Configure a managed employee

Choose the deployment path

Managed prompt or custom bundle

Use deploy-prompt for a first-class managed employee with presets, approvals, revisions, and cloud execution. Use the bundle deployment path when you need your own runtime, entrypoint, dependencies, or packaged code. Both paths run on Seren Cloud, but only the managed path exposes the resolved employee specification through Seren Agent.

Step 1

Deploy a read-oriented employee

Start with the narrowest useful policy. The research_monitor template is suited to research and monitoring, while workflow_agent supports action-oriented work. Tool presets select groups of capabilities; approval policy decides whether mutating publisher and MCP calls are available.

seren agent deploy-prompt --name "Earnings Monitor" --template research_monitor --tool-preset live_data,database --approval-policy read_only --model-policy balanced --prompt "Monitor quarterly filings for companies in the research queue. Summarize changes in revenue, margins, guidance, and material risks, and cite the source documents."

The model policy chooses among fast, balanced, and deep profiles. To pin a specific model instead of the platform default, list the available models with seren agent private-models list and pass its identifier with --model-id.

Step 2

Inspect the resolved specification

Inspect the managed deployment and its immutable revision history before changing it. The resolved view includes the selected presets, effective approval policy, visible resources, remote delegation allowlist, and any attached eval gate.

seren agent managed-get <deployment-id>
seren agent managed-revisions <deployment-id>

Step 3

Preview policy changes

Preview an update before applying it. Remote A2A delegation remains disabled unless the employee has an explicit origin allowlist. Entries may be complete origins or hostnames; leave the list empty when the employee should not call remote agents.

seren agent managed-preview <deployment-id> --allow-remote-agent-origin https://agents.example.com --approval-policy allow_mutations

seren agent managed-update <deployment-id> --allow-remote-agent-origin https://agents.example.com --approval-policy allow_mutations

Step 4

Require a fresh passing evaluation

An eval gate blocks scheduled and API-triggered runs unless the selected eval set has a recent passing verdict. Set the allowed result age in seconds, preview the change, then apply it. Clear the gate when it is no longer part of the employee's operating policy.

seren agent managed-preview <deployment-id> --eval-gate-set-id <eval-set-id> --eval-gate-max-age-seconds 86400

seren agent managed-update <deployment-id> --eval-gate-set-id <eval-set-id> --eval-gate-max-age-seconds 86400

seren agent managed-update <deployment-id> --clear-eval-gate

Advanced tools

Set per-tool limits when needed

Managed deployments accept --agent-config with a path to a JSON file for advanced tuning of the managed fields. Raw tool_definitions belong to custom bundle deployments: pass --orchestration-config <path> to seren agent cloud deploy. A tool definition can override its execution timeout and cap captured output without changing the global employee policy.

{
  "tool_definitions": [
    {
      "name": "fetch_large_report",
      "description": "Fetch and summarize a large report",
      "timeout_override_seconds": 120,
      "max_output_bytes": 16384
    }
  ]
}