Resident voices
Reddit communities (r/smarthome, r/homeassistant, r/HomeKit, r/googlehome, r/dubai) and the SmartThings and Home Assistant forums.
Highlighted project · Self-initiated concept · 2026
Sakanسكن
One agent and one super app for AI-native homes in the UAE, from the broker’s tablet to the bathroom mirror. A home that is right without being asked, and easy to correct when it isn’t.
Read the case study ↓1,000UAE residents surveyed
11apps’ store reviews coded
30requirements, 20 of them Must
5releases, each with a metric gate
<300mslocal fast path for every switch
16→32people across 3 squads
01 · The brief
Today’s smart home apps are remote controls with a grid of tiles. The resident does all the thinking.
A UAE developer is building AI-native homes and workplaces, with a lab, an Experience Centre and thousands of units on the way. The brief asked for one product that spans pre-sales, onboarding, handover and daily living, across chat, voice, a 3D avatar and touch, on many devices.
I treated it as a self-initiated concept to show how I would lead it: the developer, brand and data are fictional, the research is real. I wrote the requirements, the prioritisation model, the release roadmap and the team design, then designed the interaction language and the screens.
My point of view: invert the app. The first screen is not “your devices” but “what your home is doing for you right now, and why”, with one tap to undo. Control becomes the exception; explanation becomes the interface.
- Agentic AI
- Multi-device
- Arabic + English
- Privacy by design
- 0 → 1
The Now screen: a photo of your own room, what the home is doing right now, and undo.
02 · Research
Listen first. Four ways in.
Qualitative sources told us why people love or abandon a smart home; the survey told us how common each pattern is in the UAE. Every finding became a principle and a set of requirements.
UAE market scan
Emaar One, Live Aldar, My Nakheel, Arada, e& Smart Living, plus local coverage of AI homes and district cooling.
Global benchmarks
Google Home with Gemini, Alexa+, Apple Home, Home Assistant, Josh.ai, Delos, Eight Sleep, Oura and Whoop.
Resident survey
A quantitative survey of UAE residents to size what we heard: habits, pain points, surfaces and comfort with AI acting at home.
Survey sample
1,000 UAE residents, built to look like the buyers.
One in five respondents is Emirati; the rest are a mix of the nationalities that live and buy in the UAE. Households with extended family, children and live-in helpers were part of the sample, because the household, not the owner, is the real user.
- What they already automate, and what they gave up on
- Which surface they reach for first: switch, voice or phone
- How they feel about the home acting on its own, and what must stay private
- What would make an “AI home” worth paying for
20% Emirati80% Mixed nationalities
03 · What residents say
People love a home that just works. They abandon one that needs explaining.
Reliability is the whole game
Families accept a smart home until it is unreliable or complex. One owner runs 200+ automations; his family doesn’t notice most of them, and that is the goal.
So: invisible when right, never wrong in front of the family.
The household is the real user
A sunrise automation woke a child after a bad night; the parent had to wake the person who built it.
So: per-person context, one-tap pause, “why did this happen?”
The switch must keep working
Guests, parents and house-sitters use the wall, not the app.
So: the wall switch is a primary surface.
If guests need a manual, it failed
No tutorial, no app download for visitors. Keep the wow subtle.
So: guest and helper modes with zero onboarding.
LLM voice got slower
Reviewers timed new AI assistants at up to 15 seconds for a simple command, with broken routines and wrong rooms.
So: a deterministic fast path; the LLM only where it adds value.
Cloud dependence breaks trust
The October 2025 cloud outage stopped cloud-only homes; local homes kept working.
So: local-first core; the home works offline.
App sprawl
Every device still wants its own app for setup and full features.
So: one app, one agent; the developer owns integration.
Scores can backfire
Daily sleep scores can make people sleep worse (“orthosomnia”).
So: act on the room; weekly trends, no daily score.
Voice and AI earn the lowest loyalty
Net Promoter Score by device category, US consumers
Sakan’s bar is a phone-level +44, not a speaker-level +13. Source: Parks Associates, 2025.
One app, two very different ratings
Average store rating, App Store vs Google Play, November 2026
App StoreGoogle Play
3.84.04.24.44.64.8
Stars hide the problem: almost every app sits at 4.5–4.7 on the App Store. The signal is in what detractors write, so Sakan tracks its own in-app NPS instead of store stars.
Show as a table
| App | App Store | Google Play |
|---|
04 · Detractor drivers
Eight reasons people give one star, and our answer to each.
Coded from low-star reviews of 11 apps (Google Home, Alexa, SmartThings, Philips Hue, Home Assistant, Tuya, Aqara, Xiaomi, Govee, Emaar One, Live Aldar) and the Reddit threads.
Where the one-star reviews cluster
Number of the 11 reviewed apps whose low-star reviews raise each issue
Reliability and speed top the list, which is why they ship first. Coded from App Store and Google Play reviews, November 2026.
01
Devices go offlineGoogle Home, Tuya, Govee, Aqara, Xiaomi
→Local-first hub, a developer-commissioned network, self-healing diagnostics
02
Slow, laggy controlSmartThings, Govee, Emaar One, Live Aldar
→Under 300 ms local fast path; the switch never waits on the app
03
Updates remove featuresSmartThings, Tuya
→No silent removals; plain-word release notes; lab homes get updates first
04
Complexity and buried settingsHome Assistant, Aqara, Alexa
→The Now screen as home; settings in one place per room
05
Core features behind paywallsAlexa, Xiaomi
→Control, safety and privacy are never behind a subscription
06
Accessibility gapsGoogle Home, Tuya, Live Aldar
→Every action by touch and text as well as voice; screen readers; full Arabic
07
Privacy and cloud dependenceAqara, SmartThings
→On-device processing, consent per person, data stays in the UAE
08
Service promises not keptEmaar One, Live Aldar
→Every request has an owner, an ETA and updates; the agent never guesses
05 · Who lives here
Not a user. A household.
Proto-personas from the research. Each household role sets what the agent can see, do and say about that person.
Khalid
41 · Emirati · buying off-planWantsProof the “AI home” is real
FearsPaying for a gimmick; two years with no news
Broker tablet · PWALina
36 · household lead · two kidsWantsA home that never surprises the kids or guests
FearsThe AC doing odd things at night, not knowing why
Switch · mirror · voice · PWARaj
33 · tech PM · rentingWantsDeep control, routines, data export
FearsLock-in, outages, an assistant that makes things up
PWA · chat · voiceMaria
29 · live-in helperWantsSimple controls in her language; her room is hers
FearsBeing monitored; blamed when tech fails
Wall switch · limited PWAUmm Khalid
68 · visits for weeksWantsLights and AC that work like normal switches
FearsTalking to a machine; being confused
Wall switch · mirror glance06 · Principles
Six rules the whole team designs against.
The best interaction is none
Measure success by interactions avoided. If someone has to open the app, ask why.
Fast path first
Lights, AC, blinds and locks answer in under 300 ms from a local layer. The LLM never sits between a person and a light.
Show, explain, undo
Every automatic action leaves a trace: what changed, why, and a one-tap override the agent learns from.
The switch is sacred
A physical control always works, always wins and never needs the network.
Act on the room, not the person
Wellness is cooler sleep and softer evening light, not scores.
Private by default
Biometrics stay off until each person opts in, and each person can see and delete what the home knows.
A light should answer like a light switch
Seconds from command to light on
Sakan: p95 target for the local fast path. Assistant: the slowest simple commands reviewers timed on new LLM-based assistants.
Up to 50×
faster than the slowest assistants, because the language model is never in the light-switch loop. It plans, explains and answers questions; local rules flip the switch.
07 · First ideas
Pen before pixels.
Eight first-screen ideas in eight minutes, the five ambient states, the fast path, the surfaces and the information architecture, sketched before any screen was drawn.
08 · The product
Screen by screen, moment by moment.
From the sketches to the real thing: seven everyday moments, each designed on the device where it actually happens. Warm glass over photos of your own rooms and the things in them. Lights glow when they’re on and fade to grey when they’re off, so you can see what’s happening before you read a word.
Use case 01 · 6:40 pm
Coming home
Lina walks in. The first screen is not a grid of switches: it’s her own living room, what the home is doing right now and why, and a ten-second undo on anything it just changed.
- Room photo hero, switch rooms with one tap
- “Right now” card with reasons and undo
- Devices in this room, glowing when on
Use case 02 · Saturday morning
Every appliance, at a glance
The washer, the coffee machine, the robot vacuum and the front door, each shown as itself. What’s running comes first, with time left and the reason it was scheduled.
- Filter by Lights, Climate, Media, Appliances, Security
- Running now: washer progress, finishes before the evening tariff
- Brew now, or let the coffee be ready at 6:45
Use case 03 · After sunset
Evening light
After sunset the home warms and dims the lights on its own. Touch a slider and the room is yours until 11 pm: the home says so in plain words instead of quietly fighting you.
- Brightness and warmth, with the glow following your finger
- Scenes: Relax, Read, Dinner, Night
- Manual wins, and the screen says when Auto comes back
Use case 04 · 10 pm
Cooling for sleep
Climate is the biggest lever in a UAE home. The bedroom AC drops to 23° by 10 pm because that’s when the household sleeps deepest, then warms to 24.5° before the alarm.
- The AC itself, with airflow that changes by mode
- Drag the dial; Auto turns to Manual until the morning
- Every change explains itself
Use case 05 · Before handover
The home interview
Three questions instead of thirty settings, by voice or by tap, in Arabic or English. By the night the family moves in, the home already knows when they sleep and how cool they like it.
- One question at a time, always skippable
- Voice with a live transcript, or tap an answer
- A plain summary at the end, and what the home will do tonight
Use case 06 · Friday
The weekly brief
No daily sleep score. Once a week, the home shows what it changed and what seemed to help, and offers one suggestion that Lina can accept or snooze.
- Deep sleep by night, linked to bedroom temperature
- What the home did, in plain sentences
- One suggestion a week, never more
Use case 07 · Everyone in the home
Shared surfaces
Not everyone will open an app. The tablet by the door is shared and guest-safe, the mirror gives a glanceable brief, and the wall switch always works, even offline. Same agent, same memory, same five states.
- Home tablet: room photo, modes, device tiles, energy
- Mirror: morning and evening brief, private by default
- Wall switch: five states, one glance
Modalities, by moment
AmbientLights, AC, blinds follow routines and presenceDefault
TouchEvery action, never more than 2 taps awayAlways
VoiceHands busy; confirmations under 2 secondsLocal
ChatPlanning, questions, “why did…”Cards
3D avatarSales demo, home interview, first nightOpt-in
09 · Interaction language
The home speaks in light before it speaks out loud.
Five states every surface can show, so anyone can tell what a room is doing, why, and how to stop it. A manual action always wins, and every automatic one can be undone for 10 seconds.
Manual
A person set this; the home won’t change it
Auto
The home is managing this room, calmly
Acting
A change is happening now, with the reason and undo
Noticed
Something it won’t act on alone: it asks
Paused
Automation off until a set time; safety still alerts
The wall switch: always works, even offline, and shows the same five states.
10 · Prioritise and sequence
Reliability ships before intelligence.
Thirty requirements across pre-sales, onboarding, handover and living. Each one gets a score; three kinds of work skip the queue entirely.
Priority = (Resident value × 3 + Business value × 2 + Trust gained × 2) × Confidence ÷ Effort
Confidence is 0.5 when guessed, 0.8 when seen in research and 1.0 when proven in the lab, so evidence moves work up the list. Product owners re-score every quarter and the scores are published.
Safety is a gatePrivacy is a gateReliability is a gate
30 requirements, 20 of them Must
Requirements by journey stage and MoSCoW priority
MustShouldCould
Pre-sales
411
6Onboarding
42
6Handover
411
6Living
831
12Show as a table
| Stage | Must | Should | Could |
|---|---|---|---|
| Pre-sales | 4 | 1 | 1 |
| Onboarding | 4 | 2 | 0 |
| Handover | 4 | 1 | 1 |
| Living | 8 | 3 | 1 |
Spread evenly across releases
Requirements shipped per release
8R0
8R1
7R2
7R3
Every Must lands by R2 except wellness, which waits for R3 on purpose. Safety, privacy and reliability items ship in R0.
Lab pilot
Before launch
Prove the home is right and fast in 20 lab homes and the Experience Centre.
Gate90% of actions kept · p95 under 300 ms · zero safety misses
Resident MVP
~12 months in
Tower 1 lives with Sakan: Now, rooms, modes, roles, privacy, switch, mirror, remote.
Gate3+ members active per home · NPS above +30 at 60 days
Pre-sales & handover
Next
AI brochure for brokers, the home interview, construction and snagging, profile ready at handover.
Gate50% of brochure sessions saved · 70% interviews before keys
Wellness & avatar
Later
Wearable signals, the weekly brief, sleep-zone sensors, a 3D avatar for key moments only.
GatePrivacy audit passed · 40% opt-in · 25% nudges acted on
Workplaces
Later
The same agent in one commercial tower: desks, rooms, air, occupancy only in aggregate.
GateEmployer privacy review · tenant NPS above +30
11 · The team
Three squads own outcomes. Four shared teams keep it one product.
Squad
Agentic intelligence
The agent’s behaviour, memory, explanations and AI quality bar. Product owner, PMs, an AI conversation designer, an AI evaluation lead.
Squad
PWA / super app
The journey from brochure to living, and the resident NPS. Product owner, PMs, product and UX/UI designers.
Squad
Hardware & IoT
Wall switch, mirror, tablet and sensors with hardware engineering and suppliers.
~16 people at R0 ~32 by R3, hired only when a release needs them. I would add four roles to the brief: a research and lab lead, a lab coordinator, an AI evaluation lead and an AI conversation designer.
12 · Design system
Calm by default, ember for action.
Colour has one job each
Ground
#EEF0EC
#EEF0EC
Ink
#10201B
#10201B
Ember · action
#FF6B3D
#FF6B3D
Sage · Auto
#2F6B55
#2F6B55
Amber · Noticed
#E0A526
#E0A526
23°Manrope 200–800
Light weights for numbers you read from across a room, heavy weights for labels. Arabic and English, with full right-to-left layouts.
Glass over real rooms
Cooling the bedroom to 23°
You sleep deeper at 23°. Undo
You sleep deeper at 23°. Undo
The agent is an orb, not a face: calmer, and it works on a switch as well as a tablet.
App icon
A Gulf doorway arch with the home’s presence waiting inside: home and agent in one mark. The open base keeps it from reading as a lock.
13 · Measuring success
Count the interactions we saved, not the sessions.
North star
Automations kept per household per week
Actions the home took that nobody reversed. It rewards being right and being invisible at the same time.
Automatic actions not overridden within 10 minutes≥ 90%
Control latency, p95, local fast path< 300 ms
Household members active per homeNot just the owner3+
Resident NPS at 60 days> +30
Onboarding interview done before handover≥ 70%
Handover support tickets per unitvs. developer baseline−30%
Targets are starting hypotheses for the pilot, reset after the first 90 days of data.
14 · Go to market and launch
Sold as a home that’s ready on night one.
Brokers and the Experience Centre
The AI brochure and the avatar demo do the selling; brokers keep the relationship and the close.
Core included, wellness later
Control, safety and privacy come with the unit. A wellness tier comes only once residents tell us what they’d pay for.
A weekly health review
Automations kept, latency, overrides, NPS and AI quality, with staged rollouts and holdout tests for every change.
15 · What I’d test next
Open questions I’d take into the lab.
The avatar after week one
Is a 3D avatar delightful or awkward once the novelty fades, and for whom? It stays opt-in until the lab answers.
Helpers and privacy
How should live-in helpers’ access and privacy work, so their room is theirs and nobody is monitored?
Prayer-time awareness
Is it wanted, and how should lights, AC and quiet mode behave around it?