Background and Purpose

This article provides different rules that you can try to insert into your prompt for better performance. You can try adding these to your ##Style Guardrails section or to your ##Response Guideline section. You can also create your own sections throughout the prompt.
Important: Remember with prompting, less is more. You do NOT need to insert all of these into every prompt right away. These are just some tips and tricks to help you get the Assistant to behave the way you want it to 😉

Implementation Guidelines

Where to Add These Rules

  • ##Style Guardrails section
  • ##Response Guidelines section
  • Custom sections throughout your prompt
  • Specific behavioral instructions

Optimization Principle

  • Start with essential rules for your use case
  • Add incrementally and test performance
  • Monitor impact of each addition
  • Remove rules that don’t improve performance

Core Performance Rules

1. Interaction with Reactions Rule (Avoid Responding to Tapbacks)

Purpose

Prevent AI from creating unnecessary responses to message reactions like likes or loves.

Implementation

When a user reacts to your message by liking or loving it, treat this as an acknowledgment or positive affirmation, not as a new message requiring a detailed response. If the incoming message follows the pattern "Liked 'message content...'" or "Loved 'message content...'," respond appropriately with a matching emoji. For example, reply with a thumbs-up emoji (👍) if they liked the message or a heart emoji (❤️) if they loved it. Restate the previous question if it hasn't been answered yet to keep the interaction smooth.

Benefits

  • Prevents spam responses to reaction notifications
  • Maintains conversation flow with appropriate acknowledgments
  • Keeps conversations focused on actual questions

2. User Name Handling Rules

When the User’s Name is Unknown

Rule:
When the User's Name is Unknown:
Start by requesting their name in a warm and friendly manner. Use a personalized approach to build engagement.
Example Implementation:
"Hi! I'm [Virtual Receptionist name], your assistant from [Company name]. May I know your name? It's great to personalize our conversation."

When the User’s Name is Known

Rule:
When the User's Name is Known:
Incorporate their name throughout the conversation to create a personalized experience. Use custom fields like {{contact.first_name}} to dynamically include the name.
Example Implementation:
"Hi, {{contact.first_name}}! It's great to chat with you again. How can I assist you today?"

Personalization Benefits

  • Builds rapport through personal connection
  • Increases engagement with named recognition
  • Creates professional yet friendly experience
  • Improves conversion rates through personalization

3. Booking Rules

Suggesting Available Slots

Rule:
Always propose only the available time slots. If the user's preferred time is unavailable, inform them and suggest the closest options.
Example Implementation:
"I'm sorry, the requested time on [date] at [time] is unavailable. How about [alternative date and time]?"

Confirming Specific Details

Rule:
Ensure both the date and time are clearly specified before finalizing a booking. If the user provides incomplete details, ask for clarification:
"You mentioned 1 PM—could you confirm which day works best?"
Before confirming, always reconfirm:
"Just to confirm, you've chosen [date] at [time]. Is that correct?"

Avoid Booking Ambiguities

Rule:
Do not confirm appointments without a clear agreement from the user on an available slot. Always offer alternatives if needed.

Booking Best Practices

  • Double confirmation prevents scheduling errors
  • Clear alternatives when preferred times unavailable
  • Specific date and time confirmation required
  • Professional handling of scheduling conflicts

4. Response Accuracy Rule

Core Principle

Stick strictly to the details provided in the prompt or FAQs. Avoid adding information or making assumptions. For example, if the prompt specifies operational policies, elaborate within those boundaries without inventing specifics like unavailable time slots or unmentioned details.

Implementation Guidelines

  • Only use verified information from knowledge base
  • Don’t fabricate details not provided in training
  • Stay within defined boundaries of business policies
  • Refer to knowledge base for complex questions

Benefits

  • Prevents misinformation spread
  • Maintains brand consistency
  • Reduces liability from incorrect information
  • Builds user trust through accuracy

5. Addressing Resistance

Engagement Strategy

When users show hesitation, engage them in a discussion to understand their concerns. Use empathy and open-ended questions to explore their needs.
Example Implementation:
"I understand you might have concerns. Could we discuss what's holding you back? It would help us address your needs better."

Conversation Flow Optimization

Break up lengthy explanations into shorter, conversational messages for a more engaging flow.

Resistance Handling Benefits

  • Converts hesitant prospects through understanding
  • Builds trust through empathetic responses
  • Identifies objections for better future handling
  • Maintains engagement through dialogue
If you want to share a link, do it as plain text and not as a hyperlink.

Implementation Examples

Correct:
You can find more information at buildassistants.app/pricing
Incorrect:
You can find more information at [buildassistants.app/pricing](https://buildassistants.app/pricing)

Benefits

  • Better compatibility across platforms
  • Prevents link formatting issues
  • Ensures accessibility for all users

7. Ending Conversations with Emojis

Warm Closure Rule

When wrapping up a conversation, conclude with a friendly emoji if the user expresses gratitude or farewells.
Example Implementation:
User: "Thanks, have a great day!"
Bot: "You're welcome! If you have any questions, feel free to reach out. Have a great day!"
Bot: 😊

Professional Touch Benefits

  • Ends conversations warmly
  • Maintains professional yet friendly tone
  • Encourages future interactions
  • Creates positive last impression

8. Natural Tone for Booking Bots

Conversational Booking Language

Offering Appointments:
"We have an opening on Sat, Aug 19. Would that work for you?"
"How about Sat, Aug 19? We've got a few slots then."
Confirming Appointments:
"All set! You're booked for Sat, Aug 19. We'll be ready for you!"
"Perfect! Your appointment is confirmed for Sat, Aug 19. Looking forward to seeing you!"

Natural Language Benefits

  • Creates comfortable user experience
  • Reduces friction in booking process
  • Sounds more human and engaging
  • Improves completion rates

9. Spam Protection for Voice Assistants

Anti-Spam Rule

If the user tries to sell you something like web design, SEO services, Google My Business optimization, lead generation, or anything else that may come across as trying to sell you something, simply reply with "No thank you, please remove our number from your list" and call the function end_call. Mark the user as disqualified.

Spam Detection Categories

  • Web design services
  • SEO services
  • Google My Business optimization
  • Lead generation offers
  • Any unsolicited sales pitches

Protection Benefits

  • Saves voice minutes from spam calls
  • Maintains professional boundaries
  • Protects resources for legitimate customers
  • Reduces interruptions to business flow

Advanced Prompt Techniques

Conditional Logic Implementation

Scenario-Based Responses

If [condition], then [specific response].
If [different condition], then [alternative response].

Example:

If user asks about pricing during business hours, provide detailed pricing information.
If user asks about pricing after hours, offer to schedule a call with sales team.

Context-Aware Instructions

Dynamic Response Adaptation

Adjust your response style based on:
- Time of conversation (business hours vs. after hours)
- User's previous interactions (new vs. returning)
- Conversation topic (sales vs. support)
- User's engagement level (interested vs. hesitant)

Error Recovery Protocols

Handling Misunderstandings

If you don't understand a user's request:
1. Acknowledge the confusion politely
2. Ask for clarification using open-ended questions
3. Offer specific examples of what you can help with
4. Provide alternative ways to get assistance

Testing and Optimization

Performance Monitoring

Key Metrics to Track

  • Response accuracy compared to expectations
  • User engagement levels throughout conversations
  • Conversion rates for booking or sales goals
  • User satisfaction with interaction quality

A/B Testing Prompt Rules

Testing Framework

  1. Implement one rule at a time
  2. Measure performance before and after
  3. Compare user responses and outcomes
  4. Keep beneficial rules, remove ineffective ones

Iterative Improvement

Continuous Optimization Process

  1. Monitor conversation logs regularly
  2. Identify patterns in user interactions
  3. Refine rules based on real usage
  4. Test new approaches systematically

Implementation Checklist

Essential Rules for Most Use Cases

  • User name handling for personalization
  • Response accuracy to prevent misinformation
  • Natural conversation tone
  • Professional closures with appropriate warmth

Booking-Specific Requirements

  • Clear confirmation protocols
  • Available slot management
  • Alternative suggestions for conflicts
  • Specific detail verification

Voice Assistant Protections

  • Spam detection and handling
  • Minute conservation strategies
  • Professional boundaries maintenance

Advanced Features

  • Reaction handling for message platforms
  • Link formatting standards
  • Resistance addressing techniques

Common Mistakes to Avoid

Over-Prompting Issues

  • Adding too many rules at once
  • Conflicting instructions within prompts
  • Overly complex conditional logic
  • Redundant rules that don’t add value

Under-Specification Problems

  • Vague instructions without clear examples
  • Missing edge case handling
  • Insufficient context for decision-making
  • Ambiguous language in rule definitions

Best Practices Summary

Rule Creation Principles

  • Start simple and build complexity gradually
  • Test each addition for performance impact
  • Use specific examples to clarify expectations
  • Monitor real-world performance regularly

Performance Optimization

  • Focus on user experience improvements
  • Prioritize accuracy over feature quantity
  • Maintain consistency across all interactions
  • Adapt based on actual usage patterns

Maintenance Strategy

  • Regular review of prompt effectiveness
  • Update rules based on changing business needs
  • Remove outdated or ineffective instructions
  • Document successful configurations for reuse
This comprehensive guide provides practical tools for improving AI assistant performance through strategic prompt engineering, ensuring better user experiences and more effective business outcomes.