Role

Product & UX Designer

Research through UI, solo

Timeline

{{ tallaTimeline }}

Complete

Tools

Figma · FigJam · Maze

Prototype linked below

Platform

iOS

iPhone, native patterns

03 · The problem

Getting dressed is a decision with no obvious first step.

People do not lack clothes. They lack a place to start. Most styling apps answer this by showing more, more inspiration, more feeds, more options which is the same problem in a nicer typeface.

Talla had to do the opposite. Narrow fast, decide once, and end the session rather than extend it.

04 · Who it is for

People deciding in the two minutes before they leave.

Not people browsing for pleasure. The design assumes a short session, on the one hand, and a person who already owns the clothes on screen or wants a personalized shopping experience.

That assumption decided nearly everything downstream: how many taps the flow gets, how much the AI is allowed to ask, and what happens when it is wrong.

Before drawing anything I walked six competing apps end to end and recorded, for each, how long it took to reach one decided outfit and where the flow lost me.

The pattern held across all six: every app was built for browsing, and none of them had an ending. That produced the single requirement: the rest of the design hangs off the flow; the flow must terminate.

Stated plainly: this is a competitive benchmark, not moderated user testing. The full analysis is below so you can check it.

A component library, not a page of screens.

Every repeated element in Talla is a component with defined states, spacing and type styles. Building the library first is what let the flow change three times without the screens falling apart.

• ·Named tokens for colour, type and spacing, so a change happens in one place.
• ·Every component documented with its states, not just its default.
• ·Built to iOS conventions throughout — native controls, sheets and navigation.

• Slate 900 #0F172AApp shell, header, navigation
• Cool Grey #6B7280Secondary text, descriptions, metadata
• Violet #7C6EE6Primary CTA, AI highlights, selected states
• Gray 200 #E5E7EBBorders, dividers, input outlines
• Light Grey #F1F5FDDividers only

The library itself, at real values

128 component sets and 196 variables. These are the ones the outfit flow leans on — rebuilt here from the Figma file, not screenshotted.

Onboarding — six questions, then it starts working

Every step is skippable and the progress bar never lies about how much is left. Answers narrow the first generation; none of them block it.

Answer first beats questions first.

Test: unmoderated task in Maze, both versions, measuring time to a decided outfit and drop-off before the first suggestion.

People will correct a wrong suggestion rather than abandon it.

Test: seed a deliberately poor first suggestion and watch whether people adjust, reroll, or leave.

The ending is what brings people back.

Test: a short diary study over two weeks, tracking whether sessions that reached a decision predict a return.

Role

Product & UX Designer

Research through handoff

Timeline

{{ careTimeline }}

Complete

Tools

Figma · FigJam

Annotated specs and tokens

Standard

WCAG 2.1 AA

Designed to, and checked

03 · The problem

Childcare is built on trust, but trust is hard to verify.

Parents rely on recommendations, scattered information, and manual communication before making one of their most important decisions.

CareNest puts that information on the first screen and makes the slot itself the thing you tap.

04 · Who it is for

Designed for busy families.

Working parents and single parents who need a faster, safer, and more transparent way to find childcare.

This is why CareNest puts trust first through verified profiles, transparent pricing, and simple booking.

Annotated specs and tokens, handed over.

The library is the deliverable, not a by-product of it. Each component carries its states, its spacing tokens and its accessibility rules in the same place a developer would look for them.

• ·Tokens for colour, type, spacing and radius, mirrored across both scripts.
• ·Annotations covering focus order, target size and error text.
• ·Every state documented — default, active, disabled, error, empty.

Typography, spacing, radius and elevation, documented as tokens and bound to variables. Scroll the type sheet for all 46 styles.

Would AI-recommended caregivers outperform manual browsing?

A/B testing comparing the current search flow against an AI-powered recommendation flow to measure which leads to more completed bookings.

If parents finding the information they need directly from caregiver cards

First-click testing to evaluate whether users can confidently select a caregiver without opening multiple profiles

If parents complete a booking without confusion

Prototype usability testing using a high-fidelity Figma prototype to identify friction points before development.

Role

Product & UX Designer

Flow through UI, solo

Timeline

2026

One month, solo

Tools

Figma · FigJam

Components and states

Platform

iOS

iPhone, native patterns

01 · The problem

In Cairo, the short trip is the expensive one.

Two kilometres across the city can cost more in time and money than the distance deserves. Traffic makes a ten-minute journey unpredictable, and the cheap options are not convenient while the convenient ones are not cheap.

A bike covers that distance well. What stops people using one is not the riding — it is everything around it: finding a station, trusting that a bike is there, and not knowing what the ride costs until it is over.

02 · Who it is for

People making the same trip every day, not tourists.

Students, young professionals and daily commuters moving a few kilometres at a time. They are price-sensitive, in a hurry, and often using a service like this for the first time.

That set the bar for every screen: someone who has never rented a bike before should finish the whole rental without asking anyone how it works.

Battery level decides which bike people pick, more than price does.

Test: an unmoderated choice task with battery and price varied independently across the station list.

A first-time user can unlock a bike without help.

Test: five people at a real station, no instructions, measuring where they hesitate and how many reach for the manual code.

An itemised total is questioned less than a single one.

Test: two summary variants, asking people to explain what they were charged for and whether the amount feels fair.

The problem with trip planning today

Planning happens in eleven tabs and ends in a notes app.

Flights in one place, stays in another, the actual itinerary written by hand somewhere neither of them can see. Every tool is good at its slice and none of them holds the plan.

The interesting question is not whether AI can draft an itinerary. It is what a person is willing to hand over, and what they insist on deciding themselves.

My part

Competitive research and survey design for the trip planning product. I build the persona pack from real respondent data and check every AI-drafted trait back against the raw transcripts before it is allowed into the pack.

Cleared for publication. Respondents are anonymised — names and ages are pseudonyms.

Early direction

Draft the plan, keep the edit cheap.

The direction I am arguing for is a plan the product drafts in full and the person edits in place — no wizard, no chat transcript to scroll back through. The AI's job is the first draft, not the conversation.

What comes next

Close the survey, then design against it.

Survey closes and the persona pack is finalised, then the first flows go up here alongside the research that produced them.

next → early flows, {{ flyDate }}

About

Sarah Hammad

Product & UX Designer, Cairo

I design booking, planning and scheduling products — the ones people open when they are tired and want the thing handled. I work in Arabic and English, right to left and left to right, and I tend to start with the task a person is trying to finish rather than the interface they will finish it in.

How I got into design

I studied Business Administration. That is not the usual route into UX, and I have stopped treating it as a gap. It is the reason I ask what a product is for before I ask what it looks like, and the reason I am comfortable in the conversation where a design decision has to survive someone else's constraints.

The design part I learned by doing it, project by project, and by writing down what went wrong each time.

What I am still learning

I care more about whether it works than whether it wins an award.

Which is a nice line, and also the thing I have to keep proving. The honest gap right now is moderated user testing — I have run heuristic evaluations and surveys, and I have not yet sat behind enough people using the thing. That is the next skill I am closing.

Tools

Figma · FigJam · Maze

Languages

Arabic, native · English, professional

CV

Email

sarahhammad776@gmail.com