Latest / The Feed & The Thread / The Feed & The Thread - August 28, 2026

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The Feed & The Thread - August 28, 2026 · The Feed & The Thread

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  We're designing the wrong kind of AI. You mean the chatbots we
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  keep building? Exactly, because the real shift is tiny models
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  living inside your existing buttons.
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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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  delivered right to your pocket.
• 0:39
  We keep treating AI like a conversation partner, but that's
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  a bad fit for complex work. Today's Feed looks at why we
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  need to stop bolting chat windows onto old interfaces and
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  start building smarter, faster tools instead. Dan Saffer at
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  CMU makes the case in "Welcome to AI Widgets" that we should
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  evolve traditional UI components rather than replacing them with
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  chat. He points out that scrollbars and menus haven't
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  changed since the seventies, while current AI integration
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  just adds a linear text box. Saffer argues that typing is
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  inefficient for complex tasks, so we need parallel interactions
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  like looking and pointing. This shifts the goal from replacing
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  the interface to making the objects inside it intelligent.
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  Patrick Neeman at UX Design.cc argues in "What Blade Runner got
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  wrong about AI (so far)" that our cinematic expectations of AI
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  are fundamentally flawed. We prepared for physical androids,
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  but we got disembodied language models trapped in text boxes.
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  Neeman uses Moravec's paradox to explain why high-level cognition
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  arrived before basic physical dexterity. We have powerful AI,
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  but we lack the affordances and signifiers needed for intuitive
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  interaction. That leaves users staring at a blank box, unsure
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  of what to do next. Luke Wroblewski writes on his blog:
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  "Little Bits of Intelligence", focusing on small, fast AI
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  models embedded directly into software. This approach lets
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  applications move away from rigid, deterministic behaviors
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  where users must adapt to computer syntax. By using
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  semantic search and multi-modal parsing, these systems interpret
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  natural language and translate intent into structured data. The
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  real transformation isn't the large model, but the little bits
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  of intelligence that bend the interface to human needs. Other
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  reads today from UX Planet on designing trust, Deque Blog on
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  testing custom elements, and ACM Interactions on designing AI
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  that knows its limits.
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  Designers are spending less time debating the ethics of
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  artificial intelligence and more time fixing the specific,
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  mechanical failures that happen when we treat chat interfaces
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  like actual workspaces. Over on r/UI_Design, someone is asking
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  for feedback on a portfolio revamp that leans heavily into
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  smooth scroll animations and interactive elements. The goal
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  is to guide visitors naturally through the content, but the
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  real question is whether those visual flourishes actually help
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  the user or just distract from the work itself. We keep adding
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  motion to prove we can, yet we rarely ask if that motion makes
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  the portfolio easier to scan. For a practitioner, this is a
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  reminder that engagement isn't the same as clarity, and a
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  pretty scroll doesn't replace a clear narrative. In
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  r/UI_Design, a designer is sharing a weather app concept
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  inspired by the retro aesthetic of an old school skiing video
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  game. They used AI tools to generate the mockups and place
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  them on device frames, asking if the community loves or hates the
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  sticker-notebook look. It's a fun exercise in style, but it
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  highlights a broader tension: we're using generative tools to
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  make things look cool, rather than to solve structural
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  problems. The risk is that we confuse visual novelty with
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  functional innovation, leaving the underlying interface logic
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  untouched. Also on r/UI_Design, a case study tackles the context
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  drift problem in AI customer support chatbots. The bot loses
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  track of history, and simply increasing the context window
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  just made the system slower and more expensive. Periodic
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  summarization helped, but the final solution required a more
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  nuanced approach to memory management. This is exactly the
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  kind of friction that proves chat windows are bad fits for
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  complex tasks. We need tools that handle state reliably, not
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  just interfaces that pretend to understand nuance through text
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  alone. Over on r/UI_Design, a student built a university
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  timetable app to replace a messy spreadsheet, explicitly applying
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  human-computer interaction principles. They're asking for
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  feedback on the quality of the work, which serves as a great
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  example of replacing a generic tool with a purpose-built
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  interface. When we stop bolting chat onto old workflows and
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  start designing for the specific task, the results are faster and
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  more intuitive. That's the shift we need to make. In r/hci, a
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  designer with two years of experience is weighing an MS in
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  HCI against an MBA to move into product management. They're
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  worried about the cost versus the value, noting that their
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  current job might offer more practical learning than a
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  degree. It's a valid concern, especially when AI is changing
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  what skills are actually needed. The credential matters less than
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  the ability to defend your decisions, and real world
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  experience often teaches that better than any classroom. The
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  common thread today isn't about the technology itself, but about
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  where we put our energy. We're moving away from surface level
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  aesthetics and toward the hard, structural work of making tools
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  that actually fit the job.
• 5:13
  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
• 5:18
  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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  Dan Saffer's argument that we should evolve existing UI
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  components rather than replacing them with chat feels like the
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  structural correction we've been waiting for. He points out that
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  scrollbars and menus haven't fundamentally changed since the
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  seventies. Meanwhile, current AI integration just slaps a linear
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  text box onto a complex problem. That's not evolution. That's
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  regression. It's inefficient. Typing is a bottleneck for
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  complex tasks. Saffer suggests we need parallel interactions
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  like looking and pointing. And looking at the thread in
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  r/UI_Design, where a student built a specific timetable app
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  to replace a messy spreadsheet, you see the practical side of
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  this. They didn't ask a chatbot to build it. They applied HCI
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  principles to create a purpose- built interface. That's the
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  shift. From generic conversation to specific utility. But
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  there's a tension there. The student's app works because the
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  domain is narrow. A university timetable has rules. But what
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  about the ambiguous, open-ended work that most of us do? Saffer
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  says we need to make the objects inside the interface
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  intelligent. But if we don't have a chat window, how does the
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  system handle nuance? We risk creating rigid tools that fail
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  the moment the user deviates from the expected path. That's
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  the trap of the chat interface too. It pretends to handle
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  nuance but often forces you into its syntax. The alternative
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  isn't rigidity. It's better parsing. Luke Wroblewski talks
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  about little bits of intelligence that translate
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  intent into structured data. We don't need a generalist chatbot.
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  We need specialized widgets that understand context. The goal
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  isn't to replace the interface. It's to make the interface
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  understand the work. So the metric for success shifts. It's
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  no longer about how conversational the AI feels.
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  It's about how well the interface bends to human need
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  without demanding a conversation. That's a harder
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  engineering challenge. It requires semantic search and
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  multi-modal parsing embedded directly into the workflow.
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  Exactly. And that's where the value lies. We stop treating AI
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  like a colleague we have to talk to.
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  That's The Feed and The Thread for today. We'll catch you next
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  time!