Living Clarity — an onboarding-first knowledge base, prototyped in Stitch.

A new designer's first ninety days are a parade of questions that someone, somewhere, has already answered: how do we run a crit, where does research live, what's the bar for a Figma file, who owns the design system, what does the legal review path look like. Most of those answers live in Slack threads, one-off docs, and the heads of two or three veterans.

Living Clarity treats onboarding as the forcing function for an org-wide knowledge product — if it works for the brand-new associate, it works for everyone.

The screens here were generated and iterated inside Stitch, Google's AI design tool. Stitch let me move from a written product brief to a navigable, multi-screen prototype in hours — which is itself the point of the case study: the operating leader's job is no longer to wait for design capacity to test an idea. It's to prove the idea is worth design capacity in the first place.

The static FAQ is the floor, not the ceiling. The vision is to wire Living Clarity into Squiggly, the home office's AI, so that every answer is personalized to the associate asking it — their location, their department, their role and function, their tenure, and the tools they actually have access to.

A new researcher in Seattle and a staff designer in Madrid ask "how do I kick off a research study?" and get two correct, different answers — same governed source, different surface. That's the difference between a knowledge base and an intelligent operating layer.

With Living Clarity in place the onboarding ramp shortens, because new associates no longer need to find the right person to ask. More quietly: calibration tightens across the function, because decisions made on Tuesday are searchable — and personalized — on Wednesday. The function moves from "ask three people and hope" to "ask once, get the answer scoped to you."