The setting
's is cloud software that manages a restaurant's website, online ordering, customer records, point of sale, fulfillment and kitchen work. It serves restaurant owners and their guests.
One checkout currently carries the work of several people choosing lunch.
Individual control over meal choices competes with the organizer’s need to finish one predictable order.
Who you’d be doing this for
“The office next door sent a screenshot of twelve lunches, then called to change three. We hadn't even started cooking.”
Akosua Okafor · Restaurant owner · a character in this brief
Runs a lunch restaurant that receives weekly orders assembled by nearby office organizers.
What is at stake
Eight of 12 lunch organizers describe correcting someone else’s meal choice. You decide how shared contributions become one order worth using again.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- participant control vs organizer certainty
- live collaboration vs stable checkout
- first-use appeal vs repeated utility
- new capability vs existing simplicity
Why Owner
Online ordering and branded apps already carry restaurant identity, but group organizers still assemble other guests’ choices outside that experience.
Written with these in mind
Not your kind of problem? 20 more at Owner, or browse every organization.
Where the organization context comes fromThe postings this brief was written from, and the reporting read before it.
The organization context comes from public information. The situation and characters are written for the brief.
Job postings it was written from
Public descriptions of the work at Owner. They are listed as sources, not as openings. The lines under a posting are its own words, where it meets this brief.
- Head of Design, Consumer (opens in a new tab)
- AI-native practitioner who prototypes, designs in code, and has shipped AI-powered product experiences.
- Set the design vision across online ordering, native mobile apps, loyalty, and lifecycle engagement.
- Staff Product Designer (opens in a new tab)
- Senior Product Designer (opens in a new tab)
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.
Where similar work appears
Other live briefs connected to this one, and what connects them.
Similar problems at other organizations
Like this one, each of these turns on easing someone in at the cost of understanding.
Shared-basket sessions edit and abandon 14% more often than comparable household baskets.
You have to weigh collaborative input against a clear final purchaser and a manageable first version.
Four of six proposed experiments would invite overlapping groups of local service businesses.
You have to weigh a shared decision point against sponsors’ need to test different ideas without another approval queue.
Repeat household riders are rebuilding familiar trip details and abandoning requests when plans change.
You must weigh a faster repeat path against a home screen that still works for everyone.
The same setting, from another role
Each is set around Owner’s Owner AI-native restaurant platform, written for a different role. They’re separate briefs, not the same scenario.
Owners cannot tell whether a payout difference is pending, refunded, or missing after service.
You have to weigh a fast daily read against financial detail people can trust.
Multi-location operators cannot see which locations are losing repeat direct guests or why.
You must weigh a useful first retention view against definitions operators and Finance can both trust.
Several owners changed promotions or hours after recommendations missed local operating context.
You have to weigh immediate protection for live restaurants against the evidence needed to improve the recommendation loop.
Other problems with a similar purpose
In each of these, as in this one, the aim is to turn a person's earliest brush with a product into a habit they keep coming back to.
Sixty-two percent of newly activated workspaces do not return for a second production session within 21 days.
You must weigh a scalable configuration-and-enablement path against a simpler setup change that uses the same capacity.
New enterprise accounts are starting tables but not returning to run a second workflow.
You have to weigh a fast activation path against a promise that still feels safe for RevOps.
New desktop users are skipping iOS setup and staying in a single-device inbox habit.
You need to decide how prominently mobile setup belongs before users reach their first inbox.
