This unit examines practical interaction patterns, information architecture, and tooling for conversational AI products, including autocomplete, plug-ins, and chat‑focused flows. Students will learn promptbook practices, how to run design spikes, and how to evaluate the role of data and mitigation strategies for hallucination as they prepare for prototyping and evaluation in the next unit.
Learning Objectives
- Analyze trade-offs and user impacts of AI-driven features (autocomplete, next-step suggestions, and plug-ins) and prioritize them for a given product context
- Apply promptbook techniques and spike experiments to produce effective prompts and lightweight prototypes that reveal system behavior and failure modes
- Demonstrate a chat-focused information architecture by creating a schematic and interaction flow that supports contextual continuity and next-step suggestions
- Evaluate data sources, continuous‑learning mechanisms, and mitigation strategies to reduce hallucinations and other AI reliability or ethical risks
Curriculum
- 1 Section
- 13 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 3 — AI Interaction & Prompt Strategies13
- 1.1AI-Driven Autocomplete20 mins
- 1.2Plug-Ins: Integrated Continuous Learning About Your Specific System20 mins
- 1.3Design Idea #420 mins
- 1.4What the Heck Is a Spike?20 mins
- 1.5AI Bullshit20 mins
- 1.6Next-Steps Suggestions20 mins
- 1.7The IA of the AI Is Straightforward, Focused on Chat20 mins
- 1.8Design Idea #520 mins
- 1.9What Is the Role of Data?20 mins
- 1.10Final Words20 mins
- 1.11Final Words20 mins
- 1.12Promptbooks: No Need to Twist into Pretzels to Write Prompts20 mins
- 1.13But Wait, Did You Catch That?20 mins
Instructor
Free
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