What is orchestration in an AI system?
Orchestration is the layer that decides what runs, in what order, and what happens when a step fails. It owns retries, timeouts, ordering, and the record of what already ran. Every system has one, whether it was designed or whether it emerged as a cron job calling a script that calls three more.
What runs, in what order, and what happens when a step fails.
Why it matters to you
The question worth asking about any orchestration layer is where the state lives. If a run half completes, what does the system know? A layer that records each step as it finishes can resume. One that does not has to start again, which is how a retry turns into a duplicate.
The aarttsii outreach system splits this deliberately into two planes that never talk directly and share only a database. A reasoning session on one machine finds, scores, drafts and schedules. A deterministic service on the VPS polls for jobs whose time has come, marks each job as it goes, and posts a confirmation per send. The intelligence and the irreversible action are in different processes on purpose.
That split is also what makes the failure behaviour describable. When the sending half has no judgement in it, there is nothing to debug about why it decided to send.
Where this turns up in something OCTYN runs
Each line carries the date it was recorded and where it came from.
- 2026-09-14
Two planes sharing one database and nothing else: a reasoning session that drafts and schedules, and a stdlib-only service that sends
docs/growth/case-studies/aarttsii.md, section 3 - 2026-09-14
Failed profiles go to a reprocess queue rather than stopping a crawl, because rate limits and blocked requests are expected rather than exceptional
docs/growth/case-studies/whofits.md, section 5WhoFits →
- stack
- TwitterAPI.io · Playwright · Ollama qual gate
- surface
- Workspace-OS dashboard · private
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