A city that explains itself.

Meaning comes from structure.

Port of Veracruz live operations in .me
Port of Veracruz — live operations
3 ships, 1 train and 500 trucks on a real OSM map.
ships["[i]"]["="]("hasWork", "remaining > 0") trucks.unit["[i]"]["="]("working", "state > 1") Operations · Veracruz A headway decision on GTFS-Madrid-Bench: routes, trips and frequency windows around the decided factor, next to the decision card
AI decides, .me computes
If Madrid's buses came 10% more often, which routes would get too tight? The AI picks the change; .me recomputes only what it touches and shows why.
policy.factor(0.9) win["="]("tight", "headway < policy.minHeadway") Decisions · Madrid Cross-section of an anthill: ants carrying seeds through tunnels between chambers
Ant City
Scouts find trees, lay trails home and recruit ant to ant. Trail weights and the queen live in .me.
ants[3].carry(1) colony["="]("food", "chambers.pantry.stock + chambers.granary.stock") Simulation · Colony A city grid at night: sidewalk robots on the streets, drones over the blocks, traffic lights at the crossings, parcels arriving at homes
City Delivery
Sidewalk robots and drones deliver parcels. Flip a light or close a street and only the ETAs that depend on it recompute; a customer sees only their own order.
couriers["[i]"]["="]("eta", "dist / speed + next.wait") city["="]("delivering", "couriers[].delivering") Live · this.me@4.2.1 Six colonias of a city at night: bin sensors with fill bars, waste robots on the streets, a recycling depot in the middle
Self-Cleaning City
Bin sensors and waste robots in six colonias. A bin fills and only its colonia recomputes; each colonia sees only its own bins.
colonias["[i]"]["="]("avgFill", "colonias[i].bins[].fill / colonias[i].bins[]") colonias["[i]"]["="]("fullN", "colonias[i].bins[].full") Live · this.me@4.2.1 Madrid GTFS as .me dependencies
GTFS Madrid — semantic graph
Real GTFS → reactive dependencies. Mutate and watch k; technical graph of stops, routes and trips as live .me paths.
Technical · Madrid Madrid fares in .me
Madrid knowledge — fares
Same city, human story: fares, abono, Sol→Atocha. Mutate → dependents + explain() without the GTFS machinery.
Human · Madrid Hospital as Smart Cities infrastructure node
Hospital — infrastructure node
City hospital tables as live dependencies: pin Raha/Baran dirty/clean, keep derived checks after correction. Domain funnel — not a data-quality paper page.
Infrastructure · Hospital
mlearning.studio
Datasets GTFS BigDaMa
me.whatever(what)
Write Syntax Derived
me.explain()
Example Fields Cutoff

Related

Hemisphere Scale benchmark
Hemisphere Scale
How the kernel holds up at 1,000,000+ nodes — the reactive scale behind the city demos.
 Extreme Fan-Out benchmark
Extreme Fan-Out
One write, many dependents. Plus GTFS-Madrid measured: k stays flat as VIG grows the data 100×, the fan-out skew run, the known weaknesses, and how to reproduce.
 Line drawing of an isometric slab
Docs
The .me documentation: what .me is, primitives, paths, me.explain(path), O(k), demos and tests.
 O(k) chart: latency vs n with k fixed
Benchmarks
O(k) scaling, throughput, fan-out, cold/warm, explain overhead, secret-scope cost.