Latest / The Feed & The Thread / The Feed & The Thread - October 13, 2026

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The Feed & The Thread - October 13, 2026 · The Feed & The Thread

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  The Yamaha DX7 synth taught us a hard lesson about presets. So
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  why are we letting AI do the same thing? Because cheap
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  prototypes are killing our ability to test real hypotheses.
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  Welcome to The Feed and The Thread, brought to you by
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  Chicago Camps. The Feed & The Thread is available online at
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  feed and thread dot com to submit your feeds, or download
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  our app for all the feeds and threads delivered right to your
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  pocket.
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  There's a dangerous gap between shipping fast and knowing what
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  you're actually building. We're producing more output than ever,
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  yet the value of that work is slipping through our fingers
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  because we've confused activity with progress. Today's stories
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  challenge the very foundation of how we decide what to build in
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  the age of generative tools. Mathieu Poli at UX Design.cc
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  argues in "The synth everyone owned and few could program: a
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  lesson for AI design" that default settings are quietly
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  eroding our creative distinctiveness. The piece draws
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  a parallel to the Yamaha DX7 synthesizer, noting that its
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  preset sounds dominated the charts of the nineteen eighties
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  because they were easy to use. Poli's benchmark of twelve app
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  briefs across seven AI models shows a similar convergence,
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  with color differences so small that the human eye can't
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  distinguish them. We're trading unique expression for the
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  comfort of the average, and that homogenization is the cost of
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  convenience. Jeff Gothelf writes "How to turn a Lean UX
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  hypothesis into an AI eval before you build anything" on
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  their blog, proposing a method to turn Lean UX hypotheses into
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  actionable AI evaluations before any code is written. The core
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  tension is that cheap prototypes often become shiny objects that
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  fail to produce clear learning outcomes. Gothelf cites data
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  from Atlassian's State of Product report, which notes that
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  while eighty percent of professionals say AI helps them
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  ship faster, customers aren't seeing value sooner. The problem
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  is a lack of clarity on what we're actually testing and why
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  it matters to the user. Marty Cagan at Silicon Valley Product
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  Group critiques the obsession with schedules in
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  "Predictability vs Outcomes". Cagan argues that the failure to
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  achieve product outcomes is caused by an organizational
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  prioritization of predictability over innovation. Frameworks like
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  SAFe optimize for schedule adherence, which fundamentally
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  conflicts with the uncertainty inherent in solving hard
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  customer problems. Predictability is the enemy of
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  true discovery. Other reads available from UX Planet on the
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  Claude Code mods and GitHub tools worth trying, and UX
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  Design.cc on how AI is hollowing out the middle of design.
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  Today's feed is full of questions about where we
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  actually stand, from senior careers to the basics of entry,
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  and the friction is that we're measuring activity instead of
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  impact. Over on r/UXDesign, a designer with nineteen years at
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  major companies is asking why they keep getting passed over
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  for senior roles. They have the metrics and the deep experience,
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  yet the market seems to want a different kind of story. This
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  highlights a gap: we've confused having a lot of output with
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  making a clear strategic impact. If your resume lists tasks
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  instead of decisions, you're invisible. In r/UI_Design,
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  someone shared a concept for a Samsung-style taskbar that
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  blends Windows aesthetics with mobile navigation. It's a neat
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  visual idea, but it's mostly about moving things around. This
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  is the kind of work that feels productive but doesn't solve a
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  core user problem. It's activity, not progress. Also
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  on r/UXDesign, a designer in a limited conference scene is
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  asking how to build a network through local universities. They
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  want to fight professional jadedness by connecting with
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  creatives in person. This is a healthy push back against the
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  isolation of remote work. Real relationships often lead to
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  better design than any tool can. Back on r/UXDesign, a beginner
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  is asking for specific stories on how people got into UX,
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  skipping the generic advice. They want to know the non-linear
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  paths, the degrees, and the self-taught routes. This is the
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  foundation of the field. We need to remember that there's no
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  single correct way to start, and that diversity of background is
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  an asset. And in r/UI_Design, a concept for a vertically
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  written chat app is challenging the standard horizontal layout.
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  It supports languages like Chinese and Japanese, where
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  messages flow right-to-left. This is a genuine gap in
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  mainstream design. We default to horizontal text so often that we
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  forget other writing systems exist. Today's discussions
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  remind us that shipping fast isn't the same as building
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  value, and we need to ask better questions about what we're
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  actually creating.
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  The Feed and The Thread is brought to you by Chicago Camps.
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  For a weekly and monthly exploration of the patterns and
• 4:35
  signals across UX, you can also check out Patterns and Signals
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  at the website patterns and signals dot com. Chicago Camps
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  will have more events in 2027. You can submit to be a speaker
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  at a future event at Chicago Camps dot org.
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  The Atlassian data point is the one that keeps pulling at me,
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  because eighty percent of professionals say AI helps them
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  ship faster, yet customers aren't seeing that value sooner.
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  That gap is a clarity problem. We're confusing the speed of
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  output with the depth of understanding, and Gothelf's
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  call to build AI evaluations before writing code is a demand
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  for that missing clarity. I hear that, and I think it's
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  right, but I'd push back on the idea that the fix is just better
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  testing. The issue is that we've let the default settings do our
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  thinking for us. When Poli shows that twelve different app briefs
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  across seven models produce colors so similar a human eye
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  can't tell them apart, that's a creative surrender. We're
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  trading distinctiveness for convenience, and that's why the
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  value feels hollow. And that's where the two stories connect,
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  because if we can't articulate what makes our version unique,
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  we can't even build the evaluation that would prove it
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  matters. The Lean UX hypothesis breaks down when the hypothesis
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  itself is just "make it faster," instead of "make this specific
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  user need better." We're measuring activity, which is
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  easy to track, instead of impact, which requires us to
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  define what success actually looks like before we start.
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  That's the shift I want to see, and it's about being more
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  intentional. We need to ask "does this solve a problem that
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  only this specific approach can solve?" rather than "can AI
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  build this?" If the answer is no, then the speed of building
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  it doesn't matter, because we're just adding noise to a market
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  that's already drowning in similar-looking products. So
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  the opportunity here is to use the tools to sharpen our
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  questions. The designers who will stand out next year won't
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  be the ones who ship the most, they'll be the ones who can
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  prove why their work matters. And that proof has to come from
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  understanding the user's specific context. The field
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  needs to focus on "why should we build this, and for whom?"
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  rather than "what can we build?" That's where the value lives,
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  and it's where the next generation of practitioners
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  needs to focus their energy.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!