Series
Designing for AI
AI products require fundamentally different design thinking. This series covers the patterns, principles, and practices for building AI-powered experiences that users actually trust and enjoy.
Articles in this series 12
Why AI Products Fail (And How Better Design Saves Them)
Most AI products don’t fail because the technology doesn’t work, they fail because the experience doesn’t work and users don’t adopt the product. Complex outputs, confusing interfaces, and broken trust leave users frustrated or skeptical. In this article, we unpack the common reasons AI-powered tools underperform, and how thoughtful design can turn a black box into a trusted co-pilot. If you’re investing in AI, invest in design first.
How to Design User Experiences That Make AI Feel Human
As AI become part of everyday software, product design is evolving from making interfaces to orchestrating intelligent, human-like interactions. This post explores where design fits in the age of AI, the new skills product teams need, and how founders can create agent experiences that feel trustworthy and natural.
Building Trust in AI Systems: The Foundation of User Adoption
75% of users worry about AI misinformation and bias. This article explores how to design transparent, ethical AI systems that users actually trust through practical frameworks for addressing bias, explaining decisions, and maintaining user control.
Designing for AI Failures: Error States and Recovery Patterns
AI will make mistakes, that's just how it works. This article explores how to design graceful failure states, recovery patterns, and error experiences that maintain user trust even when AI gets things wrong.
How to Turn AI into a Co-pilot, Not a Black Box
The future isn't bots that replace people, it's interfaces where AI collaborates with the user. This article explores how to design for human-AI collaboration, creating co-pilot experiences where software becomes a trusted teammate that enhances human decision-making while keeping people in control.
Designing Conversational AI: Beyond the Chatbot Paradigm
Chatbots are just the beginning. This article explores how to design sophisticated conversational AI experiences that feel natural, contextual, and helpful through better prompt design, conversation flows, and multimodal interactions.
AI in Traditional Interfaces: Beyond Chat Bubbles
The future of AI isn't chat windows, it's AI seamlessly integrated into existing workflows. This article explores how to embed AI suggestions, automation, and intelligence directly into traditional interfaces users already know and love.
Testing & Iterating AI Features: Beyond Traditional UX Methods
Traditional usability testing falls short for AI features. This article explores specialized testing methods, metrics, and iteration strategies for AI-powered experiences, from prototype to production optimization.
Multi-Modal AI Experiences: Designing Beyond Text
The future of AI is multi-modal. Learn how to design AI interfaces that work seamlessly across text, voice, vision, and gesture while maintaining consistency and user control.
Advanced AI Patterns: Personalization, Learning, and Adaptive Systems
As AI systems mature, they're becoming more personalized and adaptive. This article explores advanced patterns for AI that learns, personalizes without being creepy, and adapts to individual and team preferences over time.
Implementing AI Design Systems: Components, Guidelines, and Team Processes
As AI features proliferate across products, teams need systematic approaches to maintain consistency. This article explores how to build design systems for AI components, establish guidelines for AI behavior, and create team processes that scale AI design effectively.
The Future of Human-AI Collaboration: Emerging Trends and Design Implications
As AI capabilities rapidly evolve, so must our design approaches. This article explores emerging trends in human-AI collaboration, from autonomous agents to brain-computer interfaces, and what they mean for designers building the next generation of AI experiences.