Videos

Leandro Casteel, design manager on Figma’s brand studio, sits with lettering artist Erik Marinovich (Nuform Type) to unpack the Q1 26 earnings posters they made together. Erik traces his approach to type back to apprenticing as a bricklayer under his dad, picking stones from a two-ton pallet to build pathways like a jigsaw puzzle. The same instinct shows up in his letterforms: graphic compositions you’d want to stare at even if you never bothered to read the word.

The on-camera companion to the Make-on-Local-Code launch. The most interesting bits beyond the blog: a Figma editing panel inside Make for direct style changes, multi-element annotations pinned to the rendered screen (including voice mode), and MCP server support for resolving merge conflicts and CI failures. The pitch is that designers get agency to ship the change themselves while the engineer’s review workflow stays untouched – apple for early access.

Lauren Budorick, a software engineer at Figma, walks through six optimizations behind a recent ​“10x faster vector editing” announcement.

A short onboarding walkthrough for the agent beta. Worth watching for the suggested starter prompts: generating alternative layouts, starting from scratch using your design system, working together on canvas, and getting feedback.

“We don’t think designers should generate a one-shot screen and call it a day.” That sentence from the announcement is Figma’s vision for the design agent in a nutshell. The framing is explicitly co-pilot, not auto-pilot: the agent runs in front of you on the canvas, riffs to spark an idea, and then hands it back to your mouse and direct manipulation. Pair that with native access to your libraries, components, and tokens, and the bet is clear – the winning AI design tool is the one that already knows your design system, not the one that generates the prettiest screenshot.

Rolling out gradually in beta over the coming weeks. During beta, the agent won’t consume credits. See also the official announcement at The Figma design agent is here.

“AI designs with you, not instead of you.” Figma’s positioning for useFigma, the new write-capable MCP tool that creates real components, variables, and auto layout on the canvas, not flat images or wireframes. The demo runs the full loop: terminal prompt to first draft, manual polish in Figma, annotations the agent later reads as design context, then back to the terminal to update the codebase. The annotations detail is the most interesting part — they double as machine-readable spec.

Designer advocate Amy Lima walks through a full code-to-canvas-to-code round trip on a sample app: install the MCP in Cursor with /add-plugin, authenticate via OAuth, generate a new screen iteration into Figma, refine it by hand, then prompt the agent to update the codebase and open a PR. Pairs well with the useFigma deep dive below.

Owen Williams, design manager at Stripe, walks Claire Vo through Protodash, the internal prototyping platform he’s been building for 18 months. The V1 was a bundle of Cursor rules plus an MCP server wired to Sail, Stripe’s design system, so any designer can open the repo and build a page without ever touching React or routing. V2 wraps the whole thing in a browser UI running on internal dev boxes, with embedded LLM chat, click-to-annotate feedback, a design review mode, and fidelity toggles (monospace, grayscale) to signal work-in-progress. The same pattern as the Notion and Vercel pieces in this section: production design system plus a thin internal harness, calibrated to one team’s review culture in a way no off-the-shelf tool can be.

Brian Lovin shows the Notion design team’s Prototype Playground, a single Next.js repo on Vercel where every designer gets a namespaced folder and a small set of shared Notion-flavored components. The interesting parts are not the scaffolding but the slash commands and skills layered on top: /figma runs a three-phase loop with the Figma MCP and Chrome DevTools MCP until the build matches the source (~80% on the first try), and a find-icon skill writes its own TypeScript search script after the team got tired of Claude hallucinating ​“search-icon.” See also the Stripe and Vercel pieces below for the same pattern at other companies, as well as another interview with Brian at Dive Club.

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.

Figma walks through the performance work shipped across the platform: vector editing up to 10x faster, Make frame rates 4x smoother, faster load times, and 92% fewer memory warnings. The vector number is the one I’d watch — it changes how heavy illustrations actually feel under the cursor.

Seven small FigJam fixes that add up: cell merging in tables (preserves the upper-left cell’s content), per-cell text colors, wider arrow routing margins with cleaner heads and dashed endpoints, drag-any-handle to flip a shape, a recenter button for big canvases, a slightly more zoomed-out default, and template publishing now on Professional plans (up to 5 per team).

Dylan Field in an interview with Peter Yang argues that AI will massively expand what’s possible in design, but the enduring edge for humans is judgment: taste, craft, and point of view, plus the ability to use AI as an iterative partner rather than a one-shot generator.

Steve Schoger from Tailwind Labs recorded a step-by-step walkthrough on taking an AI-designed dashboard and turning it into something that looks like it was designed by a pro.

Brad Frost and Chromatic cofounder Dominic Nguyen walk through how Storybook’s new MCP exposes design systems for agents to use reliably. The key insight: AI doesn’t invent states your components don’t have — it amplifies what’s documented. Coverage, completeness, and constraints are now load-bearing.

Ed Bayes leads design on Codex at OpenAI; Gui Seiz leads AI product design at Figma. Together with Aakash Gupta, they give a rare behind-the-scenes look at what the Codex-to-Figma MCP integration actually changed inside their teams. The workflow is genuinely bidirectional, code and canvas reading from each other directly. The most concrete signal that something shifted: designers are working directly in staging.

Figma and Anthropic demonstrate the Claude Code roundtrip in both directions. Write to Canvas lets Claude Code create and modify designs directly in Figma; Code to Canvas brings live browser UI back in as editable frames. Worth watching alongside the Agents on Canvas blog post and Figma Skills page for the full picture of what this workflow ecosystem looks like.

Jony Ive on redesigning the Christie’s auction rostrum, an object with 260 years of history and specific ceremonial weight.

Luis Ouriach argues that modern design systems have become the centerpiece of software development in an AI-first world, shifting from a siloed support function to the primary mechanism that tells LLM-based tools what to build, and therefore directly shaping code quality, speed, and brand differentiation.

The Claude Code version of Figma’s ​“Code to Canvas” tutorial. Clear and short, covers the same workflow as the above.