Latest / The Feed & The Thread / The Feed & The Thread - October 27, 2026

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The Feed & The Thread - October 27, 2026 · The Feed & The Thread

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  The time AI saves designers usually vanishes. So the
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  efficiency gains are actually a myth. It's a workflow trap that
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  swallows the savings, and we're breaking down how to keep them.
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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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  Speed used to be a competitive advantage. Now it's table
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  stakes, and the time you save is only worth what you spend it on.
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  Kai Wong at UX Design.cc challenges the productivity hype
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  in "The time AI saves designers usually disappears. Here’s how
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  to keep it.", revealing that the hours saved by AI often vanish
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  into scope creep rather than strategic value. Wong argues
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  that without deliberate workflow structures, designers simply
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  fill the empty hours with more output. Reclaiming that time for
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  deeper user research is the win. Jeff Sauro, Jim Lewis, and Will
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  Schiavone at MeasuringU unpack the salary data in "User
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  Experience Salaries & Calculator (2026)", showing that the
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  reported nineteen percent increase is largely an illusion
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  created by inflation and a shift toward senior roles. When you
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  adjust for the cost of living, entry-level and mid-level
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  salaries have actually dropped in real terms. That means the
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  entry barrier for new designers is getting higher. Luke
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  Wroblewski makes a bold claim in "Technology Limits are
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  Temporary": technology limits are temporary, and skepticism
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  often stems from fixating on current flaws rather than long-
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  term potential. He points out that early criticisms of AI,
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  like image models failing to draw hands, have largely
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  resolved, suggesting that betting against these
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  capabilities is a risky strategy. The professionals who
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  dismiss new tools today may find themselves obsolete tomorrow.
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  Other reads available from Microinteractions on speculative
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  futures, Baymard Institute on AI engagement metrics, and UX
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  Planet on coding agent configurations.
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  Today's discussions center on the gap between effort and
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  evidence, asking whether we're actually validating our work or
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  just assuming it works. Over on r/UserExperienceDesign, a
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  designer is weighing three interior renovation services
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  after their first project failed, specifically looking for
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  transparent pricing and reliable workmanship. It's a classic
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  service design failure, where the absence of clear feedback
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  loops left the user stranded. The lesson here is that speed in
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  delivery means nothing if the outcome is broken. In
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  r/ProductDesign, a team is questioning whether they're
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  doing real market research or just building products
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  executives personally like. This tension between calculated risk
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  and personal preference is a recurring theme in the field.
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  The problem isn't the risk itself, but the lack of data to
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  back it up. Also in r/UserExperienceDesign, a senior
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  designer is asking how to make invisible work visible,
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  especially when preventing bad ideas is the main value. This is
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  the preventative side of UX, where the win is the thing that
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  didn't happen. We need better ways to articulate that
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  preventative value to stakeholders. Back in
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  r/UserExperienceDesign, someone redesigned a pasta sauce page to
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  reduce friction near the add-to- cart button, listing eight
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  specific hypotheses to test. This is the right approach,
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  treating design changes as testable claims rather than
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  finished products. It's about validating the user's
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  uncertainty, not just removing it. Finally, in
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  r/ProductDesign, a designer is proposing a laptop setup that
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  folds out into three screens to solve the tab-juggling problem.
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  It's a bold hardware solution to a software workflow issue. The
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  question is whether the physical complexity justifies the digital
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  convenience. We're seeing a clear shift from shipping fast
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  to proving value, and that shift is defining the current state of
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  practice.
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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
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  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 nineteen percent salary increase that MeasuringU
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  highlighted this week is a mirage, and it's dangerous
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  because it's masking a real contraction in the entry-level
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  market. When you adjust for inflation and the cost of
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  living, the data shows that entry and mid-level roles have
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  actually dropped in real terms. That means the barrier to entry
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  is rising, while the reported average goes up purely because
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  the mix of roles is shifting toward senior positions. I hear
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  that, and the math checks out, but I think we're looking at the
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  wrong signal. The community is complaining about the lack of
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  evidence. I saw a thread today where a team was asking if they
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  were doing real market research or just building what executives
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  liked. That's the price of doing business right now. If you can't
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  prove your work with data, you don't get the senior role, and
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  you don't get the raise. That's a fair point, but it creates a
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  catch-22. If the market is tightening for juniors, they
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  don't have the resources to build the robust evidence base
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  that the market now demands. We're seeing a gap between the
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  effort people put in and the evidence they can produce. It's
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  a systemic issue where the expectation for proof is
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  outpacing the support structures that allow for that proof to be
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  generated. But that's exactly why the "productivity hype" is
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  so misleading. I read a piece today arguing that the time AI
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  saves us usually just vanishes into scope creep. If we use that
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  saved time to do deeper user research, to test those
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  hypotheses we mentioned earlier, then we're not just filling
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  hours with more output. We're creating the evidence that
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  justifies our value. The skill is knowing what to validate when
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  you get that time back. I agree that validation is key, but I
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  worry we're overestimating how much time is actually being
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  saved. The claim that time disappears is based on anecdotal
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  reports. If the time savings are minimal, then the pressure to
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  produce more evidence becomes just another burden on an
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  already strained team. We need to be careful not to assume that
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  AI is the silver bullet that frees us up to do the deep work.
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  That's a valid concern, but I'd push back on the idea that it's
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  a burden. If you're not using the time to do something
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  valuable, you're just working faster at the same thing. The
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  opportunity here is to shift the culture. Instead of asking "how
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  much faster can we go?", we should be asking "what can we
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  now afford to learn?" That's where the leverage lies. So the
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  question is about the standard we hold ourselves to. If we
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  can't articulate what we learned and how it changed the product,
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  we're not just a designer; we're a pair of hands. The market is
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  shifting to reward people who can connect the dots between
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  user behavior and business value, and that's a skill anyone
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  in the field can build, regardless of their title.
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  Exactly. The value of your work is defined by the clarity of
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  your evidence, not the speed of your execution. If you can't
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  show me the connection between the user's problem and the
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  solution you built, you don't have a design problem, you have
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  a communication problem. And that's a problem we can all
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  solve, right now, by starting to document our "why" as rigorously
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  as we document our "how."
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  That's The Feed and The Thread for today. We'll catch you next
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  time!