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.

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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.

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.