Marketing autopilot

marketing-autopilot — run the loop on its own

The loop self-improves only if it keeps turning. This driver turns it. The hard part — a published video must mature ~48–72h before its metrics mean anything — is handled by the engine (studio/marketing/loop.py): it's a state machine over time, so each tick does the single action that's actually due, never blindly publish→measure in one go.

One tick = ask the engine, do the one due action

studio marketing tick --channel <name> --json

Returns the next action with everything you need:

next	what to do (agent-driven)
measure	studio marketing measure --channel <name> — measure_due videos have matured
learn	invoke marketing-measure-learn (its learn step: reflect → strategy); enough new measurements accrued
ideate	invoke marketing-ideate (web-search + recall → bets); backlog is low
produce	invoke marketing-deploy for produce_entry at produce_max_cost
idle	nothing due — sleep until the next tick (maturation / cadence wait)

Do that ONE action, then tick again. Prefer the lego-block skills for the creative steps (ideate/learn/produce) so the thinking is yours; measure is deterministic.

Running it continuously

Pick a cadence (ticks every few hours are plenty — the engine gates the real timing):

• Agent-driven (smartest): use the /loop skill to re-invoke this skill on an interval, or /schedule to register a cron routine. Each firing: tick --json → do the due action.
• Headless (no agent): studio marketing autopilot --channel <name> [--produce] does one tick using the SCRIPTED ideate/learn fallbacks. Producing spends money + publishes, so it's gated behind --produce. Wire it to cron for fully unattended operation.

Before first run — configure the channel

studio marketing budget --channel <name> --per-minute 0.40   # or --per-video 0.60  (sizes --max-cost)
studio marketing tick   --channel <name>                     # see what it would do

Cadence/maturation knobs live in Journal.loop (maturation_hours 60, min_hours_between_produces 20, daily_produce_cap 2, learn_every 3, backlog_min 2, target_duration_s 60) — edit runs/_marketing/<name>/journal.json to tune.

Cold-start

While < 10 videos are deployed the engine/ideate stay in exploration (diverse bets); it won't over-exploit a baseline that doesn't exist yet. Measurement still runs, but outcomes read cold-start until the portfolio is big enough to rank.

Memory

Reads the whole journal to decide; each delegated step writes its own slice. learn stamps last_learn_at; link stamps published_at (the maturation clock). Memory model: docs/50-marketing/memory.md.