Designing Context for AI Systems
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Unclaimed ProfileThis course applies established Information Architecture principles (taxonomy, labeling, hierarchy, relationships) to AI systems, teaching students to design the "context" that shapes AI behavior, including memory, instructions, retrieved knowledge, and tool/skill organization, rather than just writing prompts. Students learn a specific evaluation method, the R.I.S.K. Framework, to identify ambiguity, inconsistency, safety, and knowledge gaps in AI systems. No coding or "prompt tricks" are required; the focus stays on structural design thinking applied to AI.
About the creator
Paz Perez
View full profileTechnology & UX Design · Not publicly disclosed
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Paz Perez is an AI Design Consultant and educator based in Southern Spain, co-founder of Nothing Fancy AI. A former architect for 8 years before moving into UX, she trained 900+ designers at Google and is a published author with the Nielsen Norman Group. She now teaches Designing Context for AI Systems, a Maven course applying Information Architecture to AI behavior.
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Learning format
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Price
Price may change · updated within 1–2 weeks
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What You'll Learn
- Building more reliable, aligned AI systems
- Evaluating AI context using the R.I.S.K. Framework
- Organizing skills so AI agents choose correctly
- Designing memory, taxonomy, and labeling for AI
- Applying Information Architecture principles to AI systems
- Understanding why context shapes AI behavior
Best For
- Content designers shaping AI behavior
- Design leaders building AI-ready workflows
- Design leaders building AI-ready workflows
- Information architects and content strategists
Not For
- Those wanting a fully self-paced format
- Complete beginners to UX or design
- People wanting prompt-engineering "tricks" only
- Those wanting to learn to code
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