Anthony Hobday on why most design career advice comes from people who don’t hire designers and reflects a single lucky path. The practical core: a five-minute curriculum, ways to look impressive without impressive jobs, and the signs an org genuinely values interface design. His argument that one strong credential can cover for a weak portfolio pairs neatly with ​“Components Are Dead” below — both circling what actually holds value as the job changes.

Luis Ouriach makes the provocative case that when LLMs make code cheap to write, edit, and migrate, the contribution model and the component-as-source-of-truth lose their reason to exist. His point is that consistency was always carried by tokens, not components, so a well-defined token set could govern ten different LLM-generated inputs at once. He stops short of full obituary, asking whether components live on as the unit of constraint.

Rauno Freiberg, a design engineer widely respected for his UI craft, keeps a running collection of short notes on the small decisions that make interfaces feel right. One entry works through why an animation delay meant to highlight a scrolled-to message backfired and felt more awkward; another walks through the redesign of cards. It’s the kind of thinking-out-loud that can teach more than any tutorial.

Just updated my annual Config Study Guide with the remainder of the recordings — all 70 talks are now organized and ready to watch. (Only the Learning Lab videos are still unavailable.) This is a practical way to work through the talks at your own pace, mark what you’ve watched, and trade recommendations with friends and colleagues.

New weekly live show by Ridd and Tommy Geoco, focused on design, tools, and the people behind the software.

A large survey of tech workers in 2026 finds the industry splitting into two groups: roughly half feel amplified by AI, while 14% feel destabilized and 12% are simply resentful. Designers and researchers are overrepresented in the fragile half. What’s striking is that the fear isn’t ​“AI will take my job” — only 22% name that. The bigger worry is unsustainable pace and doing more work for the same pay. Career optimism is down, burnout is up, and 53% would actively discourage someone from entering their field.

Dylan Field’s own Config 2026 recap, covering all six announcements at once: Code Layers, Figma Motion, Shader fills and effects, Generative Plugins, Weave Tools, and the Figma Agent. His framing: ​“AI has lowered the floor, but it has not raised the ceiling. Designers, creatives, builders: You will raise the ceiling.” A deliberate pushback against the narrative that AI replaces creative work.

Dylan Field opens Config 2026 by settling the design-vs-code debate once and for all: ​“Code is not the opposite of design. Code is material for design.” The keynote’s headline feature, Code Layers, puts live interactive code directly on the canvas alongside design layers, with a shared agent chat so teams can explore and riff together rather than each going a hundred prompts deep alone. From the same team: Figma Motion in beta, a full timeline-based motion tool with shader effects, 3D transforms, and export to MP4, GIF, and animated SVG. Worth watching in full: the Weave AI tools and custom shader section is genuinely impressive, and the generative plugin demos near the end show where the platform is heading.

A fresh edition of my annual Config Study Guide, with all recordings grouped by day, organized by stage (from larger to smaller), and color-coded by theme. The stage size is a good cue for how important organizers considered a specific talk — I recommend starting from the top of deep dives and themes you’re interested in. Some talks haven’t been published yet, so the study guide will be updated.

I make this resource because even while attending in person, I can only make it to a small fraction of talks I’m interested in. Use the Stamp tool to mark the talks you want to watch or have already watched, add your thoughts with stickies, and share your version of this file with friends.

Marcin Wichary, Design Architect at Figma, made this interactive essay about fingers, latency, and why our interfaces still fail the hands using them. Starting with 1890s typists who routinely hit 70 wpm when scientists said 40 was the ceiling, he traces a direct line from terminal echo buffers and UI blocking to Notes on a Mac that can’t keep up with your typing in 2026. The embedded demos — where you feel the difference between a blocked UI and a parallel thread — do more to explain debouncing and latency than any amount of text could. This essay is a fantastic companion to Marcin’s Unsung blog on software craft and quality.

Nikita Prokopov makes the case that great UI isn’t just about nailing the start and end states of an animation, it’s about every frame in between. His rule of thumb: if you freeze the screen at any moment, you should be able to explain what you’re looking at. The post walks through a set of GIF examples — from Safari’s misaligned cursor-and-placeholder animation to YouTube’s inexplicable rectangle transition — showing how mid-animation frames that don’t hold up on their own erode user trust.

“As code becomes cheaper, an increasingly large portion of it is written for prototyping, not production.” Yitong Zhang argues that prototype coding and production coding are diverging into distinct disciplines with near-opposite requirements: prototyping wants speed, mock data, no types, no tests, and wide-ranging agents; production wants the opposite. Cursor, Stripe, and Notion have already shown this with their internal playground environments — and Figma just needs to follow that path. Parallel design exploration means more inference runs, less complexity per run, and better margins than production – making Figma one of the best-positioned companies outside the labs to run agents at scale.

“Behind products that just ​‘feel good’, there is an insane amount of design and engineering that you never get to see.” Enri Tarta got rare access to Figma’s product team for a day, and the result is the kind of process tour we almost never get to see.

A design vocabulary guide by Emil Kowalski and Glenn Carstens-Peters. 188 terms across 12 categories — typography, color, layout, IA, accessibility, measurement — defined with the precision designers reach for when they actually know what they’re looking at. It’s a preview of a larger ​“design education for an era of change” arriving fall 2026.

The Community profile redesign adds role, experience, tech stack, pinned work with images and links, and social channels. Combined with the FigPal customization, it reads less like a profile page and more like a creator landing page. Figma clearly wants Community to function as a discovery layer for designers, not just for resources.

Soleio’s guest is Rasmus Andersson: founding designer of Spotify, one of Figma’s first designers, co-creator of GraphQL, and creator of Inter. The part that stayed with me is his description of how Figma operated: one person on one problem for a year, sometimes binned at the end, while shipping something visible every month. He also makes a case that the production side of design — the part AI is eating fastest — was never actually the hard part. What’s left is the intention. The other link in this section is Soleio’s talk on the geometry of luck, making this pair worth watching together.

“Luck isn’t something that you have. It’s something that you leave behind.” Soleio — designer of the Like button and angel investor in Figma, Cursor, and Framer — delivered this as the closing line of his Tokyo Design Forum talk, and it’s the kind of sentence that reorganizes how you think about a career. The talk, now archived by The Forum Library, reframes luck as a generative force you shape through how you live and work, not a resource you accumulate.

Matt Colyer, Figma’s director of product management for developers, makes the case on Dan Shipper’s AI & I podcast that the SaaS apocalypse narrative has it exactly backwards. He’s been running his own agents for two years and is buying more software subscriptions than ever, because shipping and maintaining a personal agent teaches you fast why people pay for someone else to run it. The more interesting half is about design specifically: chat is linear, which makes it good at converging on a single direction but terrible at generating lots of options. Figma’s on-canvas agent is a first attempt at the divergent side — letting you branch frames in different directions, then bring in a convergent agent to cluster them. He also walks through how the MCP server closes the code-to-design loop, and why ​“review” has quietly become the biggest bottleneck in AI-assisted product work.

Designer Fund surveyed 900+ designers across 60+ countries and conducted 20+ interviews with leaders from Anthropic, Framer, Linear, Notion, Shopify, Sierra, and Stripe. The headline number: half of respondents have shipped AI-generated code to production, and designers are now using double the AI tools they were a year ago. Designers are quietly absorbing PM and engineering work, but hiring loops, performance reviews, and team shapes haven’t caught up.

Tom Scott breaks down how the Staff role differs from Senior in kind, not degree. Senior designers execute well-defined features. Staff designers question whether the work should happen at all, spot where teams are solving the same problem in three different ways, and turn that into reusable patterns. Useful if you’re trying to figure out which of your current habits actually point toward Staff, and which are just more Senior.

Daily curated design news and resources for product designers, design engineers, and PMs — read all week, then get the best links in your inbox every Tuesday.

Config 2026 lands June 24–25 at Moscone. The agenda confirms the obvious: this year is about AI workflows and design systems built for them. Build your schedule now — last year the best talks filled up fast.

The May edition is mostly a demo of Figma’s MCP server, with Amy Lima and Anthony DiSpezio walking through three workflows: code-to-canvas import of a vibe-coded prototype, round-tripping a dark mode so variables stay in sync between code and Figma, and using the pre-installed figma-use-scale skill to generate first-pass directions on a production dashboard. The closing update reel includes vector editing up to 10x faster, memory warnings down 92%, macOS eyedropper now samples anywhere on screen, FigJam MCP can read and write boards (ERDs, architecture diagrams), Make Kit packages your design system’s code for Figma Make, and Weave gets a timeline for video.

Luis Ouriach makes the case against single-number design system adoption metrics. His argument: one number collapses three things that should stay separate, across artifacts (a brand token and a complex data table component need different definitions of ​“used well”), surfaces (a logged-in dashboard component has no business on a sign-up screen), and people (a marketer, a senior product designer, and a front-end engineer all want different things from the same system). The throughline is that compliance with a benchmark is not the same as value, and most design system dashboards are quietly measuring the wrong one.

“Claude Design can read a design system carefully when the prompt is about the system. When the prompt is about a composition that uses the system, it stops respecting the components and just generates lookalikes.” TJ Pitre spent a few hours testing Claude Design against two real design systems and concludes that the tool references your system, but doesn’t consume it. Claude would happily inline HTML tags with style props instead of importing them from your component library.

“The pitch for Claude Design’s workflow is roughly: I have a design system, I want to generate new product surfaces from it, and I want AI to do most of the lift. That workflow exists today. You can pair Figma with an MCP server like our Figma Console MCP, or with Figma’s own MCP server, or with Code Connect, and then point an AI app generator at it. Lovable, v0, Replit, Figma Make, Claude Code working inside your repo. Your Figma file stays the canonical source. Your codebase stays the production surface. AI does the generation in between.That flow is more linear, more honest about where source of truth lives, and it produces output that actually uses your component library, because the AI is operating inside the repo where the components live.”

“Design is a process, not an artifact. Design is the act of deciding what should exist, why it should exist, and what ​‘right’ looks like before you’ve committed to building it.” A new piece from Jake Albaugh, dev advocate at Figma, articulating what design actually means in 2026. The four-point framing — design is process not artifact, AI accelerates execution not clarity, 100×0 = 0, collaboration amplifies intent.

Especially the second point: ​“The most expensive thing you can do isn’t build something badly. It’s to execute well on the wrong idea.” If you’ve been struggling to explain why polished AI demos can be worse than no demo at all, this is the piece to send.

Grace Li lists 7 common design smells in GPT 5.5: huge typefaces with tight tracking, lack of textures, bento boxes with unrelated icons, pill-with-dot in hero sections, gradient keywords, grid background, and rounded cards with three nested cards. ​“TLDR: if you’re vibe coding with GPT 5.5, the easiest wins are: loosen the tracking on your headlines, delete the status pill, and pick one accent color instead of a gradient. That’ll get you out of the uncanny valley before the next model release closes the gap on its own.”

GPT 5.5 is strong at programming, but not great at visuals: ​“Across 5,000+ preference pairs, GPT‑5.5 ranks #13 in Website Arena, #16 in UI Component Arena, and #19 in 3D Design Arena. It loses to Claude Opus 4.7 and Sonnet 4.6, to Gemini 3.1, to GLM 5.1, and to Kimi K2.6.”

Kris Puckett, Design Manager at Stripe, spent months building Epilogue, a real iOS app with 14,000 lines of Swift, entirely through conversation with Claude. This essay is a specific and honest account of what the designer-building-with-AI experience actually looks like: what broke, what he learned about asking precise questions, what ​“vague frustration keeps you stuck, specific confusion gets you answers” actually looks like in practice. ​“I realized the bottleneck was never coding ability. It was articulation. The ability to describe what I wanted clearly enough that something else could build it.”

Karri Saarinen, CEO of Linear, writes one of the more grounded takes on AI’s current state. Linear’s cloud agent now fixes more than 1,000 issues per month, but Karri is clear that hard problems remain hard and design tools are still challenging to use. On having a design tool operate directly on the production codebase: ​“A lot of the design work I do is not production design. I am not trying to implement the final version or test every edge case. Most design work is about making decisions, understanding the problem, and finding the fit. That process generates many variations and messy ideas.”

The expertise paradox section is the most useful: ​“AI often feels most impressive in domains where you know the least.” Expertise makes AI harder to use but also more valuable, because experts know how to steer, constrain, and evaluate the output.

“Designers have always (and will always) answer the question ​‘What’s worth making?’ ” Joel Lewenstein, Head of Design at Anthropic, argues that as the cost of software drops, the most important decisions shift from ​“can we make this?” to ​“should we?” Design, in his framing, is what narrows the possibility space fast enough to keep up with the speed of delivery. He describes Claude Design as a tool for getting ideas ​“good enough to move discussion forward,” cutting idea-to-internal-feedback time from days to hours.