My Process

I use frameworks like Design Thinking, Lean UX, and the Double Diamond as guides, not prescriptions. The problem defines the process, not the other way around. I often enter projects midstream, adapting methods to what the work actually demands.

“Okay, but what does Marlon actually do when things are unclear, constrained, or already in motion?”

Researching the Organization

When I join a new organization, I start by understanding the system before trying to change it. I treat the environment as a research space learning how people work, what motivates them, where friction exists, and how decisions are made.

Through early conversations with stakeholders and peers, I assess UX maturity, constraints, and priorities. This context helps me adapt my approach and focus on improvements that align with both user needs and organizational reality

Decision-Making Under Constraints

In enterprise environments, decisions are rarely made with complete information. Constraints—time, budget, technical limitations, and regulatory requirements—are constant. Rather than treating them as blockers, I treat them as inputs that help focus decision-making and reduce risk.

My approach is grounded in established UX principles and standards, including Jakob Nielsen’s usability heuristics and foundational work by Don Norman and Steve Krug. These frameworks provide a reliable baseline when conditions are uncertain. While consistency is important, I’m comfortable making intentional exceptions when doing so clearly benefits user understanding or task success.

When constraints are present, I shift from pursuing ideal solutions to delivering meaningful progress. I focus on defining the smallest viable improvement, often an MVP, that can be implemented with low development cost and high user impact. Prioritization techniques such as MoSCoW help align teams around what must ship now versus what can be deferred.

I surface constraints early and work closely with product owners, product managers, and engineering partners to make informed tradeoffs. Collaboration is central to my process; shared understanding reduces rework and leads to better decisions under pressure.

Data and existing knowledge guide these decisions whenever possible. I leverage analytics, customer support insights, prior research, personas, and competitive context, while also aligning closely with the technical landscape frameworks, design systems, and testing capabilities, so design decisions are realistic from day one.

When time is limited, I’m comfortable conducting lightweight, expedited research to validate assumptions and reduce risk using just enough signal to inform confident decisions.

When a fast decision is required, my guiding question is simple:

What can we deliver now that aligns with proven UX standards, minimizes development effort, delivers the greatest improvement for users, and allows us to iterate based on outcomes?

I treat new environments like a research assignment, understanding people, systems, and constraints before proposing change.

Reducing Cognitive Friction

In high-volume, high-risk workflows, small moments of friction compound quickly. Extra clicks, unclear system state, inconsistent patterns, or forced context switching increase cognitive load and raise the risk of error.

I focus on reducing cognitive friction by aligning designs with how users already think and work, preserving mental models when they matter, simplifying decision paths, and making system behavior predictable and visible. The goal is to help users stay oriented, move confidently, and focus on judgment rather than navigation.

This approach is especially critical in regulated and operational environments, where clarity, consistency, and trust directly impact efficiency, accuracy, and outcomes.

Good enterprise UX doesn’t ask users to think harder; it lets them think less about the interface and more about the decision.

Preserve mental models when they matter

In critical systems, consistency is secondary to comprehension. When users rely on established ways of reading, comparing, or validating information, aligning with those mental models reduces cognitive load, prevents errors, and supports faster, more confident decision-making.

In critical systems, the fastest path isn’t always consistent; it’s familiarity.

Make decisions visible and defensible

I treat UX as a decision-support discipline, not just UI polish, designing interfaces that clarify choices, expose system logic, and help users understand what’s happening, why it’s happening, and what action to take next.

Good UX doesn’t just look right, it helps people make the right decision.

Entering Projects Midstream

Much of my work begins after a project is already underway, scoped, in progress, or partially live. In these situations, my role is not to restart the process, but to quickly understand the current state and identify where UX can add the most value.

I focus on efficiently diagnosing the problem space: understanding existing decisions, constraints, technical realities, and user impact. From there, I look for leverage points, areas where small, targeted changes can reduce friction, improve clarity, or lower risk without disrupting delivery.

This approach allows teams to maintain momentum while improving outcomes. By working within what already exists, I help stabilize complex efforts, reduce rework, and make progress without introducing unnecessary friction or process overhead.

How Research Shows Up in My Work

Research is not a phase I complete and move past. It’s an input that shapes decisions throughout the work. I use research to reduce uncertainty, challenge assumptions, and clarify where design effort will have the greatest impact.

I rely on direct conversations and observation to understand users’ mental models and uncover friction that systems often hide. When scale matters, I use lightweight surveys and existing data to validate frequency and priority, ensuring we’re solving problems that affect more than edge cases.

I use personas and artifacts as synthesis tools, not deliverables, ways to align teams around shared understanding and guide decisions, rather than documents created for their own sake. The value of research, for me, lies in how clearly it informs tradeoffs, supports defensible choices, and keeps design grounded in real user behavior.

How I Define Success

I measure UX success by outcomes, not artifacts. Strong UX reduces rework, shortens decision cycles, and helps teams move forward with clarity and confidence.

In practice, this means fewer escalations, fewer corrections, and less time spent recovering from avoidable errors. For users, success shows up as confidence, knowing what to do, understanding why a decision was made, and trusting the system to behave predictably under pressure.

At an organizational level, success is measurable: improved operational efficiency, reduced backlog, faster throughput, and clearer alignment between product, design, and engineering. When UX is working well, teams spend less time debating and more time delivering.

Where AI Fits

I use AI as an augmentation tool to accelerate research synthesis, explore scenarios, and support documentation, not to replace judgment or decision-making. AI helps me move faster through low-leverage tasks so I can focus on interpretation, tradeoffs, and outcomes that require human judgment.

Used this way, AI supports better decisions without compromising rigor, accountability, or user-centered thinking.

AI accelerates my process. It doesn’t define it.

In Closing

My process is grounded in judgment, adaptability, and outcomes—not rigid frameworks. By designing for real workflows, working within constraints, and focusing on what matters most, I help teams deliver UX that reduces risk and scales with confidence.

Foundational UX standards as a baseline

  1. Comfort making tradeoffs

  2. MVP thinking

  3. Early constraint discovery

  4. Collaboration with PMs, POs, and engineers

  5. Data-informed decisions

  6. Iteration based on outcomes

Understand the real work
How people actually do their jobs, not how systems assume they do.

Reduce cognitive friction
Especially in high-volume, high-risk workflows.

Preserve mental models when they matter
Consistency is secondary to comprehension in critical systems.

Make decisions visible and defensible
UX as a decision-support discipline, not just UI polish.