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.

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.

“The role of someone who figures out what needs to exist, why, how it should work, how it should be positioned, differentiated and made memorable has never been more in demand.” Josh Puckett (also the maker of Pica included below) separates the deliverable from the practice: he agrees the mockup-maker role is going away, but argues the ​“what should this be and why?” role is more in demand than ever.

“The first casualty won’t be design. It’s the deliverable.” Tommy Geoco backs it with numbers: a recent State of Prototyping survey of 1,478 design engineers finds 80.9% spending most of their week vibe coding, and 59% having shipped their own internal tool in the last six months. ​“The design function isn’t being eliminated. It’s absorbing engineering.”

Pica is a native macOS font manager from Josh Puckett, built for designers who want proper font organization. ​“Organize into collections, test color themes and logos, watch folders, manage what’s installed, and much more.”

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.”

Jacob Miller left the PM role at Figma to build Diffui, a new way to approach the design to dev process with AI. In this thread, he compares designs generated by his tool and Claude Design. One is more expressive and diverse, another is more polished and organized. The point is not that one is better than another, but how can we combine different approaches and tools to get to the most interesting result.

Hugo Raymond breaks down Swap Instance vs. Slots as two ends of a control–composability spectrum: Swap Instance hard-locks a single nested component in a fixed position, while Slots act like open containers that accept almost anything and can be freely rearranged. For design system teams, his key point is that the ​“right” choice isn’t about which feature is more powerful, but about how much you trust consumers of your components and whether you fear incorrect composition more than full detachment from the library.

Rasmus Andersson, creator of Inter and former principal designer at Figma, draws the sharpest distinction in the launch coverage: ​“This is really neat but it’s not a design tool as much as it’s a design production tool. The practice of design is mostly about what comes before production.”

Karri Saarinen, CEO of Linear, makes a similar point that AI design tools conflate producing interfaces with designing them, leaning on Christopher Alexander’s ​“Notes on the Synthesis of Form” to make the case that real design is the search for fit between form and context, not the generation of form itself. He points to a visible symptom: AI-assisted products that look polished but unravel under use, full of decisions that were never genuinely worked through.

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.

A thorough, practical guide from Christine Vallaure on what design systems need to work well with agents. Five things most systems are missing: semantic tokens, full state coverage, slot-based composition, exact Figma-to-code property matching, and token-based auto layout. Pairs well with the Brad Frost video — both cover the same design system moment from different angles.

Christine Vallaure built a five-person AI editorial team from one text file and seven lines. Five named agents: Rachel brings reader feedback, Joan brings numbers, Caitlin flags voice problems, Miranda raises buyer concerns, and Elke runs the room as editor in chief. Technically one model shifting between personas inside a single Claude conversation, but behaviorally a team critique. The most concrete personal account I’ve read of what agentic AI actually feels like to operate as a solo creator.

Jenny Wen, who brought FigJam from concept to launch at Figma and is now design lead at Anthropic, talks at the Double Diamond podcast about designing Claude itself. The key difference from traditional software: ​“When you are designing now with these LLMs, you basically can’t map out all those flows. You basically just have these core primitives and these specific states that you want the model to get to, but the possibilities in which the user can actually interact with the model are just basically endless.”

Figma Community now includes Apps, a new category that connects Figma to external tools, including AI systems and third-party products. Find them in Extensions alongside plugins and widgets.

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.

Luis on what the ​“shadcn-ification” debate is actually about — not the visual uniformity, but the organizational misread: ​“The mistake isn’t in the ingredient. It’s in thinking that having access to good ingredients is the same as knowing how to cook.”

Stakeholders are concluding that the design system infrastructure is done because a great foundation exists. The teams that have spent years practicing design systems understand exactly why that conclusion is dangerous.

Ridd interviews Kris Puckett, design manager at Stripe and formerly design lead at Mercury and Dropbox, on becoming an AI-native designer by using tools like Claude Code, OpenClaw, and personal AI to ship his own apps, supercharge his design practice, and build highly personal systems for life and work. I’m deeply curious about the last part and can’t wait to dig into his course Neuma on building a personal AI system.

Ridd walks through a workflow where Paper acts as a visual canvas that Claude can ​“proactively” explore and prototype in. The interesting bit is his framing of Claude Code as a coworker and Paper as a shared whiteboard. That’s exactly what I wanted when last week I commented on missing agents in Figma after spending more time in Cursor.

Jenny Wen leads design for Claude at Anthropic, and in the past, she was Director of Design at Figma, where she led the teams behind FigJam and Slides. At Lenny’s podcast, she lays out how AI is collapsing the classic ​“research → mock → iterate” workflow into two main jobs for designers: supporting rapid implementation alongside engineers, and setting shorter 3–6 month product visions that keep a swarm of agents and builders pointed in a coherent direction. Jenny describes the day-to-day at Anthropic as equal parts surfing internal prototypes, pairing with engineers, and doing last-mile implementation herself. She still sees Figma as critical for exploring many directions and fine visual decisions, but treats Claude as her primary stack for long-running tasks and front-end polish.