Takes an outcome, not just a prompt
Describe the result you need — a researched brief, a built file, a completed analysis. Operator breaks it into steps and works the plan instead of waiting for you to choreograph every move.
The Execution Agent
OperatorGive it an outcome. Operator researches, builds, and finishes the work — with evidence.
Operator is Super Amplify's execution agent. Where a chat gives you an answer, Operator carries a job through: it investigates sources, works across your tools and AiOS data, creates real deliverables, checks its own work, and reports back with proof of what was done — under your permissions and approval rules the whole way.
Who it's for
- Operators and chiefs of staff drowning in multi-step follow-through
- Teams that need research, documents, and analysis actually finished, not drafted
- Anyone who delegates work and wants evidence back, not just activity
Product demo
Watch Operator in action
A real delegation, end to end: the brief, the run, the approval moment, and the evidence that comes back.
Demo video coming soon
We're recording a walkthrough of Operator. Want to see it live in the meantime?
A real delegation, end to end: the brief, the run, the approval moment, and the evidence that comes back.
Product demo · Watch at your own pace
What Operator does for you
The execution agent that finishes multi-step work
Works across your real tools
Operator uses governed AiOS operations, connected tools, browsing, and file work in one run, so a single delegation can span research, data, and deliverable creation.
Verifies before it declares done
Runs pass through verification gates and completion evidence, so you review results and proof — not a confident summary of work that may not have happened.
Stays inside your guardrails
Operator inherits your role, company policies, and approval settings. Consequential actions pause for a human; blocked actions stay blocked.
How Operator works, step by step
Delegate the outcome
State what done looks like: the deliverable, the sources to trust, the deadline that matters. The clearer the definition of done, the better Operator performs.
Operator plans and executes
It discovers the operations and tools it is entitled to use, works the steps, and keeps a durable record you can follow while it runs.
You approve what matters
Approval-required actions surface in the confirmation rail with context, so human judgment lands exactly where the risk is.
Review the evidence
You get the deliverable plus the trail behind it — sources, actions, and verification — so trusting the result takes minutes, not re-doing the task.
From 'can you look into this?' to a finished, sourced brief
Anonymous professional services leadership team
Leaders kept commissioning the same kind of work — market checks, account research, first-draft analyses — and getting back either a shallow chat answer or nothing, because nobody had the hours to carry a multi-hour task to completion between meetings.
The team started delegating those jobs to Operator with an explicit definition of done: the questions to answer, the sources to prefer, and the format to deliver. Operator researched, assembled the brief inside their AiOS context, and returned it with sources and evidence for a partner to review.
Work runs under your company's identity, permissions, and approval policies — with Super Amplify's SOC 2 Type I and Type II audited controls behind it.
What changed
Recurring research and first-draft work came back finished and sourced instead of stalling in someone's queue
Reviewers checked evidence and conclusions rather than redoing the research to trust it
Leaders delegated more, because the cost of asking dropped to writing a clear definition of done
Try this playbook yourself
- 1Pick one recurring multi-hour task — a weekly research brief, an account summary, a first-pass analysis — and write its definition of done on one page: questions, trusted sources, format.
- 2Run it once side-by-side: a person and Operator, same brief. Compare where each spent time. The gaps tell you what context or access Operator needs.
- 3Add your approval rule before you scale: which actions Operator may take alone, and which always pause for a person.
- 4Keep a simple log for two weeks of what you delegated, what came back usable, and what needed rework. That log, not enthusiasm, should decide what you delegate next.
The honest takeaway
Operator's first runs were only as good as the briefs it received. Vague delegations produced vague work, quickly and at scale. The teams that got the most from it invested in clear definitions of done and approval boundaries up front — the same discipline that makes human delegation work.
Anonymized example based on real Super Amplify delivery patterns. Outcomes depend on scope, data quality, and team readiness.
Metrics worth tracking
Hours from delegation to a reviewable deliverable
Percentage of Operator deliverables accepted with light or no rework
Reviewer time per deliverable, which should fall as your definitions of done improve
Delegate your first job to Operator
Bring one real workflow. We'll show you Operator on your own context — what it does, how it works, and where the human stays in charge.