Three months into life as a public company, Figma has its first activist. Hedge fund Findell Capital sent a letter to Figma’s CEO and board pushing for three things: streamline the product portfolio down to Design, Dev Mode, FigJam, and Make; cut R&D (projected to exceed 30% of revenue in 2026) and stock-based comp (around 27% of revenue versus Adobe’s 8%); and launch an independent investigation into the Anthropic relationship. Findell flags the sequence in April — Mike Krieger resigned from Figma’s board on the 14th, Anthropic shipped Claude Design on the 17th — and notes two remaining board members are material Anthropic investors. The fund still calls Figma “a generational company” with “a true moat.”
Five workflows that show what Figma Weave is actually for: chaining AI nodes on a canvas to blend two references into a style guide, fan out variations across aspect ratios, run eight distortion filters in parallel, generate rotatable 3D models through Rodin 3D V2, and composite stills into rendered video.
Alexia Danton, Designer Advocate at Figma, walks through seven tactics for stretching Make credits further. The most useful ones are the least obvious: use the Edit tool and “Go to source” for small visual tweaks instead of prompting, codify repeated instructions into a guidelines.md file so Make doesn’t relearn your conventions every turn, and reach for Gemini Flash on routine iteration while saving Claude Opus for ambiguity and high-fidelity work.
Make can now connect to a local repo and edit your real production code, not just a sandboxed project. Designers point at an element, adjust properties or leave an annotation, and the agent finds the relevant code, commits the change, and opens a PR through standard GitHub flow (SSH for other providers). It also handles dependency installs and spins up the dev server for you. Closed beta on the Mac Beta desktop app and beta usage doesn’t burn credits.
Brett McMillin shows a concrete loop: an agent reads a coded export flow, finds every state the developer shipped (success, error, loading, edge cases), and generates fourteen designable frames on the canvas using the design system. From there, the designer riffs on three animation directions, the /sync-figma-token skill flags token drift between code and variables, and a generate_figma_design call produces an annotated side-by-side diff.
Emma Webster’s overview of why MCP exists and what it changes. Without context, AI coding tools work from a screenshot — they see the end result, not the decisions that went into it. The Figma MCP server hands agents structured access to components, tokens, and layout decisions instead. Useful as the conceptual baseline before getting into the applied workflows in the lab.
A conversation between Figma’s Design Director of AI Gui Seiz and engineer Alex Kern on how AI inverts the old economics, code used to be expensive and design cheap, now both are cheap and the bottleneck moves to intent. The companion piece to the two MCP posts and the Code to Canvas tutorial elsewhere in this section.
Round up of four AI workflows Figma sees teams adopting: prototyping in code first and pulling it back to the canvas via Codex to Figma, generating dozens of layout variations on the canvas, building a Figma Make prototype before writing the spec, and using Make kits with MCP to carry design system context into the code. The through-line is that the artifact teams align around is shifting from the mockup to the working prototype.
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.
