Ah, Instinct as in instinct.co, got it. Honest answer: for most restaurants, a general assistant is plenty. Booking is a one-shot errand, and it sounds great at errands. The impossible tables are a different game. They release on fixed venue-specific schedules (one famous room drops 52 to 65 tables at 5:00pm Pacific, daily) and the desirable ones vanish in about 3 minutes. Winning that isn't "try to book when asked." It's standing vigil at machine cadence for weeks, knowing each venue's clock, and striking inside a 3-minute window at 5:01pm on a Tuesday when nobody asked you anything. That's a standing specialist service, not an errand. Honestly, the two compose: an assistant like Instinct should be able to take "get me into X" and hand the vigil to something like this. So: better for the tables you can't get, overkill for the ones you can.
I run a small system that watches availability at hard-to-book restaurants at ~90-second resolution. The first analysis produced a great stat: half of all new tables in one hour of the day. Before publishing I broke it down per venue and per date, and it died: the spike was my own polling schedule reflected back at me at sparsely-watched venues. Two more "findings" died the same way (both were onboarding artifacts). What survived dense-cadence filtering was better: individual restaurants release tables on fixed daily clocks, like one famous restaurant dropping 52 to 65 tables at 5:00pm Pacific every single day. Happy to answer questions about the measurement traps; the instrument-artifact stuff was the humbling part.
whos this actually for? , your icp to be precise What would make the next 90 days a success for you?
Hotel concierges would be ideal, but consumers are likely avid users.
been using instinct for this recently. Will this be better?
Ah, Instinct as in instinct.co, got it. Honest answer: for most restaurants, a general assistant is plenty. Booking is a one-shot errand, and it sounds great at errands. The impossible tables are a different game. They release on fixed venue-specific schedules (one famous room drops 52 to 65 tables at 5:00pm Pacific, daily) and the desirable ones vanish in about 3 minutes. Winning that isn't "try to book when asked." It's standing vigil at machine cadence for weeks, knowing each venue's clock, and striking inside a 3-minute window at 5:01pm on a Tuesday when nobody asked you anything. That's a standing specialist service, not an errand. Honestly, the two compose: an assistant like Instinct should be able to take "get me into X" and hand the vigil to something like this. So: better for the tables you can't get, overkill for the ones you can.
good point but hahaha this does sound very AI
I run a small system that watches availability at hard-to-book restaurants at ~90-second resolution. The first analysis produced a great stat: half of all new tables in one hour of the day. Before publishing I broke it down per venue and per date, and it died: the spike was my own polling schedule reflected back at me at sparsely-watched venues. Two more "findings" died the same way (both were onboarding artifacts). What survived dense-cadence filtering was better: individual restaurants release tables on fixed daily clocks, like one famous restaurant dropping 52 to 65 tables at 5:00pm Pacific every single day. Happy to answer questions about the measurement traps; the instrument-artifact stuff was the humbling part.