Human-on-the-Loop (HOTL)
Monitor AI agents in real-time with the ability to intervene when needed.
What is HOTL?
Human-on-the-Loop (HOTL) is a governance pattern for continuous monitoring. Agents run autonomously while humans observe and can intervene if issues arise.
When to Use HOTL
- Production Monitoring - Watch live agent behavior
- Anomaly Response - React to unusual patterns
- Gradual Rollout - Monitor new agent versions
- High-Volume Systems - Where HITL isn't practical
- Learning Phase - Build trust in new agents
Enabling HOTL
Via SDK
from turingpulse_sdk import instrument, GovernanceDirective
@instrument(
name="trading-agent",
governance=GovernanceDirective(
hotl=True,
escalation_channels=["slack://trading-alerts"],
severity="high",
)
)
def execute_trade(symbol: str, quantity: int):
return trading_service.execute(symbol, quantity)Via UI
- Navigate to Governance → Policies
- Click Create Policy
- Select Human-on-the-Loop (HOTL)
- Configure alert channels and thresholds
- Save and enable
HOTL Alerts
HOTL generates alerts when:
- Anomalies Detected - Unusual behavior patterns
- Error Spikes - Sudden increase in failures
- Threshold Breaches - KPIs exceed limits
- Drift Events - Behavior changes detected
Intervention Options
| Action | Description |
|---|---|
| Acknowledge | Note the alert, continue monitoring |
| Investigate | Drill into affected runs |
| Pause | Temporarily stop the workflow |
| Escalate | Notify additional team members |
| Create Incident | Open formal incident |
HOTL Configuration
| Option | Description |
|---|---|
hotl | Enable HOTL governance |
escalation_channels | Where to send alerts |
severity | Default alert severity |
reviewers | Who receives alerts |
Combining with Controls
HOTL works best when combined with:
- KPI Thresholds - Define what triggers alerts
- Drift Detection - Monitor for changes
- Anomaly Rules - Detect outliers
- Alert Channels - Route notifications