Apple HIG 25 cross-component 'interaction flow' design patterns. Onboarding trio (Launching · Loading · Onboarding) / Data and input (Entering data · Drag and drop · Undo and redo · Searching · Charting) / Feedback and interruption (Feedback · Modality · Managing notifications) / Account settings (Managing accounts · Settings · Ratings and reviews) / Content and media (Audio · Video · Haptics · Full screen · Live-viewing) / System collaboration (Collaboration and sharing · File management · Multitasking · Printing · Workouts). Each pattern provides core principles + best practices + anti-patterns + platform differences. For component-level usage, see components; this section covers 'stringing components into flows'.
Nielsen Norman Group 'Design Patterns' ethics, globalization, and emerging technology subset: 15 curated articles, reorganized by theme into five clusters. ① Design Ethics and Deceptive Patterns (Dark Patterns, coined by Harry Brignull in 2010): 5 categories of tactics (Obstruction · Visual/Text Traps · Nagging · Emotional Manipulation · Sneaked Preselection) + Sludge + the line between persuasion and deception (LinkedIn/Booking.com) + 9-question cognitive walkthrough; three types of Sneaking (Forced Continuity · Hidden Costs · Sneak into Basket, with negative examples from Spotify/Ticketmaster/Airbnb/GoDaddy/LinkedIn vs positive examples from Apple/United); Dangerous UX (high-risk actions placed adjacent to harmless actions, shape coding from Chapanis' B-17 landing gear case · visual signals · increasing distance per Fitts' Law); legal risks including GDPR/CPRA/Amazon Prime lawsuits. ② Inclusivity and Autonomy (boundaries between Inclusive Design ≠ Accessibility (WCAG) ≠ Universal Design; 5 pattern categories: senior-friendly fonts/dark mode · global surnames · 30+ gender identities · inclusive filtering · diverse illustrations; three methods for user Autonomy: Customization · Scannability · Timing and Sequence, with the cattle chute metaphor + meaningful defaults). ③ Global Cross-Cultural Design (Translation vs Localization; Hofstede's 6 dimensions: Power Distance/Individualism vs Collectivism/Masculinity vs Femininity/Uncertainty Avoidance/Long-term vs Short-term Orientation/Indulgence vs Restraint; 6 tips for language switchers · language vs country switchers · local language names Español/Deutsch; international sizing with local size + original size + body measurements + brand-specific charts; WeChat/Alipay login; 94% of TV viewers use a mobile phone as a second screen; Collaboration among the 5 elements of omnichannel coordination + QR codes to reduce interaction cost). ④ Emerging Interactions (applying 10 VR heuristics to Oculus Quest; 3-step AR testing with 11 users · discoverability · glasses conflicts · no gratuitous AR; 4 uses of GenAI Prompt Controls: discoverability/educational inspiration/setting limits/facilitating follow-up, icons must have labels with negative example of ERNIE Bot magic wand). ⑤ UX Copy and Recommendations (three tiers: Long ≥3 paragraphs/Short 2-3 paragraphs/Micro <3 sentences; 5 guidelines for recommended content: personalized top placement · source labeling · categorization · feedback mechanisms · real-time updates; Explicit vs Implicit Differentiation comparison table + progressive disclosure + SERP). Target audience = product managers, with in-line explanations of jargon, decision-oriented (when to use/how to choose/negative examples).
A self-contained bilingual essence of Emily Campbell’s *Shape of AI* AI product UX pattern library (all 49 .md files fully read), reorganized into 36 specific patterns across 7 categories plus 1 set of overarching design guidelines, following a queryable structure of “Pattern Name → What Problem It Solves → How to Use It → Examples”. The seven categories are: ① Wayfinders (4 patterns: Follow up / Nudges / Suggestions / Templates) — solves the problem of new users not knowing how to use a blank input box; ② Inputs (8 patterns: Open input / Auto Fill / Inline action / Madlibs / Remix-Blend / Summary / Synthesis / Token layering) — feeds user intent and context to the AI; ③ Tuners (8 patterns: Filters / Parameters / Inpainting / Model management / Personal voice / Primary sources / References RAG / Workflows) — lets users fine-tune or restructure results; ④ Identifiers (6 patterns: Color scheme purple-green / Symbols icons ✨🔮🤖 / Name / Personality / Disclosure / Initial CTA) — distinguishes AI content from human content; ⑤ Governors (9 patterns: Citations / Controls stop/continue / Footprints / Prompt transparency / Regenerate / Sample response / Show the work / Token transparency / Variations) — preserves user agency and explainability while the AI works; ⑥ Trust indicators (3 patterns: Incognito / Memory management / Watermarks C2PA); ⑦ Dark matte hidden patterns (3 patterns: Data Ownership / Caveat disclaimer buck-passing / Rating) — gray-area designs that are questionable or erode trust. For PMs building AI chat or interactive narrative products: this is a quick reference manual for “which pattern to look up when you encounter interaction problem X next time”, with emphasis on Why / When to use / Counterexamples. It complements nngroup-ai-ux-design — the latter offers NNGroup’s conversational interface research perspective (6 types of conversation / no fluff / anthropomorphism / sycophancy), while this piece presents Shape of AI’s perspective as a “reusable UI pattern parts library”.
