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

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

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  AI speeds up interfaces but misses the messy human evidence.
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  So we're getting fast, empty shells. Exactly. We're building
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  pretty screens without the empathy that makes them work.
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  Let's look at what's missing.
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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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  We trade speed for depth, and the gap between what AI can
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  generate and what we actually need is widening. Rachel Krause
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  at Nielsen Norman Group argues in "AI Can't Replace Real
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  Research in Empathy Mapping" that efficiency isn't empathy.
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  AI organizes data well, but it can't produce the messy,
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  specific evidence that makes an empathy map valid. Teams under
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  pressure use it to simulate user perspectives, creating
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  superficial insights that lack real-world grounding. The map
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  becomes a shared reference point built on hallucinations rather
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  than interview notes. That rewrites the assumption that
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  faster research is better research. Nick Babich writes at
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  UX Planet in "The Horrible State of AI-Powered Product Design in
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  2026" that we've solved the easy part of design. AI tools now
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  generate convincing layouts from text prompts in seconds,
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  democratizing the mechanical side of UI creation. But this
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  speed masks a critical failure to understand user needs or
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  business logic. We can execute visuals instantly, yet we still
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  struggle with holistic product strategy. The tool builds the
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  skin, but the team must still figure out the bones. Matt
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  Stone details his portfolio work in "Goodgrowth: Boot Sequences,
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  Spinning Discs, and the Art of the Portfolio", showing how AI
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  extends technical reach. He used Claude Code to build complex
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  three-dimensional interactions he couldn't have coded alone,
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  moving beyond his standard HTML and CSS comfort zone. The result
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  is a seamless scroll loop and rotating disc that mimics old
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  console boot sequences. It proves AI can handle the heavy
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  lifting of implementation, letting designers focus on the
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  nostalgic experience. Other reads today from CSS-Tricks on
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  animation triggers and Nielsen Norman Group on cleaning up
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  after AI.
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  Designers are currently wrestling with the gap between
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  what tools can generate and what the work actually requires.
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  Over on r/hci, a management consultant is asking for a
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  roadmap to switch into human- computer interaction,
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  specifically seeking programs that lean into psychology rather
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  than coding. It's a reminder that the field still struggles
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  to define what entry looks like when you don't come from design
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  school. The tension here's real because we're trading speed for
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  depth in hiring, often overlooking people who
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  understand the human side of the equation without the traditional
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  technical pedigree. In r/UI_Design, a newcomer with a
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  branding background shared a pharmaceutical interface mockup,
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  highlighting the friction between minimal aesthetics and
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  strict regulatory needs. This matters because it exposes how
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  hard it is to apply standard SaaS design rules to industries
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  where clarity isn't just about beauty, but about safety and
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  compliance. We're seeing more designers try to force familiar
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  visual languages into contexts where they don't quite fit. A
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  senior designer on r/UI_Design broke down inventory screens,
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  arguing that visual hierarchy and rarity systems often create
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  more clutter than value. The advice focuses on efficiency
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  over decoration, which hits home when we consider how much effort
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  we spend making things look cool instead of making them usable.
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  It's a practical check against the urge to over-design simple
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  functional spaces. On r/ProductDesign, a senior
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  designer questioned whether strategic oversight roles can
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  actually exist in freelance models, or if that work is
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  strictly an in-house glue. It's a valid concern because the
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  market often reduces design to execution, ignoring the high-
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  value synthesis that happens when you're embedded in the
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  team. If we outsource the thinking, we lose the context
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  that makes the work valuable. Another thread on
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  r/ProductDesign highlighted the pain of scattered information
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  across siloed teams, asking how we can better synthesize
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  insights from product managers and engineers. This connects
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  directly to the widening gap between generated output and
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  actual need, because without that synthesis, AI just
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  amplifies the noise. We're building faster, but we're not
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  necessarily building smarter. The common thread today is that
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  speed is easy, but depth requires the kind of human
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  context that tools still struggle to replicate.
• 4:35
  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
• 4:44
  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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  Rachel Krause's argument at Nielsen Norman Group cuts
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  through the noise. She says efficiency isn't empathy. When
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  teams use AI to simulate user perspectives, they're building
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  maps on hallucinations rather than interview notes. That's
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  the trap. We're confusing speed with validity. An empathy map
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  generated from data patterns looks clean, but it lacks the
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  messy evidence that makes it useful. If the map doesn't
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  reflect real human friction, it's just a pretty diagram.
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  Exactly. The systemic risk is that we start treating AI-
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  generated insights as ground truth. We're widening the gap
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  between what tools can generate and what we actually need to
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  know. Depth requires context that models simply don't have.
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  But here's where I diverge. I don't think the solution is to
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  abandon the tool. It's to change the incentive. If we value speed
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  over depth, we'll keep getting superficial maps. We need to
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  reward the messy work of verification, not just the
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  initial output. So you're saying the problem isn't the AI,
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  it's how we measure success. Right. The tool is neutral. The
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  metric is the problem. If we stop rewarding fast, fake
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  empathy, and start paying for validated, uncomfortable truths,
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  the tool becomes a helper instead of a hazard. Then the
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  shift is cultural, not technical. We have to build
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  processes that penalize unverified assumptions.
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  Precisely. Empathy isn't a deliverable you generate. It's a
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  discipline you maintain.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!