The AI workforce manager for teams on Neuro OS
Stop babysitting agent output — coordinator owns work through verified done: machine checks, review, labeled self-report, daily brief.
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AI made you the bottleneck
Teams adopt AI; output volume doubles; founders spend the same hours on review and re-checking. Tools generate — they do not manage to finished.
Neuro OS coordinator role is the AI workforce manager: assigns, sequences, unblocks, verifies, briefs.
Manager vs tool
| Tool | Manager on Neuro OS |
|---|---|
| Executes prompt | Owns outcome to done |
| Stops when model finishes | Checks acceptance criteria |
| You discover blockers | Surfaces blockers + options |
| Thread archaeology | 2-minute daily brief |
How “done” is decided
- Machine verification — tests pass, endpoint 200, numbers reconcile
- Review — second role or human against brief
- Self-report — only as labeled fallback
What reaches you is finished, not “agent said done.”
Built for teams
Whole team on org chart; coordinator routes across people and roles; one company pricing model; steady state in ~2 weeks — brief replaces morning scramble.
Related: First AI hire blueprint · Chief of staff · Agent collaboration protocol