Working with engineering, product, and the rest of the org.
39 entries
Merholz borrows Scott's legibility lens to explain why design chronically struggles: businesses only see determinate work, and design's most valuable moves are indeterminate.
Yeo turns murmurations and goose formations into an operating model — async telemetry, rotating leads, domain pods, three anchors, and a scheduled molt for design debt.
Stone oversees engineering, product, and design as one system. Her hiring bar for the AI era: systems thinkers who see the whole machine, with fluency expected of everyone.
Fernandez turns Butterfield's 2013 promise into a working framework — utility, usability, feel — with named failure modes and a gut-check: are we proud to ship this?
Hoang names the discipline forming around agents as users — access, context, tools, orchestration — and argues for parallel paths built for two different kinds of minds.
The forty-minute scope debate now costs more than generating the diff. Abuadas's move: produce a constrained probe, then argue from evidence instead of vibes.
When PMs and engineers prompt, every generation is a design decision. Alicea's answer: stop writing documents that persuade humans and curate context that steers models.
Loop engineering jumps from individual developer habit to team infrastructure: describe a recurring job in plain language and the agent runs it with workspace context.
Boom is building a supersonic airliner and its engine at once, on software's rhythm: short cycles, tools built by every engineer, real parts in hand fast.
Twenty exec interviews, the Config crowd, and a 458-response pulse check converge: how your org behaves predicts how design feels about AI.
Production capacity stopped being the constraint. Dean maps what design leaders manage instead: judgment, team cohesion, and the moment to stop generating.
Litt argues understanding agent-written code keeps you fluent enough to have the next idea, and offers four techniques for getting there.
Callahan splits product quality in two: the design system sets the floor, and how product teams use it sets the ceiling.
A Linear engineer on how agent-heavy review freed him from parsing lines to judging whether the work earns its place.
Sheta Chatterjee walks through the design calls behind Gemini Enterprise: a shared AI inbox, team project spaces, and keeping people in control.
Martyn Reding argues the old shape of design leadership is gone, and lays out what changed and how to adapt.
Citing a 515-startup field experiment, Nielsen argues AI pays off when teams redesign whole workflows, not single tasks.
An early-career designer notices she keeps reaching for connective work wherever structure is missing, and asks what that instinct reveals.
Five lessons from serving 127 million customers, where hiding complexity is a deliberate architectural and cultural decision, not polish.
GitHub's five-year accessibility program turns outward, with audit data, design tooling, and AI agents making inclusion operational rather than aspirational.
Merholz reads the layoff wave through decades-old org theory: under uncertainty, executives copy each other, then call it AI strategy.
A multi-agent read of 638 Lenny pieces, June 2019 to March 2026, charting what production loses and judgment keeps.
The AI holds context across Linear, Slack, and research; you do the thinking. · Code prototypes move feedback from visual details to actual UX problems.
Frame it as infrastructure, not UX, or it gets deprioritized before the meeting ends. · If you don't define the cost of inaction, leadership assumes there isn't one.
GitHub's accessibility agent reviewed 3,535 PRs at a 68% fix rate. The sharper lesson is what they taught it not to touch.
Slack's VP of Product Design on guiding roughly 70 designers through AI without mandates: stay curious, stay skeptical, and keep the bar high.
AI-readiness isn't a separate category. The same fundamentals (tokens, layout intent, accessibility, governance, handoff contracts) finally have to read clearly to a non-human.
AI-generated code defers cost, it doesn't reduce it. Seven debt categories concentrate far from where the velocity gain was booked, including reviewer fatigue and security debt.
Frontier AI teams optimize what's measurable, not what matters. Microsoft's user researchers want a seat at the evaluation table, as a safeguard against the metric chosen for being convenient.
Most teams treat canvas, code, and PRD as three competing artifacts. Brett McMillin's reframe: a connected system, with an agent translating between them and the designer's judgment moving through both.
Most companies don't write down how they hire because writing it down forces honesty about what they actually value. Linear did the work and published it.
Microsoft's 2026 Work Trend Index covers 100,000+ Copilot conversations and surveys 20,000 workers across ten countries. Only 26 percent say leadership is consistently aligned on AI.
An engineer at Linear scopes coding-agent tasks tight enough that they can't wander. The discipline is the same as scoping for a junior teammate.
Maggie Appleton reads Steve Yegge's chaotic agent orchestrator as speculative design fiction. The coding bottleneck is gone; the design bottleneck was always there.
Coding agents collapsed the implementation window. The alignment checkpoints that used to live inside it just disappeared, and the PR cannot carry their weight.
Microsoft spent years replacing plastic packaging with paper. The commitment was easy; getting every millimeter to behave was the actual work.
Linear took designers and engineers to Athens and shipped a working build by Friday. The trust that made the loop close, not the offsite, is what's worth lifting.
An engineer at Linear scopes coding-agent tasks tight enough that they can't wander. The discipline is the same as scoping for a junior teammate.
Nubank ran a real A/B test on whether to scale or shut down an internal HR product. The data was unambiguous; the team's reaction to it was not.
