Senior UX & Product Designer

About

Designing and optimizing online services and applications that work effectively, without complicating the life of the user. That's what I love to do.

I don’t make big plans upfront, but create and test to validate the assumptions. From business objectives to user research, from requirements to wireframes, and from functional design to user interface design and prototypes. I love each part of my work.

• I'm passionate about UX/UI and driven to design functional and user-friendly interfaces.
• I have a foundational background in frontend development (HTML, CSS, JS).
• I have a solid understanding of data-driven design and mobile strategy.
• I enjoy working in Scrum teams with experts on well-defined goals.
• I have a deep sense of empathy, which fuels my passion to craft honest and meaningful experiences for people.
• I embrace experimentation and I'm not afraid to be wrong.
• I'm a creative, big-picture thinker obsessed with crafting the details.
• I have a solid foundation in design principles and typography.

Tools

Figma   ·   Cursor   ·   OpenAI   ·   NotebookLM   ·   Gamma   ·   Miro   ·   Jira   ·   Notion   ·   Maze   ·   Baymard   ·   Slack   ·   Lookback   ·   Post-its   ·   Pen & Paper   ·   Brown Paper   ·   Hotjar   ·   Principle   ·   UsabilityHub   ·   Productboard   ·   Photoshop   ·   Illustrator   ·   OmniGraffle   ·   Google Analytics   ·   GoogleOptimize   ·   Lighthouse   ·   Axure   ·   Confluence   ·   MacBook Pro

Successes

1. Increased transactions by 8.9% (on desktop), with the redesigned navigation for Wehkamp Retail Group.
2. Increased efficiency of the planning department, with a custom-built planning application for Veneta.com. More incoming calls were handled and more advisor and installation appointments could be scheduled with hardly any errors.
3. Increased conversion by 12,9% overall (on all devices), with the redesigned Shopping basket & Checkout funnel for Veneta.com.
4. Increased conversion by 168% in just three months, through a redesigned application process and an improved Saxion.edu website for international students.

Case study

Sentient Design & AI

AI and intent-driven UX.
Explored using Wehkamp as the reference platform.

I started working on this concept in 2025, exploring how AI could enable a different way of interacting with e-commerce—one that is guided by user intent rather than traditional interface structures.

Why this project

From earlier e-commerce work, I noticed how platforms evolve over time. As functionality grows, navigation, search and filter become richer and more capable, but also more complex.

In practice, users are exposed to a lot at once: categories, filters, sorting options, campaigns, recommendations and product details. While all of this is valuable, it can make it harder to quickly move toward the right result—especially when users are still narrowing down what they are looking for.

This project explores whether AI can support a fundamentally different interaction flow—one where intent becomes the primary input, allowing the system to guide users more directly toward relevant options instead of requiring them to manually navigate each step.

The hypothesis was that this approach could make shopping journeys faster, more focused and easier to move through, while still keeping users in control.

Project setup

This project was approached as an exploration at the intersection of UX, design systems and AI.

Instead of starting purely in Figma, I set up a design system and styleguide directly in code. Using the Figma MCP server, I brought design structures into Cursor and translated them into React components, design tokens and a shared icon library.

I worked in Cursor with multiple large language models and created extensive prompts to control structure, interaction logic and consistency across the system. An OpenAI API key was configured to power intent detection and response logic.

While the system is designed to learn from interaction data over time, all behavior is constrained by explicit UX rules to ensure predictable and understandable interactions.

Starting from the existing platform

The prototype intentionally starts from the existing Wehkamp e-commerce interface.

This makes it clear that Sentient Design is not a visual redesign of the platform, but a new interaction model layered on top of it. The familiar interface remains visible underneath, allowing users to stay oriented and return to the classic experience at any moment.

A layered and focused experience

Sentient Design is implemented as a semi-transparent overlay that introduces a clean, focused interaction layer.

Instead of presenting all options at once, the interface reduces visual noise and supports one task at a time. Flows and screens are intentionally different from traditional e-commerce pages and are shaped around intent rather than structure.

For the visual language, I chose an Apple-inspired Liquid Glass aesthetic. This emphasizes clarity and depth, while maintaining a clear connection to the underlying website.

Intent-driven interaction model

At the core of Sentient Design is an intent-driven interaction model.

I defined ten intents to represent common user goals within an e-commerce context.

• Explore
• Inspire
• Refine
• Compare
• Decide
• Deal
• Delivery
• Returns
• Support
• Account

Each intent is linked to one or more predefined UI patterns. To keep the system coherent and understandable, the interaction model was deliberately limited to six patterns.

• Card Feed
• Inspiration
• Quick Filter Panel
• Info Panel
• Shop the Look
• Support FAQ

Based on detected intent and context, the AI selects the most appropriate pattern. Multiple patterns can belong to a single intent. Pattern selection follows strict rules, while the underlying model is designed to learn from interaction data over time.

Design decisions and refinement

One of the main challenges in this project was shaping how the system proposes next steps.

Early iterations showed that follow-ups could easily become too specific, which sometimes led to assumptions that did not fully match the user’s intent.

By keeping follow-ups more generic, the system supports progress without forcing direction. Users remain free to explore or adjust course, while the interface continues to provide guidance.

Dashboard and insights

Alongside the user-facing interface, I designed a dashboard to observe how the system behaves over time.

The dashboard shows detected intents, selected UI patterns and follow-up usage. This makes it possible to identify patterns in user behavior and understand how the AI supports different types of shopping journeys.

Final thoughts

Sentient Design demonstrates how AI can add practical value to e-commerce by making interactions faster, more focused and easier to navigate—especially in moments where users are still exploring or deciding.

By responding to intent and context, the experience becomes more supportive and more efficient, without overwhelming users or taking control away from them. Early signals from the MVP suggest that this approach helps users move forward with greater clarity and confidence.

While exploratory in nature, this project shows how sentient, intent-aware interaction can complement existing e-commerce platforms and points toward a future where shopping experiences adapt more naturally to the needs of the user.