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OperatorNest

More than one operator, working in parallel

OperatorNest lets you run multiple AI agents, called operators, each with its own role, memory and permissions, such as one for research and one for your inbox. Each runs in its own cloud workspace, so a two-hour research task on one never queues behind a five-minute inbox digest on another.

How the work moves

  1. Starts when

    You create a new operator and give it a role, such as inbox or research.

  2. Uses

    Only the tools, accounts and files you connect to that specific operator.

  3. Asks you before

    The same approval rules as any operator, set separately for each one.

  4. You get

    Each operator's own results, delivered separately from the others.

  5. On the record

    A separate task history and receipt trail for every operator you run.

On this page

One operator per job

You don’t have to funnel every task through a single generalist operator. Set up several, each scoped to a role: for example, one for inbox triage and follow-ups, one for research, and one for scheduling and admin. Each works independently, in its own workspace, with its own memory and its own access.

A small team gets built the same way: a few people, each with a clear remit and exactly the access their job requires.

What splitting by role looks like

A small operations setup might run three operators: an inbox operator that triages messages and drafts replies, a research operator that handles recurring competitor and market briefs, and a scheduling operator that manages meetings and follow-ups. Each gets only the access it needs. The inbox operator doesn’t need your research sources, and the research operator doesn’t need to send emails.

That scoping is a control. An operator with narrower access is simpler to reason about and needs less oversight, because there’s less it could get wrong.

Working in parallel

Each operator runs in its own cloud workspace, so they never wait for the same turn. A research operator can be two hours into a background task while your inbox operator finishes a five-minute digest and your scheduling operator holds a meeting request for your approval. You check in on each separately, and none of them waits on the others.

That’s separate work happening at the same time, not one operator switching contexts.

Separate memory, separate permissions

Each operator keeps its own memory by default. Your research operator doesn’t know what your inbox operator has learned about a client’s tone preferences, and your scheduling operator doesn’t carry research context it doesn’t need. If you want two operators to share some context, you set that up deliberately.

The same goes for approvals: rules are set per operator and per task, so an operator that can send client-facing emails can carry stricter approval requirements than one that only reads and summarizes.

Naming and organizing operators

Each operator gets its own name, such as “Research” or “Inbox”, so it’s clear at a glance which one you’re talking to or reviewing. You can rename an operator, adjust its role and access, or retire it without affecting the others.

Keeping track of several operators at once

Every operator has its own task history and its own receipts, so you can review one without wading through another’s activity. Your morning check-in can cover all of them at once: what the inbox operator handled overnight, what the research operator’s weekly brief found, and what the scheduling operator has waiting for approval.

A concrete example

A small consulting firm might run an executive-assistant operator for scheduling and travel, and a separate research operator for client briefs. The executive-assistant operator has access to calendars and booking sites and asks for approval before it confirms anything. The research operator has access to reference material and the web and never touches billing or accounts, so it runs comparisons and drafts on its own with fewer approvals. Each shows up separately in your day, with its own history, and neither one’s access widens to cover the other’s job.

When one operator is enough

Plenty of people run a single, well-rounded operator for everything, and that’s a reasonable way to work. Splitting by role tends to pay off once the access, the volume of tasks, or the need to keep work separate, like client-facing versus internal, makes one generalist operator harder to trust or to review at a glance.

Common questions

Why would I want more than one operator?

Splitting work by role keeps each operator focused. An inbox operator with only email access is simpler to reason about than one operator with access to everything, and you can review each one's work separately.

Do operators share memory or access with each other?

Not by default. Each operator keeps its own memory and only the access you've given it, so your research operator doesn't carry details from your inbox operator unless you set that up.

Can operators work on tasks at the same time?

Yes. Each runs in its own workspace, so a research task on one operator and an inbox digest on another run at the same time.

Can I give operators different approval rules?

Yes. Approval settings are per operator and per task, so you can be stricter with one that has broader access and looser with one that's narrowly scoped.

How many operators can I run?

There's no requirement to run more than one. Add a second or third operator when splitting work by role helps, such as separating client-facing tasks from internal ones.

Hand off your first task tonight.

Tell us your email and what you'd hand off first. We'll send your access details and help you set up your operator.