Live briefs
Only one way to find out.
A live brief drops you into a decision an organization is actually facing. You won’t have everything you need. Someone will push back. You call it anyway, using whatever you already know how to do.
Some people finish one and think “I could do this.” Some realize they’d hate it. Some find out it’s harder than it looked, or easier than they feared. All of that is worth knowing before you spend a year on it.
Your first one is free. No card.
1,927 live right now across 76 organizations.
Take a turn in one right now, without an account.
A real situation
Built from what the organization is publicly working on. There’s money or a deadline behind it, and nobody has solved it for you.
People who push back
A customer, a colleague, someone senior who wants something else. They read what you write and answer it.
The call is yours
You decide, then defend it while someone argues back. You keep whatever comes out of it. Nobody grades it.
Open one.
Trace fail-safe causes before onsite evidence disappears
Fail-safe events are consuming onsite testing time because the evidence points to competing causes. You must decide what AI can assemble and what engineers must confirm before a fix ships.
Turn field notes into sourced CRM next steps without AI promising buyers
Account prospects are receiving follow-ups that miss the cash-flow problem they described in person. You have to weigh faster CRM capture against keeping every merchant detail and promise under seller review.
Stop double-counted purchases in attribution when schemas change
Schema-driven duplicates are reaching downstream shopping metrics even when aggregate checks pass. You must decide what AI flags on its own and what an engineer must verify before holding data.
Flag the suspect rows in ads data before downstream models use them
A quality alert is reaching engineers after a dashboard or ML input has already used the affected run. You must weigh faster evidence gathering against keeping every data hold under engineer review.
Run deployment fixes to the gate before regressions lose their window
A known Kubernetes deployment failure keeps pushing scheduled simulation regressions past their window. You must choose what AI can classify and run, and where an engineer must take over.
Structure discovery before proposals inherit missing answers
Partner-led opportunities are reaching proposal reviews with missing ownership and governance answers. You must decide what AI extracts, what sellers verify, and how source evidence stays attached.
Reading them won’t tell you.
Run your first brief, freeBrowse by organization
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