Designing in the age of AI.

AI in my design process

This is a pretty incredible time to be a designer. Everything is shifting fast, and rather than feeling overwhelmed by that, I find it genuinely exciting.

My workflow looks quite different than it did two years ago. I move between Figma and code more freely now, use AI at almost every stage, and keep adjusting as I learn what actually works. Here’s where it fits:

• Research and synthesis — I use Claude and ChatGPT to get through large amounts of information quickly: interview notes, competitor research, documentation. It frees me up to do the thinking that actually requires a person.
• Ideation — Good for getting unstuck and exploring more directions early on. I still make the calls, but AI gets me to more interesting starting points faster.
• Specs and PRDs — I cowork with Claude to turn rough thinking into product-requirements docs and thorough specs, structured and complete enough to actually build from.
• Placeholder copy — Copy that sounds real, so prototypes feel like the actual thing from the start.
• Prototyping — Figma Make in particular has changed how I prototype. I can test ideas much earlier, which changes the whole shape of a project.
• Design systems and build — This is the part I’m most excited about right now: using Claude Code to write directly into Figma files, build design systems, find problems and inconsistencies, and reorganise things at scale. It’s opened up work I simply couldn’t do before.
• Working in parallel — I’ve started using AI agents to work on multiple tasks at the same time. It’s a bit like having several versions of me running in parallel, each focused on a different problem. The amount of ground you can cover is hard to describe until you’ve tried it.

Made for AI

I got the chance to work on very exciting AI features that helped the sales team save time writing personalized cold emails at scale. Have a look →

Made with AI

I’m always building small AI-focused projects to test new features and models and stay current. A few on the go:

Staying current

I follow researchers, practitioners, and critics across design, engineering, and ethics. I read documentation. I try things. I pay attention to what the broader conversation is missing, especially around accessibility, trust, and how real people actually experience AI-powered products.

Watching the pitfalls

When shipping gets this easy, the risk isn’t that you’ll move too slow. It’s that you’ll move too fast, on the wrong things.

AI can generate a lot quickly. But generating more has never been the hard part of design. The hard part is knowing what’s actually worth building, and staying honest about whether it serves real people or just feels satisfying to ship.

I’ve had to get more decisive about that. More opinionated, earlier. When the cost of execution drops, the quality of your judgment matters more than ever. Users don’t care how fast something was built. They care whether it works for them.