Latest / The Feed & The Thread / The Feed & The Thread - August 31, 2026

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The Feed & The Thread - August 31, 2026 · The Feed & The Thread

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  Autonomous agents failed because they couldn't handle basic login
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  screens. So the AI broke on authentication? Exactly, and
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  that failure exposes why human oversight is actually the most
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  efficient part of the workflow now.
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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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  We've spent years designing interfaces, but what happens
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  when the software stops waiting for us? That shift is rewriting
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  the rules of trust, control, and career meaning. Lucas Camara at
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  UX Design.cc argues in "UX in 2027 may be less about
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  interfaces and more about behavior" that we're moving from
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  fixed screens to defining the behavior of agentic software. As
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  AI agents execute tasks autonomously, complexity hides
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  inside system logic, making errors harder to detect. We
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  can't just design buttons anymore; we have to design
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  transparency so users understand how the system infers their
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  intent. Jeff Gothelf shares a cautionary tale in "The Last
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  Cheap Moment: Optimizing Human- in-the-Loop AI Workflows" about
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  human-in-the-loop workflows that fail because humans are brought
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  in too late. When reviewers lack visibility into the AI's
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  rationale, they end up rubber- stamping work just to avoid the
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  cost of starting over. This isn't collaboration; it's a
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  breakdown in accountability that leaves users disconnected from
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  the final outcome. Darren Yeo challenges the corporate ladder
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  in "Rethinking success beyond the corporate stairs in the
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  world of design", arguing that AI pressure strips design of its
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  intrinsic value. When we reduce complex concepts like user
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  delight to simple click-through rates, we lose the meaning of
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  the work. The struggle and judgment involved in design
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  aren't inefficiencies to be automated; they're the source of
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  the value we're trying to protect. Other reads today from
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  UX Design.cc on neuroqueering practice and ACM Interactions on
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  play as interrogation in GenAI.
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  Designers are hitting a wall where speed no longer equals
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  value, and the tools they use to prove their worth are starting
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  to feel like the problem. Over on r/UXDesign, someone asked
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  about the most annoying fights with web design tools while
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  building a portfolio. It's a familiar frustration. We spend
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  years mastering static interfaces, only to get stuck
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  translating them into functional code. The tension here isn't
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  just about technical skill. It's about whether our portfolios
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  actually reflect how we think, or just how well we can fight a
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  website builder. And if the software stops waiting for us,
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  we need to know if we're designing the experience or just
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  debugging the tool. In another r/UXDesign thread, a designer
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  sped up wireframing using automation, cutting two days of
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  work down to minutes. But the handoff to developers didn't
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  change. The same questions about logic and edge cases still came
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  up. This is the real shift. We used to think faster wireframes
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  meant faster development. Now we see that wireframes don't convey
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  the complex flow states developers actually need. If the
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  output doesn't change, what was the wireframe doing? It's
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  forcing us to question if we're optimizing for speed or for
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  actual clarity. Over on r/UXResearch, there's a serious
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  conversation about paying participants outside the US. The
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  author argues that simple currency conversion is
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  embarrassing and unfair. They're calling for compensation that
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  considers local cost of living and niche availability. This
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  matters because ethical research isn't just about getting data.
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  It's about respecting the people who give it. When we automate or
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  outsource, we can't lose sight of the human cost. Fair pay is
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  the baseline for trust, not a luxury feature. Back in
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  r/UXDesign, a burnt-out designer asked how to build a case study
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  when their company dismissed UX entirely. They couldn't collect
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  data or run proper tests. So how do you show impact when you
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  weren't allowed to do the work? It's a brutal reality for many
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  of us. The challenge is translating "what I wanted to do
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  but couldn't" into a professional narrative. It
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  reveals a deeper issue. If we can't demonstrate value because
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  the process was broken, does our career meaning come from the
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  tools we used or the constraints we navigated? Today's
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  discussions show that when we remove the friction of
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  traditional tools, we don't get more freedom. We get a clearer
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  view of what actually matters. It's not about the wireframe or
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  the portfolio site. It's about the logic, the ethics, and the
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  ability to define value even when the system works against
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  you.
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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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  Lucas Camara's argument that we're moving from designing
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  interfaces to designing behavior hits a nerve because it exposes
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  a structural blind spot in how we currently measure success. If
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  the AI agent is executing tasks autonomously, the interface
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  disappears, and with it, our primary mechanism for feedback.
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  We're left with opacity, where errors hide in system logic
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  rather than appearing as broken buttons. That opacity is
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  exactly what Jeff Gothelf warns against when he talks about the
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  rubber-stamping of human-in-the- loop workflows. When reviewers
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  lack visibility into the AI's rationale, they don't correct
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  the output; they just approve it to avoid the cost of starting
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  over. It's not collaboration. It's a breakdown in
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  accountability that leaves the user disconnected from the final
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  outcome. And that disconnect creates a dangerous incentive
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  structure. If we can't see the decision path, we can't audit it
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  for bias or error. We end up optimizing for speed rather than
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  trust. The real risk isn't that the AI makes a mistake, but that
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  we build systems where the mistake is invisible until it
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  causes real harm. We need transparency mechanisms that are
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  as rigorous as our current usability tests. But
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  transparency isn't just a technical feature; it's a
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  cultural shift in how we value judgment. Darren Yeo points out
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  that when we reduce design to simple metrics, we strip away
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  the intrinsic value of the work. If we don't pay attention to the
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  human cost of these automated workflows, we lose the very
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  thing that makes the product useful. Fair pay for research
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  participants is a baseline for trust, not a luxury. So we have
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  a dual challenge. We need technical transparency to
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  prevent rubber-stamping, and we need ethical transparency to
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  ensure we're not exploiting the people who provide the data. The
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  systems that survive this shift won't be the fastest. They'll be
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  the ones that make their reasoning legible. Legibility
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  is the new usability. If a system can't explain its
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  decisions to the humans who rely on it, it's not a tool. It's a
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  black box we're afraid to open. We've spent years designing for
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  screens. Now we have to design for understanding. And if the
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  system can't justify its choices, it has no business
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  making them.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!