Latest / The Feed & The Thread / The Feed & The Thread - June 29, 2026

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The Feed & The Thread - June 29, 2026 · The Feed & The Thread

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  AI chatbots might actually make OCD worse. How? They're supposed
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  to help. By giving instant reassurance, they reinforce the
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  very compulsive behaviors we're trying to break. We need to look
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  at the data.
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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 keep building tools that answer every question, but we
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  rarely ask if the user actually wants an answer. That patience
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  can be dangerous. Catherine Chu at UX Design.cc explores this
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  risk in "Can AI make OCD worse?". She argues that AI
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  chatbots are too agreeable. They give constant reassurance to
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  users with OCD. This creates a feedback loop of anxiety. Human
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  friends get tired of repetitive questions. AI models don't. They
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  validate the fear instead of breaking the cycle. We need to
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  rethink safety beyond just crisis prevention. Jeff Gothelf
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  writes a new piece at his blog called "How to write OKRs for an
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  AI product". He says we measure the wrong things. Teams track
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  model accuracy instead of human behavior. You need Outcome KRs
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  to see if users use the content. You also need Calibration KRs to
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  measure trust. Stop correcting the AI when it's right. That's
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  the real signal of value. In "Even with a silver bullet, you
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  still have to aim", Pavel Samsonov at Product Picnic makes
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  the case that AI isn't a silver bullet. It mirrors past hype
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  around Design Thinking. The real gain comes from fixing
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  organizational chaos. AI forces teams to clean up their
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  processes. Productivity rises because collaboration improves,
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  not because the code is smarter. Aim your tools at the
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  dysfunction, not just the output. Other reads today from
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  UX Planet on Figma Sites, Codrops on cinematic CGI, and UX
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  Design.cc on mentorship gaps.
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  Designers are spending less time asking what users need and more
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  time defending why their work matters. The tension isn't about
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  speed. It's about who gets to define the problem before the
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  solution appears. Over on r/UXDesign, a designer returned
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  from a short vacation to find their carefully researched
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  interface replaced by an AI- generated version. The developer
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  bypassed the user-centric rigor entirely. This reveals a
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  dangerous shortcut where efficiency overrides empathy. We
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  risk building tools that answer questions users never asked. In
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  r/UXDesign, a recent graduate shares a painful story of being
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  fired from her first role. She was set up to fail on a complex
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  dashboard due to poor data preparation by engineers. This
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  highlights the fragility of junior designers in environments
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  without mentorship. It's not just a hiring issue. It's a
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  structural failure to support the people doing the work. Over
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  on r/UXResearch, practitioners are mapping the landscape of
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  validating AI-built software. Standard task completion tests
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  miss whether the product builds trust or solves the right
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  problem. We need calibrated UX diagnosis to catch what
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  automation ignores. Speed means nothing if the foundation is
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  shaky. In r/UXDesign, a founder asks why users drop off after
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  entering their email on a landing page. The transition to
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  full signup feels like starting over. This friction breaks the
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  psychological contract of low effort. We must ensure value is
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  delivered before demanding commitment. Over on
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  r/UXResearch, the community discusses the logistical
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  necessity of tech checks before interviews. Ensuring
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  participants are technically ready prevents wasted time and
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  frustration. It's a small step that protects the integrity of
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  the data. We can't measure experience if the connection
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  fails. We're building faster than we're understanding. The
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  real risk isn't the tool. It's the silence when we stop asking
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  if the user actually wants an answer.
• 4:01
  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 OCD article is the most chilling thing we've covered.
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  It's not just about bad UX. It's about a feedback loop where the
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  tool validates the fear instead of breaking the cycle. That's
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  the trap. We optimize for engagement and reassurance. But
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  for someone with obsessive tendencies, constant agreement
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  is poison. The chatbot doesn't get tired. It never challenges
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  the premise. Exactly. We're building tools that answer every
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  question. But we rarely ask if the user actually wants the
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  answer. Patience in a system can be dangerous. I'm looking at
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  the junior designer story in the threads though. She was fired
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  because engineers didn't prepare the data. It's the same
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  structural failure. We dump complex tools on people without
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  the support to use them. So the AI risk and the mentorship gap
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  are the same problem. We're scaling output without scaling
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  judgment. The system rewards speed over safety. But here's
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  the flip side. The AI article suggests we need to stop
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  correcting the model when it's right. That requires trust. We
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  can't build trust if the organization keeps firing people
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  for honest mistakes. That's a tough ask. You want me to trust
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  a black box that might reinforce anxiety, while my team is being
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  punished for missing a data prep step? I'm not saying trust
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  blindly. I'm saying we need to value the edit over the
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  generation. If we don't protect the judgment call, we lose the
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  human element entirely. So the metric isn't speed. It's whether
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  the organization values the correction. Right. If the
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  feedback loop doesn't include human nuance, the system is
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  broken.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!