Articles

Yuhki Yamashita, Figma’s CPO, lays out the company’s worldview behind the Design Agent, Make, and Weave launches. When generating a working app is cheap, the bottleneck moves upstream: choosing the right direction and shaping it with care. He proposes a ​“go broad and deep at the same time” workflow, where Make spins up parallel prototypes and Weave becomes the room where teams compare, argue, and refine. A tidy thesis for a launch week, and the tools clearly exist to enact it.

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.

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.

Figma’s first quarter as a public company: $333.4M in revenue, up 46% year-over-year, accelerating from 40% last quarter. Full-year guidance raised. Dylan Field’s framing in the release — ​“when code is a commodity, design is the competitive edge” — is the line the company will be repeating all year.

Paul Bakaus has packaged 23 design commands into a single agent skill that teaches Claude Code, Cursor, Codex, and Gemini CLI how to actually design. Type vocabulary, color systems, motion, spatial logic — the foundations most prompts miss. The Live mode that writes accepted variants back to source is where it gets genuinely interesting.

Figma Make now supports custom skills — markdown files that capture conventions and workflows you use repeatedly, callable from any prompt with a slash command. Pair /build-from-prd with a Notion connector and any PRD becomes a prototype that matches your standards.

Hannah Hearth runs a tooling Show and Tell with her team at Vercel and writes up the results: Codex + Claude pair programming, Conductor for parallel agent threads, UI Fork for in-browser variant exploration, and Cleanshot’s Pin tool still earning its place.

Jakub Krehel launched Interfaces, a paid magazine for design engineers built around interactive demos and source code, not text. Initial issues cover gestures in motion, gradients, OKLCH, and shared layout animations.

A useful baseline study on how people actually use AI well. The most uncomfortable finding for designers: in conversations that produce artifacts (code, UI, documents), users are less likely to question the model’s reasoning. Polished output suppresses critical evaluation, even though that’s exactly when it’s most needed.

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.”

A useful companion to Google’s announcement above. Meng To shares 15 takeaways from actually using the format: when to Remix vs. Iterate, how to treat DESIGN​.md as ​“reusable project memory,” and why curation is part of the design process. The most actionable takeaway: ​“Start with DESIGN​.md, generate the first design, remix and expand it, create section variations, move into a builder, then assemble the full site.” Don’t miss his video tutorial on turning a DESIGN​.md into landing pages, mobile screens, and motion design.

DESIGN​.md encodes your design rules, colors, typography, and component preferences in a plain Markdown file that AI agents can parse and validate against. Google moves DESIGN​.md from a Stitch-specific feature to open-source format specification. If the format gains traction across tools, it could become the missing link between design systems and AI generation pipelines.

“A state-of-the-art image model that can take on complex visual tasks and produce precise, immediately usable visuals, with sharper editing, richer layouts, and thinking-level intelligence.” OpenAI’s second-generation image model promises a step change in instruction following, precise object placement, dense text rendering, and cross-aspect-ratio generation.

“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.

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.

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.”

Sam Henri Gold argues that Figma’s decade of components, variables, and tokens has become an overgrown, pre‑agentic system that no one would design from scratch now that LLMs work directly with code. He frames Claude Design as ​“truth to materials”: HTML/JS-first, tightly coupled to Claude Code, and better aligned with a future where the source of truth moves back into repositories instead of opaque design files. The interesting provocation is his prediction that tooling will split in two—agentic, code-native tools like Claude Design on one side and pure, system-free exploration playgrounds on the other—leaving Figma facing its own ​“Sketch moment” unless it radically rethinks what it’s for.

Anthropic launches Claude Design, a new product that lets you collaborate with Claude to create designs, prototypes, slides, and more. Powered by Claude Opus 4.7, it reads your codebase and design files during onboarding to build your team’s design system automatically, then applies it to every project. This release kicked off many interesting conversations in the community, some of which I gathered below.

Carina B. Velasquez, a Design Systems Lead locked out of AI tools at work, spent a Friday afternoon on her personal laptop with Claude Code and the Figma MCP server. By 6pm she had built Prisme: a complete three-tier token system, four brand themes, and a bidirectional plugin (Prisme Bridge) translating between Token Studio and native Figma variable formats. Her conclusion: ​“AI is amazing, Claude Code built my design system for me, the future is here. That is not what happened. What happened is that I showed up with years of accumulated knowledge, a specific problem I understood deeply, and a clear enough mental model to describe what I wanted with precision. Claude Code was fast; impressively fast, and smart in ways that genuinely surprised me. But it was executing a vision I already had. The intelligence in that Friday afternoon was not artificial.”