Latest / The Feed & The Thread / The Feed & The Thread - August 12, 2026

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The Feed & The Thread - August 12, 2026 · The Feed & The Thread

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  AI only caught half the usability issues. So the other
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  half slipped through? Exactly, and we need to know which ones
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  it missed before we let it run our tests.
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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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  delivered right to your pocket.
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  The tools that promise to flatten hierarchy are also the
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  ones generating the most noise. We're trying to decide if AI
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  makes us more autonomous or just more prone to error. Kai Wong
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  at UX Design.cc reframes the anxiety in "Design’s dreaded
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  phrase is coming back. This time we’re in control.". He argues
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  that when everyone can design, it doesn't dilute standards. It
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  lets designers bypass managerial bottlenecks and ship work
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  without waiting for permission. This turns design into a
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  proactive practice rather than a service waiting for approval.
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  You control the narrative because you don't need a
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  gatekeeper to prototype. Jim Lewis and Jeff Sauro at
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  MeasuringU test those promises in "Using AI To Find Usability
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  Problems: A Replication". They replicated a study to see if AI
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  can spot usability issues in video recordings. The AI found
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  half the problems humans caught. But it also produced seven false
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  alarms and three hallucinations. Ninety-one percent of AI-only
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  findings needed correction. Speed means nothing if you have
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  to fix the noise. Alexey Kopytin at Smashing Magazine
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  details a different approach in "Building Tactile UX: Honoring
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  Intentional Design With Lottie". He challenges the use of heavy
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  physics engines for tactile interfaces. Instead, his team
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  used programmatic Lottie controls for a digital squeeze
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  toy. They mapped clicks to specific animation frames using
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  distance math. This ensures the motion honors the original
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  keyframes. Precision beats algorithmic approximation every
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  time. Other reads available from UX Planet on executable
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  design systems, Codrops on procedural geometry, and CSS-
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  Tricks on SmashingConf Freiburg.
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  Practitioners are navigating a landscape where the tools meant
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  to flatten hierarchy are generating more noise than
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  signal, forcing us to question whether AI grants autonomy or
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  just amplifies error. Over on r/UXResearch, a recent graduate
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  is asking how to translate academic thesis work into
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  industry-relevant insights for an upcoming internship
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  interview. The tension here's real because hiring managers
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  want to see research thinking, not just final outputs. It
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  reveals that entry-level candidates must demonstrate
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  their process clearly, even when bridging a gap between academic
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  rigor and commercial speed. In r/UXResearch, another designer
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  is wondering if they should abandon a personal finance app
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  project because the target users are invisible online. This
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  highlights a persistent blind spot in digital research because
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  the people who need financial help often lack the bandwidth to
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  participate in niche communities. It forces us to
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  consider how we reach invisible audiences without relying solely
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  on existing digital footprints. Over on r/UXDesign, a career
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  switcher with a Master's in Information Science is asking
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  how to leverage a non- traditional product specialist
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  role to stay relevant for a future UX transition. The
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  question matters because it challenges the linear career
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  path myth. It suggests that adjacent roles in manufacturing
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  or analysis can build the systemic understanding that
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  senior designers value, provided you frame that experience
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  correctly. In r/UXResearch, a freelance designer shared a low-
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  cost process for conducting user research, using voice-to-text
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  dictation immediately after interviews to capture insights
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  while they're fresh. This practical workflow addresses the
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  common client resistance to paying for research phases. It
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  shows that efficiency doesn't have to mean cutting corners,
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  especially when you use tools to preserve the nuance of human
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  interaction. Over on r/UXDesign, a senior designer
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  wrote a letter to juniors arguing that hiring managers now
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  prioritize the ability to learn new skills over static tool
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  proficiency. The core message is that while tools change, the
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  need for judgment and empathy remains constant. It encourages
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  a hands-on approach to building and testing, reminding us that
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  curiosity matters more than any single software certificate.
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  The common thread today isn't about the tools themselves, but
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  about how we use them to maintain human judgment in an
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  increasingly automated workflow.
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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 MeasuringU replication study shows AI found half the
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  usability issues humans caught, but ninety-one percent of those
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  findings needed correction. That noise-to-signal ratio is the
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  real bottleneck. It's not that the AI is blind. It's that it's
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  hallucinating context. We're trading human fatigue for
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  algorithmic confidence in errors. I see it differently.
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  The problem isn't the noise. It's that we're still measuring
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  success by "finding problems" instead of "solving them." If
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  the AI gives you seven false alarms and three real hits, and
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  you spend ten minutes verifying them, you've actually saved time
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  compared to an hour-long review. The value isn't in the accuracy
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  of the detection. It's in the speed of the iteration loop.
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  That assumes the verification cost is static. But when you
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  have to manually correct hallucinations, you're not just
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  verifying. You're re-doing the analysis. And if the AI misses
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  the nuanced interaction flows that humans catch, you're
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  shipping broken experiences faster. Speed means nothing if
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  you're accelerating toward a wrong answer. Maybe we're
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  asking the wrong tool to do the wrong job. We're treating AI
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  like a junior researcher. But what if we treated it like a
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  chaotic brainstorming partner? The value isn't in the final
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  report. It's in forcing the designer to engage with the data
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  immediately. You don't wait for permission to prototype because
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  you don't need a gatekeeper. You just build, test, and correct.
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  That shifts the burden entirely onto the designer's judgment.
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  And that's risky when the data is noisy. We need standards for
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  verification, not just speed. Standards will follow the
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  practice. Right now, the gap between generating a prototype
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  and validating it's where the real work lives. We're not
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  replacing the reviewer. We're replacing the wait time.
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  Exactly. The discipline isn't in avoiding mistakes. It's in how
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  fast you can fix them before they ship.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!