This Week’s Updates

Enabling the Team

Redesigning Workflows For AI by Jakob Nielsen
AI creates more value when teams redesign the whole workflow instead of just speeding up one task at a time. Removing handoffs, automating the glue work, and shifting people toward higher-judgment exceptions can unlock bigger gains than isolated productivity wins.

Mockups Were Never The Hard Part by Luke Wroblewski
AI makes it easier for anyone on a team to generate mockups, but the real design challenge is still creating coherent products with clear intent, shared mental models, and strong cross-functional alignment.

Product Direction

My Proven Success-Metric Framework by Büşra Coşkuner
Success metrics get clearer when teams start with the user journey, identify the turning-point steps that matter most, and then define signals that show whether those steps are working. The GSM framework helps turn vague goals into measurable progress, making it easier to choose better metrics even in B2B or low-data environments.

Competitive Differentiation Is Poison by Ravi Mehta
Product strategy gets stronger when teams stop asking what makes them different and start asking what makes them better for customers. Real advantage comes from improving the things people value most and building strengths that compound over time, not from inventing differences that sound distinctive but do not improve the product.

Continuous Research

Your Best Work Won’t Speak For Itself: Tried-And-Tested Sales Tactics For Researchops Professionals by Glenn Familton
ResearchOps work gets more traction when teams explain it in terms that leaders care about, not just in terms of activity or effort. Framing the need, the solution, and the business benefit makes it easier to win buy-in, build champions, and get important infrastructure work understood before its impact is fully visible.

User Personas Of Consequence by Chris R Becker
Personas create more value when teams treat them as a rigorous representation of real people, not a fast template to fill in. Slowing down, adding more inclusive context, and resisting AI-generated shortcuts can help teams build personas that support better design decisions instead of generic user fiction.

Continuous Design

Designing Trust For Agentic AI In Enterprise Software by Brooke Bell, Shrut Kirti Saksena
Agentic AI works better when teams match the interface and level of autonomy to the risk and complexity of the task. Clear previews, visible reasoning, checkpoints, and reversible actions help users trust AI enough to use it without losing control when the stakes are higher.

The Last Interface by Joshua Leigh
As agents take on more of the navigation and execution, design work shifts from arranging screens to defining the rules, guardrails, and defaults that shape what users get. Teams will need to design simpler core interfaces, support outcome-first workflows, and make sure dynamically generated experiences still stay usable, accessible, and coherent.

Continuous Development

Harness Engineering For Coding Agent Users by Birgitta Böckeler
Coding agents become more useful when teams surround them with clear guidance, fast feedback, and checks they can use to self-correct before humans step in. Strong tests, linters, architecture rules, and review loops help reduce repeated mistakes, improve code quality, and make higher-autonomy AI delivery safer to trust.

From T-shape To Comb-shape: How Developer Knowledge Needs To Evolve In The AI Era by Luca Mezzalira
As AI takes on more of the routine implementation work, developers create more value when they can judge trade-offs across architecture, domains, and system constraints rather than relying on narrow technical depth alone. Building knowledge across several important areas makes it easier to direct agents well, catch bad assumptions earlier, and focus human effort on the parts of software that matter most.

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Apply Now To Become A Speaker For Our Next Events!

We’re always looking for real-world case studies from product, UX, design, and engineering leaders who are changing how modern product development works.

Share what you tried, what worked, what didn’t, and what others can learn from your experience. Apply to speak here: https://uxdx.com/speak/

UXDX San Francisco 2026

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Video Of The Week

AI in Learning & UX Design: Augmenting, Not Replacing

AI is already changing how teams work, but the biggest gains are not always coming from full automation. Often, the real value is in smaller process improvements that save time, improve quality and still keep humans firmly in the loop.

In this talk, Mike Brown, Head of Design at Barclays, shares how his team tested AI across internal learning workflows, what produced measurable gains, and where the tools fell short. A practical watch for anyone trying to adopt AI inside complex or regulated organisations, where speed matters, but accuracy, oversight and risk management matter even more:

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

This Week’s Updates

Enabling the Team

Finally, The Handoff Is Dead by Luke Wroblewski
AI does not fix collaboration on its own. Teams work better when design decisions, development standards, and project context are carried in a shared system so people can contribute in parallel without losing alignment or creating handoff waste.

AI Layoffs: The Leadership Choice Behind Every Headline by Pim de Morree
AI layoffs dominate headlines, but IKEA proves there's another way. When AI could replace 57% of their work, they chose reskilling over firing.

Product Direction

Outcomes Vs. Outputs: What's The Difference And Why Does It Matter? by Teresa Torres
Product teams make better decisions when they measure the impact of what they ship, not just whether it shipped. Choosing outcomes that reflect real customer value helps teams avoid feature-factory thinking, focus discovery on the right problems, and stay accountable for results instead of delivery alone.

The AI Documentation Paradox by Florian Bonnet
AI makes it easier to produce polished documentation, but that does not mean teams are thinking more clearly or making better decisions. Shorter, sharper docs that lead with the decision and separate judgment from evidence are more useful than longer documents that signal effort without changing the quality of the thinking.

Continuous Research

The missing Seat At The Frontier Team Table by Martin Linde Danty, Rabeeza A., Anne Klærke-Olesen, Madhumay Sinha, and Michael O’Sullivan
AI evaluations work better when researchers help define what “good” looks like before teams start measuring it. Bringing qualitative insight into scenarios, assumptions, and success criteria helps teams catch unrealistic abstractions, avoid misleading metrics, and build AI features that perform well in real workflows instead of just looking good in evals.

The Research Operating System Too Few Are Building: Why “I-Me-Mine AI” Isn't Enough by Kate Towsey
Research teams will get more value from AI when they stop treating it as an individual productivity tool and start building shared systems around where it should be used, where it should not, and what good looks like. Clear standards, guardrails, and workflows help research scale more safely and make it easier for the function to create visible organizational value instead of isolated efficiency gains.

Continuous Design

What Designers Actually Struggle With On Product Teams by Laura Klein
Designers create more impact when they are brought in early, can connect user needs to business outcomes, and have clearer ways to work with product, engineering, and stakeholders. Alignment, influence, and role clarity matter as much as craft when teams are trying to shape better product decisions.

Google Says “Vibe Design” Is Here, But It Didn’t Pass My Vibe Check by Elvis Hsiao
AI can take on more of the making, but designers still create value through problem framing, taste, judgment, and deciding what is worth building in the first place. The pressure is real, but the stronger response is to use AI to extend your range while protecting the thinking skills that generic outputs still cannot replace.

Continuous Development

The Golden Rules Of Agent-first Product Engineering by Jina Yoon
Agent-first products work better when teams give agents full product capabilities, expose the right abstraction layer, front-load the context every session needs, and encode product judgment into the system. Treating agents like real users through dogfooding, trace review, and evals helps teams catch fragile experiences earlier and improve trust before bad behavior scales.

Explaining, Understanding, And Data Compression by Anton Zaides
Technical leaders are more effective when they explain complex thinking in a way others can actually absorb. Clearer communication, fewer unnecessary details, and checking what people understood can reduce confusion, speed up alignment, and make feedback more useful.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Managing Your Career In The Age Of AI

Have You Read My E-Book Yet?

AI is changing the shape of product, UX, design and engineering careers. Junior-level tasks are being automated, expectations are shifting, and the skills that help people progress are becoming less about output and more about judgment, influence and cross-functional thinking. My ebook, Managing your Career in the Age of AI, breaks down the 4 levels of career thinking, the shift from pyramid to diamond-shaped teams, and why the old T-shaped skills model is giving way to a more connected, comb-shaped approach.

Download the ebook to understand where you are today, what skills matter next, and how to position yourself for the AI-powered world of work.

UXDX San Francisco 2026

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Video Of The Week

From Cross-Functional To Cross-Purposes:
Why Collaboration Falls Apart Over Time

Cross-functional teams do not fall out of alignment because people stop caring about collaboration. More often, the problem is hidden in the structures, habits, and language teams use every day.

In this talk, Mihaela Draghici shares what she learned from embedding business stakeholders into hybrid product teams and why even strong collaboration frameworks can slowly break down. A practical watch for anyone trying to keep product, business, and engineering aligned beyond the first workshop, kickoff, or team restructure:

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

This Week’s Updates

Enabling the Team

Who In The C-Suite Should Own AI? by Toby E. Stuart
AI initiatives work better when companies stop treating them as the responsibility of one function alone. Clear ownership, shared accountability, and tighter coordination across technology, operations, risk, data, and finance help organizations move faster without creating gaps in decision-making or control.

I’m An Introvert. This Is How I Get Myself To Speak Up. by Wes Kao
Prepare go-to phrases to insert yourself in meetings, ask a colleague to keep you accountable, and other tactics I personally use to get myself to speak up.

Product Direction

Messy Docs As Helpful Pattern by John Cutler
Teams often work better when they use messy, evolving docs to keep context visible, revisit assumptions, and connect signals that do not fit neatly into tickets. The trick is not forcing the mess away, but creating simple routines and shared language so others can understand the work without flattening how it really happens.

How To Close Your Confidence Loop by Tim Herbig
Product decisions get stronger when teams can clearly connect what they are building to the behavior change they expect and the business goal it supports. AI can help fill in the story faster, but confidence only becomes real when the team can explain and defend each link in that chain for themselves.

Continuous Research

Don’t Design For Average Users by Jakob Nielsen
Research gets more useful when teams look beyond the average user and study the needs of higher-value and more complex segments separately. Better segmentation can reveal where simple experiences matter most, where advanced workflows create disproportionate value, and why one-size-fits-all decisions often miss both groups.

Winning The Game Of Broken Telephone: A Blueprint For Evaluating AI Across The Research Pipeline by Lindsey DeWitt Prat
AI research workflows get more reliable when teams define what accuracy means for their context, compare tools side by side, and keep checking where outputs start to drift from the source. Better evaluation makes it easier to catch hidden errors early, stay closer to the participant's meaning, and stop polished outputs from creating false confidence.

Continuous Design

How I’m Dealing With The Pressure To Adopt AI As A Designer by Martin Wright
Teams do not need to adopt every AI tool at the speed of the hype cycle. Experiment widely, deploy narrowly, and use AI where it improves the work without outsourcing the judgment, synthesis, and craft that make the work valuable in the first place.

Something Big “Might” Be Happening by Elvis Hsiao
AI can take on more of the making, but designers still create value through problem framing, taste, judgment, and deciding what is worth building in the first place. The pressure is real, but the stronger response is to use AI to extend your range while protecting the thinking skills that generic outputs still cannot replace.

Continuous Development

Agents Don’t Know What Good Looks Like. And That’s Exactly The Problem. by Luca Mezzalira
AI agents can make code behave correctly against a spec while still making systems worse in production. Teams need guardrails around architecture, scale, resilience, and ownership so faster generation does not create software that passes tests but fails in the real world.

Every Layer Of Review Makes You 10x Slower by Avery Pennarun
Shipping gets slower when every extra layer of review adds more waiting time to the work. Teams move faster when they reduce unnecessary approvals, build quality into the system earlier, and create smaller, better-defined components that need less coordination to change safely.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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The First Speakers Of UXDX San Francisco

5 - 6 November 2026

If you missed our announcement on stage at UXDX, here is the big news: UXDX San Francisco 2026 is locked in for November 5–6. Our core theme, Becoming AI Native, will tackle how product, design, research, and engineering teams can move past the hype cycle and embed AI deeply into their operational rhythm.

We’re launching with a stellar first look at our speaker lineup, featuring product and design leaders from Snap Inc., ŌURA, Expedia Group, Target, and Verizon. Early tickets and the first version of the agenda are now live. Be part of our West Coast event and grab your ticket today: Get your tickets for UXDX San Francisco 2026

UXDX San Francisco 2026

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Use ‘NEWSLETTERSF26’ at checkout to get 10% off the price!

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Video Of The Week

Bridging the Gap:
How Product, UX, and Dev Can Build AI-Native Products Together

AI-native products need more than strong models. They need product managers, designers, and engineers working from a shared understanding of what is technically possible, what users actually need, and how decisions should be made along the way.

In this conversation, Carsten Wierwille, Global VP of Product & Design at HTEC, and Jacobus Kok, VP of Product at Priceline, explore how teams can bridge the gap between bottom-up machine learning approaches and top-down product and UX thinking. A practical watch for anyone trying to build AI products without creating new silos in the process.

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

This Week’s Updates

Enabling the Team

Demand Mix, Shaping, And AI As (Dys)function Multiplier by John Cutler
Orgs spend a lot of time talking about dependencies, intake, predictability, “discovery,” capacity, and so on. But far less time talking about the harder questions around the mix of demand teams are dealing with, and how they are actively involved in shaping that demand.

Positional Leadership: The Emperor's New Clothes Of Management by Joost Minnaar
Teams work better when authority comes from competence and trust, not just title or rank. Clear roles, psychological safety, and decision-making closer to the work help people speak up sooner, reduce distortion as information moves upward, and keep leadership grounded in reality. 

Product Direction

Product Management On The AI Exponential by Cat Wu
Product teams can move faster when they replace long planning cycles with short experiments, demos, and evals that make ideas tangible early. As models keep improving, teams need simpler implementations, faster feedback loops, and the habit of revisiting what is already built as new capabilities change what good looks like.

5 Ways Product Discovery Breaks Down by Itamar Gilad
Product discovery breaks down when teams fast-track “must-have” features and use plans as a substitute for clear outcomes. Stronger goals, better evidence, and fewer roadmap assumptions help teams validate ideas properly and focus on business and user results instead of just shipping. 

Continuous Research

Deprivation Studies: Take The Product Away To Reveal What Users Truly Need by Jakob Nielsen
Standard usability testing can show where users struggle, but deprivation studies reveal what they would actually miss if a product or feature disappeared. Watching the workarounds people create helps teams separate real value from habit, clutter, and lock-in, making it easier to cut bloat and protect the parts that truly matter.

A Practical Guide To Structuring ResearchOps Through Organizational Change by Carolyn Morgan
ResearchOps works best when its structure fits the organisation around it, rather than following a fixed model. Choose clear ownership, consistent standards, and the right mix of centralised and embedded support to help research scale through change without losing quality.

Continuous Design

Agentic UX: 7 Principles For Designing Systems With Agents by Alexandra Vasquez
Agentic systems work better when teams fix messy workflows, capture the right context, and keep automation inside familiar product patterns instead of bolting on separate AI surfaces.

Field Study: Prototypes Over Mockups by Édouard Wautier
Teams can make better design decisions when they test behaviour in real, runnable prototypes instead of debating static mockups. Working in code with shared components helps expose edge cases earlier, tighten feedback loops, and reduce the gap between what gets explored and what actually ships.

Continuous Development

Comprehension Debt - The Hidden Cost Of AI-Generated Code by Addy Osmani
AI-generated code creates hidden risk when teams can merge changes faster than they can truly understand them. Strong testing still matters, but teams also need clear intent, meaningful review, and enough system knowledge to judge whether the code is actually right, not just syntactically correct.

Engineering Managers Are Going To Hate Openclaw by Anton Zaides
Proactive AI agents can create real value, but they also raise the risk of teams shipping automation before they have thought through reliability, guardrails, or the blast radius of mistakes. Engineering leaders need to get involved early so hype does not turn into agent features that act too confidently and create more damage than value.

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Shoutout To Our Partners In Berlin!

UXDX EMEA 2026 Happens Next Week.
Don’t Miss Our Partners:

UXDX EMEA 2026 kicks off next week in Berlin, supported by partners helping teams research, design, test, and build better products: Optimal, UXIA, Baymard Institute, TestingTime, Leadium, and AccessiBe.

• Speak to one of Baymard Institute’s reps to get an exclusive UXDX discount on any Baymard plan subscription. Head to their booth at UXDX EMEA or book a meeting using this link: https://calendly.com/julie-baymard/30min?month=2026-05

• Outside of the event, UXIA is also running a UX Innovation Session. You can find out more here: https://www.uxia.app/ux-innovation-session

A huge thank you to all our sponsors and partners for helping make UXDX EMEA possible!

UXDX San Francisco 2026

Use ‘NEWSLETTERSF26’ at checkout to get 10% off the price!

Click here and book San Francisco!

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Video Of The Week

From Output to Outcome:
Driving Cultural Change in Product Teams

This week, we’re highlighting an insightful UXDX EMEA 2025 session focused on one of the hardest shifts in product management: moving from output to outcomes. Jay shares how Eneco successfully tackled this challenge by transforming their culture alongside their KPIs.

The session explored what it really takes to build a customer-focused culture across product, design, and engineering. Jay openly discussed the breakthroughs and lessons learned while implementing frameworks like ‘Opportunity Solution Trees’ to keep teams aligned on user value. If you’re trying to move your organization away from feature-factory thinking and toward true customer centricity, this talk is a must-watch:

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

This Week’s Updates

Enabling the Team

Organizational Silos: What The Titanic Teaches Us About Information That Never Arrives by Joost Minnaar
Silos are usually created by structure, not bad intent, when teams optimize for local metrics instead of shared outcomes. Shorter paths between signals and decisions, more transparency, and cross-functional ownership help important information reach the right people before delays turn into bigger problems.

Technical Leaders Make These 3 Common Storytelling Mistakes by Wes Kao
Technical leaders lose people when they overload stories with details, backstory, and caveats instead of making the point clear first. Simpler stories, shorter examples, and a stronger hook make it easier to hold attention, build buy-in, and share the deeper details only when they are needed.

Product Direction

The “Be More Strategic” Trap by Stephanie Leue
Telling someone to “be more strategic” is not helpful unless teams make clearer what strategic thinking actually looks like in practice. People create more impact when they connect initiatives to business context, explain work in terms leaders care about, and are given the space to think beyond immediate delivery.

You Don’t Need Another Prioritization Framework: Just These 4 Components by Ant Murphy
Prioritization works better when teams stop searching for one perfect framework and start judging work through impact, effort, urgency, and confidence. The better decisions come from linking choices to goals, revisiting time-sensitive opportunities, and being honest about what you still do not know.

Continuous Research

From Gatekeepers To Enablers: The UX Researcher's New Role In 2026 | Sponsored Content by Optimal
Research creates more value when teams use it to answer clear decision-making questions, not to slow work down or create the appearance of rigor. Standardising what you need to learn, using existing data where possible, and matching the method to the problem can help teams learn faster and ship with more confidence.

How To Become An AI Super User: Your Complete Guide | Sponsored Content (Dovetail) by Emily Brogan & Peter Wooden
Teams get more value from AI when they treat it as support, not a replacement. Build enough hands-on experience to develop good judgment, use AI to speed up research and execution, and keep humans responsible for quality, decisions, and catching where the output falls short.

Continuous Design

What Design Leaders Must Unlearn To Lead In An AI-first World by Arin Bhowmick
AI adoption is not just about giving teams new tools. Design leaders need to strengthen fundamentals, blur rigid role boundaries where needed, and treat trust, clarity, and reliability as part of quality, so that faster work does not lead to weaker decisions.

The Hidden Cost Of AI Prototypes That Are Made To Die by Allie Paschal
AI prototypes save time early, but they create extra work later when teams cannot extend, hand off, or reuse what they have made. Choose prototyping tools based on whether the output needs to validate an idea quickly or carry forward into real product development.

Continuous Development

What We Wish We Knew About Building AI Agents by Ian Vanagas
AI agents create more value when teams start with the simplest useful architecture, give the system strong product context, and treat observability and evals as core product infrastructure from day one. Better adoption comes from reliability, transparency, and solving real user problems, not from piling on more agent capabilities.

Software Engineering Calories: What Would Cal.ai Say About Your Product? by Anton Zaides
Teams make better delivery decisions when they measure the real weight of what they are shipping, not just count PRs or assume more code means more progress. Tracking input more honestly can help uncover bottlenecks, surface wasted effort, and show when the better move is not to build more, but to improve adoption or remove features.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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NEW: UXDX San Francisco 2026

We are expanding to the West Coast!

UXDX is heading to the West Coast. We announced it on stage last week at UXDX USA in New York, and now the newsletter community gets the first look: UXDX San Francisco 2026 is happening on 5–6 November. The sessions are around Becoming AI Native, focused on how product, design, research, and engineering teams move beyond AI experiments and start rebuilding the way they work.

The first speakers are already live on the website, and tickets are now available. If you want to be part of the first UXDX San Francisco event, you can check out the agenda and secure your spot here: https://uxdx.com/sanfran/2026/

UXDX EMEA 2026 Click here and book EMEA now!

UXDX San Francisco 2026 Click here and book San Francisco!

FREE COMMUNITY EVENTS 

Video Of The Week

How to Build an AI-Powered Product Development Process

This week, we’re resharing one of the most-watched sessions from UXDX USA 2025. Anthony Maggio, Head of Product at Airtable, shows how his team is using AI across the product development process, from interpreting user feedback at scale to improving strategic alignment and accelerating roadmap decisions.

The session gives a practical look at how AI can help teams turn complex data into clearer product choices, keep plans connected to business goals, and respond faster to changing customer needs. If you’re exploring how AI can move from isolated experiments into the operating rhythm of product management, this talk is well worth watching:

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

This Week’s Updates

Enabling the Team

Will Claude Code Ruin Our Team? by Justin Jackson
AI coding is collapsing role boundaries across design, product, and engineering, so teams need new ways of collaborating that preserve shared judgment and respect instead of letting tool access turn cross-functional work into turf war chaos.

How To Manage An Insecure Leader by Jeffrey Yip and Dritjon Gruda
Senior roles become unsustainable when expectations, scope, and availability keep expanding without being reset. Redesigning the job around clearer boundaries, better support, and more realistic priorities can help leaders stay effective without sacrificing their wellbeing.

Product Direction

Concepts I Use Every Day: BAPO by Jason Yip
BAPO argues that business and product strategy should drive architecture, ways of working and org structure, helping teams avoid inside out decisions where existing structure quietly limits what product strategy is allowed to be.

Stakeholder Management For Product Teams: Show Your Work, Don't Sell Your Conclusions by Teresa Torres
Stakeholder management works better when teams show how they reached a decision instead of defending a recommendation at the end. Sharing outcomes, opportunities, and test results as the work unfolds helps stakeholders contribute earlier, reduces opinion battles, and keeps discovery focused on solving the right problem.

Continuous Research

Accelerating Learning Velocity In Product Development | Sponsored Content (Capital One) by Jen Cardello
Research creates more value when teams use it to answer clear decision-making questions, not to slow work down or create the appearance of rigor. Standardising what you need to learn, using existing data where possible, and matching the method to the problem can help teams learn faster and ship with more confidence.

UX Questionnaires. Is It Rocket Science? by Maxim Kich
Design decisions get stronger when teams test them with structured user feedback instead of relying on instinct alone. Questionnaires can help quantify whether a flow, layout, or interaction is working, making it easier to validate assumptions before treating them as truth.

Continuous Design

Design Careers In The Age Of AI: Specialize Or Generalize? by Matheus Cervo
AI can help designers work across disciplines, but relying on it to replace real expertise can lead to weaker judgment and more generic output. The better use is to deepen specialist strengths while building enough understanding of adjacent areas to collaborate better and innovate with more confidence.

From Mockups To Momentum: How Vibe Coding Is Changing The Design Process by Jamie Stamer
Vibe coding shifts prototyping from static mockups to living behaviour, helping designers, engineers, and product teams surface edge cases, trade-offs, and AI uncertainty earlier, when learning is cheaper, and alignment is still easy to change.

Continuous Development

Design And Engineering, As One by Matthias Ott
We inherited our product processes from a 19th-century steelworks. Frederick Winslow Taylor separated thinking from doing, managers from makers, designers from builders – and a hundred years later, most digital product teams are still running on that model. The gap between design and engineering isn’t an accident. It was designed in. And it can be designed out.

Design Docs Considered Harmful by Lucas Fernandes da Costa
Teams learn more from a small prototype and a clear one-pager than from a long design doc written before the real constraints are known. Focus early writing on the problem, system boundaries, and hard-to-reverse decisions, then use implementation to discover the details instead of pretending they can all be known upfront.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
Click here to share an article

The Team Behind The Conference

Do You Know The Team Behind UXDX?

UXDX USA is happening right now, and UXDX EMEA is just two weeks away, so it feels like a good moment to introduce the small team behind the scenes. UXDX is built by a team focused on helping companies improve how they work so they can build better products with happier teams. Catherine and Rory lead the vision, Paula shapes the programme and speaker experience, Rafael keeps event operations moving, Ed grows the global community, and Arjan & Baosheng take care of the brand and communications.

If you’re at the event, come and say hello. Speak to Paula if you’re interested in speaking at UXDX, Ed if you’d like to bring UXDX to your city as a community ambassador, or anyone on the team if you just want to learn more about what we’re building!

UXDX EMEA
27 - 29 May, 2026, Berlin

Click here and book EMEA now!

10% Discount: 10NEWSLETTEREMEA26

FREE COMMUNITY EVENTS 

Video Of The Week

Driving Transformational Business Results:
The Role of Design Across the Org

Throwback to one of the most discussed talks of UXDX USA 2025! Unpack Daniela's perspectives on building world-class design organizations at some of the world's most iconic brands. Dive into how design at Capital One is helping drive meaningful value for the company and its 100+ million customers, and her thoughts on aligning design initiatives with broader organizational strategies.

The session also explored how design collaborates with business-critical functions to ensure a cohesive approach to product development and organizational growth that is customer-backed and grounded in business priorities. Watch the full session below:

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

This Week’s Updates

Enabling the Team

AI Doesn’t Reduce Work—It Intensifies It by Aruna Ranganathan and Xingqi Maggie
AI can make teams faster, but without clear boundaries, it also expands workload, increases context switching, and makes it harder to switch off. Leaders need stronger norms around pace, focus, and review so AI boosts performance without turning productivity gains into burnout.

Trios Of Generalists: How To Organise People by Jonah McIntire
AI shifts the balance from specialist handoffs to generalist judgment, making small teams of broadly capable people more effective, with trios offering the minimum structure for challenge, resilience and shared ownership without slipping into coordination drag.

Product Direction

Non-Code Moats by Rich Mironov
Shipping faster is becoming a weaker advantage, so teams need to build moats that are harder to copy, like proprietary data, trusted communities, strong market position, and business models rooted in real-world advantage. The more AI lowers the cost of replication, the more product strategy shifts from what you build to what competitors still cannot easily reproduce.

How Your Team Structure Shapes Your Product by Joca Torres
Team structure shapes product outcomes more than most leaders realise, so organising around users and business value rather than systems alone opens up better solution spaces and keeps structure working in service of strategy instead of quietly against it.

Continuous Research

Calibration Matters More Than Automation: What AI’s History Suggests About Building Agentic Research Systems by George Jensen
Building agentic research systems is less about automating analysis and more about encoding standards, calibrating outputs, and governing workflows, so ResearchOps shifts from tool support to designing the structures that keep AI useful, auditable, and methodologically sound.

AI Needs A Human Touch: Why Researchers Should Lead AI Evals | Sponsored Content by Nathan Reiff (Dscout)
AI features improve when researchers do more than validate them at the end. Involving research early in prompting, output review, and evaluation helps teams catch weak results sooner, connect AI performance to real user needs, and make better product decisions before poor experiences scale.

Continuous Design

Intent By Discovery: Designing the AI User Experience by Jakob Nielsen
As AI takes on more of the execution, design needs to focus less on guiding every step and more on helping users express intent, review actions, and correct mistakes safely. Teams should design for clear delegation, strong verification, and visible system reasoning so AI feels useful without becoming risky.

Design’s Influence Is Expanding, And Here’s Why That Feels Hard | Sponsored Content by Andrew Hogan (Figma)
As AI accelerates creation and raises expectations, designers are navigating a field that’s bigger, faster, and more demanding than ever.

Continuous Development

The Software Development Lifecycle Is Dead by Boris Tane
AI agents collapse requirements, implementation, testing, and deployment into a much tighter loop, making context and observability more important than the old stage-based SDLC as teams shift from managing handoffs to steering intent and feedback.

WTF Does A Product Manager Do? (And Why Engineers Should Care) by Jina Yoon
Helping engineers think more like product managers means teaching them to gather the right context, close feedback loops, and communicate toward action, so better product decisions happen closer to the work instead of being lost in handoffs.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Shoutout to our partners in New York!

UXDX USA 2026 Happens Next Week.
Make Sure To say Hi To Our Partners:

UXDX USA 2026 kicks off next week in New York, and we’re proud to be supported by partners helping teams build, research, design and scale better products: Figma, dscout, Great Question, Strella, Dovetail, Knapsack, and Capital One.

From design systems and research operations to AI-powered insight, continuous discovery, product decision-making and enterprise innovation, these organisations are shaping how modern product teams work. A huge thank you to all our sponsors and partners for helping make UXDX USA better every year. Still don’t have your ticket? Grab the last available tickets with the discount code below.

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

FREE COMMUNITY EVENTS 

UXDX 2026 Speaker Announcements

Product, design, and engineering teams are under pressure to move faster, work smarter, and make better decisions with less certainty. But speed only creates value when teams can align around the right problems, building across functions and reducing the cost of getting things wrong. Here’s what you can look forward to at UXDX 2026:

In Berlin, Tasha Melchior (Everway) and Mike Brown (Barclays) will explore why empathy, negotiation, judgment, and human connection are becoming essential skills for modern product, design, and leadership teams. They look at how teams build trust, navigate tension, and make better decisions in high-pressure environments.

Also in Berlin, Carsten Windler (Plan A) will show how product and engineering teams can embed sustainability into everyday software delivery. He will cover practical ways to measure carbon emissions across software and cloud infrastructure, reduce waste costs, and make greener delivery part of existing workflows.

In New York, Vicky Chin (Mozilla) will share how Firefox uses open development, early community feedback, and Firefox Labs to learn faster before delivery gets expensive. She will show how teams can reduce rework, focus engineering effort on validated needs, and improve quality before launch.

Also in New York, Melissa Appel (Aperture Product) will lead an interactive workshop on stakeholder alignment. Through a fast-paced simulation, participants will practise navigating competing priorities, understanding incentives, negotiating trade-offs, and making decisions that senior stakeholders can actually support.

Each session explores a different part of the same challenge, helping teams move with more clarity, confidence, and impact. Join the conversations shaping more responsible, resilient, and effective product delivery.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in March here.

Video Of The Week

Transforming Enterprise AI with Scalable LLM Deployments

Most teams can get a model to answer a prompt. The real test is what happens when you put it in front of employees, connect it to sensitive data, and ask it to perform reliably inside real workflows.

In this week’s video, Mahmoud Fahmy, Lead AI Engineer at Mastercard, breaks down why enterprise genAI succeeds or fails in the layers around the model. He explains the “closed book” problem, why grounding matters, how RAG reduces hallucinations but adds new complexity, and why the software layer, governance, and observability are where most of the work actually lives. Watch the full session below:

The Results of Last Week’s Poll

The question: If you were asked to lead a smaller team for a high-potential new initiative, how would you feel?

This week’s poll asked how people would feel about being asked to lead a smaller team on a high-potential new initiative, and the results show how much career progression is still tied to visible scope. The largest group (37%) would be excited by the growth opportunity, but almost as many (34%) said it depends on how leadership frames it. That framing matters because a smaller team can either feel like a strategic bet or a quiet downgrade.

The concern is real too. 19% would worry it was a career step backward, and 10% would feel frustrated about losing their current scope and status. That tells me many organisations still reward the size of remit more clearly than the quality of impact. If promotion, recognition, and influence are linked to headcount or surface area, then asking someone to lead a smaller, sharper initiative will naturally feel risky.

The takeaway is that leadership needs to be much clearer about what “bigger” means. A bigger team does not always mean a bigger impact. Sometimes the highest-growth opportunity is a small team tackling a hard problem, with senior visibility and a real chance to shape direction. But if organisations want people to take those bets, they need to make the value of the move explicit.

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

Single-Threaded Leaders: Breaking Through the KPI Prison

When companies launch transformational initiatives, they typically assign them to existing leaders who are already measured on current business KPIs. This creates an inevitable conflict: leaders will always prioritize the metrics they're evaluated on over new strategic projects.

As Amazon discovered, "culture eats strategy for breakfast, but KPIs drive culture." so they created the concept of a Single Threaded Leader: executives who are "100% dedicated and accountable to a specific product".

Amazon's Digital Media division succeeded because it operated independently with its own two-pizza teams, dedicated resources, and CEO-level attention.

I go into more detail about when you need , and when you don't need, a single threaded leader in my article below.

This Week’s Updates

Enabling the Team

Single-Threaded Leaders: Breaking Through The KPI Prison by Rory Madden
Many new strategic initiatives fail because of the misalignment between how companies structure accountability and how they allocate attention. If you want a new initiative to succeed, it can't be some executives part time job.

Something Big Is Happening by Matt Shumer
AI is moving from assistant to operator, which means the bigger challenge for teams is no longer whether to use it, but how quickly roles, expectations, and workflows will need to change around it. Leaders who ignore the pace of change risk leaving their teams unprepared for a much more automated version of knowledge work.

Product Direction

Basic Links by John Cutler
Shipping does not deliver outcomes on its own. Teams need to make the links between actions, early signals, and longer-term results explicit so they can choose better bets, test assumptions earlier, and learn whether their strategy is actually working.

In Praise Of Guessing by Christina Wodtke
Teams make better goals and estimates when they treat early numbers as informed guesses instead of pretending they are certain. Creating space to predict, measure, and learn helps teams build stronger judgment over time without encouraging sandbagging or decision paralysis.

Continuous Research

The End Of The Passive Researcher: Trading Academic Rigor For Radical Agility | Sponsored Content by Claire Bonneau (Dovetail)
Research has more impact when it shapes decisions as teams build, rather than arriving as a polished report after the fact. Sharing smaller insights earlier, working ahead of the roadmap, and staying close to product teams helps reduce the risk of building the wrong thing.

Calibration Matters More Than Automation: What AI’s History Suggests About Building Agentic Research Systems by George Jensen
I adds more value in research when teams use it to challenge, calibrate, and strengthen analysis rather than treat it as an oracle. Build governed workflows, test outputs against clear qualitative standards, and use human review to catch drift, bias, and weak reasoning before insights shape decisions.

Continuous Design

GenUI vs. Vibe Coding: Who’s Designing? by Kate Moran
Generative UI and vibe coding both produce AI-generated interfaces, but they differ in a critical way: who decides to build. Learn how this distinction shapes design accountability, failure modes, and who actually benefits.

Houston, We Have A Problem: Building Trust In The Age Of AI | Sponsored Content by Kim Miller (Knapsack)
AI is easier to trust when it is grounded in a strong design system rather than generating from scattered files and inconsistent standards. Clear guardrails, shared patterns, and a reliable source of truth help teams create more consistent outputs and make AI support design quality instead of weakening it.

Continuous Development

So You Want To Hire A Forward Deployed Engineer by First Round
Forward deployed engineers work best when companies need technical people close to customers to shorten feedback loops, uncover product opportunities, and help land complex enterprise deals. The model creates value when teams give FDEs real engineering scope, clear success measures, and the freedom to solve recurring customer problems rather than just run implementations.

Towards A Decentralised Delivery Of Infrastructure: A Data Platform Journey by Jose Moreno
Infrastructure teams move faster when application teams can provision what they need through shared patterns, clear guardrails, and automated delivery instead of waiting on a central backlog. Strong platform standards, role clarity, and reusable tooling make self-service possible without creating drift or weakening governance.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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VOTE NOW!

Who Should Win The UXDX EMEA 2026 Awards?

Vote now on LinkedIn: Unblocker Award | Best Use of AI Award | Impact Award

The public vote is now open for the UXDX Awards and counts for 25% of the final score. Across the Unblocker, Impact, and Best Use of AI categories, this year’s finalists show what strong product teams can achieve when they remove blockers, connect evidence to outcomes, and use AI to change how work gets done.

Read the finalist case studies, then vote for the team you think should win in each category. The winners will be announced live on stage at UXDX EMEA 2026 in Berlin.

Dive in deeper before voting by checking out the details for each case study on our website here: Unblocker Award | Best Use of AI Award | Impact Award

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

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UXDX 2026 Speaker Announcements

AI is already reshaping how products are built, which means the real challenge is no longer speed alone, but judgment, trust, and how teams adapt. Here’s what you can look forward to at UXDX 2026:

In Berlin, Alex Radu (JPMorgan Chase), Pamela Mead (SumUp) and Aastha Yadav (Bolt) will explore what actually changes when AI becomes embedded in the way teams work. As execution gets easier, they’ll look at why depth, understanding, and better decision-making become the real advantage.

Also in Berlin, Sam Bradley (PayPal) and Pallavi Modi (zooplus) will debate one of the biggest challenges in personalisation today: where it genuinely helps people and where it starts to feel intrusive. Expect a practical discussion on trust, context, restraint, and what responsible personalisation looks like when money and identity are involved.

In New York, Kent Eisenhuth (Waymo) will share how thoughtful UX can make AI experiences more intuitive and human. Drawing on work integrating visual data into a chatbot environment, his session offers practical lessons for teams building AI products people can actually understand and use.

Also in New York, Donnie D'Amato (Design Systems House) and Alex Wilson (T. Rowe Price) will discuss what design systems become when AI starts generating more of the interface layer. Their session will explore the next generation of design systems as rules, constraints, and infrastructure for dynamic experiences.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in March here.

Video Of The Week

The Real Impact Of Mergers & Acquisitions On Your Product Team

Seven acquisitions. One major merger. And the product team is still expected to ship, keep customers happy, and somehow feel “aligned.” In this talk, Tasha Melchior (VP of Product at Everway) shares what M&A really does to the holy trinity of people, product, and process. The board game version is fun. The real version feels like the rules changed mid-play.

Tasha breaks down why every acquisition tips the scale and pushes teams into storming, how overlapping product portfolios turn into painful consolidation decisions, and what happens when a process that works gets replaced overnight because leadership changes. Her most useful takeaway is not a framework slide. It is a reality check: M&A requires emotional agility as much as agile delivery. Feeling off balance does not mean you are failing. It means the family just changed, and you are doing the work of becoming one team. Watch the full talk now:

The Results of Last Week’s Poll

The question: What's the biggest challenge your team faces when making product decisions?

Last week’s poll asked what the biggest challenge is when teams make product decisions, and the results point to a clear theme: decision-making breaks down when teams do not have a strong enough shared direction. The top response was lack of clear strategic direction from leadership (36%). That feels significant because product teams can often handle complexity, ambiguity and trade-offs, but only if they understand what they are optimising for. Without that strategic clarity, every decision becomes harder than it needs to be.

Two answers tied at 26%: too much information but unclear priorities, and teams working in silos without shared context. Those two are closely connected. More data does not automatically lead to better decisions if teams are missing a shared framework for what matters most. And when teams are working from different contexts, they are more likely to interpret the same information in different ways. Only 7% said decisions get bottlenecked waiting for approval, and just 5% pointed to limited access to customer or market data. The main issue is not simply governance or a lack of inputs. In many cases, teams are not waiting because they cannot decide; they are struggling because the criteria for making the decision are not clear enough.

The takeaway is that better product decisions do not come from more meetings, more data or more approvals. They come from clearer strategy, shared context and stronger prioritisation. Without those foundations, even well-informed teams can end up moving slowly, second-guessing themselves or making decisions that do not connect back to the bigger business direction.

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

Empowering Strategic Decision-Making For Product Teams

When companies empower teams without providing strategic context, a predictable pattern emerges: teams make logical decisions based on incomplete information while leadership sees these choices as misguided.

This "strategy translation failure" occurs because traditional strategy documents often lack the context of why decisions were made.

Teams need a framework that transforms abstract strategy into concrete decision-making criteria. The DIBBs framework (Data, Insight, Belief, Bet) helps to communicate the underlying logic behind strategic choices.

In my article this week, I share how DIBBs aligns with other strategy frameworks and how you can use it to help empowered teams succeed.

This Week’s Updates

Enabling the Team

Why “They” Is The Most Dangerous Word At Work by Joost Minnaar
Teams work better when people stop blaming a vague “they” and start taking shared ownership of problems. Replacing separation with clearer responsibility, direct conversation, and stronger cross-team communication can improve trust and make collaboration more effective.

What To Do When Your Senior Role Feels Totally Unsustainable by Darcy Eikenberg and Tony Martignetti
Senior roles become unsustainable when expectations, scope, and availability keep expanding without being reset. Redesigning the job around clearer boundaries, better support, and more realistic priorities can help leaders stay effective without sacrificing their well-being.

Product Direction

Dibb Framework: Empowering Strategic Decision-making For Product Teams by Rory Madden
When companies empower teams, it's common for teams to make decisions based that leaders disagree with. But without sharing the context behind the strategy, teams are being set up to fail.

Execution Problems Are Usually Decision Problems In Disguise by Brent Harrison
Teams struggle to execute when leaders leave too many decisions soft, unclear, or easy to reopen. Clearer decisions reduce rework, make priorities more durable, and stop product teams from absorbing leadership ambiguity as delivery pain.

Continuous Research

The Surprising Ways Customers And Fans Are Using AI by Susan Kresnicka & Karis Eklund
Fans are using AI to learn faster, plan experiences, create content, and deepen their connection to the things they love. The opportunity is to build AI that enhances participation and discovery while protecting human creativity, user agency, and the emotional value that made people care in the first place.

Ethical AI Integration In User Research by Optimal
AI can speed up research, but teams still need clear privacy rules, bias checks, and human review to protect users and trust. Collect only the data you need, be transparent about how AI is used, and validate automated insights with direct research before acting on them.

Continuous Design

You’re Still Designing For An Architecture That No Longer Exists by Adrian Levy
AI is changing the architecture behind digital products, shifting teams from designing screens and flows to designing intent, autonomy, and orchestration.

UX Works Through Social Relationships. AI Tools Are Erasing Them. by Pavel Samsonov
Stakeholders want to vibe code and have designers clean up after them afterwards. But rather than helping with velocity, there is just more noise and more work for everyone.

Continuous Development

The Engineeringification Of Everything by Ian Vanagas
As tools get more powerful, more roles are starting to do work that used to sit with engineers. Teams that embrace this well can move faster and reduce handoffs, but they still need clear ownership, good judgment, and the right support so broader access to building does not turn into confusion or poorer quality.

Flow Focused Testing Strategies by Karl Evard and Rebecca Wirfs-Brock
Testing works better when teams focus on the flows that matter most in production, not just on hitting the right mix of unit, integration, and UI tests. Prioritizing realistic end-to-end execution paths helps catch meaningful failures earlier while balancing speed, resiliency, and maintenance cost.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Throwback to 2025

Last chance to get insights from the previous events

With UXDX EMEA and UXDX USA happening next month, this is your last easy chance to revisit the thinking, themes, and lessons that shaped the 2025 events before the 2026 conversation takes over. The 2025 Post Show Report is a useful snapshot of what teams were wrestling with, what resonated most, and why so many attendees used it to make the case internally for coming back.

If you are still deciding, seeking approval, or want a clearer sense of what UXDX actually delivers, the report is the best place to start. Download it here: https://uxdx.com/post-show-report/

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

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UXDX 2026 Speaker Announcements

What does real change look like inside product teams? Not the strategy deck or the AI hype, but the practical shifts that help teams work better every day. These upcoming sessions at UXDX EMEA 2026 in Berlin and UXDX USA 2026 in New York explore exactly that.

In Berlin, Sara Kalinoski will unpack how her team spent nearly two years changing how design showed up in planning, decision making and execution, and what it takes to make design a real strategic partner. Marieke de Ruyter de Wildt will share how to build a traceability platform in a low UX maturity environment by focusing on simplicity, evidence, experimentation, and the right use of IoT across growing channels. Ramona Ziemann will show how a design system became part of a legal framework and helped make design a formal requirement in national digital transformation.

In New York, Shruti Gupta's workshop will demonstrate how AI can reduce validation cycles, improve cross-functional alignment, and help enterprise teams build faster with the right guardrails, workflows, and governance. Evan Cannarozzi will run a workshop that offers a practical, human-first method for using AI personas to speed up feedback, compare synthetic and human input, and help stretched teams make better design decisions without replacing research.

These sessions are ideal for leaders working through AI adoption, organizational change, and the challenge of building better products across design, product, and engineering. Book your tickets today and join the conversations shaping how modern teams work and grow.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in March here.

Video Of The Week

Who Moved My Roadmap? Navigating the Unpredictable Future
of UX and Product in the Era of AI

Donal O’Mahony has heard “once in a lifetime shift” so many times that it has lost its meaning. Dot com chaos. Flash is dying overnight. A multi-billion dollar acquisition that rewires culture. Now, generative AI is landing with enough speed to make leaders feel like their roadmap has been stolen in broad daylight.

He uses the Who Moved My Cheese parable to explain why teams react so differently when priorities reset, then brings it to life with three “seismic shifts” from his own career. The takeaway is practical: spot fear early, counterbalance it, and replace “what’s the worst that could happen?” with “what’s the best that could happen?” so you can move with energy rather than stress.

If your roadmap is shifting weekly and AI is amplifying uncertainty, this talk will help you keep momentum without burning out:

The Results of Last Week’s Poll

The question: What's the biggest challenge when creating product visions?

Last week’s poll asked what the biggest challenge is when creating product visions, and the answers highlight a familiar tension between ambition and execution. The top response (29%) was staying focused on outcomes rather than features, which suggests many visions still drift into describing what gets built instead of what actually changes for the customer or the business.

Close behind, 23% struggle to make visions concrete and actionable, and 22% point to getting stakeholder buy-in. Those two are often linked. If a vision is too abstract, it is hard to act on, and even harder to align people around. That is usually when teams fall back into features, because they feel more tangible and easier to agree on.

Only 7% selected balancing ambition with believability, which is interesting. My read is that most teams are not struggling to dream big; they are struggling to make those ideas usable. The 19% who chose “all of the above” reinforces that this is not a single problem, but a system problem.

The takeaway is that a strong product vision is not just inspiring; it is operational. It connects clear outcomes to real decisions, makes trade-offs visible, and gives teams something they can actually move on. Without that, visions tend to stay as well-written documents rather than tools that shape what gets built.

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

How To Create A Compelling Product Vision

The most effective visions paint vivid pictures of customer transformation through a systematic four-step approach:

1. Develop rich personas that go beyond demographics

2. Identify their jobs to be done across functional, emotional, and social dimensions

3. Envision transformational rather than incremental improvements

4. Craft a customer-centric narrative

The first three steps help you to identify the content, whereas the fourth step is how you communicate it. Successful product visions don't just describe features; they illuminate better lives made possible for real people.

Structuring the story as a hero's journey where your customer overcomes challenges to reach success helps you to keep the focus where it needs to be. The best visions make people believe that transformation isn't just possible but inevitable, turning customers into believers who help build the future you're selling.

This Week’s Updates

Enabling the Team

Distributed Leadership: When Everyone's A Captain by Joost Minnaar
Flat organisations still need leadership, but it needs to be shared across the team rather than concentrated in formal managers. Clear principles, direct communication, and strong peer sponsorship help people take ownership without losing accountability.

Why Great Innovations Fail To Scale by Linda A. Hill, Emily Tedards and Jason Wild
Strong ideas do not scale on their own. Innovation works better when leaders can connect teams, share ownership across boundaries, and keep partnerships working long enough to turn promising concepts into repeatable results.

Product Direction

How To Create A Compelling Product Vision: A Step-By-Step Guide by Rory Madden
A powerful product vision serves as the North Star for your entire development team, but too often, product visions are abstract statements that sound impressive yet fail to inspire action. In this article, I'll share how you can create an inspiring vision that drives action.

Use These Practices To Build Safer AI Products | Dscout (Sponsored Content) by Meredith McDermott, Marysia Winkels, Elizabeth Allen
Launching new AI products comes with risk. These protocols and approaches will help you build a safer product for users and your company.

Continuous Research

Tell Me Where It Hurts: Moderating Real Users In UX Research by Ticiana Paura
Good research depends on hearing where users struggle in real situations, not ideal ones. Create enough trust and space for people to show confusion, hesitation, and workarounds, then use that evidence to ground decisions in real behaviour rather than assumptions.

Your Research Tools Got Smarter… Did You? by Josh LaMar
As AI automates more of the collection and analysis work, researchers create more value when they connect evidence to business decisions. Use AI for speed and scale, then focus human effort on synthesis, stakeholder trust, and judging where automation helps or harms the user experience.

Continuous Design

Designing AI Experiences People Actually Use by Buzz Usborne
AI features work better when they reduce ambiguity, show value early, and let users shape or verify the output before more autonomy is introduced. Use structured starting points, human-in-the-loop flows, and lower-risk interactions to build trust without increasing effort.

Design Process Isn't Dead, It’s Compressed by Sarah Gibbons and Huei-Hsin Wang
As AI speeds up design work, the argument to "throw out the process" misrepresents how experienced designers work.

Continuous Development

One List To Rule Them All by James Stanier
Teams make better progress when leaders turn competing initiatives into one clear, ordered list. A single ranking makes trade-offs visible, reduces resource spreading, and helps teams focus effort on the work that matters most.

Building Foundations For Continuous (AI-Accelerated) Change by Susanne Kaiser
AI speeds up delivery only when the system around it can absorb the extra output. Reduce handoffs, clarify ownership, improve architecture, and focus teams on flow so AI acceleration increases throughput instead of creating more queues, rework, and instability.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
Click here to share an article

Price Increase Alert!

Only A Few Weeks To Go, Only A Few Tickets Left

There are now only a few weeks left until UXDX EMEA and UXDX USA 2026, and the next ticket price increase is this weekend on 19/4. If you already know Berlin or New York is on your radar, this is the moment to get your ticket(s) before the rate moves up.

With the full agenda live, you do not need to buy on hope. You can see the speakers, the sessions, and the themes shaping this year’s events, then decide while the current pricing is still available. If you are planning to join, it makes sense to do it now rather than pay more a few days from now. Go to the ticket page by clicking on one of the events below:

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

FREE COMMUNITY EVENTS 

UXDX 2026 Speaker Announcements

Something is shifting inside product teams. AI is not just speeding up delivery. It is changing how ideas are shaped, how decisions get made, and how product, design, and engineering work together from the start. These sessions at UXDX EMEA 2026 in Berlin and UXDX USA 2026 in New York show why.

At UXDX EMEA 2026 in Berlin, John Vetan (Design Sprint Academy) will focus on one of the biggest problems teams face right now: how to turn AI enthusiasm into something clear, useful, and worth building. His session is designed to help teams move past vague ambition and get better at identifying the problems AI can genuinely solve.
Also in Berlin, Michael McKay (Mckay Consulting - Five Mindsets) will explore how storytelling, video, and synthetic personas can help teams shape stronger product value propositions. As more teams move faster with AI, the ability to align around the right story and the right customer need becomes even more important.

At UXDX USA 2026 in New York, Keyvan Azami (Google) and David Kossnick (Figma) will take on one of the biggest changes happening in modern product development: the collapse of the old handoff model. What used to be a sequence of product, design, then engineering is becoming a more continuous, AI-assisted loop. Their conversation will look at what that means for team structure, decision-making, and the way ideas move from concept to shipped product.
Cristina Fuser (BuzzFeed) will bring the organisational view, looking at what happens when board-level AI pressure meets the reality of fragmented experiments, tired teams, and legacy systems. Drawing on BuzzFeed’s work across news, entertainment, and subscriptions, she will show how to turn pressure into practical value across teams and products.
And Christina Kalsow-Ramos (Work & Co) will lead an interactive workshop on how teams can collaborate better when AI is part of the workflow. With real examples and a grounded approach, she will explore how product managers, designers, and engineers can align earlier, apply better judgement, and avoid the common mistakes that slow good teams down.

Book your ticket for Berlin or New York and be part of the conversations shaping how modern product teams actually work.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in March here.

Video Of The Week

Framework for Balancing Short-Term Wins With
Long-Term Product Goals

Strategy is the easy part; execution is the test. In her talk, Michelle Parsons shares a portfolio framework that helps product teams turn strategy into measurable outcomes without losing the thread when reality hits. Instead of treating the roadmap like a single queue, she balances three types of work:

• Quick hits to test hypotheses fast

• Small bets to improve what you shipped and protect trust

• Big bets that drive step-change results once de-risked.

The Netflix Kids case study brings it to life. The team wanted a bold “favourites-first” kids experience, but it was too risky to build without proof. So they ran a quick hit where kids already were: search. By replacing “popular searches” with “watch again” for kids' profiles and making play easier, they drove a 15% lift in watch time. That result earned credibility, unlocked the larger investment, and shifted the conversation from debate to learning. Check out the full talk here:

The Results of Last Week’s Poll

The question: Which SpaceX narrative technique would be hardest to replicate for other products?

Last week’s poll asked which SpaceX narrative technique would be hardest to replicate, and one answer clearly stood out. Nearly half (44%) pointed to starting with a human scale before showing the technology. That is interesting, because on the surface it looks simple, but in practice it requires real confidence in your product. You have to believe the value is strong enough to land before you explain how it works.

The next biggest challenge (32%) was demonstrating complex processes without narration. That is a different kind of difficulty. It is not about confidence, but clarity. If your product, system, or journey cannot be understood visually or through interaction alone, it often means the experience itself is still too complicated. The smaller responses are still telling. Only 13% chose using technical specs as “reality anchors,” and 11% picked selling the ultimate transformation. My read is that most teams are comfortable talking about features and future vision. The harder part is bridging the gap between the two in a way that feels immediate, intuitive, and grounded in real user value.

That is what makes the top two answers so hard to replicate. They both force teams to simplify. Either you make the value obvious at a human level, or you make the system understandable without explanation. Most products struggle with both, which is why they fall back on specs, slides, and storytelling that explains rather than shows.

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

Analysing A Successful Product Vision

Most product visions end up as abstract statements that sound impressive but fail to inspire action or drive decision-making. To understand what makes a vision truly powerful, we analysed SpaceX's Mars mission video, which transforms the company from a transportation logistics provider into the architect of humanity's multi-planetary future.

The four-act story begins with people, not rockets, because a vision is about your users, not your product. It then builds credibility by demonstrating that they've thought through some of the more complex elements of a Mars flight, such as the reusability of the rockets and the solution to challenges like fuel capacity and a Mars landing.

By using proven storytelling principles, SpaceX has developed a product vision that aligns the teams internally, is a great recruitment tool and has attained a lot of free marketing. Check out my article below for a deeper dive.

This Week’s Updates

Enabling the Team

Positive Vs Negative Freedom In Organizations by Joost Minnaar
Removing hierarchy creates structural freedom, but that alone does not make people self-directing, so organisations also need the relational conditions and human capabilities that help teams use autonomy well, rather than recreating dependence in new forms.

Beyond The Waterfall State: Why Missions Need A Different Decision-Making Architecture by Jack Strachan
Innovation efforts often fail not because of weak ideas, but because learning arrives after the key decisions have already been made. Dive into decision architecture, cross-functional sense-making, and how to structure missions, prototypes, and commitments so teams can adapt before direction gets locked in.

Product Direction

Analysing A Successful Product Vision: SpaceX by Rory Madden
The SpaceX-to-Mars video is a masterclass in narrative marketing. It positions SpaceX as the architect of our multi-planetary future rather than just a transportation company. Let's break down exactly how they do it and why it is so effective.

On Coding Agents And The Future Of Design by Jeff Veen
Coding agents could push products toward clearer, more atomic capabilities, making design more about strategy than screens. Go into AI-native product direction, interface abstraction, and what the product really exposes underneath.

Continuous Research

Harness The Power Of Users' Unmet Needs | Dscout (Sponsored Content) by Nikki Anderson
Taking actions like looking through existing data, mapping the customer journey, and identifying high cognitive load can set you on the right track.

AI Can Help With Survey Writing, But It Still Requires Human Expertise by Rachel Banawa
AI can produce polished survey drafts quickly, but experienced human review is still needed to catch subtle survey-design flaws that weaken data quality.

Continuous Design

When Design Stops Asking Why And Starts Asking “Can AI Do It?” by Dolphia
AI is flipping the order of product decisions, pushing teams to react to polished outputs before asking whether the work should exist at all.

Vibe Prototyping Is A Double-edged Sword by Ed Orozco
A strong caution against letting vibe-coded prototypes create false confidence. Useful in the difference between making something look real and actually testing whether the idea, flow, or business case holds up.

Continuous Development

My AI Adoption Journey by Mitchell Hashimoto
Mitchell's experience adopting any meaningful tool is that he has necessarily gone through three phases: (1) a period of inefficiency, (2) a period of adequacy, and finally (3) a period of workflow and life-altering discovery.

The AI Vampire by Steve Yegge
AI can raise output quickly, but without clear limits, the gains often show up as more pressure, longer hours, and faster burnout. Teams need to set healthier expectations around pace, workload, and who benefits from productivity gains before AI speed turns into extraction.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Quick Entry Is Closing For The Unblockers!

Don’t miss your chance to shine at the awards in EMEA

Due to requests, we have extended the quick entry of ‘ The Unblockers’, our first ever EMEA Awards, to the 10th of April. Which means the final entries can go in this week for a shot to shine on the stage at UXDX EMEA 2026. There are three categories you can submit for:

• Impact Award — evidence that led to real outcomes

• Best Use of AI — AI that meaningfully changed how you work or what you built

• The Unblocker Award — removing the barriers that help cross-functional teams move faster

If your team has done something worth sharing, the entry takes 3 minutes. Just a quick form and we'll send you the next steps afterwards. Finalists get team tickets to UXDX EMEA 2027, global exposure, and a published case study. The deadline is this Friday: https://airtable.com/appZDHX5d901bzueE/pagjVBIAq87H1G8rU/form

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

FREE COMMUNITY EVENTS 

UXDX 2026 Speaker Announcements

As pressure builds on product teams, the real challenge is no longer just speed. It is ownership, alignment, and making sure work actually translates into business impact. That is exactly what these upcoming UXDX 2026 sessions are digging into.

At UXDX USA 2026 in New York, Deb Kawamoto (Vanta) and Ellen Linardi (Synctera) will debate one of the biggest organisational questions right now: does bringing product and engineering under one leader create clarity, or just shift the bottlenecks? Russ Wilson (Splunk) will share Fidelity’s “Digital Athlete” case study, showing how product managers can work more effectively with design and shift culture towards value. In his interactive workshop, Jose Coronado (Digital Impulsum) will focus on how design leaders can move beyond delivery support and build real strategic influence.

At UXDX EMEA 2026 in Berlin, the focus shifts to removing friction across teams. Mihaela Draghici (UXDX) will tackle how unclear language creates hidden delays, and how shared definitions can unlock faster decisions. Ather Nawaz and Aitor Gomez Matias (Ørsted) will show how to bring IT closer to the business without adding coordination overhead, turning strategy into executable trade-offs. Duygu Stubrys (Nestlé) will share how peer-led, gamified learning can drive lasting change in collaboration, flow, and customer focus.

These sessions go beyond theory and get into the operational reality of how modern teams align, collaborate, and deliver impact under pressure.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in March here.

Video Of The Week

The UX Scorecard:
Transforming Research Into Measurable Impact Across The Org

“The most expensive usability test that you’ll ever do is the one that you actually don’t do.” Amit Sathe and Marina Lin share how Docusign stopped treating research as a late-stage tiebreaker and turned experience quality into something teams can measure, track, and use in release decisions.

In this talk, they break down the UX Scorecard, a repeatable framework that scores experience across three dimensions: usability, usefulness, and satisfaction. It blends observed metrics (like task success and time on task) with self-reported measures (like ease and CSAT), then rolls it into a single score that teams can use to spot what is not ready and what to fix next.

The shift is not “putting a number on UX.” It is making experience quality operational. At Docusign, a scorecard is now required before products can exit beta, and it is discussed at senior levels, including the C-suite. Watch the full talk now:

The Results of Last Week’s Poll

The question: Which best describes your current team structure?

Last week’s poll asked which team structure best describes how people are working today, and the results suggest that true cross-functional teams are still not the norm. While 30% say they have real cross-functional teams with shared goals, blurred roles, and team-owned processes, the biggest group (36%) still describes their setup as teams of functions: mixed disciplines on paper, but with separate reporting lines and ways of working. Another 19% sit somewhere in between, while 15% remain mostly siloed by function.

That split matters because structure shapes behaviour. A team of functions can look collaborative from the outside, but if incentives, processes, and decision-making still live inside functional boundaries, you tend to get handoffs instead of shared ownership. True cross-functional teams are different: they are organised around outcomes, not disciplines, and that changes how quickly they learn, decide, and adapt.

My read is that many organisations are in transition, but haven’t finished the move. They’ve assembled the right people, but not yet redesigned the system around them. Until goals, reporting lines, and operating rhythms all support shared ownership, most teams will stay in that halfway state where collaboration sounds right but still feels harder than it should.

If you want to go into how careers and leadership are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

Cross-Functional Teams vs. Teams of Functions

Many organizations believe they have cross-functional teams when they actually have "teams of functions" - groups where each member still reports to separate functional managers, follows distinct processes, and adheres to rigid role boundaries with formal handovers between disciplines.

True cross-functional teams operate fundamentally differently, with everyone working toward shared goals, blurred role boundaries, collective ownership of end-to-end processes, and a focus on outcomes rather than individual functional achievements.

Transforming to genuine cross-functional teams requires changes to KPIs, processes and significant training and support. But the juice is worth the squeeze, as they say.

You can read more in my article below.

This Week’s Updates

Enabling the Team

Cross-Functional Teams vs. Teams of Functions by Rory Madden
Many organisations claim to have cross-functional teams. But scratch the surface, and the collaboration is often cosmetic and this reduces the expected benefits.

One Bottleneck At A Time by James Stanier
Treating teams and organisations as systems means finding the single constraint that is truly limiting throughput, then subordinating everything else to fixing it so leaders stop spreading effort thinly and start improving real flow.

Product Direction

Synthesizing Qual, Quant, And Strategy With Claude Code + Posthog MCP by Else van der Berg
A practical walkthrough: from diagnosing revenue drops, onboarding friction, to validating "aha" moments and business opportunities

Fixing Strategy by Roger L. Martin
Fixing strategy means moving away from technocratic planning and treating it as a general management practice built on imagination, principles, iteration and distributed choice, so teams shape the future through judgment and learning instead of pretending analysis can predict it.

Continuous Research

How A Few Usability Tests Changed Our Whole Product Roadmap | Dscout (Sponsored Content) by Bex Jeanson
Usability testing can uncover the issues that matter most before roadmap decisions are locked in. Use early research to spot friction, challenge assumptions, and redirect effort toward the problems that will have the biggest impact.

A Practical Guide To Structuring Researchops Through Organizational Change by Carolyn Morgan
ResearchOps works best when its structure fits the organisation around it, rather than following a fixed model. Choose clear ownership, consistent standards, and the right mix of centralised and embedded support to help research scale through change without losing quality.

Continuous Design

The Design Engineer Symptom: What A Rising Job Title Reveals by Anne Lefour
The rise of the design engineer title signals a broader shift in how digital teams work, as design and engineering blend around shared tools, faster iteration and more technical design practice, forcing organisations to rethink collaboration, expectations and career paths.

Designers As Agent Orchestrators by Benhur Senabathi
How designers can move from handoff to orchestration by using AI with clearer intent, better documentation, stronger systems thinking, and faster prototype-to-product workflows.

Continuous Development

No Management Needed: Anti-Patterns In Early-stage Engineering Teams by Antoine Boulanger
Early-stage teams do not usually need more management; they need better hiring, sharper founder attention and less process, using lightweight coordination and extreme transparency until team size and complexity create a real need for structure.

The Hidden Danger Of Shipping Fast by Cleo
Shipping fast only works when users can keep up with what is changing. Treat attention as a constraint, promote fewer things more deliberately, and surface features in context so product velocity leads to adoption instead of wasted output.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Early Sale Is Ending!

Prices Rise This Week

These are the last tickets available at the early sale rate for UXDX USA and UXDX EMEA 2026. Prices go up this week, and after that, tickets move to the regular rate.

If you already know Berlin or New York is on your 2026 plan, now is the moment to secure your place. And if you’re a startup, freelancer, or student, don’t forget you can also apply for discounted tickets.

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

FREE COMMUNITY EVENTS 

UXDX 2026 Speaker Announcements

The pressure on product teams is only getting bigger. Organisations are being asked to move faster, make smarter decisions, and adapt how they work without losing focus, quality or momentum. That is exactly what these upcoming UXDX 2026 sessions are tackling.

At UXDX USA 2026 in New York, Josh Payton from Wise will share how losing nearly half the team forced a complete rethink of the design organisation. His session looks at how Wise moved from burnout and constant firefighting to a culture built on autonomy, balance and impact.
Also in New York, Randy Hunt from Notion will explore how Notion reshaped its design organisation around skills and behaviours rather than titles and functions. As the company scaled from personal users to global enterprises, this approach helped the team stay adaptable, creative and close to the craft.

At UXDX EMEA 2026 in Berlin, Kristina Gibson, ex-Dott, will lead a hands-on workshop for teams that feel stuck waiting for perfect data before making strategic moves. She will share a practical framework for exploring opportunities, evaluating bets and turning product strategy into roadmap action.
Meanwhile, Pooja Dey from Sage will show how product marketing and UX can work together to shape product investment, not just go-to-market plans. Drawing on Sage case study experience, she will share how buyer journeys, onboarding insights and in-life usage can help teams prioritise better, reduce risk and design for adoption.

These sessions are packed with practical lessons and grounded examples of how leading teams are rebuilding, aligning and moving forward with confidence.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in February here.

Video Of The Week

From Cross-Functional to Cross-Purposes:
Why Collaboration Falls Apart Over Time

In this week’s video, Mihaela Draghici (Volkswagen Digital Solutions) shares the honest sequel: why collaboration falls apart over time, even after you’ve done the work to remove silos. She breaks down the forces that quietly pull teams back into old patterns:

• Budget cycles vs quarterly planning

• Governance and steering committees are slowing down decisions

• Role ambiguity and mismatched expectations

• Language gaps that create invisible misunderstandings

• Rituals that turn performative instead of useful

Then she gets practical on what helps teams stay aligned: pairing, shared glossaries, rotations into each other’s worlds, and regularly resetting the working model as teams and contexts change. Watch the full session below:

The Results of Last Week’s Poll

The question: What is the biggest blocker to using AI for higher-level work in your organisation?

Last week’s poll asked what most blocks organisations from using AI for higher-level work, and the top answer was telling: missing context and decision history (30%). In other words, the problem isn’t that AI cannot generate options; it’s that it doesn’t know enough about the why behind past decisions to be trusted with the next one. Close behind was trust and reliability at 27%, which shows that even when teams do try to use AI at a more strategic level, confidence in the output is still fragile.

The lower answers matter too. Only 10% picked data privacy and vendor risk, and 12% chose organisational resistance, suggesting that for many teams, the biggest blocker is not policy but knowledge design. If your decision history is trapped in people’s heads, buried in Slack, or scattered across decks and docs, AI will always struggle to help at the level that actually matters. One commenter captured the tension well: higher-level work can use AI as a lever, but human judgment still responds best to uncertainty, serendipity, and the unexpected cuts that frameworks miss.

My read is that this is a documentation problem disguised as an AI problem. Teams that want AI to support better strategic thinking need clearer context, stronger records of trade-offs, and more explicit reasoning around past decisions. Without that, AI will stay stuck as a fast producer of plausible outputs rather than a useful partner in higher-level judgment.

If you want to go deeper on how careers and leadership are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

All Jobs Have Four Layers. AI Wants Three of Them.

Most product jobs are really four layers of work.

Level 1 is task execution. Level 2 is choosing the right solution and trade-offs. Level 3 is deciding what problem is worth solving. Level 4 is setting direction under uncertainty.

AI is already compressing the bottom two layers. The timelines in this piece are opinionated, but the sequence is the point: as models get better at consistency and “remembering” your system, task execution gets automated first, then solution design starts to follow. That shifts the baseline from “can you produce” to “can you decide”.

Where humans keep leverage is higher up the stack. Problem framing is hard to automate in established organisations because the context and decision history often is not captured anywhere. Direction setting stays human because accountability cannot be delegated.

The practical takeaway is to move up a layer on purpose. Get fluent in trade-offs, then in systems thinking across functions, and start caring about the “why” behind decisions, not just the “what”. That is where careers and companies stay resilient as AI improves.

This Week’s Updates

Enabling the Team

All Jobs Have Four Layers. AI Wants Three Of Them by Rory Madden
If you work in product development, as an engineer, designer, product manager, or researcher, you're watching AI reshape your profession in real time. The question isn't whether AI will change your work. It's when, how much, and what you should do about it.

The Best Leaders Are Great Followers by Tomas Chamorro-Premuzic and Amy C. Edmondson
The most effective leaders are those who exhibit the same attributes as exemplary followers. They excel at listening, learning, and adapting rather than commanding from the top. Leadership and followership are co-created, fluid roles, not heroic acts of command.

Product Direction

Is AI Disrupting Product Development? by Itamar Gilad
AI is changing how teams work, but not the fundamentals of product development, so the real advantage still comes from improving discovery, judgment and time to outcome rather than just shipping faster with new tools.

How PMs Can Vibe Code To Build Stronger Requirements by Chris Butler
Using vibe coding to explore rough ideas, generate variations, and pressure test assumptions helps PMs turn fuzzy thinking into clearer requirements, stronger trade-offs and better aligned product decisions before the wider team gets involved.

Continuous Research

GenAI for Complex Questions, Search for Critical Facts by Maria Rosala and Josh Brown
Users choose AI to explore and synthesize information, but they rely on traditional search when accuracy and trust are critical.

A Practical Guide To Structuring Researchops Through Organizational Change by Carolyn Morgan
Reorgs force ResearchOps teams to rethink structure, support and decision rights, so choosing between centralized, decentralized and hybrid models means balancing consistency, proximity and scale instead of chasing a perfect org chart.

Continuous Design

AI Sped Up Execution. Your Team’s Decision-Making Hasn’t Caught Up by Niyati Gupta
As AI makes execution cheap, judgment becomes the real constraint, so teams need explicit decision systems that surface dissent, clarify ownership and match deliberation to the stakes of the bet instead of mistaking fast prototyping for real progress.

Design Leaders Need To Jam With Their Teams by Jon Daiello
Treating design leadership as apprenticeship rather than distance management means pairing on hard problems, giving detailed craft feedback, and modelling how decisions get made, so junior designers grow through proximity instead of being left alone with frameworks and design systems.

Continuous Development

Who Does What And How To Support Them by Anton Zaides
Allocating work well means balancing company needs, individual growth and team resilience, then matching support to task-specific maturity rather than job title so stretch assignments build capability without creating fragile teams.

Why We've Tried To Replace Developers Every Decade by Stephan Schwab
Every wave from COBOL to AI promises to make developers optional, but the real bottleneck is not syntax or typing speed; it is the judgment needed to handle complexity, edge cases, and evolving systems well.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Want To Make Your Case To Join UXDX 2026?

This is where you can start:

If you’re trying to make the case for UXDX 2026 internally, the 2025 Post Show Report is a useful place to start. It provides a clear picture of the types of talks, themes, and practical takeaways teams gained from last year’s event, making it much easier to show your manager the value in real terms.

A lot of people use it as a simple way to support approval conversations: what was covered, what problems were tackled, and why it matters for product, research, design, and engineering teams heading into 2026.

Download it here: https://uxdx.com/post-show-report/

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

FREE COMMUNITY EVENTS 

UXDX 2026 Speaker Announcements

AI Readiness Starts Here! Ready to move beyond AI hype and tackle what real implementation looks like inside complex organisations? Here are some workshops you can look forward to at UXDX 2026:

Mirela Mus joins us at UXDX EMEA 2026 in Berlin with a hands-on workshop focused on how to future-proof careers, products, and business models in the age of AI. Through three real case studies, Mirela will show how to move from using LLMs to speed up workflows toward identifying and prioritising AI-first product opportunities that can create genuine value.

Llewyn Paine will lead a strategic workshop on Agent Experience (AX) testing at UXDX USA 2026 in New York. She will show how leaders can spot where websites, SaaS products, and apps break for AI agents, and what that reveals about commercial risk, operational readiness, and product strategy, helping teams understand their Agent Gap and what it takes to close it.

These workshops are ideal for leaders who want practical, grounded ways to respond to AI transformation, strengthen cross-functional decision-making, and build products that are ready for what comes next.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in February here.

Video Of The Week

Data Science at The New York Times

Chris Wiggins (Chief Data Scientist at The New York Times) walks through what it takes to turn behavioural data into better product decisions, without losing the human intent behind the numbers. As the Times evolved from a newspaper into a bundle of digital experiences across apps, audio, cooking, games, Wirecutter, and Wordle, the real challenge became alignment: what are we optimising for, and what are we willing to trade off?

Chris breaks down the difference between prediction and prescription, why experiments come first, and how data science creates the most value when it helps teams decide what to do, not just report what happened. You will also hear practical examples, from tuning paywall friction with a real-time model and “knob meetings,” to building recommendation systems with editorial guardrails and self-serve tools that fit real workflows. Watch the full talk by clicking the banner below:

The Results of Last Week’s Poll

The question: How confident are you that you get the unfiltered truth at work?

Last week’s poll asked how confident people are that they get the unfiltered truth at work, and the results are not exactly reassuring. Only 11% say they are very confident that people challenge them directly. Another 21% feel fairly confident, but only in certain rooms. That leaves the majority either not confident because feedback is filtered or delayed (27%), worried because they mostly get agreement (15%), or unsure because they have no real signal at all (26%).

That matters more than most teams realise. Once feedback starts getting softened, delayed, or selectively shared, decision quality drops fast. Leaders end up managing the version of reality that is safest to say out loud, not the most useful one. And when “everything sounds fine” becomes the default, you often find out the truth only after the costs have compounded.

Getting the unfiltered truth is not about asking people to be braver. It is about building systems where honesty is normal: direct access to users, exposure to raw evidence, regular challenge from peers, and enough trust that disagreement is seen as contribution, not disloyalty.

If you want to go deeper on how careers and leadership are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.

Truth Is Becoming Your Scarcest Resource

AI has made competent analysis cheap. What it cannot give you is the messy, human truth: what is actually happening, which assumptions are wrong, and what people are not saying out loud.

That gets harder as you grow. The more authority you have, the more feedback gets filtered by politeness, hierarchy, and self-interest. You lose the ability to think out loud because a half-formed idea can turn into someone else’s priority, or a quiet complaint you never hear.

The fix is not another dashboard. It is relationships and habits that keep you close to reality. Early on, you need people who show their reasoning so you can build judgement. Mid-career, you need cross-functional reality-checkers who will challenge your framing. Senior levels, you need a small circle of truth-tellers who are not impressed by your title and will tell you when you are about to make a mistake.

In an AI world, truth becomes a competitive advantage. Build the channels now, because by the time you realise you need them, the filtering has already set in.

This Week’s Updates

Enabling the Team

In an AI World, Truth Becomes Your Scarcest Resource by Rory Madden
The decisions that matter most depend on inputs that don't live in dashboards. The quality of your inputs has always mattered, but as people become increasingly reliant on AI to help with high-level decision-making, it is becoming more critical.

The Blame Game: How Bureaucracy Eats Responsibility by Joost Minnaar
When organisations optimise for blame, they add layers, rules and sign-offs that protect people from accountability while quietly killing initiative, so replacing guilt with learning, trust and shared ownership is what lets teams adapt and improve.

Product Direction

The Real-World Journey To Value And Product-Centricity by John Cutler
Moving from delivery centricity to product centricity is not a clean maturity curve, it is a messy shift where work, goals and value models overlap until teams, funding, org design and strategy gradually align around how the business actually creates value.

The Circular Logic Of Our Metrics by Pavel Samsonov
Chasing dashboard metrics as if they were strategy pushes teams to copy whatever is most salient and measurable, so real product thinking means reverse engineering the value behind the numbers and redefining success around what actually matters.

Continuous Research

Why The Distributed Growth Model Is Failing Research Teams—And What To Build Instead by Kate Towsey
Scaling research through distributed growth models spreads support thin and quietly degrades quality, so research teams need operating models built for resilience, clear service boundaries, and sustainable impact instead of growth era assumptions.

How AI Literacy Shapes GenAI Use by Maria Rosala
Using generative AI often doesn’t mean using it well. AI literacy requires both prompt fluency and the ability to assess outputs.

Continuous Design

Showing The Work Of Agents In UI by Luke Wroblewski
Designing UIs for agentic AI means neither hiding the process behind a spinner nor flooding people with every tool call; using progressive disclosure turns the agent’s step-by-step work into an optional progress layer and audit trail while keeping the main view focused on outcomes

Why AI Is Exposing Design’s Craft Crisis by Dolphia Arnstein
Regaining strategic influence means helping designers build enough technical fluency to judge feasibility, challenge constraints, and contribute meaningfully to product decisions.

Continuous Development

AI Makes Interfaces Disposable by Chris Loy
AI coding agents make it trivial for power users to spin up disposable interfaces on top of durable capabilities, so teams need to treat APIs and service layers as the real product and design them for openness, safety and extension instead of assuming everyone will always come through their official UI.

Use It Or Lose It by James Stanier
As managers offload more planning, reasoning, and synthesis to AI, they risk eroding the very cognitive skills their role depends on, so staying effective means keeping a minimum effective dose of coding, staying hands-on with new tools, and using AI to support judgment rather than replace it.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
Click here to share an article

THE UNBLOCKERS

Is Your Team’s Hard Work Getting Noticed?

The deadline for The Unblockers Awards at UXDX EMEA 2026 is March 22nd.

Unlike other programs, we value impact over aesthetics. Whether you’ve mastered AI integration, cleared organizational hurdles, or driven massive retention, we want to see the "how" behind your "wow."

What’s in it for your team?

• Validation: Direct feedback from our panel of expert judges.

• Visibility: Promotion through post-event content and professional photos.

• Value: Finalists can win team tickets to UXDX EMEA 2027 and a published case study.

It takes exactly 3 minutes to start the process. No long-form applications required right now. If your team has done work worth sharing, start with the quick entry form here, and we’ll send you the next step for the full submission.

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

FREE COMMUNITY EVENTS 

UXDX 2026 Speaker Announcements

If you are working through the realities of AI adoption, legacy systems, and organisational change, these are two sessions to keep firmly on your radar.

At UXDX EMEA 2026 in Berlin, David Sward from Siemens shares how his team tackled one of the toughest design system challenges at enterprise scale. He will unpack the journey from multiple specialised systems to a single design language across highly complex industrial products, and explain why Siemens chose to open source its design assets. Expect practical lessons on handling legacy products with decades-long lifecycles, designing for acquisitions, and building systems that can evolve without forcing one tech stack across the business.

At UXDX USA 2026 in New York, Andra Bond and Olivia Lucas, from Electronic Arts, will show how EA used its Experience Atlas and evolution mapping to move from product-centric planning to joined-up experience journeys across identity, loyalty and support. This session offers a practical look at how to align design, research, data science and operations, unblock delivery and create better customer outcomes through shared frameworks and measurement.

These sessions are essential for leaders trying to scale better ways of working across complex organisations, especially where transformation needs to lead to real outcomes rather than more process.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in February here.

Video Of The Week

The Superpowers and Shadows of A/B Testing:
Balancing Data-Driven Success with Bold Innovation

A/B testing can feel like a cheat code. You get clarity, confidence, and a chart that makes the decision look obvious. Ryan Leffel (Head of Design) makes the case for why that same superpower can quietly trap teams in over-optimisation, risk avoidance, and a slow drift away from bold product thinking.

In this talk, Ryan shows how Priceline uses testing to de-risk change, not just chase bookings, then unpacks the four strengths of A/B testing and the shadow each one can cast: reactivity, tunnel vision, analysis paralysis, and runaway complexity. He also breaks down the biases that quietly distort decision-making, using Groupon’s email fatigue spiral as a warning, and shares how leaders can build a culture where curiosity beats certainty.

The sharpest takeaway is the “local maxima” trap: months of tiny tweaks that never unlock the bigger opportunity. Sometimes the real move is not another button test. It is the breakfast sandwich. Watch the full talk now:

The Results of Last Week’s Poll

The question: Is your company ready to adopt empowered autonomous teams?

Last week’s poll asked whether companies are ready to adopt empowered autonomous teams, and the answer is more sceptical than optimistic. Only 23% say they already work this way, with another 12% saying parts of the organisation are moving in that direction. The majority are still on the outside: 38% say they’re not ready, and 27% say they simply do not want to go there.

That split matters. A lot of organisations talk about empowerment as if it is an obvious next step, but the results suggest many still see it as either impractical or undesirable. In some cases, that is honest self-awareness. If the organisation lacks a clear strategy, fast feedback, or trust in teams, “autonomy” can quickly turn into drift. In other cases, though, the resistance is more about leaders not wanting to let go of control.

The real question is not whether autonomous teams sound good in theory. It is whether the surrounding system is designed to support them. Teams need clear outcomes, boundaries, and evidence loops. Without those, autonomy feels reckless. With them, it becomes one of the few ways to increase speed and ownership without increasing layers of management.

If you want to go into how careers are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI digs into the levels of thinking and how to keep building judgment in a world that keeps trying to automate it.

The Role Of Stream Teams In ZeroBlockers

Empowered, autonomous teams can design and build better products because they are closer to the customers and can get quicker feedback.

But it isn't often clear how to go about setting up teams to work like this, because it is a dramatic change from the traditional way of working.

In this week's article, I go into detail about scope, core responsibilities, team composition, ways of working, and potential risks. I'd love to hear your thoughts on this approach, so feel free to reply to this email with any ideas, thoughts, or feedback.

This Week’s Updates

Enabling the Team

The Role Of Stream Teams In ZeroBlockers by Rory Madden
Stream Teams are the driving force behind a scalable, high-performing product organization. By maintaining alignment with strategic objectives while executing autonomously, they create a continuous flow of value without bottlenecks.

Your Strategy Needs A Visual Metaphor by Martin J. Eppler, Andri Hinnen and Fabienne Bünzli
Many strategies fail not for lack of vision, but because employees don’t understand or aren’t sold on enacting them. Effective metaphors pass the “4 Fs” test: fitting, familiar yet fresh, and facilitating action. Finding a metaphor that fits these principles will help leaders institutionalize meaningful visuals.

Product Direction

AI Is Not A Strategy. It’s An Amplifier by Vandana (Vinni) Munjal
Treating AI as an amplifier, not a strategy, means using pilots to surface gaps in information architecture, governance, and ownership. So automation lands on a coherent system instead of accelerating existing chaos

The Art Of Saying ‘No’ by Luke Albest
Treating “no” as the core product skill means guarding teams from the complexity trap, involving engineering early, and using feasibility checks, a minimum delightful product, and analytics to cut bloat so roadmaps stay focused on the few features that actually create value.

Continuous Research

How A Few Usability Tests Changed Our Whole Product Roadmap | Dscout by Bex Jeanson (Sponsored Content)
Bex shares how advanced usability testing unexpectedly changed her company’s product roadmap for months (and years) to come.

Five Research Questions That Provide The Foundation For Good Design by Sharma Hendel & Brenda Weitzer
Shifting from “we think” to “we know” means running every product idea through five evidence questions about audience, real use cases, unmet needs, solution fit and team fit, so design decisions rest on validated assumptions instead of personas, vibes and competitor copycats.

Continuous Design

A New Navigation Paradigm by Francisco Nunes
AI does not eliminate navigation; it delegates it to invisible systems, creating cognitive debt and hidden power, so designers need to treat interfaces as structures of thought and deliberately decide what to reveal, hide, and automate to preserve human agency and navigational skill.

The Hidden Cost Of AI Prototypes That Are Made To Die by Allie Paschal
AI makes it trivial to spin up glossy prototypes, but treating them as disposable creates hidden drag when nothing can be extended, handed off, or reused, so teams need to choose tools and workflows that produce structured, portable UI when the goal is to evolve ideas into a real product rather than just win a thirty-minute review.

Continuous Development

Where Good Ideas Come From (For Coding Agents) by Sunil Pai
Applying Steven Johnson’s seven ways to coding agents shows that LLMs excel at adjacent possible diffs and scaffolding but only become reliably useful when engineers supply explicit constraints.

The Next Two Years Of Software Engineering by Addy Osmani
Frames the next two years through five scenarios on juniors, skills, roles, specialisation and education in an AI heavy industry, giving developers and leaders concrete moves to stay valuable as coding shifts from typing to supervising complex, agent driven systems.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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THE UNBLOCKERS

Awards For Cross-Functional Teams In EMEA

At UXDX EMEA 2026, we wanted to do something a bit different. We’re launching The Unblockers to recognise teams that can show a real chain from evidence to decision to impact. There are three categories:

• Impact Award for evidence that led to real outcomes

• Best Use of AI Award for AI that meaningfully changed how you work or what you built

• The Unblocker Award for removing the barriers that help cross-functional teams move faster

If your team has done work worth sharing, start with the quick entry form here before 22 March, and we’ll send you the next step for the full submission.

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

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UXDX 2026 Speaker Announcements

Two newly announced speakers for UXDX 2026 are tackling the hard part of AI: making it work inside real enterprise constraints, with real teams, and real accountability.

At UXDX EMEA 2026 in Berlin, Timo Ilola from Taxfix will share how they are becoming an AI native organisation by embedding AI across design, product, and engineering. He moves beyond the hype with practical examples of where AI genuinely accelerates workflows, how roles are evolving, and what changes when teams stop shipping incremental updates and start driving strategic impact.

Over at UXDX USA 2026 in New York, Anya Gerasimchuk from McKesson will take you inside a three-year AI transformation across oncology and multispecialty care, where the bar for trust, safety, and compliance is non-negotiable. She will share how her team explores where AI can genuinely improve clinician productivity and patient outcomes, while being clear about where it must be constrained, how they reduce administrative burden, and how strong UX guardrails help protect trust in high-risk healthcare environments.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in February here.

Video Of The Week

Design isn’t dead, but the narrative might be

Most teams are not asking whether design matters. They are asking whether design is anything more than polish, screens, and speed inside a sprint machine. In this week’s video, Pamela Mead challenges the story many of us have helped normalise: design as the UI layer, the misunderstood hero, the function that “plays around” in tools. Her point is simple and uncomfortable. When we reduce design to artifacts, we make it easier for organisations to treat it as optional and easier to imagine it can be automated away.

She unpacks what needs to change if design is going to stay influential through the next cycle: making decision-making legible, reclaiming design as problem-solving grounded in human behaviour, and moving from hero narratives to value-centered collaboration across disciplines. She also brings AI into the frame without the drama, arguing it is not a winner-takes-all game; it is a test of how teams evolve their ways of working together. Watch the full session:

The Results of Last Week’s Poll

The question: Where do you see the biggest risk of “perfecting the wrong thing” in your org?

Last week’s poll asked where organisations are most at risk of “perfecting the wrong thing,” and the results show that the biggest problem still sits right at the start of the process. The top answer (31%) was teams jumping to solutions before the real problem is properly understood. Close behind, 26% said they ship quickly, but measurement and learning lag behind, while 24% pointed to siloed functions where nobody really owns the end-to-end result. Only 19% chose output optimisation, though I’d argue that’s often what sits underneath the rest.

What these answers have in common is a failure of feedback. Teams either start with weak problem framing, lose ownership as work moves through silos, or move so fast that learning arrives too late to shape the decision. That’s how organisations end up doing excellent work on the wrong thing: polished design, well-written PRDs, fast delivery, all aimed at a problem that wasn’t the highest-value one to solve in the first place.

The fix isn’t just “do more research” or “measure more stuff.” It’s building a stronger decision chain from evidence to problem framing to clear ownership to learning loops. Speed is useful, but only if it’s attached to judgment. Otherwise, you just get to the wrong answer faster.

If you want to go into how careers are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI digs into the levels of thinking and how to keep building judgment in a world that keeps trying to automate it.

Outcomes Become Your Competitive Advantage

AI is making outputs cheap. That changes what gets rewarded.

When anyone can generate a solid PRD, a decent design direction, or a passable analysis in minutes, the edge is no longer how well you produce. It is whether you are working on the right thing, and whether it actually moves an outcome.

That is the trap this week’s piece tackles. Teams (and careers) get stuck perfecting solutions to problems that do not matter. In the past, slow delivery gave cover. Now the feedback loop is faster, so you hit “did it work?” sooner, and there is nowhere to hide behind effort.

The shift is from being a specialist who optimises your slice to being someone who can connect the system across functions and align people around the real problem. That is what “comb-shaped” capability is getting at: enough cross-functional fluency to spot the wrong framing, translate between incentives, and make the problem visible so teams can solve it together.

This Week’s Updates

Enabling the Team

As AI Commoditises Outputs, Outcomes Become Your Competitive Advantage by Rory Madden
A cross-functional team built a solution: a centralised system that aggregated feedback from every channel. Customer voices would finally drive the roadmap. There was just one problem. It didn't work.

Head Up, Feet Moving by Jen Briselli
Treating collaboration like hockey in a complex system means keeping your “head up” to read patterns and possibilities while your “feet keep moving” through experiments, so teams learn to navigate uncertainty together instead of waiting on perfect plans from the sidelines.

Product Direction

So You Want To Define “the Problem”? by John Cutler
Defining “the problem” means layering customer stories, other actors’ perspectives, and the surrounding incentives and power dynamics instead of hunting for a single root cause.

Key Practice: Continuous Discovery, Continuous Design, Continuous Delivery (CD3) by Jason Yip
Framing discovery, design, and delivery as simultaneous, continuously rebalanced activities helps leaders decide when to deepen problem discovery, expand solution options or double down on shipping.

Continuous Research

Lean Thinking in UX Research: More Value, Less Waste | Great Question by Sara Ulius-Sabel (Sponsored Content)
Sara on the power of Lean Thinking, the seven wastes in UX research, and her strategies for minimizing each and maximizing value for customers.

UX Leadership In The AI Disruption | Dscout by Michael Winnick
Treating AI as a new design material, not an existential threat, means UX leaders need to model curiosity, run small bets, and talk in business outcomes, so their teams stay relevant and credible instead of getting stuck in fear or hype driven extremes.

Continuous Design

Public Design Systems Are Worth It by PJ Onori
Treating public design systems as libraries, not leaks, keeps craft knowledge flowing between companies and generations, raising the bar for documentation and giving teams a shared reference instead of hiding patterns behind private walls.

Most AIUX Is Just Search With Extra Steps? by Imran Saif
Imran argues that most AI products still mimic search boxes and show alternative patterns like one-click actions, structured commands, and guided flows that treat AI as a collaborator instead of a fancy query field.

Continuous Development

Holistic Engineering: Organic Problem Solving For Complex Evolving Systems by Vanessa Formicola
Holistic engineering treats software as a socio-technical system where reward structures, org charts, and hidden dynamics shape architectures as much as code, so leaders need to model these forces explicitly.

The Rise Of Industrial Software by Chris Loy
AI coding is shifting software from handcrafted craft to industrial production, flooding the world with cheap, disposable apps, so leaders need to anticipate Jevons’ style overproduction, mounting technical debt, and stewardship problems for software that no one really owns, rather than just celebrating lower build costs.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Wildcard Winner: Rahul Balu

New UXDX EMEA 2026 Speaker Joins The Stage

Rahul Balu is taking the final wildcard slot for UXDX EMEA 2026. Rahul is Senior UX Designer at Amazon, and he’ll be speaking on “From Opinions to Outcomes: How Clarity Builds Trust and Better Design.” It’s a session for anyone who has felt design work stall, not because of a lack of talent or research, but because everyone is right in different ways.

Rahul’s argument is simple and sharp: design teams rarely fail due to missing tools. They fail when research, delivery, stakeholders, and designers all speak different languages. Somewhere in that mix, clarity disappears. In his talk, Rahul will share practical ways to build a shared design language that turns debate into decisions, aligns teams around outcomes, and helps design move faster without losing judgement.

A quick reminder: ticket prices increase this weekend. If you’re planning to join us in Berlin or New York, now is the moment to secure your spot before rates go up.

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

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THE UNBLOCKERS

Awards for cross-functional teams

This year in Berlin, we will be celebrating teams that deliver real impact. We are excited to announce The Unblockers, three awards built to recognise teams who can show a clear chain from evidence to decision to impact. No popularity contest, no glossy decks, no “best process” awards. Just practical case studies that other teams can learn from, grounded in what actually changed and what it moved.

Here are the categories:

• Impact Award: Evidence that led to real outcomes (adoption, retention, conversion)

• Best Use of AI Award: AI that changed how you work or what you built

• The Unblocker Award: Removing barriers so cross-functional teams move faster

You can fill out your initial expression of interest with quick entry here before March 22nd. From there, you will be given instructions to create your official submission.

UXDX 2026 Speaker Announcements

Two more speakers are joining the UXDX 2026 stage! Both sessions cut straight to what senior teams are wrestling with right now: real AI implementation and the organisational change that comes with it.

At UXDX EMEA 2026 in Berlin, Des Traynor will share how Intercom rebuilt its entire way of building software to succeed in an AI-first world. He will cover what changed across process, pace, teams, and roles, and what Intercom learned while launching Fin, its AI Agent for customer service.

At UXDX USA 2026 in New York, Sneha Narahalli will share how Sephora keeps journeys simple across web, app, store, and chat. She will break down the core loop (search, discover, purchase, receive), how they cut friction, and how they use experiments to prioritise tech work, including practical patterns for conversational commerce.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in February here.

Video Of The Week

Building Customer Intuition Across the Product Lifecycle

At DocuSign, Marine Palamutyan and Morgan Davis were given an ambitious mandate: build stronger customer intuition across the organisation. They started by defining what “intuition” actually means, then turned it into a repeatable system that scales across product, engineering, marketing, sales, and leadership.

In this talk, they share the framework that made it practical: a Customer Intuition Pyramid with three layers. Foundation knowledge teams can return to “built together” workflows that turn insights into decisions, and cross-org partnerships that embed customer readiness into how the business ships. Watch the full talk now:

The Results of Last Week’s Poll

The question: Where does “AI slop” show up most often in your organisation?

Last week’s poll asked where “AI slop” shows up most often inside organisations, and the results point to a familiar pattern: it’s not the obvious failures that hurt most, it’s the polished work that quietly erodes quality. The top answer was designs that look finished but break consistency (28%), followed by research summaries that miss key context (24%). Together, that’s over half of respondents calling out the two areas where “looking right” can mask “being wrong”.

What’s interesting is that the risks are different but connected. In design, slop shows up as UI that ships faster than the system can absorb, creating fragmentation that teams pay for later. In research, it shows up as a believable synthesis that skips the nuance needed for good judgment. Add in the 18% seeing features that ship but solve the wrong problem, and the theme is clear: AI makes it easier to produce outputs that feel high-quality, while making it easier to miss the deeper work of coherence, context, and intent.

The 21% who aren’t seeing this yet are worth paying attention to too. That can mean teams are using AI cautiously, or it can mean the costs just haven’t surfaced. Either way, the best guardrail isn’t banning tools, it’s raising the bar on what “done” means: consistency checks, stronger definitions of ready and done, and human ownership of the frame before AI accelerates the execution.

If you want to go deeper on how careers are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI digs into the levels of thinking and how to keep building judgment in a world that keeps trying to automate it.

The Technical Debt Machine & Managing AI Slop

AI will build whatever you ask for, quickly and confidently. That is exactly why it is dangerous. It will not challenge the brief, spot the long-term trade-offs, or warn you when a “reasonable” choice breaks your architecture, your design system, or your product strategy.

Before AI, teams accumulated debt slowly enough that reviews and critiques could catch most of it. Now you can generate a year’s worth of technical and product debt in a single afternoon, because every session starts with missing context and the model fills the gaps with plausible guesses.

That is what creates “AI slop”: work that looks finished, but quietly violates your patterns. The fix is not better prompts. It is explicit principles that travel with the work.

Principles have always mattered, but teams got away with keeping them in people’s heads. AI cannot absorb that osmosis. If constraints are not written down, they do not exist. The teams that do well here keep a short set of guardrails for architecture, product, and design, then link out to deeper docs when needed.

The unexpected upside is that this rigour pays back immediately for humans too: faster onboarding, cleaner reviews, fewer opinion battles, and a more coherent product.

This Week’s Updates

Enabling the Team

The Technical Debt Machine: How To Manage The Risk Of AI Slop by Rory Madden
AI is the perfect yes-man. And yes-men are how organizations accumulate debt. This gap produces what we call "slop": output that looks finished and sounds plausible but contains debt that will slow down future work. 

The 5 AI Tensions Leaders Need To Navigate by Rebecca Hinds and Robert I. Sutton
Introducing AI into work exposes five core tensions – experts vs novices, centralised vs decentralised, steep vs flat hierarchies, fast vs slow, and top down vs bottom up change – so effective leaders treat these as design constraints to balance rather than problems to eliminate, using them to shape org structure, incentives, and ways of working around AI.

Product Direction

Governance By Principle, Not By Template by John Cutler
Treating governance as principle-driven risk management instead of project templates means shifting from faux precise codes and business cases to durable units like products, platforms, and capabilities, so investment oversight actually matches how value is created. 

The AI Bubble Isn’t Bursting — It’s Diffusing by Ian Batterbee
Treating AI not as a bursting bubble but as a diffusing technology reframes the moment as a shakeout, where hype gives way to slow, uneven integration into workflows, infrastructure and roles.

Continuous Research

Mastering The Art Of Research Communication | Great Question by Jesse Livingston (Sponsored Content)
Jesse on why most research fails to land, the four principles of effective research communication, and why plain language is powerful language.

The Business Is The Only Stakeholder That Matters by Josh LaMar
Treating UX and market research as rival camps misses the point; research becomes indispensable only when it clearly makes the business money, so aligning questions, methods, and storytelling to business outcomes matters more than defending disciplines or methods.

Continuous Design

Stop Chasing AI Design Demos. Start Designing Better Decisions by Allan Cardozo
Start from outcomes and kill criteria, build interaction systems that govern AI behaviour, and align resources and KPIs around value streams so strategy actually shapes what ships instead of decorating AI hype.

Silicon Clay: How AI Is Reshaping UX Design by Andrew Tipp
Five years of academic studies show UX teams already use AI most in discovery and testing, gaining speed and lower costs. However, risking generic, biased work and skill atrophy unless human judgment, critical thinking, and ownership stay at the centre.

Continuous Development

What Happens When The Coding Becomes The Least Interesting Part Of The Work by Obie Fernandez
Treating coding agents as partners, not threats, lets senior engineers offload mechanical typing and stay focused on judgment, trade-offs, and intent, turning “writing code” into the least interesting part of the job.

Why Does Development Slow? by Kent Beck
Every new feature quietly shrinks your future options, so keeping development fast means alternating between adding capability and restoring optionality through refactoring, tests, and simplifying decisions.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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EMEA VOTE NOW - For Your Favourite Talk!

Which speaker should be on stage at UXDX EMEA 2026?

You get to choose who takes the final speaking slot on the UXDX EMEA 2026 agenda in Berlin. Four amazing sessions are up for the vote:

• Angela Pesta (GitLab) on designing for “unknown unknowns” in the age of AI, and why human creativity still matters when the problem isn’t even clear yet.

• Caroline Arvidsson (Danmarks Fængsler) with a grounded reflection on the analogue, human side of design in a tech-heavy world.

• Rahul B (Amazon) on moving from opinions to outcomes, using clarity and shared language to turn debate into decisions.

• Tim Makin (CDL Software) on the AI delivery lifecycle, with real examples of where AI speeds collaboration, where it adds friction, and what teams learn the hard way.

Voting is live on LinkedIn. Click on your favourite and help decide the final slot here: https://www.linkedin.com/feed/update/urn:li:activity:7431627647711059968

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UXDX 2026 Workshop Announcements

Two new hands-on workshops just landed for UXDX 2026, built for product, design, and engineering leaders who want real progress on AI implementation (without breaking quality, trust, or delivery).

In Berlin, Rina Volovich and Haim Repael Azoulay (accessiBe) lead “AI & Accessibility in Practice: Closing the Design to Code Gap”. If accessibility keeps getting lost somewhere between Figma, handoff, and production, this workshop is built for you. You will work through an end-to-end flow using AI-powered tools (Figma plugins, code assistants, automated tests) and leave with a practical mental model for an accessibility aware pipeline across design, engineering, and deployment.

Jim Morris (Product Discovery Group) is bringing to New York “AI Prototyping for Non-Engineers: Demo + Hackathon”. This is about moving beyond basic prompting into higher leverage work: tooling, agents, prototyping, and shipping learning fast. You will get an intro to vibe coding, watch a live demo, then build your own interactive prototype in a hands-on hackathon, and share what you learned with the group.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in January here.

Already have a ticket but need a place to stay? Find exclusive UXDX Hotel deals here:

Video Of The Week

From Cost Centre to Strategic Asset: Earning a Real Seat at the Table

Paul Strike (Principal: Design and Research Strategy at Reforme Design) and Falguni Desai (Managing Director, Strategy, Banking & Capital Markets at Microsoft) get specific about why design keeps being treated as execution in complex organisations, especially in banking and capital markets, and what actually shifts it. Not a rebrand. A practice: literacy, framing, and partnerships that change decisions early, before momentum makes change expensive.

They cover how to translate design into the language leaders trust (risk, cost to serve, time to serve), why “UX vs design” confusion persists when leaders only see the visual layer, and how to build allies through product and strategy roles so influence becomes durable rather than dependent on one sponsor. Watch the full talk now:

The Results of Last Week’s Poll

The question: How does your organization typically respond when product features fail to deliver expected results?

Last week’s poll asked how organisations typically respond when product features miss their expected results, and the answers show a familiar instinct: add structure rather than improve learning. A combined 51% either add more approval layers (29%) or hire more coordinators and project managers (22%). Another 26% double down and push harder on the original plan, which usually signals sunk-cost pressure and a fear of admitting the bet was wrong.

Only 23% said their organisations empower teams to iterate and learn faster. That gap matters because feature failure is rarely solved by more control. More gates and more coordination can reduce visible risk, but they also slow down feedback, stretch decision cycles, and make it harder to uncover what actually caused the miss.

The healthiest pattern is the one that treats “failed expectations” as a learning moment, not a governance problem. Empowered teams with clear outcomes, decision boundaries, and tight feedback loops can run smaller experiments, correct course earlier, and build real confidence through evidence. Without that, organisations often end up with the worst of both worlds: slower delivery and the same uncertainty, just wrapped in more process.

If you want to go into how careers are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI digs into the levels of thinking and how to keep building judgment in a world that keeps trying to automate it.

The Risk Of NOT Empowering Teams

When products fail to deliver expected business value, most organisations respond by tightening control through more detailed business cases, approval layers, and coordinators.

This approach ignores two fundamental market realities:

1. We don't fully understand what customers want, and

2. We cannot effectively manage dependencies at scale.

We are experts, so we think customers will love our ideas - but the data says otherwise. And as the company grows larger, and development speeds slow down, we introduce new coordination roles - project managers, program managers, scrum masters.

But our fixes only make the problems worse. We cannot manage our way out of exponentially increasing dependencies. Organizations caught in this cycle face declining product performance as features fall short with customers. Market share erodes as more agile competitors respond faster to customer needs, while development costs spiral upward.

Empowered teams offer a better approach because they acknowledge the reality of modern software development. They solve the uncertainty problem through outcome focus, short cycles, and iteration. And they solve the dependency problem through intentional dependency removal instead of management.

This Week’s Updates

Enabling the Team

The Risk Of NOT Empowering Teams by Rory Madden
Empowering teams is risky, but that doesn't mean that you should abandon the effort because the risk of not empowering teams is worse!

Why Labeling Relationships Is So Important by John Cutler
Labeling the relationships between goals, initiatives, teams, and data turns messy org charts into real operating maps, surfacing hidden assumptions so leaders can design strategy, portfolios, and learning loops that match how work actually happens.

Product Direction

Prototypes VS Products by Marty Cagan
Drawing a hard line between “build to learn” prototypes and “build to earn” products stops teams confusing happy path AI demos with shippable systems, forcing clearer conversations about scope, engineering demands and when something is genuinely ready to run a real business on.

Four Product Discovery Models: A Practical Map by Itamar Gilad
A clear map of the four ways companies decide what to build. Why command-and-control isn't the best and how to avoid gradual drift.

Continuous Research

The Complete Guide To Research Incentives | Great Question by Ned Dwyer (Sponsored Content)
Learn what to pay research participants, from consumer rates to executive interviews. Includes compliance frameworks, non-monetary incentives, and operational best practices.

AI Agent Ideas In Research Knowledge Management by Jake Burghardt
Designing specialised agents for alignment, ingestion, connection, reporting, and “gardening” turns research repositories into active systems that push relevant insights into roadmaps and docs instead of leaving past studies to rot in a passive database.

Continuous Design

Human Engineering by Michael Parent
Human engineering treats design as shaping systems so it is easy to do the right thing and hard to do the wrong thing, using affordances, constraints, and feedback loops to align human behaviour with safe, effective outcomes in everyday interactions.

Stop Craft Negging by Catt Small
“Craft negging” is vague, vibe-based criticism of visual design. This kills confidence and burns out systems-minded designers, so leaders need to name expectations, invest in visual upskilling, and reward strengths instead of weaponising taste.

Continuous Development

Are Developers Slowed Down By AI? by Cat Hicks
Picking apart a hyped “RCT” on AI coding tools shows how tiny samples, messy task design, and loose AI usage make strong slowdown claims shaky, and argues that measuring developer productivity with AI needs better methods, clearer definition,s and more humility about what current studies actually prove.

You Can’t Debug A System By Blaming A Person by Busra Koken
Blameless doesn’t mean pretending. Engineering teams can move beyond blame, debug their socio-technical systems more honestly, and turn incident reviews into real learning spaces to build better systems.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Prices increase this week!

Get your tickets now before prices increase on Sunday

Prices for UXDX USA 2026 (New York) and UXDX EMEA 2026 (Berlin) go up in 4 days, and once they rise, they won’t come back down. If you’re planning your 2026 learning and travel now, this is the moment to lock in the current rate before the next tier kicks in.

With the agenda already live, you can plan properly now: pick the sessions that matter, align it to your team’s priorities, and get the ticket sorted while the current rate is still available. If you want the best price, grab your ticket now while it’s still on the current tier. Click below to secure your tickets:

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

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UXDX 2026 Speaker Announcements

Daria Tarawneh (Head of Design Enterprise & Growth at Miro) is joining UXDX EMEA 2026 to share the unglamorous truth about enterprise AI: the work that determines whether anything ships. If your AI roadmap keeps stalling in compliance, legal reviews, or security gates, Daria will break down how to build the right foundations and keep product, design, and legal moving in sync without turning delivery into a waiting game.

For UXDX USA 2026, Paul Svoboda (Director & Head of User Experience Strategy and Design / Product Manager at EMD Digital) will tackle transformation fatigue from a product angle. Instead of more meetings and top-down mandates, he’ll show how workflow tools can bake better ways of working into the day-to-day, then how AI can gradually make those systems smarter so change scales through behaviour, not slide decks.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in January here.

Want A Taste Of UXDX? Download The 2025 Post Show Report For Free

Want a feel for what UXDX is actually like before you book 2026? The 2025 Post Show Report is the clearest snapshot: what teams were wrestling with, what resonated most, and the patterns that kept coming up across product, design, engineering, and research.

2025 set the tone. But 2026 will be a different conversation as AI moves from experiments to operating model changes. Download the 2025 Post Show Report here: https://uxdx.com/post-show-report/

Video Of The Week

Navigating Enterprise Transformation:
Design and Data for Competitive Advantage

Most enterprises are trying to scale AI on top of disconnected data, manual exports, and endless deck building. In this talk, Seth Johnson (Design Program Director) and Ed Lovely (Chief Data Officer) break down how IBM is solving the real blocker first: creating a single operational truth that leaders can actually run the business on.

You will hear how IBM uses a “client zero” loop to adopt its own products internally, why Enterprise Performance Management (EPM) matters, and what changes when end-to-end workflows are integrated across marketing, sales, finance, billing, and support. The standout moment: IBM’s C suite runs operating reviews live on dashboards, drilling from top-line numbers down to invoice level, with no spreadsheets and no slides.

If you are serious about AI in a complex organisation, this is a clear blueprint for connecting data, governance, and experience design so decisions move faster and trust stops breaking in the room:

The Results of Last Week’s Poll

The question: Which risk feels most urgent in your organisation as AI reduces execution work?

Last week’s poll asked which risk feels most urgent as AI reduces execution work, and the answers point to a career system under pressure. The biggest concern is the entry-level pipeline breaking (37%), closely followed by weaker knowledge transfer over time (28%). That combination is the real danger: fewer ways in, and fewer ways to learn once you are in.

The next signal is capability drift. 29% worry that senior titles are starting to outpace real judgment and decision quality, which is exactly what happens when output gets easier but thinking does not. Only 6% picked “too few strong middle managers,” but I read that as an outcome of the other three: if entry roles shrink and knowledge transfer weakens, you eventually feel it as a missing middle.

AI is not just changing how work gets done; it is changing how people become good at the work. If we want resilient teams, we need to design new learning loops on purpose: apprenticeships, pairing, deliberate reviews of AI output, and clearer expectations for what “good judgment” looks like at each level. Otherwise, we will ship faster while quietly eroding the capability that makes speed sustainable.

If you want to go deeper on how careers are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI digs into the levels of thinking and how to keep building judgment in a world that keeps trying to automate it.

The Pyramid Is Collapsing: How AI Is Reshaping Workforce Structure

The old workforce pyramid was built on a simple trade: junior hires did high-volume execution, and in return, they got repetition, proximity, and time to develop judgment. AI is removing the economic need for that base, and with it, the default training path most organisations relied on.

As execution gets automated, the shape shifts from pyramid to diamond. Fewer entry roles. A bigger middle of people who can diagnose, coordinate, and direct work across humans and AI. The problem is that the diamond breaks the pipeline that created that middle in the first place.

This creates three risks at once. An entry crisis, where candidates need judgment to get hired but cannot get the reps to build it. A capability gap, where titles and tenure no longer match the level of thinking people can operate at. And a missing middle, where organisations may struggle to produce the next generation of leaders because the learning-by-osmosis model has been severed.

The point is not just “people should adapt.” Organisations need new entry paths, clearer capability assessment, deliberate cross-functional development, and better ways to transfer judgment, not just decisions. Otherwise, they will end up with powerful AI, and not enough people who can direct it responsibly.

This Week’s Updates

Enabling the Team

The Pyramid Is Collapsing: How AI Is Reshaping Workforce Structure by Rory Madden
Entry-level hires did the grunt work, writing tickets, processing data, creating basic designs, conducting routine research, while slowly building the judgment that would carry them upward. That structure is collapsing.

How To Make A Seemingly Impossible Leadership Decision by Daisy Auger-Domínguez
There are four guidelines leaders can apply when making high-stakes decisions: 1) Map the tradeoffs, 2) pressure-test the plan, 3) use principles to guide decisions, not just policies, and 4) name the change.

Product Direction

Strategic Portfolio Management Meets Product-centricity by John Cutler
Treating strategic portfolio management as leadership’s job, not a reporting layer, means accepting that bets in software are illiquid and teams are not fungible.

The Why Always Comes First by Tobias van Schneider
Starting from a clear WHY and a small set of hard principles lets teams bake privacy, calm UX, and no-engagement-hacking into every decision, so AI and growth tactics amplify a coherent product philosophy instead of eroding it over time.

Continuous Research

The Ugly Truth About Net Promoter Score Surveys by Dan & Louis-Xavier
Poorly timed, generic NPS popups annoy users and skew results, arguing for fewer, better-targeted surveys with context and follow-up so feedback becomes a real source of insight rather than a vanity metric.

AI-Moderated Interviews: If, When, And How To Use Them by Maria Rosala
AI interviews offer faster feedback at scale, but they're not a replacement for in-depth, human-led semistructured interviews.

Continuous Design

Invisible Users: The People Our Design Processes Forget by Dolphia
How design teams systematically exclude 1.3 billion people by treating marginalized users as “edge cases”.

The AI Era Needs Sigma (σ) Shaped Designers (Not T Or Π) by Darren Yeo
Sigma-shaped designers treat their craft as system-level synthesis, orchestrating data, ethics, product, and engineering loops so AI features align with outcomes and constraints instead of just adding another spike of specialist skill to the team.

Continuous Development

Good Enough Is A Strategy by Trevor I. Lasn
Treating “good enough” as a deliberate strategy means taking on intentional tech debt to ship working, safe code fast, learn from real users, and refactor once there is traction instead of disappearing into perfect architectures nobody ever uses. 

The Rosetta Stone Of Design Engineering by Yann-Edern Gillet
A deeper look at how design and engineering meet, overlap, and translate meaning. A shared language of making is the only way to build real shipping velocity.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
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Wildcard Winner: Benjamin Hewett

New UXDX USA 2026 Speaker Joins The Stage

Benjamin Hewett is taking the final wildcard slot for UXDX USA 2026. Benjamin is Director of UX at Allied Solutions, and he’ll be speaking on “Never Done: Evolving UX teams who earn influence.” It’s a session for anyone who’s realised that building a design team isn’t a one-time org chart exercise, it’s an ongoing design problem.

Benjamin’s angle is refreshingly honest: high-performing UX teams don’t get there by accident, and they don’t stay there by pretending they’ve “arrived.” He’ll share what it looks like when teams design how they evolve, earn trust in the moments that matter, and grow influence in the messy reality of real organisations.

FREE COMMUNITY EVENTS 

UXDX 2026 Speaker Announcements

Larkin Brown (Sr. Director, Product Research at Pinterest) is joining the UXDX USA 2026 to share how Pinterest keeps real user insight at the centre while shipping GenAI features. Expect a very practical look at how research signals get translated into design decisions and then into engineering execution across Visual Search and the Pinterest Assistant, including the workflow patterns that held up and the moments that forced ethical and quality course-corrections.

For UXDX EMEA 2026, Haydyn Phillips (Director of User Experience at AstraZeneca) will unpack what it takes to build an AI product when the ground shifts mid-flight. It’s a true 0 to 1 case study: aligning research, design, analytics, and engineering around a shared AI context, keeping delivery moving while models and tooling evolve, and measuring impact through trust, quality, and adoption rather than productivity theatre.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in January here.

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

Video Of The Week

The Holistic Product Journey:
Redefining Design’s Role in Cross-Functional Teams

Christina Goldschmidt shares a practical playbook for design leaders who want to be more strategic without waiting for permission. Her core idea is simple: most teams are not short on talent; they are stuck. The fastest way to unstick them is to make the future tangible enough that everyone can align.

In this talk, Christina breaks down how she earned trust inside Warner Music Group through visible delivery first, then used that momentum to shape direction across the product journey. She shows how prototypes, sizzle reels, and low-fidelity artefacts can collapse weeks of miscommunication, build cross-functional buy-in, and turn strategy into something teams can actually execute:

The Results of Last Week’s Poll

The question: When you use AI to speed up your work, what do you think you lose most often?

Last week’s poll asked what people feel they lose when they use AI to speed up their work, and the results are a pretty sharp warning label. The two biggest answers were confidence in your own reasoning (37%) and deep understanding of the problem space and context (35%). That’s 72% saying the cost isn’t quality or speed, it’s cognition: you move faster, but you feel less certain about why you’re doing what you’re doing, and you’re less grounded in the reality of the problem.

Only 12% pointed to the loss of iteration as the main issue, which is interesting because it suggests the bigger risk isn’t craft reps, it’s sensemaking. If you skip the slow work of building a mental model, it becomes easy to accept a plausible answer instead of earning conviction. And once you start deferring to AI, you can end up shipping “clean” work that isn’t deeply understood, which is exactly how teams accumulate product, design, and technical debt without realizing it.

The best teams I’m seeing treat AI like an accelerator, not a substitute for judgment. They use it to widen the search space, but they still insist on human ownership of the frame: what we’re solving, what constraints matter, and what evidence would change our minds. If you want to go deeper on how careers are shifting as AI compresses the ladder, my ebook Managing Your Career In The Age Of AI digs into the levels of thinking and how to keep building judgment in a world that keeps trying to automate it.

AI Makes Work Easier, And Growth Harder

AI is making it radically easier to produce impressive work, but it is quietly removing the friction that used to build judgment.

The boring repetition, the dead ends, the rewrites, the debugging, the slow iteration, that was where pattern recognition came from. Over time, pattern recognition became taste. Taste became judgment. And judgment is what makes someone effective when the situation is messy and unclear.

Now we can generate outputs in minutes, but that speed can bypass the thinking that the output was meant to develop. You can look experienced on the outside while the foundations are still missing.

The shift is simple but uncomfortable: learning is no longer a side effect of doing the job. If you want to grow, you have to design your own practice. Study systems, not tasks. Ship real work and reflect on what AI got right and wrong. And seek out visible reasoning from people with stronger judgment so you can learn how they think, not just what they decided. Check out my full article below.

This Week’s Updates

Enabling the Team

AI Makes Work Easier, And Growth Harder by Rory Madden
Today, a designer can generate fifteen variations in fifteen minutes. The output is faster, and the quality is often higher. But something essential is missing: the learning that used to come from the struggle. This is the central paradox of the AI era.

Middle Managers Feel The Least Psychological Safety At Work by Jan U. Hagen and Bin Zhao
To restore learning and agility, companies must redesign accountability systems, normalize fallibility from the top, and build stronger communities of practice for the middle layer.

Product Direction

The Hidden Cost Of Shipping Too Fast by Anton Sten
Treating speed as progress without shared clarity turns shipping into rework, so pausing to align on the problem, users, and definition of progress lets teams turn raw speed into real velocity instead of months of untangling rushed decisions.

Your Product Ideas Probably Suck (That's Ok) by Ian Vanagas
Treating ideas as hypotheses, not precious visions, means listing real problems, pounding the pavement for interviews, and validating the problem, then solution, so weak product ideas die fast, and only evidence-backed ones move to build.

Continuous Research

The Algorithm Aversion Paradox by Dr Maria Panagiotidi
Algorithm aversion often masks status quo bias, so framing AI as the conventional choice and designing clear override paths matters as much as accuracy if you want people to tolerate errors and keep relying on automated decisions.

The Illusion Of Unmoderated UX Testing by Sanna Rau
Without context, probing and real engagement unmoderated testing often produces shallow, misleading data, so teams need to treat it as a complement to moderated work, not a cheaper replacement.

Continuous Design

The Art Of Vibe Design by Ivan Cernja
As AI makes execution trivial, “vibe design” shifts the bottleneck to taste, where designers win by naming references, directing iterations, and articulating how something should feel so models become production muscle for a clear human point of view.

Is Addiction The Responsibility Of UX? by Daley Wilhelm
Comparing scrolling to drinking shows how infinite feeds and habit loops can mimic addiction, so UX responsibility is less about blaming users and more about designing interventions, constraints, and off-ramps.

Continuous Development

A Scientist’s Guide To Debugging Engineers by Anton Zaides
Treating performance issues as nervous system overload rather than laziness or skill gaps lets managers “debug” engineers by spotting patterns like over responsiveness, chronic lateness and messy PRs, then changing expectations and workflows so people can do their best work without burning out.

You Need To Become A Full Stack Person by Den Delimarsky
AI tools are commoditizing single-skill roles. The future belongs to people who can think, build, and ship across the entire stack.

Seen an interesting article online? Share it with us, and we might feature it in our next issue!
Click here to share an article

VOTE NOW - For Your Favourite Session!

Which wildcard should be on stage at UXDX USA 2026?

You get to choose who takes the final speaking slot on the UXDX USA 2026 agenda.

Four standout sessions are up for the wildcard vote:

• Kaitlyn Daleiden (Nordstrom) on getting ahead of the product lifecycle by aligning teams to a future vision

• Benjamin Hewett (Allied Solutions) on a seven-year journey growing UX from 3 to 25 and proving measurable value

• Rafael Poiatti (Amil) on what agile looks like in digital health in the Global South under real regulatory constraints

• Eric Olive & Joseph Mauriello (DocuSign) on moving from siloed products to unified experiences.

You can vote on LinkedIn by clicking on your favourite here: https://www.linkedin.com/feed/update/urn:li:activity:7424082793711919104

FREE COMMUNITY EVENTS 

Have you already seen that these speakers are also joining us in 2026?

Dana Lawson, CTO at Netlify, is speaking about what might be the most provocative talk of the conference: "Are We Designing for Humans or for Agents?" As AI agents become more common, are we still designing experiences for people, or are we optimizing for bots? It's an uncomfortable question, and Dana's not going to shy away from it.

Tanya Adlam, Director of UX Research at monday.com, will share "When AI and Teams Blur the Lines: Who Owns the Research?", which addresses a question a lot of teams are quietly grappling with: when AI can generate insights, what's the role of dedicated researchers? She'll share frameworks for keeping research quality high even as the tools and team structures evolve.

Missed the announcements of other speakers? You can find the highlights of the speakers announced in January here.

UXDX USA May 11 - 13, 2026, New York Click here and book USA now! 10% Discount: 10NEWSLETTERUSA26

UXDX EMEA 27 - 29 May, 2026, Berlin Click here and book EMEA now! 10% Discount: 10NEWSLETTEREMEA26

Video Of The Week
Ways of Working in the Age of AI: From Solo Hero to Team Music

Jeff Chow (Chief Product & Technology Officer at Miro) makes a simple point that lands hard: AI is not just a productivity wave; it is a cultural opening. Most organisations are still built around tool-centred bureaucracy, constant “record scratch” moments, and processes that optimise for the middle, not the best teams.

Jeff breaks down three shifts that change the game: omnipresent knowledge, democratised craft, and faster automation. The prize is not replacing people. It is freeing teams to spend more time problem-solving together, co-creating with real “yes, and” momentum, and making decisions without freezing progress. Watch his session here:

The Results of Last Week’s Poll

The question: Which question best describes the work you are mostly doing right now?

Last week’s poll asked which question best describes the work you’re mostly doing right now, and it’s a strong signal that many of you are operating at the higher levels of thinking. The biggest group (41%) is focused on “Is this the right direction?”, with another 28% on “Is this the right problem?” That means nearly 7 in 10 respondents are spending most of their energy on strategy, outcomes, and systems thinking, not just shipping.

Only 18% are mainly in solution design and trade-offs, and 13% are in pure task execution. My read is that the work is moving up the stack faster than most org design is keeping up. When people are asked to set direction and frame problems, but are still stuck with old cadences, unclear decision rights, and endless dependency management, the job starts to feel like steering with no steering wheel.

The opportunity is to match the level of thinking with the right environment. If your teams are working at problem and direction level, they need clearer outcomes, tighter constraints, and faster feedback loops, not more process. Otherwise, you end up with senior people doing senior thinking inside a system that only rewards delivery mechanics.

Want to dive deeper into levels of thinking and how it is affected by AI? Make sure to read my new ebook: Managing Your Career In The Age Of AI.