Join us for a nice breakfast and mingle with other people in the mingle area

Welcome to the conference!

Working with AI can often feel intimidating and opaque, but thoughtful UX can change that. This talk highlights how Kent’s team used timeless design methods to create more intuitive, informative, and engaging consumer AI experiences with data visualization. Drawing on his work with Google Health’s (formerly Fitbit) Personal Health Coach, Kent will walk through the process of integrating visual data into a chatbot environment. He will share guiding principles and practical takeaways for anyone building human-centered AI data experiences, created by humans, for humans.

What you’ll learn:

• A behind-the-scenes look at integrating co-design and UX research into AI workflows.
• Key lessons learned when applying data visualization to generative AI products.
• Why design craft, attention to detail and originality matter now more than ever.

Lets grab a cup of coffee and something to eat!

Describe your design persona using a template, introduce yourself to the other participants.

Traditional design patterns assume a predictable system – but while generative AI is built on predictions, it is anything but predictable. As a psychologist and a designer working in Zendesk, an AI-first company and one of OpenAI’s top 30 customers, I’ll walk you through some of the most important new design patterns around AI. We’ll cover disclosing AI outputs to users, optimal levels of AI anthropomorphism, managing expectations, as well as ethical and psychological aspects, including common biases. Expect real-life use cases and fresh points of view.

Whether you're a designer, developer, or strategist, we've all been there: advocating for inclusive design only to hear, "It's not on the roadmap yet." Being the lone voice trying to ensure intelligent technologies respect human dignity is exhausting, especially when ethical, accessible design is treated as a "nice-to-have" or a task delayed for the next sprint.

That lack of buy-in carries real risk. With the EAA in full force since June 2025, and AI scaling at unprecedented speeds, a "fix it later" strategy is a bigger gamble than ever. Without a shared framework to build ethical technology, we risk designing an unsustainable future that excludes the very diverse communities we aim to uplift while rendering our products invisible to modern AI search agents.

When you build clear semantic hierarchies for screen readers, you are natively optimizing your content and code for Large Language Models. Aligning accessibility with AI optimization creates a massive growth engine: our client’s AI traffic grew nearly three times faster after implementing our framework.

This year, you're invited to the Contrast Clinic, an immersive experience that bridges the gap between human creativity and intelligent technology. Together, we will prove that ethical accessibility isn't a checklist or a roadblock, but a powerful catalyst for AI visibility, innovation, and our ultimate competitive edge.

A brief lands on your desk, and states a presenting issue. But it is almost always wrong about what the problem is. In sex therapy, it is the same: erectile dysfunction, low desire or vulvodynia, the real issue lies deeper.

My session shares a three-part diagnostic framework inspired by psychosexual assessment to change how we challenge client briefs, ditch lazy templates and over-automated solutions, in exchange for rigorous, human-centred diagnosis.

You'll come away from this session with at least one brave question you can ask when you're next briefed on a project.

AI has made producing solutions almost free. The constraint is no longer "can we build it?" but "should we?". Building the wrong thing faster isn't innovation, it's a waste of resources, team energy, and our users' trust.

This workshop is a hands-on introduction to the Opportunity Solution Tree, Teresa Torres' method for anchoring product decisions in real customer evidence before a single prompt is written. You'll try the method on a concrete case and leave with:

• An understanding of the tree's structure: outcome → opportunities → solutions → assumption tests

- A feel for the hardest part in practice: telling genuine customer opportunities from solution ideas in disguise

• The confidence to sketch a rough tree with your own team, and know what to read when you get stuck

Government projects integrating AI decision making into their user journeys have taken off.

But have we done enough work to understand what AI automation really looks like in high risk government spaces and if, when and where we should keep humans in the loop?

We need to do more with less, now more than ever. In the context of lower UK economic output, but the higher demand for public services (with larger populations) we need to make sure we use AI to get our decision making right, keep costs down, reduce mistakes and stop the potential public scandals caused by AI inaccuracies/a lack of human oversight.

Laura will share learnings from working in an exclusively AI-orientated team in government, playing back the practical challenges of integrating AI decision making in previously human-led spaces (internal to the organisation) and what potholes we need to avoid.

The session will include recommendations on appropriate uses and considerations for the audience to take away and apply in their own work places.

AI agents are starting to know more about us than any technology we've used before. They remember what we say, understand our habits, and increasingly make decisions on our behalf. That raises an important question: how do we design AI that helps people without quietly influencing or manipulating them?

This talk explores the fine line between AI assistance and manipulation, revealing how the way we design AI shapes whether it empowers people or influences them in ways they may not even notice.

Key takeaways
- Help vs. Hijack: A practical way to tell when AI is genuinely helping users versus nudging them toward someone else's goals.
- Spotting Agentic Risks: Learn how to identify UX dark patterns unique to AI agents before they reach users.
- The AI Review Kit: A lightweight framework for evaluating AI experiences from an ethical and human-centered perspective.

Fill up does cups and shake your legs!

We tend to think of design process as a set of steps to follow. But process is never neutral. What gets celebrated, what gets skipped, who gets involved, and how decisions get made all shape the culture a team actually experiences.

In this talk, I'll share how we redesigned the design process at Fortnox for a growing team of 60+ designers, not as a workflow to enforce, but as a way to reinforce the culture we wanted to build. This shapes everything from collaboration and decision-making to the responsible use of AI.

Key takeaways:

• Why process shapes culture more than values statements do
• How to design processes that reinforce desired behaviors
• How responsible AI adoption starts with ways of working, not policies

I’ve built design organisations for a long time, and the same questions keep coming back. Where should designers sit for the company to get the most out of their work? How should teams work together? Who gets to decide about the user experience, and how do we balance what users need with what the business needs? And how do we give designers room to grow, do good work, and feel good doing it?

Then I spent this year building a product with AI, hands on. When anyone can produce a prototype, an interface or working code in a matter of days, roles change, both within design and around it. The way we collaborate has to change at its core, and so does what we expect a junior and a senior designer to do. Those old questions need new answers.

I’ll share where I’ve landed, and why I think we might finally move from opinions to insights. For real this time.

Time for lunch and find someone new to talk to!

Let's try a framework which can be used to decide if you should prompt or not for a given task. We work two by two and then present for the whole group.

Too many teams treat user research and A/B testing as competing methodologies — one for the qualitative believers, one for the data people. But conviction and evidence aren’t opposites. Good research earns you the confidence to make a strong design call, and strong hypotheses make for better tests. In this session, we’ll explore how user research and A/B testing work best as a loop — not a debate — and why the teams that ship the best products aren’t the ones who test everything to death, but the ones who know when to back their instincts and when to let the data speak.

Key takeaways

• Why designing with conviction produces better tests — and better outcomes
• How to use research to build hypotheses, not just validate assumptions
• Where A/B testing alone goes wrong — and what research catches that data can’t
• How to run the research → design → test → learn loop in practice
• When to trust your instincts, and when to let the numbers win

We know that users with disabilities are simply end users too. Some use hardware and software every day to interact with your designs (think screen reader, keyboard, zoom magnification, etc.). Once you learn about how diverse human experience is, it becomes an exciting opportunity to innovate and grow your skills. The Web Content Accessibility Guidelines (WCAG 2.2) as can be overwhelming, where you don't know where to start, or you feel you might get it wrong! I'm a former UX Designer turned inclusive design advocate for 15+ years. In this workshop, I'll share:

• real user stories of what people with disabilities need
• examples of beautiful and elegant designs that are also accessible and meet global standards (WCAG, EN 301 549, etc.)
• a fun, easy framework to apply when you're designing products (W3C Accessibility Roles and Responsibilities Mapping (ARRM))
• a team exercise called the "Decision Tree" for identifying the shared responsibility for each WCAG requirement (UX or Visual Designers, Developers, Content Authors).

Today’s UX researchers are expected to wear more hats than ever before. Beyond conducting research, they are often asked to influence strategy, manage stakeholders, mentor others, adopt AI tools, and deliver impact at increasing speed.

In this interactive masterclass, two experienced UX research leaders share practical lessons from their careers across government, finance, healthcare and digital transformation. Participants will explore the hidden cost of context switching, experience first-hand how multitasking affects performance, and reflect on the skills that help researchers create influence and impact in complex organisations.

Through facilitated discussion, reflection exercises and peer learning activities, attendees will leave with practical approaches for protecting focus, navigating organisational dynamics, leveraging AI effectively, building confidence, and increasing the strategic value of research.

Key Takeaways

• Understand the impact of multitasking and context switching on research quality and effectiveness
• Learn practical strategies for increasing influence and stakeholder engagement• Explore how AI can support research workflows while preserving human judgement and empathy
• Reflect on approaches to mentoring, career growth and building confidence as a senior practitioner
• Develop a personal action plan to improve effectiveness and impact within their organisation

Building with AI takes what good product people already have: a vision, a plan, and the taste and judgement to steer. In this hands-on hour you'll put yours into an AGENTS.md, the file Claude Code reads before it builds, so what you make comes out like you and not AI slop.

You'll leave with:

• a working prototype, built in the session and shaped by your AGENTS.md

- your own AGENTS.md to keep, use and adapt on your next project

• a method that lasts as the tools change

For UX and product people who have used Claude to build or design and want to go further. You'll need a paid Claude plan (Pro or Max); setup steps arrive before the workshop.

Designing something that works isn't the same as designing something that's right. You can hit every metric — but are those metrics right?

Through a real-world example from building an e-commerce returns portal, we'll explore how chasing the wrong metrics can damage businesses, people, and the planet — and why sustainable design starts with asking better questions.

We'll challenge core UX assumptions about friction and conversion, learn to apply ethical techniques to the design process, and explore how to apply those same principles when shaping AI products responsibly.

Software has never been cheaper to build, which makes it easier than ever to build things nobody needs.

With a background in both artificial intelligence and human–computer interaction, Kim looks at what the evidence says about using LLMs in place of real users. Having worked on both sides, she sees a real danger when teams ask the AI what their users think instead of asking the users. She'll also share the workflows she uses to set up AI as a research assistant: one that helps you run your research while leaving the judgement to you.

You'll leave knowing when a model is a reasonable stand-in, when it isn't, and how to get more out of the research you're already doing.

Maybe time for a energizer?

How do you make a digital experience feel alive and human, moving beyond the screen to spark a real connection with the user?

In this talk, we take you through our journey of designing for our most honest and demanding audience: children. When we built the login experience for NRK Super, we couldn't rely on text or standard conventions. Instead, we used gamification, nudging, and storytelling, turning it into a login flow that children actually want to complete again and again.

We’ll share our lessons in extreme accessibility and inclusive design that apply to all users, demonstrating how sometimes adding in extra steps and intentional friction can actually drive higher completion. It is a reminder that the most impactful products are those that still know how to spark wonder.

As AI becomes increasingly integrated throughout the design process, this talk focuses on the deep, intentional, and strategic craft that AI cannot replicate. We believe that by utilising play, mischief and wonder, we can reclaim the sense that technology is still magic.

Bring a real UX problem or goal. You'll unpack the assumptions inside it, weigh the evidence you already have and turn a belief into a hypothesis that could actually be proven wrong - then map out the cheapest test/s that could kill it.

You'll leave with one testable hypothesis and a first test you could run this week.

Too many chatbots make people want to escape to a human. But the problem isn’t always the technology — it’s often the design. 

In this workshop, Michael shares practical techniques from designing Länsförsäkringar’s new LLM-based chatbot, showing how tone, behaviour, language and conversational structure can transform the user experience.

You’ll get five hands-on techniques you can use to design conversations that feel clearer, more helpful and more human — and make your chatbot worth talking to.

Learn how to use AI to make UX writing more efficient, consistent, and scalable – without generating AI slop. In this hands-on workshop, you’ll explore how to build AI skills and agents that can review UX copy, apply content guidelines, identify inconsistencies, and support better writing decisions. Learn from an industry practitioner, try new skills as you learn, and leave with actionable takeaways.

AI products are becoming deeply integrated into everyday life, yet most users still struggle to understand what these systems can do, when they fail, and whether they should trust them at all.

This talk explores how designers can shape trust in AI products through interaction design, transparency, feedback loops, and behavioral UX patterns, not branding or visual polish alone.

Drawing from real product experience, UX strategy, and research on cross cultural digital interfaces, the session will examine how trust emerges through predictability, explainability, user control, and the design of failure itself.

Key take aways:

• Design patterns for creating trustworthy AI experiences
• Common UX mistakes that reduce trust in AI systems
• How to communicate uncertainty and limitations effectively
• Why designing for failure matters more than designing for success
• How cultural expectations shape trust in AI interactions across different users and societies
• The evolving responsibility of designers in AI product development

Most designers feel behind on AI, and the honest answer is that everyone is. New tools appear every week, and the gap between reading about AI and actually trying it is where most of the anxiety lives.

Over the past year, Terry has run AI and product design community events in Stockholm, bringing together around 300 people to experiment with how designers learn in a field that won’t sit still. In this talk, she shares what worked, what didn’t, and what she found: tools can be learned alone, but judgment grows best together. And to shape a sustainable future with AI, we first need to understand it well enough to question it.

What you’ll learn:

• Why “learning AI” means different things to different people, and how to clarify it for yourself and your team

- A breadth-to-depth approach that anchors learning in real problems, not tools

• Honest lessons from running a community through three stages, and lightweight formats to bring back to work

Present your top 2 moments of SXC, and if you want to keep the discussion going, paste your LinkedIn-url to the Miro board so the other participants can connect with you. 

Lets get some last minute coffee and start getting excited about the last part of the conference.

When AI can generate interfaces, prototypes and working products in minutes, the role of design begins to change.

What should designers stop doing? What must design continue to own? How do we protect craft, judgement and human responsibility when production becomes increasingly automated? And how will future designers learn when AI performs many of the tasks that once helped people develop their skills?

This panel brings together different perspectives from design, leadership and business for an open discussion about the future of experience. Not to predict exactly what will happen, but to explore the choices we need to make now.

Creativity is often framed as a skill: something you can learn, optimise, and scale. But in practice, most creative work doesn’t fail for lack of ideas. It fails because we don’t know how to handle uncertainty, tension, and the dynamics around ideas.In this talk, the Norwegian drag queen Miss Beehives takes the audience on a journey through the worlds of drag and design, revealing the surprising parallels between the two. Through personal stories, creativity, performance, and point of view, the talk explores how ideas come to life when we dare to draw inspiration from unexpected places and when we allow ourselves to stand in what makes us different.This talk will be honest, personal and thought-provoking.

Lets round up the conference with some final words.

Wow - an amazing day to finish of with a after conference with new friends and good discussions!

Grab a beer from your refrigerator and mingle with other digital participants.

This session is unmoderated, and you will be able to talk with people on your own.