Jorge Arango, an expert in information architecture, shares insights on aligning systems with user mental models. He emphasizes that effective designs bridge user understanding and system data, creating learnable interfaces. Jorge discusses how contextual organization simplifies decision-making, tackling the paradox of choice. He also highlights the importance of progressive disclosure to accommodate users of varying expertise, and examines the transformative impact of large language models on search experiences.
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question_answer ANECDOTE
Physical vs. Digital Organization
Jorge Arango enjoyed a podcast conversation with the Danish Broadcasting Company's record collection manager.
They discussed the challenges of organizing physical music in one dimension, unlike digital organization with multiple dimensions.
volunteer_activism ADVICE
Smart Defaults
Embrace smart defaults to simplify choices and reduce system maintenance.
Jorge Arango realized that extensive customization requires ongoing effort and learned to appreciate default settings.
insights INSIGHT
Data Models and User Experience
Data models reify conceptual models, impacting user interfaces.
Designers act as translators, aligning user needs with technical implementation for a better user experience.
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Today on How AI Is Built, Nicolay Gerold sits down with Jorge Arango, an expert in information architecture. Jorge emphasizes that aligning systems with users' mental models is more important than optimizing backend logic alone. He shares a clear framework with four practical steps:
Key Points:
Information architecture should bridge user mental models with system data models
Information's purpose is to help people make better choices and act more skillfully
Well-designed systems create learnable (not just "intuitive") interfaces
Context and domain boundaries significantly impact user understanding
Progressive disclosure helps accommodate users with varying expertise levels
Chapters
00:00 Introduction to Backend Systems
00:36 Guest Introduction: Jorge Arango
01:12 Podcast Dynamics and Guest Experiences
01:53 Timeless Principles in Technology
02:08 Interesting Conversations and Learnings
04:04 Physical vs. Digital Organization
04:21 Smart Defaults and System Maintenance
07:20 Data Models and Conceptual Structures
08:53 Designing User-Centric Systems
10:20 Challenges in Information Systems
10:35 Understanding Information and Choices
15:49 Clarity and Context in Design
26:36 Progressive Disclosure and User Research
37:05 The Role of Large Language Models
54:59 Future Directions and New Series (MLOps)
Information Architecture Fundamentals
What Is Information?
Information helps people make better choices to act more skillfully
Example: "No dog pooping" signs help predict consequences of actions
Poor information systems fail to provide relevant guidance for users' needs
Mental Models vs. Data Models
Systems have underlying conceptual structures that should reflect user mental models
Data models make these conceptual models "normative" in the infrastructure
Designers serve as translators between user needs and technical implementation
Goal: Users should think "the person who designed this really gets me"
Design Strategies for Complex Systems
Progressive Disclosure
Present simple interfaces by default with clear paths to advanced functionality
Example: HyperCard - visual interface for beginners with programming layer for experts
Allows both novice and expert users to use the same system effectively
Context Setting and Domain Boundaries
All interactions happen within a context that influences understanding
Words acquire different meanings in different contexts (e.g., "save" in computing vs. banking)
Clearer domain boundaries make information architecture design easier
Hardest systems to design: those serving many purposes for diverse audiences
Conceptual Modeling (Underrated Practice)
Should precede UI sketching but often skipped by designers
Defines concepts needed in the system and their relationships
Creates more cohesive and coherent systems, especially for complex projects
More valuable than sitemaps, which imply rigid hierarchies
LLMs and Information Architecture
Current and Future Applications
Transforming search experiences (e.g., Perplexity providing answers vs. link lists)
Improving intent parsing in traditional search
Helping information architects with content analysis and navigation structure design
Enabling faster, better analysis of large content repositories
Implementation Advice
For Engineers and Designers
Designers should understand how systems are built (materials of construction)
Engineers benefit from understanding user perspectives and mental models
Both disciplines have much to teach each other
For Complex Applications
Map conceptual models before writing code
Test naming with real users
Implement progressive disclosure with good defaults
Remember: "If the user can't find it, it doesn't exist"
Notable Quotes:
"People only understand things relative to things they already understand." - Richard Saul Wurman
"The hardest systems to design are the ones that are meant to do a lot of things for a lot of different people." - Jorge Arango
"Very few things are intuitive. There's a long running joke in the industry that the only intuitive interface for humans is the nipple. Everything else is learned." - Jorge Arango
How AI Is Built