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.