Practitioner Wiki
The intellectual foundation, including history, LLMs, GANs, and what designers must know to evaluate AI tools critically.
Cognitive biases, mental models, emotional design, and behavioral patterns that underpin every user decision, and how to account for them in research.
A structured, human-centered methodology for solving complex problems, Empathize, Define, Ideate, Prototype, Test. How AI accelerates every phase.
Problem brief synthesis, competitive landscape research, opportunity mapping, and assumption stress-testing with AI.
AI-assisted interview guides, transcription, pattern identification, and insight synthesis across user interviews.
Cited web research, academic paper synthesis, trend signals, and structured competitive landscape briefs.
Using AI for divergence while protecting the creative phase, including prompt sequences, analogous inspiration, and concept stress-testing.
Core visual design principles every designer must master, including Laws of UX, Gestalt psychology, and perceptual rules that make design decisions defensible.
Scale-calibrated AI design tools, from solo v0 scaffolding to enterprise-level design system governance.
Unmoderated testing with AI summaries, predictive heatmaps, and A/B hypothesis generation from design variants.
AI-accelerated audit delivery, from 3 days to 6 hours. Custom checklists, severity-rated findings, executive summaries.
Comprehensive guide to accessing powerful LLMs without subscription costs. Open-source alternatives and free tiers.
