Engineering

Human-in-the-Loop for AI Agents

When should AI agents ask for permission? Implementation patterns for approval workflows, escalation rules, and oversight mechanisms.

Veto TeamJanuary 28, 20268 min

The most effective AI agents know when to ask for help. Human-in-the-loop systems let agents operate autonomously while escalating important decisions.

When to Escalate

escalation_criteria.pypython
from veto import Veto, Policy

veto = Veto(api_key="veto_live_xxx")

# Define escalation rules
veto.register_policy(
    name="approval_workflow",
    policy=Policy(
        tool="send_email",
        rules=[
            Policy.allow_if(recipients_lte=5),
            Policy.require_approval_if(recipients_gt=5),
            Policy.require_approval_if(domain="external"),
        ]
    )
)

# Configure notification channels
veto.configure_notifications({
    "email": "approvals@company.com",
    "slack": "#agent-approvals",
})

Approval Workflows

Veto supports multiple approval patterns:

  • Single approver — Any authorized user can approve
  • Multi-party approval — Requires N approvers for high-risk actions
  • Time-based — Auto-deny if not approved within timeframe

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