The language
written by AI,
for AI.

use http
use db

type User
  id:    Id
  name:  Text
  email: Email          -- semantic type: validated at the boundary

intent "serve the user API with health checks"
flow main
  http.serve(port: 8080)
    route GET  "/health"    -> { status: "ok", uptime: sys.uptime() }
    route GET  "/users/:id" -> db.find(id) ? http.not_found
    route POST "/users"     -> create_user(body)

flow create_user(u: User) -> User
  expect u.name.len > 0
  ensure result.id != Id.none
  db.insert(u) ? retry(3) ? fail

use ai
use web

intent "summarize any webpage into three sharp bullet points"
flow summarize(page: Url) -> [Text]
  ensure result.len == 3
  let doc = web.fetch(page) ? retry(3) ? fail
  ai.complete(
    model:  "claude-fable-5",
    prompt: "Summarize in exactly 3 bullets:\n{doc.text}",
  ) |> lines |> take(3)

flow main
  let pages = args() |> map(Url.parse) ? skip
  spawn for page in pages          -- all pages, concurrently
    summarize(page) |> each(print)

use csv
use stats

type Reading
  sensor: Text
  value:  Float where self >= 0.0   -- refinement type
  at:     Time

intent "clean sensor data and report anomalies per sensor"
flow main
  let readings =
    csv.load("sensors.csv") ? skip   -- bad rows just drop out

  let report = spawn readings
    |> group_by(.sensor)
    |> map_values(detect_anomalies)

  for (sensor, anomalies) in report
    print("{sensor}: {anomalies.len} anomalies")

flow detect_anomalies(xs: [Reading]) -> [Reading]
  let mean = xs |> map(.value) |> stats.mean
  let dev  = xs |> map(.value) |> stats.stddev
  xs |> filter(abs(.value - mean) > 3.0 * dev)