Drift — FigBuild 2026 Submission

Slide link: https://www.figma.com/proto/iop24QCjKGmg3N6tr6ZY0w/FigBuild-2026?page-id=116%3A92&node-id=116-95&viewport=829%2C-12%2C0.08&t=7J3GMuitA9NDrkEL-1&scaling=min-zoom&content-scaling=fixed

Inspiration

Everyone with ADHD knows the feeling: you sit down after dinner, look up, and it's midnight. You'd have guessed 45 minutes. This is time blindness — a core symptom affecting 8.7 million adults in the US alone — and no app addresses it. Productivity tools assume you can feel time passing. For ADHD brains, that assumption is broken. We built Drift to make the invisible visible.

What it does

Drift is an Apple Watch + iPhone experience that tracks chronoception — your subjective perception of time. Using biometric signals your Watch already captures (HRV, heart rate, movement, wrist raises), Drift detects three temporal states:

Flow — time compresses
Neutral — clock matches feeling
Drag — time stretches

It calculates how long your day actually felt versus how long it was, surfaces patterns over weeks and months, and delivers gentle nudges during hyperfocus episodes before you lose an entire evening.

How we built it

We designed entirely in Figma. We used Figma Slides for the presentation deck and Figma Make for the interactive prototype. The design language references Apple Health's visual patterns (swim lane charts for daily view, stacked bars for trends) to feel native and familiar. We wrote a detailed design system guideline, created screen-by-screen build prompts, and iterated through multiple rounds of style fixes to achieve visual consistency across prototype screens spanning Watch and iPhone.

Challenges we ran into

There were so many random problems that we ran into. Fundamentally, we struggled in defining the different types of states, and what the philosophy of this app is. We first assumed in the beginning that the flow state is good and drag state is what we want to avoid. But after doing some research, even by the original author of the 'Flow' concept, we came to conclusion that being on any state is totally fine, and this app is just there to mirror our state mainly. We were also thinking the method of analyzing the chronoception the user is feeling, and the formula for the time they feel without having to manually enter. We were also discussing whether we should make the user manually put their perceived time, because it is what they actually thought of about the time so it is 100% accurate. But we thought that ADHD people will not bother too much time manually responding to every prompt for their activities. We were thinking how we can solve the problem that ADHD people are having, without breaking the philosophy of the Flow and the time states that our app has. Since we are not serious ADHD people, we were not sure what problems ADHD people were actually going through. Even interviewing people with ADHD people didn't solve the whole problem, because everyone had different problems with different strengths on ADHD symptom.

Accomplishments that we're proud of

I think we really went through deep thinking and problem solving while working on this project. The topic of the project itself was very unique that it was like building a project that is totally new from the zero ground.

We're also proud of:

The sensing model — no new hardware, no constant check-ins, just a new lens on data the body already generates using the formula for analyzing and how to convert them into perceived time.
The "felt time vs actual time" hero stat — that single number communicates the entire product in one glance
The hyperfocus nudge — one gentle tap that can save an evening

What we learned

Flow is not always good, so as drag. 8 hours of playing video game in flow state is not necessarily better than 1 hour of reading in drag state.

Designing for neurodivergent users requires rethinking assumptions baked into most apps:

We also learned that having solid architecture and the user flow of the app with stable brand guidelines is very important. Not just that, planning what to do with dividing up the task with the teammate is very crucial, so that we are not confused on what to work on.

What's next for Drift

The immediate next step is building a functional prototype with Apple HealthKit integration to validate the sensing model against real biometric data. We want to explore partnerships with ADHD researchers to calibrate the time-perception multipliers using clinical data.

Longer term, we see Drift enabling a new category of tools: