flâneur

Mapk Uraine

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on the atlas — 43

highlights — 74

  • Design doesn’t hand you a moment where you’re allowed to call something finished.
    The hard things about design ・ Hardik Pandya
  • A broken build stops a merge for everyone, whether anyone in the room cares about code quality that day or not. There’s no equivalent for a mediocre screen. Nothing technical stops it from shipping. The only thing that stops it is someone caring enough to say so, and depending on the week, on the company, on who else happens to be in the room, that someone is often just you, alone, at an hour no one else is awake for.
    The hard things about design ・ Hardik Pandya
  • When I’m hiring for taste, I look for three things: Discernment: Can they articulate what’s not working and why? A good answer is nuanced, reflecting a deeper way of seeing than most. Great designers have language for things most people only feel. Empathy: Do they think about the person on the other side—not just the screen? The tell is when they describe an interface decision that accounted for something you wouldn’t have thought to ask about. Creative energy: Are they always making something? People with taste have a compulsive relationship with their craft—side projects, obsessions, things …
    You Never Stop Cultivating Taste | Figma Blog
  • The details you choose to invest in, the compromises you refuse to make—that’s where your taste lives.
    You Never Stop Cultivating Taste | Figma Blog
  • Having taste doesn’t mean everyone will love your work. Taste is particular. Two designers can have completely different sensibilities and both have taste.
    You Never Stop Cultivating Taste | Figma Blog
  • Full-stack AI designers need to have a general fluency across all inputs into the experience, so they can influence, mitigate, or receive the impacts that upstream work has on the end experience.
    Designing beneath the surface: The layers of AiUX
  • The goal of design is not to eliminate variance or unknown behaviors, but rather to design the conditions that either minimize or mitigate these effects, and make them easier to observe, diagnose, and correct where possible.
    Designing beneath the surface: The layers of AiUX
  • Finally, AI experiences are affected by emergence, the unexpected behaviors that arise when probabilistic systems operate in real-world contexts.
    Designing beneath the surface: The layers of AiUX
  • Policies, regulations, standards, and preferences are all examples of outside forces that directly or indirectly govern the user experience.
    Designing beneath the surface: The layers of AiUX
  • As a result, governance cannot be treated as separate from the product, even if many of its underlying decisions live in legal, compliance, security, or executive decision-making.
    Designing beneath the surface: The layers of AiUX
  • Latency, verbosity, confidence, refusal patterns, creativity, consistency, and reasoning depth are behaviors that can be tuned, contributing to the distinct feel of the product in use.
    Designing beneath the surface: The layers of AiUX
  • Each model carries distinct characteristics into the end product, like changes in tone or personality, tolerances for risk or ambiguity, general reliability, and other traits that could be good or bad depending on the circumstances.
    Designing beneath the surface: The layers of AiUX
  • Together, connectors, tools, skills, and agents form the operational surface of AI systems. They define the boundary between human intent and machine execution.
    Designing beneath the surface: The layers of AiUX
  • AI systems therefore require an operational layer around the model for processing information and coordinating their actions within defined constraints. This serves as the model’s harness, enabling it to complete tasks independently while remaining governed by permissions and user preferences that promote security and more predictable outcomes.
    Designing beneath the surface: The layers of AiUX
  • Too much context, through long context windows and bloated memory files, burns through token budgets and can degrade results, a failure commonly called context rot. Too little or unmaintained context allows the system to become inconsistent, unpredictable, or dependent on constant user intervention.
    Designing beneath the surface: The layers of AiUX
  • A well-constructed context keeps an AI experience from having to start cold every time a person asks for help.
    Designing beneath the surface: The layers of AiUX
  • Interface design is therefore becoming less about choosing a single pattern for the use case and more about matching the surface to the state of the relationship between the user and the model at any given time.
    Designing beneath the surface: The layers of AiUX
  • User interfaces are not going to disappear, but their role changes the deeper into a session a user progresses, supporting the system rather than driving it.
    Designing beneath the surface: The layers of AiUX
  • Behind the scenes, designers need to consider the artifacts an agent may use for shared interactions; the evaluation tools that track the model’s accuracy and flag issues; and the surfaces where people can view and adjust memory, skills, and instructions.
    Designing beneath the surface: The layers of AiUX
  • The right interface depends on the context surrounding the interaction, like how familiar the user is with the domain, how much the AI knows about them, how sensitive the situation is, and how much confidence the system has in its response.
    Designing beneath the surface: The layers of AiUX
  • When this sub-surface system is working well, the model can act with more autonomy, and the purpose of the interface leans toward oversight, allowing the user to manage and orchestrate the model without requiring constant intervention.
    Designing beneath the surface: The layers of AiUX
  • In any case, we expect AI products to build context about us over time so they can anticipate our needs rather than wait to be told.
    Designing beneath the surface: The layers of AiUX
  • AI asks designers to go one layer deeper again: into the model, the harness, the context, the policies, and the emergent behaviors that produce the experience before it ever reaches the interface.
    Designing beneath the surface: The layers of AiUX
  • I try fewer things now, because I get to something decent so quickly. The first output is a 5. Why would I do nine more? The friction that used to force me through the variations is gone. So I stop.
    The 2–7 problem – Anton Sten
  • Taste is the residue of trying a lot of things.
    The 2–7 problem – Anton Sten
  • AI can’t replace the best. True, and irrelevant for most people. The floor argument is the one that actually matters. AI raises the median to a 5. That’s where the displacement happens. Anyone who was already at a 5 wasn’t safe before AI. They’re less safe now.
    The 2–7 problem – Anton Sten
  • Picture a one-to-ten grade for quality. A 10 is the thing you remember for years. A 1 is the thing that makes you stop scrolling because it’s so off it’s interesting. A 5 is competent. Forgettable. Fine. Most things in the world live somewhere on that scale, and most of them sit around the middle. His point: AI output never leaves the middle. It always lands somewhere between a 2 and a 7. Never a 1. Never an 8.
    The 2–7 problem – Anton Sten
  • AI is bad at making things that are bad.
    The 2–7 problem – Anton Sten
  • The designers who maintained influence through this period share one thing: technical depth. Not necessarily coding ability, but deep understanding of technical systems. They can evaluate AI output. They can participate in architecture discussions. They can advocate for users in technical terms that actually influence decisions.
    DOC • Why AI is exposing design’s craft crisis
  • The technical skills that matter most: • Understanding data models and how they constrain user workflows • Knowing enough about APIs to design technically feasible features • Recognizing performance bottlenecks that should influence interaction patterns • Evaluating AI-generated outputs for technical correctness • Understanding how design systems map to component libraries • Participating in build-versus-buy discussions with actual technical context • None of this requires a computer science degree. It requires curiosity about how things actually work and a willingness to learn technical funda…
    DOC • Why AI is exposing design’s craft crisis
  • Strategic literacy means you can: • Evaluate whether AI-generated code is functional or broken • Understand API constraints well enough to design features that are actually feasible • Recognize when performance implications should influence interaction patterns • Participate in technical debt conversations because you understand what’s being traded off+ • Spot when “technical constraints” are actually implementation choices masquerading as limitations
    DOC • Why AI is exposing design’s craft crisis
  • The root cause is simple: most product decisions are fundamentally technical. They involve technical constraints, technical trade-offs, technical debt, and technical feasibility. If you can’t participate in technical conversations, you can’t influence product strategy. You can’t influence product strategy, you end up in alignment meetings explaining user needs to people making technical decisions you don’t fully understand.
    DOC • Why AI is exposing design’s craft crisis
  • Executive-level design roles are disappearing across corporate America, and it’s not because AI replaced them. It’s because the roles stopped delivering strategic value.
    DOC • Why AI is exposing design’s craft crisis
  • The “Great Design Handoff” wasn’t a single event — it was a slow erosion of strategic control. Growth teams took over conversion optimization. Algorithms dictated layout and personalization. Business stakeholders made product decisions. Design leaders found themselves defending the existence of their teams rather than shaping product strategy.
    DOC • Why AI is exposing design’s craft crisis
  • If you can’t tell the difference between functional code and broken code, between accessible design and inaccessible design, between scalable architecture and technical debt, these tools just let you fail faster.
    DOC • Why AI is exposing design’s craft crisis
  • Stated plainly, today's frontier LLM research is not about building animals. It is about summoning ghosts.
    Animals vs Ghosts | karpathy
  • We do not in fact have an actual, single, clean, actually bitter lesson pilled, "turn the crank" algorithm that you could unleash upon the world and see it learn automatically from experience alone.
    Animals vs Ghosts | karpathy
  • AI can still be useful. It can help prototype, explore, and surprise you. But that is different from design. Design still requires judgment, conversation, tension, and time.
    Output isn’t design - Linear
  • Christopher Alexander came closer than anyone to naming this clearly. In Notes on the Synthesis of Form, he describes design as the search for a good fit between a form and its context. Context, in his sense, is not a background condition. It is the full set of forces that make a problem what it is: human needs, technical constraints, conflicting requirements, habits, edge cases, and relationships that are easy to miss until you spend time with them.
    Output isn’t design - Linear
  • Aside from conductor skills, we’re also focusing on people who: Take token design just as seriously as pixel design. Are comfortable in engineering-dominated environments like VSCode and Terminal. Don’t wait for others to tell them what to do. Push the frontier forward, rather than just ape what very-online trendsetters are doing. Make working software, not just the blueprints for it.
    Mike Industries » A running commentary of occasionally interesting things — from Mike Davidson.
  • The assembly layer is going away.
    Mike Industries » A running commentary of occasionally interesting things — from Mike Davidson.
  • I think design tooling forks into two distinct shapes from here
    sam henri gold on X: "Thoughts and Feelings around Claude Design" / X
  • LLMs were trained on code, not Figma primitives, so models never learned them. As code becomes easier for designers to write and agents keep improving, the source of truth will naturally migrate back to code.
    sam henri gold on X: "Thoughts and Feelings around Claude Design" / X
  • The beast is hairy enough that entire design roles now specialize in wrangling the system itself.
    sam henri gold on X: "Thoughts and Feelings around Claude Design" / X
  • autonomy is about becoming sufficiently informed to credibly shape shared product decisions.
    Boost Design Autonomy with an Information Pipeline - NN/G
  • It expands the role of design from defining what should happen to shaping how systems actually behave and creates space for deeper learning.
    From mockups to momentum: How vibe coding is changing the design process
  • A coded prototype is not a shortcut around engineering rigor.
    From mockups to momentum: How vibe coding is changing the design process
  • This creates an opportunity for teams to engage before production begins—when learning, iterating, and change are still cheap. Engineers encounter design ideas as behaviors, not specs. Designers spend less time polishing pixels in isolation and more time helping product teams learn what works. And product managers get earlier signals before scope hardens.
    From mockups to momentum: How vibe coding is changing the design process
  • AI-assisted coded prototyping, or vibe coding, changes that dynamic. By enabling designers to test their designs and workflows with live content, ideas can be explored under more realistic conditions before product requirements solidify.
    From mockups to momentum: How vibe coding is changing the design process
  • AI lets us work at similar levels of abstraction. We can focus on intention, structure, and meaning while the tool handles implementation.
    Craft is Untouchable - Christopher Butler