Controlled Operator Systems

Give your AI a job, a budget, and a boss.

I install one controlled decision-and-action loop around work your company already repeats. No general-purpose AI employee. No unlimited authority. One workflow, explicit boundaries, and proof from the outside system.

Workflow readiness

Operator Readiness Score

Score all six dimensions
Repetition

Does the same signal trigger this decision every week or every day?

Reliable inputs

Can the operator read the source data through an API, export, inbox, or event?

Decision clarity

Can a competent person explain when to ignore, recommend, ask, act, or stop?

Authority

Can you define automatic, approval-required, and forbidden actions?

Recoverability

Can mistakes be contained with caps, a kill switch, or rollback?

External proof

Can another system confirm the action actually happened?

The system

An operator is not finished when it says “done.” It is finished when the outside system proves it.

A defined job

One recurring signal, one decision policy, one action surface, and one measurable outcome.

Bounded authority

Automatic, approval-required, and forbidden actions—with money, volume, and impact caps.

A real receipt

Platform IDs, CRM events, published URLs, before-and-after state, and owner briefings.

Already operating

Start custom—or use an operator I already built.

Founding offer

Start with the Blueprint.

For $750, I map one workflow into a complete operator specification and fixed implementation scope. If you build within 30 days, the Blueprint price is credited toward the founding Sprint.

Score and map my workflow
  • Workflow and readiness map
  • Signal and decision contracts
  • Authority matrix and caps
  • Failure, rollback, and kill-switch plan
  • Acceptance tests and fixed implementation SOW

Founding implementation hypothesis: $5,000 for one tightly bounded workflow. Managed Ops begins at $1,000/month. Complex, regulated, or high-risk workflows require custom scope.

Proof standard: Operator demonstrations are labeled production, pilot, sandbox/testnet, or simulation step by step. The June 2026 ad demonstration used a Base Sepolia testnet settlement and a labeled stand-in creative; it proves the controlled loop, not production mainnet procurement or improved campaign performance.

Open-source attribution: Some implementations use Hermes Agent by Nous Research, independent open-source software not owned by Connor Gallic. The paid work here is workflow architecture, safeguards, integrations, verification, and implementation—not a license to or ownership claim over Hermes.

Fixture / simulation / mechanism proof

I tested a Lead Operator with six leads. Five correct results were non-actions.

See the approval packet, cap, blocked cases, simulated receipt, failure drill, and the exact line between what the fixture proves and what it does not.

Open the proof