AI Agents · Lesson

Human-in-the-Loop Approval Gates

Pause-request-approve patterns for high-stakes agent actions.

Human-in-the-Loop Approval Gates is a free AI Agents lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the AI Agents learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

When Agents Need Human Approval

For high-stakes actions — sending a contract, deleting production data, spending budget, sending a public announcement — an agent should not act autonomously. It should pause and request human approval before proceeding.

This is the Human-in-the-Loop (HITL) pattern.

Defining High-Stakes Actions

Define a classification function that identifies which actions require human approval. The threshold can be tuned per deployment based on risk tolerance.

HIGH_STAKES_ACTIONS = {
    'send_email',
    'delete_records',
    'publish_content',
    'transfer_funds',
    'modify_production_config',
    'export_all_data',
    'send_push_notification_to_all'
}

HIGH_STAKES_THRESHOLDS = {
    'transfer_funds':    1000,    # USD — require approval above this
    'delete_records':    10,      # rows
    'send_email':        50,      # recipients
    'push_notification': 1000     # users
}

def requires_approval(action: str, parameters: dict) -> bool:
    if action not in HIGH_STAKES_ACTIONS:
        return False
    threshold = HIGH_STAKES_THRESHOLDS.get(action)
    if threshold is None:
        return True   # all instances require approval
    # Check parameter against threshold
    amount = parameters.get('amount') or parameters.get('count') or 0
    return float(amount) >= threshold

if __name__ == '__main__':
    print('Small transfer:', requires_approval('transfer_funds', {'amount': 200}))
    print('Large transfer:', requires_approval('transfer_funds', {'amount': 5000}))
    print('Publish content:', requires_approval('publish_content', {}))

Creating an Approval Request

When approval is required, the agent creates an approval request record and suspends execution. The request includes a description of what will happen, the parameters, and a deadline.

import uuid, time

approval_requests: dict[str, dict] = {}   # approval_id -> request

def create_approval_request(agent_id: str, user_id: str, action: str,
                             parameters: dict, timeout_minutes: int = 30) -> str:
    approval_id = str(uuid.uuid4())
    approval_requests[approval_id] = {
        'approval_id':  approval_id,
        'agent_id':     agent_id,
        'user_id':      user_id,
        'action':       action,
        'parameters':   parameters,
        'status':       'pending',     # pending / approved / rejected / timed_out
        'created_at':   time.time(),
        'expires_at':   time.time() + timeout_minutes * 60,
        'decided_by':   None,
        'decided_at':   None
    }
    return approval_id

if __name__ == '__main__':
    approval_id = create_approval_request(
        'agent-1', 'user-42', 'delete_records', {'count': 50}
    )
    print('Created approval request:', approval_id)
    print('Status:', approval_requests[approval_id]['status'])

Notifying via Slack

Send the approval request to the approver via Slack. Include a summary of what the agent wants to do, a link to approve or reject, and the timeout deadline.

import requests

SLACK_WEBHOOK = 'https://hooks.slack.com/services/YOUR/WEBHOOK/URL'
APPROVAL_BASE_URL = 'https://your-agent-dashboard.com/approvals'

def notify_approver_slack(approval_id: str, approver_slack_id: str):
    req = approval_requests[approval_id]
    import time as t
    from datetime import datetime
    expires = datetime.fromtimestamp(req['expires_at']).strftime('%H:%M UTC')

    payload = {
        'text': f'<@{approver_slack_id}> Agent approval required',
        'attachments': [{
            'color': '#ff9900',
            'fields': [
                {'title': 'Action',      'value': req['action'],    'short': True},
                {'title': 'Requested by','value': req['user_id'],   'short': True},
                {'title': 'Parameters',  'value': str(req['parameters'])[:200]},
                {'title': 'Expires',     'value': expires,          'short': True}
            ],
            'actions': [
                {'type': 'button', 'text': 'Approve',
                 'url': f'{APPROVAL_BASE_URL}/{approval_id}/approve'},
                {'type': 'button', 'text': 'Reject',
                 'url': f'{APPROVAL_BASE_URL}/{approval_id}/reject'}
            ]
        }]
    }
    requests.post(SLACK_WEBHOOK, json=payload)

Notifying via Email

As a backup channel (or primary for organizations without Slack), send approval requests via email with clear approve/reject links.

import smtplib
from email.mime.text import MIMEText

SMTP_HOST  = 'smtp.yourcompany.com'
SMTP_PORT  = 587
SMTP_USER  = 'agent-noreply@yourcompany.com'
SMTP_PASS  = 'YOUR_SMTP_PASSWORD'

def notify_approver_email(approval_id: str, approver_email: str):
    req = approval_requests[approval_id]
    body = (
        f'An AI agent is requesting approval for:\n\n'
        f'Action: {req["action"]}\n'
        f'Parameters: {req["parameters"]}\n\n'
        f'Approve: {APPROVAL_BASE_URL}/{approval_id}/approve\n'
        f'Reject:  {APPROVAL_BASE_URL}/{approval_id}/reject\n\n'
        f'This request expires in 30 minutes.'
    )
    msg = MIMEText(body)
    msg['Subject'] = f'Agent Approval Required: {req["action"]}'
    msg['From']    = SMTP_USER
    msg['To']      = approver_email

    with smtplib.SMTP(SMTP_HOST, SMTP_PORT) as server:
        server.starttls()
        server.login(SMTP_USER, SMTP_PASS)
        server.send_message(msg)

Polling for the Approval Decision

After sending the notification, the agent waits for the decision. Use a polling loop with a short sleep interval. Stop polling when the status changes from 'pending' or the deadline passes.

import time

def wait_for_approval(approval_id: str, poll_interval: float = 5.0) -> dict:
    while True:
        req = approval_requests.get(approval_id)
        if not req:
            return {'decision': 'error', 'reason': 'Approval request not found'}

        if req['status'] == 'approved':
            return {'decision': 'approved', 'decided_by': req['decided_by']}

        if req['status'] == 'rejected':
            return {'decision': 'rejected', 'decided_by': req['decided_by']}

        if time.time() > req['expires_at']:
            req['status'] = 'timed_out'
            return {'decision': 'timed_out', 'reason': 'No decision within deadline'}

        time.sleep(poll_interval)

Recording the Approval Decision

When the approver clicks Approve or Reject, record who decided and when. This creates the full approval audit trail: requested → notified → decided → executed (or cancelled).

def record_decision(approval_id: str, decision: str,
                    decided_by: str) -> dict:
    req = approval_requests.get(approval_id)
    if not req:
        return {'error': 'Approval request not found'}

    if req['status'] != 'pending':
        return {'error': f'Request already in state: {req["status"]}'}

    if time.time() > req['expires_at']:
        req['status'] = 'timed_out'
        return {'error': 'Request has expired'}

    req['status']     = decision   # 'approved' or 'rejected'
    req['decided_by'] = decided_by
    req['decided_at'] = time.time()
    return {'ok': True, 'decision': decision}

Timeout Handling: Auto-Cancel

If no decision arrives within the timeout window, the agent automatically cancels the action and notifies the original requester. This prevents actions from being permanently blocked by unresponsive approvers.

def handle_timeout(approval_id: str, agent_session: dict) -> str:
    req = approval_requests.get(approval_id, {})
    action  = req.get('action', 'unknown')
    user_id = req.get('user_id', 'unknown')

    # Log the timeout
    import logging
    logging.warning(
        'Approval timeout: action=%s user=%s approval_id=%s',
        action, user_id, approval_id
    )

    # Tell the user
    timeout_message = (
        f'The "{action}" action was automatically cancelled because '
        f'no approver responded within the 30-minute window. '
        f'Please request again or contact your administrator.'
    )
    return timeout_message

Full Approval Gate Orchestration

Combine all steps: check if approval is needed, create request, notify, wait, then either proceed or cancel based on the decision.

def execute_with_approval_gate(agent_id: str, user_id: str, action: str,
                                parameters: dict, approver_email: str,
                                execute_fn) -> dict:
    # Step 1: Check if approval needed
    if not requires_approval(action, parameters):
        result = execute_fn(action, parameters)
        return {'approved': True, 'auto': True, 'result': result}

    # Step 2: Create approval request
    approval_id = create_approval_request(agent_id, user_id, action, parameters)

    # Step 3: Notify approver
    notify_approver_email(approval_id, approver_email)
    print(f'Approval requested: {approval_id}. Waiting...')

    # Step 4: Wait for decision
    decision = wait_for_approval(approval_id)

    # Step 5: Act on decision
    if decision['decision'] == 'approved':
        result = execute_fn(action, parameters)
        return {'approved': True, 'decided_by': decision['decided_by'], 'result': result}
    elif decision['decision'] == 'rejected':
        return {'approved': False, 'reason': 'Rejected by approver'}
    else:
        msg = handle_timeout(approval_id, {})
        return {'approved': False, 'reason': msg}

Approval Audit Trail

Every approval lifecycle event must be recorded in the audit log: request created, notification sent, decision made, action executed or cancelled. This trail is required for SOC 2 compliance.

import logging, json, time

approval_logger = logging.getLogger('agent.approvals')

def audit_approval_event(event: str, approval_id: str, details: dict):
    entry = {
        'timestamp':   time.time(),
        'event':       event,
        'approval_id': approval_id,
        **details
    }
    approval_logger.info(json.dumps(entry))

# Usage flow:
# audit_approval_event('request_created', approval_id, {'action': 'delete_records', 'user': 'u123'})
# audit_approval_event('notification_sent', approval_id, {'channel': 'email', 'approver': 'admin@co.com'})
# audit_approval_event('decision_received', approval_id, {'decision': 'approved', 'by': 'admin@co.com'})
# audit_approval_event('action_executed',  approval_id, {'result': 'success'})

if __name__ == '__main__':
    import sys
    approval_logger.setLevel(logging.INFO)
    approval_logger.addHandler(logging.StreamHandler(sys.stdout))
    audit_approval_event('request_created', 'appr-1', {'action': 'delete_records', 'user': 'u123'})

Escalation When Primary Approver is Unavailable

If the primary approver does not respond within half the timeout window, escalate to a secondary approver. This prevents all approvals from blocking on a single person being out of office.

def escalate_if_needed(approval_id: str, secondary_email: str,
                        escalation_at_pct: float = 0.5):
    req = approval_requests.get(approval_id)
    if not req or req['status'] != 'pending':
        return

    total_window  = req['expires_at'] - req['created_at']
    elapsed       = time.time() - req['created_at']
    escalation_at = req['created_at'] + total_window * escalation_at_pct

    if time.time() >= escalation_at and not req.get('escalated'):
        req['escalated'] = True
        notify_approver_email(approval_id, secondary_email)
        print(f'Escalated approval {approval_id} to {secondary_email}')

What happens to a pending approval request when the timeout expires?

The timeout handling behavior is a critical part of HITL design. Choosing the wrong default has different consequences for safety and usability.

Human-in-the-Loop Approval Gates Recap

HITL approval gates work by: classifying high-stakes actions, creating a suspended approval request, notifying approvers via Slack/email, polling for decisions, auto-cancelling on timeout, and recording every lifecycle event in the audit trail.

Escalation to secondary approvers prevents approval deadlocks due to unavailability.

Frequently asked questions

Is the “Human-in-the-Loop Approval Gates” lesson free?

Yes — the full text of “Human-in-the-Loop Approval Gates” is free to read here on the web, and the AI Agents course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the AI Agents course, upgrade to CoddyKit PRO.

What will I learn in “Human-in-the-Loop Approval Gates”?

Pause-request-approve patterns for high-stakes agent actions. You practise AI Agents with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start AI Agents?

No prior experience is required. AI Agents on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Human-in-the-Loop Approval Gates” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

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