience design.

Understand model architecture tradeoffs and their implications for relevance, accuracy, and interface design decisions.

efine quality standards for AI outputs based on user needs and communicate these requirements effectively to technical teams.

Evaluate model performance beyond accuracy metrics using frameworks that assess UX impact and user trust.

Work with systems that learn from user input, designing feedback loops that improve model performance without breaking user trust.

Anticipate and design for emergent behaviors that arise as models encounter edge cases and evolving user patterns.

Design experiences that surface model reasoning, explanations, and confidence levels so users understand AI decisions.

Create human-in-the-loop patterns that maintain user agency and enable intervention when AI makes high-stakes decisions.

Create patterns for agents that act autonomously across tasks while balancing proactive assistance with user control.

Design decision points where agents escalate to users and how to communicate agent progress across multi-step workflows.

Participate in model selection and agent architecture discussions using frameworks that connect technical choices to UX impact.

Position your design expertise strategically in product decisions before implementation, shaping what gets built, not just how it looks.