The Evolution of a Design Philosophy
From Pixels to Purpose: A 20-Year Journey
The First Truth
My design philosophy crystallized during the summer of 2015 at Hulu. We were reviewing user feedback about our show pages when I noticed a gap in the experience. The content algorithm was displaying current season key art and series art across the entire ecosystem, which often included characters and themes that weren't introduced until later in a viewer's journey through that series.
When I raised this concern, the resistance was immediate: "That's how it's always been done. Current season art is fresh, it's new, it's what's out in the world across commercial networks. That's the standard."
But that was exactly the problem. We were following network television's playbook—where current means everything because ad dollars depend on driving viewers to tonight's episode. But streaming isn't network TV. Our viewers were binging from Season 1. They were discovering shows years after they premiered. They were creating their own viewing schedules.
The beautiful irony? Hulu already had the solution in its infrastructure. The Yoshi database contained all the original metadata from past seasons—every piece of key art, every season-specific description—because we needed to reference those materials at the episodic level anyway. The data was there. We just weren't using it intelligently.
The engineering lift would be minimal. But rolling it out globally felt risky to leadership. So I found the perfect test case: the Apple TV project I was leading. Since it required a custom build anyway, I could implement contextual content display without affecting the entire ecosystem. A controlled experiment with minimal risk and maximum learning potential.
I designed the Apple TV experience to be contextually aware—key art and descriptions adapted based on where users were in their viewing journey. Select Season 2? See Season 2 artwork. Start from the beginning? See the journey unfold naturally. The interface became a trusted guide, not a marketing billboard.
The results on Apple TV were undeniable. This "minor" change set the tone for Hulu's evolution into a premium content destination, fundamentally different from both network TV and other streaming services. It proved that streaming viewers deserved experiences designed for how they actually watch, not how networks wish they would watch.
The lesson that shapes everything I design: The obvious solution often already exists in your infrastructure—you just need to see it differently. Sometimes achieving substantial impact means challenging industry assumptions while working within existing constraints. The best innovations don't always require new technology; they require new perspective on what you already have.
This is why the obvious solution is never the first solution. The first solution would have maintained the status quo. The obvious solution recognized we were playing an entirely different game—and we already had the pieces to win it.
The Journey to Mastery
My path never followed the typical designer trajectory. I started as an interactive designer and Flash animator, where every pixel had to earn its place through storytelling and purpose. You couldn't just make something pretty in Flash—it had to load fast, engage immediately, and drive action. Purpose wasn't something I discovered; it was baked into the medium.
The real journey was learning to navigate a world that didn't always share this belief.
Years 1-5: The Purpose Defender
Fighting for meaning in every project. Watching the "Quantum" game die in 2011 was formative—a stunning, mechanically brilliant game that never launched because we spent months debating the height of "Big Data Dave's" shirt collar while no one could answer: "How does this benefit their business?" The client lost interest because we lost the plot. Beauty without purpose isn't just decoration—it's waste.
Years 6-10: The Value Translator
Learning to articulate purpose in business terms. Not just "users need this" but "this drives X outcome worth Y dollars." Developing the vocabulary to defend meaningful design against "make it cool" requests.
Years 11-15: The System Architect
Realizing individual purposeful elements weren't enough—entire systems needed purpose. Building design languages that enforced meaning at every level. Creating frameworks that made purposeless design impossible.
Years 16-20: The Industry Shaper
Moving from defending purpose to embedding it in organizational DNA. Teaching teams to ask "why" before "what." Building cultures where "because it's cool" was no longer acceptable currency.
Year 20+: The Future Builder
Designing systems so purposeful they shape their own evolution. Creating architectures where a foundational purpose guides every future decision. Like at Anagram—features still shipping in 2025 work because they were designed with clear purpose in 2019.
The irony? I never had to learn that design needs purpose. I had to learn patience with a world that's still figuring that out. Every "Chester Cheetah Battle Game" for enterprise data storage taught me: brilliance without purpose is just expensive failure waiting to happen.
This shapes everything I create: Start with why, or pay the compounding rework taxes.
Philosophy Crystallized
Knowledge-Driven Design
When designing Anagram's provider portal, I didn't just interview doctors. I studied medical coding. I learned CPT codes. I understood claim adjudication at a level that surprised our medical consultants. This depth revealed that 53% of claim denials stemmed from a single UI pattern. We fixed it. Claim success rates jumped to 99%.
Details at Scale
Anyone can obsess over details. The magic happens when you systematize that obsession. My component library at SmithRx included 100+ elements, but more importantly, it included the logic for when and why to use each one. Engineers ship features faster when every micro-decision is pre-solved.
Continuous Metamorphosis
Last year, I returned to my college grid theory textbooks while designing my portfolio. Why? Even after 20 years, there's always more to master. I learned 3D design for OPVS. I studied narrative structure to make case studies engaging. Every project is an opportunity to expand capabilities.
The result? I don't just solve today's problems. I anticipate tomorrow's opportunities.
The Nexus Design Method
An Adaptive Design Framework
The Core: Diagnostic Intelligence
My methodology isn't a rigid process—it's an adaptive framework that responds to what root cause analysis reveals. The magic isn't in following steps, it's in knowing which tools to deploy when.
The Fundamental Question: Change or Conform?
Every deep analysis leads to a critical decision:
Change Behavior: When users' mental models prevent them from seeing value (Q.ai)
Map to Behavior: When users' expertise should drive the experience (UDT)
At Q.ai, retail investors needed behavior modification—their preconceptions about trading apps prevented them from understanding AI-managed investing. The 22-step onboarding wasn't about complexity; it was about education and belief-shifting.
At UDT, enterprise users were industry experts using clunky workflows. They didn't need education—they needed their deep knowledge respected and their workflows streamlined. By mapping to their expertise, I eliminated the need for spreadsheet macros and V-lookups, saving hours per day.
The same diagnostic rigor, opposite strategies. That's the power of adaptive design.
The Diagnostic Framework
1. Deep Immersion
Industry fluency (learning medical coding, investment theory, enterprise workflows)
Stakeholder archeology (what they say vs. what they mean)
Constraint mapping (what can't change—regulations, business model, infrastructure)
2. Root Cause Excavation
Behavioral observation (what users do vs. what they claim)
Mental model mapping (beliefs, biases, expertise levels)
Value gap analysis (where expectation meets reality)
3. Strategic Decision Based on findings, choose the approach that creates the most value. This is where 20 years of pattern recognition pays dividends—knowing instantly which strategy fits the discovered problem.
The Selection Intelligence
Knowing which approach to use comes from pattern recognition across industries:
Healthcare: Compliance is king, efficiency saves lives
Strategy: Map to expertise while ensuring compliance
Fintech: Trust is currency, complexity is the enemy
Strategy: Educate while building confidence
Enterprise: Time is money, workflows are sacred
Strategy: Enhance don't replace, automate don't complicate
Consumer: Attention is scarce, delight drives adoption
Strategy: Simplify ruthlessly, surprise strategically
The Execution Principles
Regardless of strategy chosen:
Start with Why: Purpose drives every decision
Design for Scale: Today's edge case is tomorrow's core feature
Build Systems: Patterns over pages
Measure Impact: Real business outcomes, not vanity metrics
Enable Teams: Self-sustaining design that outlives your involvement
The Real Framework
My process is knowing:
What methodology to apply
When to apply it
Why it's the right choice
How to execute flawlessly
This isn't about having a process. It's about having the intelligence to adapt the process to what the problem actually needs.
The obvious solution emerges not from following steps, but from deeply understanding the problem and having the expertise to choose the right approach. That's what 20 years of pattern recognition across industries provides—the ability to diagnose accurately and prescribe precisely.
Every client gets a custom approach because every problem is unique. The value isn't in the framework—it's in knowing how to apply it.