Skip to main content

Overview

This guide is designed to help you craft effective prompts for CallHQ Voice AI agents. You’ll learn how to structure, iterate, and optimize prompts to ensure accurate, human-like responses and high task completion rates.

Why Prompt Design Matters

Prompt design is the foundation of how your voice agent behaves. A well-structured prompt:
  • Guides the AI toward precise, context-aware responses
  • Reduces the need for human fallback
  • Increases success rate for automated workflows
Poorly written prompts often result in confusion, misinterpretation, and user frustration.

Measuring Success

A good prompt drives a high completion rate — the percentage of conversations that reach a successful outcome without requiring human intervention. Iterate on prompts to raise this success metric over time.

Prompt Engineering Workflow

Follow this iterative process:
1

Design

Create an initial version of the prompt with clear goals and instructions, tailored to the agent’s task and use case.
2

Test

Simulate conversations and observe how the agent responds to different inputs. Record gaps or unexpected behavior.
3

Refine

Adjust the prompt to add clarity, improve flow, and handle edge cases based on what you observed.
4

Repeat

Continuously test and refine the prompt until responses are consistent, helpful, and aligned with user expectations.

Principles of effective prompts

Organize prompts into sections

Break down system prompts into clear sections, each focused on a specific aspect:
  • Identity: Define the agent’s persona and role
  • Style: Set stylistic guidelines (conciseness, tone, humor)
  • Response guidelines: Specify formatting, question limits, or structure
  • Task & goals: Outline objectives and steps
Example:
wordWrap

Break down complex tasks

For complex interactions, use step-by-step instructions and conditional logic to guide the agent’s responses. Example:
wordWrap

Control response timing

Explicitly indicate when the agent should wait for the user’s response before proceeding. Example:
wordWrap

Integrate tools and APIs

Specify when and how the agent should use external tools or APIs. Reference tools by their designated names and describe their functions. Example:
wordWrap

Silent transfers

If the AI determines that the user needs to be transferred, do not send any text response back to the user. Instead, silently call the appropriate tool for transferring the call. This ensures a seamless user experience and avoids confusion.

Include fallback and error handling

Always include fallback options and error-handling mechanisms in your prompts. This ensures the agent can gracefully handle unexpected user inputs or system errors. Example:
wordWrap

Additional tips

  • Iterate as much as possible. AI is driven by experimentation and iteration—refining prompts through trial and error will help you achieve more precise, relevant, and effective responses.
  • Use Markdown formatting: Structure your content for clarity and easy scanning.
  • Emotional prompting: Use expressive language to shape the AI’s tone and create more engaging, relatable responses. For example, “Can you tell me a cozy bedtime story that’s warm and comforting?”
  • Add voice realism: Incorporate natural speech elements like stuttering, hesitations, and pauses:
    • Stuttering: Use repeated letters or sounds (e.g., “I-I-I don’t know”).
    • Hesitations: Add fillers like “uh,” “um,” or “well” (e.g., “I was, uh, thinking about it”).
    • Pauses: Use ellipses (”…”) to indicate a pause (e.g., “I… I don’t know how to say this”).
    • Emotional emphasis: Use capital letters, exclamation marks, or ellipses to reflect tone (e.g., “I can’t… I just can’t believe it!”).

Common issues

Numbers sound robotic?
  • Spell out numbers in prompts for more natural-sounding speech.
How to make assistants sound more human-like?
  • Add personality and tone to the assistant. For example:
    wordWrap

Example: Appointment setter prompt

wordWrap

Additional resources

Check out these additional resources to learn more about prompt engineering: