Latest / The Feed & The Thread / The Feed & The Thread - October 3, 2026

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The Feed & The Thread - October 3, 2026 · The Feed & The Thread

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  Building with AI is free now. So why are these systems breaking?
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  They're turning into fragile messes that no one can fix.
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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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  AI speed is no longer just a tool. It's a pressure valve.
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  Pedro A. Brêtas at UX Design.cc challenges the efficiency myth
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  in "The feed I produce myself", arguing that saved time doesn't
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  rest, it fills. Professionals expand their roles to keep
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  agents running, creating a trap of constant cognitive load where
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  we lose the ability to step back. That rewrites the
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  assumption that speed equals progress. Tanner Kohler at
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  Nielsen Norman Group warns about fragile systems in "The New Big
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  Ball of Mud: Why Agentic AI Systems Turn Fragile", noting
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  that low barriers to entry have created "vibe architects" who
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  build without structure. These agentic systems start working
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  but become unmaintainable as complexity accumulates, turning
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  into big balls of mud that are hard to diagnose. The real risk
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  isn't building too fast, it's building without a plan. Adam
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  Cutler at Chicago Camps distinguishes between artifacts
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  and judgment in "What’s Yours to Keep: Designing alongside AI
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  without giving up the work that made you a designer.", pointing
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  out that AI can generate screens but can't select the best one.
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  Judgment is a human skill that atrophies if we let machines do
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  the choosing. We need to actively practice that selection
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  process to keep our unique value intact. Other reads available
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  from UX Planet on Blender workflows, Nielsen Norman Group
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  on empathy mapping, and UX Design.cc on design consensus.
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  A job description that demands unpaid labor before a single
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  human conversation happens. Over on r/UXResearch, a senior
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  researcher with nearly a decade of experience at major tech
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  firms is considering a pivot to product design. The core issue
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  isn't just burnout, but the feeling that research outcomes
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  are ignored in favor of faster, tangible creative outputs. This
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  shift reflects a broader tension where the rigor of research is
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  often undervalued compared to the visible deliverables of
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  design. For practitioners, this signals a need to explicitly
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  articulate the strategic impact of research to ensure it remains
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  central to product decisions. In r/UXDesign, a university
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  student is asking whether user personas should be defined
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  before or after data collection. The confusion stems from a
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  curriculum that jumps straight to journey mapping without
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  teaching the underlying research process. This highlights a
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  persistent gap in foundational education, where students learn
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  to create artifacts without understanding the evidence
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  behind them. Clarifying this workflow is essential for new
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  designers to build defensible, data-driven solutions rather
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  than speculative assumptions. Over on r/UXDesign, another user
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  is seeking resources to enter UX for robotics and physical AI.
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  They cite Jakob Nielsen's view that UX is moving beyond
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  traditional digital interfaces. This query points to a growing
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  demand for interaction design skills that bridge the physical
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  and digital worlds. As AI integrates into physical
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  devices, practitioners who understand spatial and tangible
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  interaction will be increasingly valuable in shaping how people
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  engage with these new technologies. In r/uxwriting, a
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  user with a diploma from two years ago is asking if anyone
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  works in the niche of lingotech, specifically focusing on grammar
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  UX and meta derivatives. The lack of immediate resonance
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  suggests this specific terminology may not be standard
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  in the field. However, the underlying need for specialized
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  language design in complex systems is valid. Practitioners
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  in this space often operate in isolated niches, making cross-
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  pollination of ideas and shared resources particularly important
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  for professional growth. Over on r/UXResearch, a poster shares
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  a job description that requires candidates to use a specific AI
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  tool and provide free data as the very first step of the
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  application. This requirement to complete an unpaid research
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  study on the company's product before any human interaction has
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  drawn sharp criticism. It raises serious ethical questions about
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  the exploitation of applicant labor in the AI era. For the
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  industry, this is a clear line in the sand regarding respect
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  for professional time and data privacy. Today's discussions
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  reveal a field grappling with the cost of speed, both in the
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  labor we give to employers and the depth of education we
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  receive.
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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
• 4:39
  at a future event at Chicago Camps dot org.
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  Pedro Brêtas makes a point in his recent piece that challenges
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  the efficiency myth, arguing that saved time doesn't rest, it
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  fills. He notes that professionals expand their roles
• 4:57
  to keep agents running, creating a trap of constant cognitive
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  load where we lose the ability to step back. That aligns with
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  what I see in the community threads, specifically a senior
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  researcher with nearly a decade of experience considering a
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  pivot to product design. The core issue is the feeling that
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  research outcomes are ignored in favor of faster, tangible
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  creative outputs. So we have a systemic conflict here. Brêtas
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  argues that speed creates a pressure valve that expands our
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  cognitive load, while the researcher feels that the rigor
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  of their work is undervalued compared to visible
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  deliverables. These are the same structural issue viewed from two
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  different vantage points. I'd argue it's a value problem. If
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  an organization treats speed as the primary metric, judgment
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  becomes a cost rather than an asset. We need to explicitly
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  articulate the value of selection and curation. Adam
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  Cutler touches on this in his article, distinguishing between
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  artifacts and judgment. He points out that AI can generate
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  screens but can't select the best one. Judgment is a human
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  skill that atrophies if we let machines do the choosing.
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  Exactly. The danger is that it removes the practice of
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  deciding. If we stop exercising the muscle of selection, we lose
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  the unique value that made us experts in the first place. So
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  the solution is to redefine what success looks like in a faster
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  process. We need to measure the quality of the decision, not
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  just the speed of the output. Right. And that shift in
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  measurement changes everything. It moves the field from
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  competing on volume to competing on insight, which is where the
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  real leverage lives.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!