This Week’s Updates

Enabling the Team

The False Alignment Trap by Julia Dhar, Kristy R. Ellmer and Philip Jameson
Transformation efforts often fail because leaders mistake polite agreement for real alignment, so teams need to surface differences around why change matters, what success looks like and how it will happen before conflicting assumptions undermine execution.

The Border Collie Faustian Bargain by John Cutler
When experienced employees can see the gap between leadership messaging and organisational reality, they often become responsible for translating the ambiguity without being able to challenge it, creating a choice between protecting the fiction, absorbing the coordination burden or deciding when to stop herding the system.

Product Direction

Your Goal Depends On Another Team - Now What? by Tim Herbig
When a team’s goal sits outside its direct control, the answer is not to shrink the ambition but to clarify the intended outcome, expand the team’s skills or create shared goals that align incentives across the teams needed to deliver real impact. 

Behind The Scenes: Building AI-Generated Opportunity Solution Trees by Teresa Torres
Building AI-generated Opportunity Solution Trees shows how product discovery can be accelerated without giving up structure or judgment, but reliable outputs still depend on validation loops, deterministic checks and careful testing rather than prompting alone.

Continuous Research

Your New UX Habit: Establishing Baselines For Impact by Taylor Dykes & Pavel Samsonov
Establishing a clear baseline before work begins gives teams a meaningful “before” against which to measure change, helping them choose relevant behavioural metrics, demonstrate UX impact and build stronger credibility with stakeholders.

Ten Minutes, Five Teams, One Pizza: Delivering Continuous Research Programs That Run Like Clockwork by Josh Morales
Running short, repeatable discovery sessions with multiple product teams and users makes regular customer contact easier to sustain, helping teams test early ideas, build empathy and bring research into everyday product decisions without replacing deeper methods.

Continuous Design

Becoming An AI-native Designer by Sen Lin
Becoming an AI-native designer means moving beyond static mockups to working prototypes, translating tacit design judgment into clear context, components and criteria, and building custom scaffolding that lets designers explore ideas directly in the medium where products actually live.

AI In Design Report 2026 by Designer Fund and Foundation Capital
AI is moving designers from static mockups toward coding and working prototypes, expanding creative range and speed while making judgment, ownership and a clear point of view more important for protecting quality and avoiding generic output.

Continuous Development

The "I Don't Know, Claude Wrote This" Pandemic by Anton Zaides
AI becomes dangerous when engineers stop understanding the code they submit, so teams need to review every change, retain ownership of architectural decisions and use agents for cognitive offloading without surrendering the judgment required to maintain reliable systems.

Why We're Bullish On Loops by Ian Vanagas
Loop engineering moves AI from responding to one-off prompts to repeatedly finding, completing and evaluating work against clear goals, context and feedback, helping teams automate smaller product improvements while keeping human direction, taste and empathy in control.

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Optimal Joins Us Again In San Francisco

What Should User Researchers Actually Automate?

AI can generate discussion guides, summarise interviews, identify patterns and produce reports in minutes. But the more important question is not what AI can do. It is which parts of research teams should allow it to do. Automating the wrong work can remove context, reinforce bias and create confidence in insights that have not been properly challenged.

At UXDX San Francisco, Gabe Young and Josh Walker from Optimal will lead a practical workshop on how to decide what to automate, what to augment and what should remain human-led. Attendees will explore how to accelerate analysis and synthesis without reducing research quality, combine AI efficiency with human judgement, and identify the risks of AI-assisted research.

FREE COMMUNITY EVENTS 

Video Of The Week

How AI Is Changing The
Software Development Workflow

AI can accelerate software development, but engineers must remain responsible for context, quality and the final product experience. In this UXDX Community talk, Liliana shares how she uses AI across the development workflow, from exploring requirements and technical risks to planning work, generating tickets, reviewing code and capturing lessons for future projects.

She explains how structured AI workflows can improve autonomy, documentation and collaboration while keeping work manageable through smaller tickets, pull requests and human review. The key is to let AI handle repetitive and exhaustive tasks without outsourcing critical thinking, accountability or engineering judgement.

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.