Latest / The Feed & The Thread / The Feed & The Thread - August 22, 2026

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The Feed & The Thread - August 22, 2026 · The Feed & The Thread

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  Users can't tell AI images from stock photos. So why do we still
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  pay for human photographers? Because the real issue isn't the
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  image, it's who owns the failure when the tool breaks. We're
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  breaking down that gap.
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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
• 0:31
  feeds, or download our app for all the feeds and threads
• 0:34
  delivered right to your pocket.
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  We're building systems that promise efficiency, yet we're
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  often unsure if they actually work or if we're just using them
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  faster. Rachel Banawa at Nielsen Norman Group explores
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  this in "AI-Generated Images Can Perform as Well as Stock
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  Photography", showing that AI- generated images perform just as
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  well as stock photos when users don't know the source. The study
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  involved seventy-seven participants evaluating a
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  consulting firm's webpage, swapping hero images without
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  revealing their origin. Results showed no significant drop in
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  trustworthiness or professionalism for the AI
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  images, challenging the hesitation many organizations
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  feel about using them. This suggests that perceived
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  authenticity matters less than the context in which the image
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  appears. Perre DiCarlo uses Wile E. Coyote as a metaphor in
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  "It really wasn’t your fault, Coyote", arguing that user
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  failure is often due to unreliable tools rather than
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  incompetence. The piece satirizes ACME Corporation as a
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  monopoly that prioritizes legal protection over product quality,
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  leaving Coyote to fail for seventy-seven years despite his
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  efforts. By highlighting specific failures like the hand
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  grenade incident, the article illustrates how fundamentally
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  flawed products deceive users. It reminds us that when users
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  struggle, we should check the tool before blaming the person.
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  Stefanie Hutka addresses the gap between technical possibility
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  and human value in "Learn to automate intentionally with What
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  Your Machines Should Do", warning against chasing full
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  automation driven by hype. She proposes using research from
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  human factors and cognitive science to determine what should
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  be automated versus what must remain human. The book provides
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  a toolkit for leaders to weigh customer value and
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  organizational readiness, helping teams avoid the
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  automation strategy gap. It's a call to automate intentionally,
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  ensuring technology serves human needs rather than replacing them
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  blindly. Other articles today from UX Planet on designing
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  complete user flows with Claude, CSS-Tricks on resolving class
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  prefix selectors, and Nielsen Norman Group on their artificial
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  intelligence glossary.
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  Designers are asking quieter questions today. They aren't
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  arguing about tools. They're asking if the systems they build
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  actually work. Over on r/hci, a new graduate student is mapping
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  out a career in human factors engineering. They want to know
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  what the day-to-day reality looks like. It's a grounded
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  question. We often talk about strategy. But the work is mostly
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  execution. Understanding the grind matters. It keeps us
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  honest about what we can actually deliver. In
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  r/DesignSystems, someone is asking if a curated hub for
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  components would truly improve workflow. It's a silent thread.
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  But the question reveals a real tension. We build libraries to
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  save time. Yet we often spend more time maintaining them than
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  using them. Efficiency is the promise. Utility is the proof.
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  If the tool doesn't make the work easier, it's just overhead.
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  Also in r/DesignSystems, a developer notes that Flo one
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  point two now gives Web Components a static create
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  function. This allows setting property values before the
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  component mounts. It's a technical tweak. But it speaks
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  to the broader issue. We optimize for speed. We want
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  things to load faster. But do we measure if the user experience
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  is actually better? Speed isn't the same as quality. On r/hci,
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  an academic researcher is recruiting survey designers for
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  a study. They offer a small incentive for fifteen minutes of
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  time. It's a standard request. But it highlights how we measure
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  our own craft. We design surveys to get data. We rarely ask if
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  our methods are valid. We assume the tool works. We rarely test
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  the tool itself. Finally, in r/UXResearch, a solo
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  practitioner wants to outsource competitive benchmarking.
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  They're stretched thin. They need to measure usability
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  against competitors. It's a practical problem. We want
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  evidence. But we often lack the resources to gather it.
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  Outsourcing the work might help. But it also distances us from
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  the findings. We need to stay close to the data. We're
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  building systems that promise efficiency. But we're often
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  unsure if they actually work.
• 4:39
  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
• 4:47
  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 Wile E. Coyote metaphor hits harder than the usual usability
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  critique. It frames user failure not as a lack of skill, but as a
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  direct result of unreliable tools sold by a monopoly that
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  prioritizes legal protection over product quality. It shifts
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  the blame from the person holding the gadget to the
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  corporation selling it. That's a strong lens, but I think we
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  need to be careful not to absolve users of all
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  responsibility. While the ACME Corporation analogy is sharp,
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  human factors research tells us that cognition plays a role in
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  how we interact with flawed systems. We can't just point to
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  the tool and stop there. We have to look at the gap between what
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  the tool promises and what the user expects. I agree the user
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  has agency, but the structural incentive is wrong. When
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  organizations chase full automation driven by hype, they
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  ignore the cognitive science that tells us what should
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  actually remain human. We're building systems that promise
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  efficiency, yet we're often unsure if they actually work or
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  if we're just using them faster. The tool isn't just broken. It's
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  designed to obscure its own failure. So we're measuring
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  speed instead of validity. That's the real issue. We design
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  surveys to get data, but we rarely ask if our methods are
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  valid. We assume the tool works because it produces output. The
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  community is starting to ask quieter questions. They aren't
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  arguing about which AI tool to use. They're asking if the
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  systems they build actually deliver value. And that
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  connects back to intentional automation. If we stop
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  optimizing for speed and start optimizing for human value, the
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  Wile E. Coyote trap disappears. We stop handing users hand
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  grenades and start giving them tools that match their cognitive
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  load. It's not about fixing the user. It's about fixing the
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  premise of the product. Exactly. The shift happens when
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  we treat judgment as a deliverable rather than a hidden
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  cost. We're building faster ways to be wrong. The goal
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  shouldn't be to automate the mistake, but to eliminate the
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  conditions that make the mistake inevitable.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!