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Hero image from Figma's Code Layers launch post
2026.10.26

Edit a design in Figma, then update the actual code with one click

Figma demonstrated this feature when it launched in open beta on October 15. Bring a Figma frame, GitHub repository, or webpage onto the canvas and it becomes a screen you can interact with. Extract it as design layers, edit it as usual, and apply those changes back to the code with one click. You can push the updated code to a GitHub branch and open a pull request for your team to review. Here are the official demos and examples from people who tried it early.

Figma Code Layers · 2 cases

Insights2026.11.09

After three months with AI, senior lawyers edited better without it than peers who had not received it. Junior lawyers showed no clear difference.

Google and MIT researchers gave an AI patent drafting tool to 90 of 133 U.S. patent lawyers, then asked everyone to complete an editing test without AI three months later. Junior lawyers with less than seven years of experience scored much higher on AI-assisted drafts than peers who did not receive the tool, but only senior lawyers who received it scored higher on the test without AI. The result for juniors remains uncertain because their control group included just seven people.

Insights2026.10.29

Subscription companies made money on forgotten renewals. Now an AI assistant cancels them for customers

Stanford researchers estimated that inertia in canceling raises revenue at large subscription services by 87% on average, close to double, and that cancellations rose sharply in months when customers had to decide for themselves. Meta's AI assistant Muse finds those neglected subscriptions and cancels them for customers, and in one person's collection of public cases, recovering money was the most common single task. What subscription companies can count on is shifting from the time customers spend putting things off to real use, the kind that makes customers say they'll keep paying when an AI asks.

Insights2026.10.29

People with no ultrasound training swept a handheld probe across pregnant bellies, and AI dated the pregnancies as accurately as expert sonographers

People who had never learned ultrasound swept a handheld device across the belly, and the AI's gestational age estimates had a mean error of 4.2 days, no worse than expert sonographers (4.5 days). In Nairobi, where the AI was never trained on local data, the AI and the experts had the same mean error: 4.3 days. What field staff learned in six hours of hands-on training wasn't how to read scans. It was how to sweep evenly, at a quality the AI could read.

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