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AI Agent Setup - Best Practices

Jonathan Goodfellow Updated by Jonathan Goodfellow

AI Agent Configuration Best Practices

To get the best results from your AI Agent, here are some best practices you should follow. βœ…

If you are just getting started with AI Agents, we recommend that you first check out our AI Agents Overview article, here.
Writing Effective Instructions πŸ“

Be Specific About Data Collection: When defining what information to collect, include examples. The English Academy use-case example above shows how providing examples of budget ranges and course types ensures accurate data capture.

Handle Variations: Account for different ways users might express the same information. In the demo, users could say "business" instead of "business course," and the agent would still capture the correct information.

You can also check out our guide to using AI Tools to create your Instructions here

Define Clear Categories for Custom Fields: For Custom Fields in the Get User Information section, clearly define the Fields that you want to collect:

Knowledge Base Optimisation πŸ“š
You can check out our full guide to Knowledge Base Optimisation here.

Upload Relevant Content: Include comprehensive information about your business that the agent might need to reference during conversations.

Keep Information Current: Regularly update your knowledge base to ensure the agent has access to the most current information about your services.

Testing Your Setup πŸ§ͺ

Verify Data Collection: Test that the agent captures information exactly as specified in your instructions.

Check Exit Conditions: Ensure the agent exits at the right time and transfers to the correct block in your rule-based flow.

Test Integration: Verify that the collected information is properly accessible in your rule-based chatbot flow and any connected systems.

Integration with Existing Systems after the Exit condition triggers πŸ”—

Once the AI agent completes its task and hands control back to your rule-based chatbot flow, all the collected information becomes available for integration with external systems. Here are five common use cases for leveraging the gathered data:

CRM Lead Creation

Automatically create new leads in your CRM with all collected information (name, email, course interest, budget) and assign them to the appropriate sales agent based on qualification criteria.

Email Marketing Automation

Trigger personalized email sequences based on collected preferences β€” send business course information to users who expressed interest in business English, with content tailored to their budget range.

Calendar Integration

For qualified leads meeting specific criteria (e.g., premium budget range), automatically send calendar booking links or schedule follow-up calls with sales representatives.

Customer Database Updates

Update existing customer profiles with new information or create new entries, ensuring all collected data is stored for future reference and segmentation.

Real-Time Notifications

Send instant alerts to sales teams when high-value leads are identified, enabling immediate follow-up while the prospect's interest is highest.

In summary...

AI Agents provide a powerful way to enhance your chatbot with intelligent conversation capabilities while maintaining seamless integration with your existing flows. The key to successful implementation lies in:

  1. Clear Instructions: Detailed guidance on agent behaviour and data collection
  2. Proper Field Configuration: Well-defined custom fields with examples in the Instructions.
  3. Effective Exit Conditions: Clear criteria for returning to rule-based flows
  4. Comprehensive Knowledge Base: Relevant, up-to-date information for agent reference.

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