How Stripe is Scaling Quality with AI

📰 3 THINGS TO CHECK OUT

How to Scale Intent, Quality, and Artistry with AI

• Stripe's Head of Design, Katie Dill, sees a parallel between today’s AI building boom and the postwar construction boom: new technology made it possible to build dramatically faster, but the intent gradually got lost.
• AI creates a similar risk for digital products. But faster building simply changes where quality control happens. When teams can build 20 ideas instead of choosing one, fewer ideas get filtered out upfront. That makes editing and refinement more important — and building design systems that uphold your standards and intent.
• When AI lowers the cost to create, design teams should spend some of that savings on making something meaningful, not disposable.

From Designer to Head of Product: Six Things I’d Do Again

• After moving from product designer to Head of Product at trbo, Nurkhon Akhmedov reflects on what helped him make the transition: he began looking beyond the screen to the problem, outcome, and tradeoffs behind it.
• This foundation already exists in design practice. Research builds the ability to listen for what customers really need; critiques build comfort defending decisions and tradeoffs. The bigger stretch is taking ownership beyond the artifact.
• His journey can be helpful for designers thinking about moving into product leadership. "At some point I stopped designing the screen and started designing the problem behind it. That was the real move — everything after it was paperwork."

Zero UI: When the Interface Disappears

• Product Designer and Systems Architect Micha Brandt explores what “Zero UI” looks like now that AI agents can act on users’ behalf. He doesn't buy that the interface will disappear but believes it will move into intent, rules, context, and systems, with screens becoming places to review, confirm, or correct what software has done.
• That changes where designers need to focus — how a product behaves instead of how an interface looks and making decisions about what can be automated and how failure and recovery work. And when a screen does appear, Brandt suggests it'll carry more weight: "Fewer screens, higher stakes per screen."
• Brandt also sees design systems evolving accordingly, from documenting how things look to encoding why and when patterns should be used, so both humans and AI can build from the same intent.

💜 INSTRUCTOR SPOTLIGHT

Jacques Debeuneure Jr. has always moved between the creative and technical sides of making things. His career has taken him from graphic design and creative advertising into UX, native apps, and full-stack development. Today, he’s a Senior Manager of UX and Engineering at Lowe’s and an entrepreneur, and at Designlab, he brings a cross-disciplinary perspective to AI Prototyping Camp, Vibe Coding Camp, and the forthcoming Lab Session, Design Systems x AI.

Jacques is continually experimenting with AI-assisted design and development workflows, applying what he learns, then bringing those lessons back into the classroom. "What I learn outside of work sharpens what I do at work, what I learn at work feeds back into my side projects, and all of it gets funneled into what I teach at Designlab as real-world experience rather than theory." He’s also been chronicling his journey. Follow Jacques to see what he’s working on next.

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🧪 FROM THE LAB

Advanced Figma Launches Next Week

As AI-assisted workflows evolve, design systems are becoming an even more important foundation for how teams build, and Figma remains at the center of that work. Advanced Figma helps designers work faster and more effectively with deeper skills in components, variables, responsive layouts, and scalable systems. The next cohort starts October 9, and we’re hosting a live info session Tuesday, October 7 at 1pm ET for anyone who wants a closer look.

October 15: Synthetic Users: Early-Stage Research With AI

Our first Lab Session, Synthetic Users: Early-Stage Research With AI, runs October 15 from 12–3pm ET. Led by Principal Product Designer Stefan Twerdochlib, you’ll learn when synthetic research is useful and build an end-to-end workflow that grounds AI personas in real market research, sends them through a live product or prototype, and turns their experience into a structured usability report. Enroll now.