Best Practices

Follow these best practices to get the most out of your AI agents and ensure reliable, efficient automation.

🚀 Agent Deployment

Start Small, Scale Fast

• Deploy one agent at a time - Master each workflow before adding complexity
• Test in development first - Use test mode to validate behavior before going live
• Monitor performance metrics - Track success rates and execution times
• Iterate based on data - Use analytics to refine agent configuration

Configuration Management

• Use environment variables - Never hardcode API keys or secrets
• Version your configurations - Keep track of what's working and what changed
• Document custom logic - Add comments explaining business rules
• Test edge cases - What happens when data is missing or malformed?

# Good ✅
HUBSPOT_API_KEY=your-key-here
OPENAI_API_KEY=sk-...
WEBHOOK_SECRET=random-secret

# Bad ❌
hardcoded_api_key = "pk_live_12345..."

🔌 Integration Best Practices

API Rate Limits

• Respect rate limits - Most APIs have request limits (e.g., HubSpot: 100 req/10sec)
• Implement exponential backoff - Retry failed requests with increasing delays
• Use webhook queues - Buffer high-volume events to avoid hitting limits
• Cache where possible - Store frequently accessed data temporarily

Data Mapping

• Validate input data - Check that required fields exist before processing
• Transform consistently - Use standard formats (ISO dates, uppercase country codes, etc.)
• Handle null values - Provide sensible defaults when data is missing
• Log transformations - Track what data changed and why

// Good ✅
if (!lead.email || !isValidEmail(lead.email)) {
  log.error("Invalid email", { lead });
  return { status: "skipped", reason: "invalid_email" };
}

// Bad ❌
const email = lead.email; // Might be undefined
sendEmail(email); // Will fail silently

🔒 Security & Compliance

Data Protection

• Encrypt sensitive data - Use encryption at rest and in transit
• Minimize data retention - Only store what you need, delete what you don't
• Implement access controls - Use role-based permissions for team members
• Audit logs - Track who accessed what data and when

GDPR & Privacy Compliance

• Get consent before processing - Ensure users opt-in to automated communications
• Honor unsubscribe requests - Immediately stop processing when requested
• Provide data access - Users can request their data at any time
• Support data deletion - Implement "right to be forgotten" workflows

📊 Performance Optimization

Agent Efficiency

• Batch operations - Process multiple records together when possible
• Use conditional logic - Skip unnecessary steps with if/else branches
• Optimize API calls - Fetch all needed data in one request
• Set timeouts - Don't let agents hang waiting for slow APIs

Cost Management

• Monitor API usage - Track third-party API costs (OpenAI, Anthropic, etc.)
• Set budget alerts - Get notified when spending exceeds thresholds
• Use appropriate models - GPT-4 for complex tasks, GPT-3.5 for simple ones
• Cache AI responses - Reuse responses for identical inputs

🐛 Error Handling & Monitoring

Graceful Failures

• Catch and log errors - Never fail silently
• Provide fallbacks - What happens when an integration is down?
• Notify on critical failures - Send alerts to Slack/email for urgent issues
• Implement retry logic - Temporary failures shouldn't stop workflows

Monitoring Dashboards

• Track success rates - What percentage of executions complete successfully?
• Monitor latency - How long do agents take to execute?
• Set up alerts - Get notified when metrics degrade
• Review logs regularly - Look for patterns in errors and warnings

🧪 Testing Strategies

Development Testing

• Use test mode - All agents support test/sandbox environments
• Create test data - Build a suite of sample inputs (valid, invalid, edge cases)
• Manual testing first - Trigger agents manually before enabling automation
• Validate outputs - Check that results match expectations

Production Rollout

• Start with low volume - Enable for 10% of traffic first
• Monitor closely - Watch dashboards during first 24 hours
• Have a rollback plan - Know how to quickly disable if needed
• Gradual scale-up - 10% → 50% → 100% over days/weeks

👥 Team Collaboration

Documentation

• Document agent purpose - What business problem does it solve?
• Explain custom logic - Why did you configure it this way?
• List dependencies - What integrations must be working?
• Create runbooks - How to troubleshoot common issues

Access Management

• Use role-based access - Admin, Developer, Viewer permissions
• Limit production access - Not everyone needs to deploy changes
• Audit changes - Track who modified what and when
• Require approvals - Use change management for critical agents