AI-ready Design System, built with strategy

How I redesigned an entire platform in 3 months, where real user data and design criteria made the AI genuinely effective, not just fast.

Case Study

Finlink

AI-ready

2026

Context and my role

An existing platform with a loyal user base and a stable number of paid users, but frozen growth. Think of it as LinkedIn for Financial Advisors. They wanted to revamp the platform and bring in new technology to reach new audiences with a stronger product.

I was in charge of redesigning the entire platform, refreshing the brand, and proposing AI integrations across the user experience. It was a 3-month project, working closely with two developers and the Head of AI, and in direct conversation with stakeholders throughout.

In this case study, I'll walk you through how designing with and for AI, grounded in real user data and led by design criteria, let me move fast without ending up with a generic product, or losing the human touch.

Strategy: starting from real users

Before improving, you need to know what's working and what's not. I audited the existing platform and interviewed four real users to understand to inform my strategic decisions.

Both pointed to the same problem: the Information Architecture was a mess. The audit exposed overlapping hierarchies and duplicated destinations. The interviews showed users were struggling with navigation and findability. Some had built their own routine to work around it, running the same manual search every day, filtering opportunities by city, then by AUM, scanning for sellers. Others had the opposite problem, they opened the platform and didn't know where to start.

So I rebuilt the architecture around more intuitive navigation. But better navigation only fixes so much. I also proposed an AI Agent as a global solution, similar to how Notion's Agent works: you can ask it to find an opportunity, match you to a job that fits your profile, help you buy or sell a practice, automate daily searches, and more. And for those who know exactly what they want, traditional search with saved filters they can re-run and a clear IA keeps that path fast too.

An AI-ready Design System

Because this was a short term, fast paced project, I made a strategic decision: while auditing and researching the current product, I also set the foundations of an AI-ready Design System, which kept growing as the redesign process advanced:

  • Structured guidelines the AI could follow: markdown docs split into the rules I wanted to keep (Guidelines.md), per-component guidance (components.md), and the available styles and how to use them (styles.md), with WCAG contrast compliance baked in.

  • A token foundation with primitive and semantic layers, the semantic layer named for meaning rather than appearance.

  • Every component structured cleanly, with Auto Layout, defined variants, and constraints.

I worked with Figma Make as my generative tool, feeding it all of this design system information and running it on Sonnet 4.6 and Opus 4.8. What I value about Make is that it lets me step in and edit the design manually whenever I need to.

Two of the biggest mistakes I've seen on projects that lean on GenAI are overly generic designs that aren't memorable, and teams that end up prisoners of a setup where every change burns through credits. Working in Figma let me avoid both: I could explore the visual identity and find creative solutions when the design called for it, while letting the AI carry the repetitive work, simple layouts, component variants, their states, etc.

From there, I used Figma MCP + Claude Code to get to code, which was reviewed and wired up by the full-stack developer in charge. The results held up because the foundation underneath was well built.

Conclusions

Creating an AI-ready Design System helped me accelerate design times, and keeping a strong focus on strategy ensured those designs would actually solve a problem. When done with design criteria, and not just for AI-FOMO, these models can make a project more effective without losing sight of the user experience.

If you want to know more about the features I planned and designed on this project, feel free to reach out for a meeting.

And now, everyone's favorite part of any case study: a bunch of screens…