01
It reads the company.
From the name and the work email, before anyone has installed anything. Who their users are, what those people are into, and what the product actually is. A company we have never heard of gets a board written for their users on day one instead of a generic city calendar in their colours.
A model call, once per company, stored on the row.
02
It reads their design language.
It opens their real site and reads it the way a designer would: what the page is made of, what type they set, how round a corner is, whether cards are outlined or filled, and how they write. The tab renders in that, so it looks like their own team built it rather than like a widget someone pasted in.
Their site, parsed for design tokens, then judged by a model.
03
It reads each person.
A ring says early riser. A running app says runner. Those are different strings, so two people who both get up and run at dawn used to match on nothing. The agent reads each person once and writes down what it understands about them in one shared vocabulary, and everything downstream runs on that instead of on whatever words a third party API happened to choose.
Refreshed on a schedule, not once at signup.
04
It writes things people actually want to do.
This is the part that is hard, and the part everything else is in service of. A model told to write for a sleep company writes about sleep, and you get a seminar with the seats taken away. The rule is that the activity has to be good with the company name removed, and the fit shows in the hour and the place instead: what makes a gathering right for people who wake at five is that it is at six in the morning and everybody there also wakes at five. The test is whether somebody would text it to a friend in those words.
Checked at the point of writing, not asked for in a prompt.
05
It programs the week.
Real gatherings, at free public walk-in places, written for that company’s people in that company’s voice. Nothing is reserved and nobody is billed for a room, which is why it can program a city it has never touched on the day a company signs up.
Runs every six hours, for every company, unprompted.
06
It learns from who turned up.
Every run reads that company’s own past board first: which shapes of gathering filled, which drew nobody twice, which hours worked. That goes in as evidence rather than as a rule, because a model is better at "these three filled and these two did not" than at any rule we could invent about a stranger’s users.
Arrivals once there are enough of them, commitments until then.
07
And from what each person did on a Saturday.
Tags describe somebody the way their device sees them. Turning up describes them the way a Saturday does, and where the two disagree the Saturday is right. Two people with identical tags used to get an identical board forever, however differently they had behaved. Now an arrival counts for more than a yes, a yes counts for more than nothing, and the hour somebody genuinely leaves the house beats any tag claiming to know their rhythm. It reorders their board and never filters it, so the worst it can do is put something last.
Three passes before anything is demoted, and one arrival outranks five.
It takes no for an answer.
The company can pull any gathering off their own board before it happens, and say why. That refusal is not weighed against how well the idea polled, it is obeyed: the agent never writes anything of that shape again, and a reworded version of it is refused at the point of writing rather than only in the prompt. It is the one control they get, and it exists because handing an agent your brand and hoping is not a thing anyone should have to do.
Reversible, and nothing is ever deleted.