Designer Fund

We're hiring a Product Design Lead at Bezi! Bezi is building the best agentic workspace for game studios. If this is interesting to you, apply below 👇 https://lnkd.in/g9qYY8Wf

AI can produce something that looks finished in seconds. We went inside Stripe’s design team to understand how they use that speed without lowering the quality bar. Katie Dill, who leads design at Stripe, compares the temptation to a microwaved burrito: it’s impressive that it’s ready in 90 seconds, but that doesn’t make it good. Stripe’s approach focuses as much on the environment as the tools. As Katie puts it, “We set the table to enable the party.” That means: ‣ Clearing the hurdles: “AI-cation” days and broad tool access give designers space to experiment outside their daily work. ‣ Letting useful ideas spread: Team members turn recurring friction into shared tools, from ProtoDash for prototyping with Stripe’s real design system to Dante for maintaining writing standards at scale. ‣ Taking roof shots, not moonshots: Small, focused experiments help teams learn what works before standardizing too early. That spirit extends across the design team, from testing interactive product concepts to exploring Stripe Press book covers. But the quality bar remains human. Katie’s test for AI-assisted work: “Would I still be proud of this if it took me two weeks to build?” Our latest AI in Design 2026 case study explores how Stripe’s design team balances speed with craft. Watch on YouTube: https://lnkd.in/g9Pt4zYM Read the recap: https://lnkd.in/giuFrPPn Full case study: https://lnkd.in/gsFCkXDq

How we built Interfere's new website In our first blog post, our Head of Design Paul F.sign Paul F. and Design Engineer Jakub Krehel discuss the thought process behind the visual identity, graphics and animations on our new website. Read more: https://lnkd.in/gVDRrGud

Our latest AI in Design case study is live, featuring Shopify. A year ago, Tobias Lütke gave every Shopify employee access to virtually every AI tool available and encouraged them to experiment. Today, roughly 60% of their designers push code directly to production (up 38% since last September) and they have built more than 5,500 live prototypes. When everything is changing this quickly, it raises a question many designers are asking themselves these days: How do you grow as a designer right now? VP of Design Katarina Batinaput it simply: "The only wrong answer is to do nothing.” Across their team, this mindset shows up everywhere: • Designers move fluidly across tools by switching between Figma, code, and custom workflows rather than waiting for a rigid process • They get closer to the product by querying merchant research, checking support logs, and learning the systems behind the interface • They build internal infrastructure like Quick, Artifact, and Purl so designers can prototype and share working software without engineering bottlenecks • They invest in human connection by doubling down on apprenticeships and side-by-side learning AI may be changing how design gets done, but at Shopify, it is ultimately reinforcing a timeless truth: the best designers have always been the ones who never stop growing. Read the case study: https://lnkd.in/gFjiqxrA Watch the video: https://lnkd.in/gwV4vpdi

“AI invites infinite usage, which can make you trust yourself less. If AI is the only tool you reach for, it reveals blind spots in your own craft.” This tension came up repeatedly in our conversations with Linear, as part of our latest AI in Design case study. For a team known for exceptional software craft, AI serves a specific purpose: protecting the parts of design that shouldn’t be compressed, like understanding the problem, exploring possibilities, and deciding what’s worth building. As AI makes it possible to turn ideas into software in seconds, CEO Karri Saarinen and product designers Charlie Aufmann and Isha Kumar treat design as a search, not an assembly line. Some of the ways Linear intentionally brings AI into that process: ‣ Interrogate, don’t just validate. Karri built a custom skill connected to 40k+ customer requests that helps him uncover the need behind a feature request and make the argument against his own thinking. ‣ Protect hands-on craft. Only 20-30% of Isha’s net-new design work happens with AI. After finding that constant AI use started to flatten her process and make her trust her own judgment less, she became much more selective about where it enters her creative loop. ‣ Bring the customer into the room. During Linear’s major interface refresh, Charlie used agents to synthesize feedback from customer calls, Slack, and Twitter, then brought the raw customer quotes into design review alongside the work. Read the full case study: https://lnkd.in/gfyPb6J4 Watch on YouTube: https://lnkd.in/g5wXVMSe

Our AI in Design case study featuring Linear is live! A couple things stood out to me right away as we were talking to Karri Saarinen and team about how they use AI in their flow - 1. They go way deeper with AI before doing any work that most teams would categorize as “design”, though they rightfully see it as a key part of the design process. This means asking AI for info on how a UI came to be, who has worked on it historically, why a certain change might work or not, etc. They really use AI to deeply understand the problem they’re about to tackle. 2. The way they use AI within Linear gives them a crazy advantage. Imagine asking something like: “What designer has touched this feature in the last 5 years and why does it work the way it does?” Good luck getting a good answer for this at most companies. At Linear they have all that context IN Linear… having all that data in one place is a huge advantage now that they’ve added AI to the product. So you both want to have a system where all this knowledge is getting captured (obviously Linear can work great here) AND make sure your team takes advantage of this context to do their work. It’s an incredible way to save unnecessary iterations and ensure you’re building a product that’s moving the company in the right direction. Lots more insights and examples in the full case study here -  https://lnkd.in/gnsxFjUH

We’re actively looking for founders to back at Designer Fund, and we know a warm intro shouldn’t be the only way to get in front of us. As a small team, the challenge has always been figuring out how to open the door wider while still giving every company a thoughtful review. So we built a new application, reviewed by our team alongside Mason, an AI agent trained on more than a decade of Designer Fund investment decisions and philosophy. Every founder who applies gets tailored feedback on what stood out, where there may be room to improve, and how what they’re building maps to the same investment framework we use ourselves. And when something looks like a strong fit, it gets surfaced to our team right away. We’re investing from Pre-Seed through Series A in mission-driven founders using design as a core part of how they’ll win, especially in health, sustainability, prosperity, and large, frustrating, or overlooked markets. If that sounds like you, we’d love to hear what you’re building: apply.designerfund.com