Latest / The Feed & The Thread / The Feed & The Thread - July 15, 2026

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The Feed & The Thread - July 15, 2026 · The Feed & The Thread

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  People actually don't want more AI in their lives. Really? That
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  contradicts every roadmap I've seen. And the data suggests
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  we're ignoring user trust for the sake of shiny new features.
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  Welcome to The Feed and The Thread, brought to you by
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  Chicago Camps. Leadership By Design is on Thursday and
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  Friday, September 17 and 18 and tickets are available now! And
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  while you're at it, get caught up on UX fundamentals with five
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  minute UX at five em UX dot com. The Feed & The Thread is
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  available online at feed and thread dot com to submit your
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  feeds, or download our app for all the feeds and threads
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  delivered right to your pocket.
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  The industry keeps pushing AI features, but users are pushing
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  back. That rejection isn't about fear of technology. It's about
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  the friction these tools create in daily workflows. Vitaly
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  Friedman at Smashing Magazine makes this case in "No, People
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  Don’t Want More AI In Their Life". He argues that people
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  don't actually want more AI in their lives. Current
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  implementations often act as disconnected bolt-ons. They
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  disrupt established habits and increase cognitive load.
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  Verifying AI outputs requires significant human effort. This
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  creates more work rather than saving time. The result is low
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  adoption and user anxiety. Users reject bad execution, not the
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  technology itself. Patrick Neeman at UX Design.cc draws a
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  parallel to the browser wars in "Designing with web standards:
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  The playbook for this AI moment". He warns that today's
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  AI models are repeating past mistakes. They're developing
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  inconsistent conventions for reasoning and citation. This
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  lack of standards leads to user distrust. Neeman highlights that
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  standards emerge from practitioner consensus. Top-down
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  committees rarely build them effectively. We risk shipping
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  chaotic interfaces if we ignore this history. Jim Lewis and
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  Jeff Sauro at MeasuringU address a statistical pitfall in
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  "Understanding Alpha Inflation". They explain the danger of alpha
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  inflation in quantitative research. Large sample sizes
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  allow us to detect nuanced interactions. But running
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  multiple tests increases false positives. The standard p-value
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  protection erodes as comparisons grow. Findings may appear
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  significant when they're just noise. Researchers must adjust
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  for multiple comparisons to trust their data. Other
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  articles today from UX Planet on implementation gaps, Intercom on
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  error handling, and UX Design.cc on DesignOps in the age of AI.
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  The job market is shifting again. Designers are finding
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  themselves passing interviews but failing to match with teams.
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  And the tools we use to evaluate work are changing faster than
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  the roles themselves. Over on r/UXDesign, someone asked what
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  interviews actually look like today. The whiteboard challenge
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  isn't dead, but it's fading. The real tension now is whether
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  we're testing for speed or for strategic thinking. If the
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  process doesn't reflect the daily friction of the job, it's
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  just theater. We need to stop optimizing for performative
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  problem solving and start looking for people who can
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  navigate ambiguity. In r/UXResearch, a host is trying
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  to fix their watch parties. Long, unedited sessions cause
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  stakeholders to disengage. But adding an agenda and snacks
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  changed the dynamic. The insight here's about respect for time.
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  If you want executives to care about research, you have to
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  package it in a way that fits their workflow, not just your
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  academic standards. It's not about dumbing it down. It's
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  about removing the friction between the insight and the
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  decision. Also on r/UXDesign, a designer with three years of
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  experience is hunting for a senior mentor. They want weekly
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  calls and critical feedback. The problem is that senior leaders
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  are stretched thin. This reveals a gap in how we pass on
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  institutional knowledge. When mentorship isn't built into the
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  org chart, it becomes a luxury good. Junior designers end up
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  guessing at senior-level thinking because there's no one
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  to show them the ropes. Another thread on r/UXDesign touches on
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  the Google interview loop. A candidate passed the final round
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  but got no team match. Their status is closed, but their
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  results are valid for seventeen months. They have to apply cold
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  now. This is a structural failure in hiring. It treats
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  candidates as disposable data points rather than potential
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  colleagues. It creates a ghost town where talent waits in
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  limbo, unsure if they're wanted or just stored. Finally, in
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  r/UXResearch, a student asks about using digital prototypes
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  in discovery. Low-fidelity wireframes invite structural
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  feedback. Polished screens distract users with color and
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  copy. The tension is real. We teach students to build fast,
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  but the industry rewards polish. If you can't separate the two in
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  your own head, you'll never get honest answers from users. You
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  have to control the fidelity to control the feedback. We're
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  building better tools while breaking the processes that
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  support the people using them. The friction isn't coming from
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  the technology. It's coming from the gaps in how we hire, mentor,
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  and validate our work.
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  Chicago Camps is hosting Leadership By Design on Thursday
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  & Friday, September 17 & 18. It's an online event, so you can
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  join from anywhere in the world! Tickets are free, thanks to the
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  generosity of the community! If it's within your budget, you can
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  purchase a general admission ticket for only twenty six
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  dollars - with limited early bird tickets at only fifteen
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  dollars. Get tickets now at Chicago Camps dot org.
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  The statistical warning about alpha inflation in quantitative
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  research hits the same nerve as the community discussion on
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  prototype fidelity. Both reveal how easily we mistake noise for
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  signal when we lower our guard. Exactly. That r/UXResearch
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  thread made it clear: polished screens distract users with
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  aesthetics, just like large sample sizes distract
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  researchers with false precision. We're rewarding
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  surface-level confidence over structural integrity in both
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  cases. But there's a difference in intent. Researchers adjust
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  for multiple comparisons to protect data validity. Designers
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  use low-fidelity wireframes to invite structural feedback. One
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  is a mathematical correction. The other is a deliberate
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  constraint to prevent premature attachment to visuals. I see
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  the constraint as the real parallel though. If you don't
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  control the fidelity of your prototype, you can't control the
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  feedback you receive. Similarly, if you don't adjust for alpha
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  inflation, you can't trust the findings you produce. Both
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  require resisting the urge to look polished or statistically
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  sexy. So the lesson is about discipline. We need to stop
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  treating statistical significance and visual polish
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  as proxies for truth. We need to build processes that force us to
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  strip away the noise before we declare a win. It's about
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  valuing the ugly, messy early stage over the clean, confident
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  final product. Until we do that, we're just decorating our
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  biases. Bias dressed up as data is dangerous. But bias dressed
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  up as design is invisible. And that invisibility is exactly why
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  we have to make the process visible again.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!