Process

The core ideas behind design thinking — such as empathy, iteration, and human-centered problem solving — trace back to design disciplines in the 1960s–1980s, particularly in architecture, industrial design, and engineering. IDEO, led by people like David Kelley, was pivotal in applying design thinking to business and technology in the 1990s and early 2000s. They helped package design thinking as a repeatable process that could be used by non-designers:

Empathize → Define → Ideate → Prototype → Test

Design Approaches for Mitigating Risks to User Adoption

Time and money don’t grow on trees—and validating business and design decisions with real users can be resource-intensive. But not every project carries the same adoption risk. When Amazon introduced the Alexa Show, it was introducing a new interaction paradigm—voice-first computing—requiring extensive user research to ensure acceptance. Contrast that with a bank launching a feature that allows car loan payments from third-party institutions—a useful update, but one that builds on familiar behavior. The five models below outline different 5 different design approaches that are defined by the level of validation effort (time and money) they employ to mitigate the perceived risk to user adoption.

Design approach models

Self Design

When the Designer only considers themselves for the design decisions.

Unintentional Design

When no consideration. is given to users. Only to technology and business objectives.

Genius Design

When a solution uses only existing research to make design decisions.

Activity Design

When the necessary time and money required to conduct activity-based user research in order. to mitigate risk is made available.

Experience Design

When the necessary time and money required to conduct experienced-based user research in order to mitigate risk is made available.

What AI can do well

Rapidly generate hypotheses, wireframes, or user scenarios.
Analyze large datasets for behavioral patterns.
Assist with survey synthesis or usability test tagging.
Simulate some user behavior (in limited contexts).

What AI cannot do (yet):

Accurately judge the emotional, cultural, or contextual nuances of user behavior.
Replace real-world exposure to novel paradigms (e.g., Alexa’s voice interface).
Understand unspoken needs or hesitations that come through in qualitative research.
Decide how much validation is necessary based on risk, regulation, or brand implications.

Experience Outcomes

A few guiding principles I continuously evangelize.

Process

AI is disrupting my process

The basics

For this process deep dive, I’m using a personal project called the Vehicle Passport. According to multiple (sycophantic?) AI agents, it’s more than just a playful concept—the idea has real potential.

Process Stages

The Elements of (the Vehicle Passport) User Experience

Stage 1: User needs & business objectives

Stage 2: Functional specs and content requirements

Stage 3: IA and IxD design

Stage 4: User interface and navigation design

Stage 5: Visual design

The original Elements of User Experience model is copyrighted 2000 by Jesse James Garrett. All rights reserved. View the original diagram.

End-to-end Product Design

From abstract ideas… to concrete deliverables

Artificial Intelligence Experiments

Guiding Principles

“A brand is a person’s gut feeling about a product or service. It’s not what you say it is. It’s what they say it is.”

“Experience Design is the design of anything, independent of medium and across media where human engagement is an explicit goal and human experience an explicit outcome.”

“If you don’t have time to do it right… when are you going to have time to do it over?”

“Enlightened trial and error succeeds over the planning of a lone genius.”

Design Thinking