Product Design and UX process methodology

AI is disrupting my process

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. Follow along as I map each stage of Jesse James Garrett’s Elements of User Experience1 to show how I’m leveraging AI to expand my skills and adapt to the rapidly evolving field of product and UX design.

Related material
Words to live by
Design Thinking (IDEO Labs)
Mitigating risk to user adoption
The Elements of (the Vehicle Passport) User Experience

< Abstract Ideas

Concrete Deliverables >

User needs & business objectives

Functional specs and content requirements

IA and IxD design

User interface and navigation design

Visual design

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

Vehicle Passport: A pet project for AI and vibe coding experiments

Not a finished, branded design but rather a scrappy, clickable MVP vibe-coded with Cursor Windsurf + Claude Sonnet 4 (including Supabase user authentication). Time to complete ~6 days.
Process deep dive. It’s evolving quickly
Stage 1: User needs and business objectives

Continue reading →

Stage 2: Functional requirements and content specifications

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Stage 3: Information architecture and interaction design

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Stage 4: User interface and navigation design

Coming soon

Stage 5: Visual design

Coming soon

What is the Vehicle Passport
The concept acknowledges user pain points that exists throughout the trade-in funnel. The concept further hypothesizes that separating the vehicle trade-in funnel from the vehicle sales funnel, leveraging IoT and emerging technologies, will boost sales and improve customer satisfaction. After mulling the idea over with several deep research tools like Claude, ChatGPT, Perplexity and Sjeel Koster’s ICP Architect agent, it seems like there might be a real world need (sycophantic?).
Inspiration
For years it seems I’ve been encumbered by workflows, processes and tools that were imposed on me by clients, employers and cultures. This pet project gives me the freedom to explore new tools, techniques and technologies at my own pace.
End-to-end Product Design

From abstract ideas… to concrete deliverables

If I were to ask you over this weekend to help build a deck on my back porch—but gave you no other details—we would both share a general understanding of what that work involves and the goal at hand. But that understanding would be mired in abstractions. Will the deck be enclosed or open-air? How many people should it be able to accommodate safely? What activities will be performed on its surface on a routine basis? Only once we align on materials, dimensions, purpose, timeline, etc. will the scope of the work come into focus with real clarity.
Every design project goes through these 5 stages. It’s an inescapable truth. AI may help accelerate, augment and perhaps replace some of the work that transpires in these 5 stages, but AI can not replace the stages themselves. My aptitude for leading a design process means facilitating the workshops and conversations that move cross-functional teams away from abstraction (stage 1) towards the delivery of tangible artifacts (stage 5).
Artificial Intelligence Experiments

Guiding Principles

I subscribe to the following definitions and beliefs.

“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.”

Marty Neumeier – The Brand Gap

“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.”

Jesse James Garrett

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

John Wooden

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

David Kelly – Founder, IDEO Labs

Design Thinking

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.

  1. Jesse James Garrett, Elements of User Experience (March 30, 2000), http://www.jjg.net/elements/pdf/elements.pdf. ↩︎