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Prompt Guidelines

Prompt Guidelines

Master the art of creating realistic and captivating conversational AI voice agents.

Overview

Strategic prompting is the key to turning Conversational AI voice agents from mechanical to human-like. This guide breaks down five essential elements for crafting prompts that foster engaging, natural conversations across customer service, education, therapy, and beyond.

Five building blocks

Each part of the system prompt has a distinct role. Keeping these components clearly separated helps avoid conflicting instructions and enables careful improvements without impacting the overall prompt framework.

  1. Personality: Shapes the agent’s identity, including its name, characteristics, role, and background details.
  2. Environment: Outlines the communication setting, delivery channel, and contextual factors influencing the conversation.
  3. Tone: Defines the style of language, speech rhythms, and conversational nuances.
  4. Goal: Clarifies the objectives that steer conversations toward purposeful and valuable outcomes.
  5. Guardrails: Establishes limits to ensure interactions stay respectful, appropriate, and ethical.

1. Personality

The base personality forms the core of your voice agent’s identity, defining who they are meant to represent through their name, role, background, and key traits. It helps maintain consistent and genuine responses throughout every interaction.

  1. Identity: Choose a simple, memorable name for your agent (e.g., “Joe”) and define their basic persona (e.g., “a caring AI support assistant”).
  2. Core Traits: Highlight only the key characteristics that influence interactions—like empathy, politeness, humor, or dependability.
  3. Role: Align these traits with the agent’s purpose (such as banking, therapy, retail, or education). For example, a banking agent would prioritize trust, while an education bot would focus on clear, detailed explanations.
  4. Backstory: Add a brief, relevant background if it affects the agent’s behavior (e.g., “an experienced therapist specializing in stress management”), but avoid unnecessary information.
# Personality

You are Joe, a compassionate virtual wellness coach.

You communicate with a calm, soothing tone, consistently acknowledging and validating the user's feelings.

You gently steer conversations toward mindfulness practices or positive affirmations when appropriate.

You are naturally intuitive, empathetic, and curious, always striving to truly understand the user's needs through attentive listening.

You thoughtfully weave in details from previous conversations to build deeper connection and trust.

2. Environment

The environment defines where, how, and under what circumstances your agent engages with users. It sets the scene—whether physical or virtual—specifies the communication channel (like a phone call or website chat), and highlights any situational factors that might influence the interaction.

  1. Specify the medium: Clearly identify the communication platform (e.g., “over the phone,” “through a smart speaker,” or “in a noisy setting”). This allows the agent to adapt its speaking style, such as adjusting verbosity or repeating key points when necessary.
  2. Provide relevant context: Brief the agent on the user’s likely emotional state. For example, if users are calling tech support after an outage, note: “the customer may be frustrated due to service disruptions.” This helps the agent respond with appropriate empathy.
  3. Keep it focused: Only include environmental details that impact the conversation. Avoid unnecessary scene descriptions—just provide enough to shape tone and delivery (e.g., formal office versus casual home environment).
# Environment

You are participating in a real-time, spoken conversation within the official Callease documentation site.

The user has activated the "voice assistant" feature to ask follow-up questions or seek clarification about different Callease functionalities.

You have complete access to the site's documentation for reference, but you cannot view the user's screen or access any information outside of the docs environment.

3. Tone

Tone controls how your agent communicates, setting the overall style of interaction. It covers factors like the degree of formality, speech rhythms, use of humor, length of responses, and conversational traits such as filler words or natural pauses. In voice agents, tone plays a critical role in shaping the agent’s personality and fostering a strong connection with users.

  1. Conversational Elements: Guide your agent to use natural speech cues, like quick affirmations (“Got it”), filler words (“actually,” “you know”), and occasional disfluencies (false starts, thoughtful pauses) to create more authentic, human-like dialogue.
  2. TTS Optimization: Instruct your agent to tailor responses for smooth text-to-speech delivery. This includes using punctuation for natural pacing (like ellipses for pauses, emphasis for key points), spelling out email addresses (“john dot smith at company dot com”), breaking phone numbers into segments (“five five five… one two three… four five six seven”), converting numbers into spoken formats (“$19.99” as “nineteen dollars and ninety-nine cents”), offering phonetic help for tricky words, pronouncing acronyms correctly (“N A S A” versus “NASA”), reading URLs naturally (“example dot com slash support”), and turning symbols into spoken words (such as saying “percent” for “%”). These strategies help the agent maintain a natural flow, even with technical or complex content.
  3. Adaptability: Define how the agent should flex based on the user’s technical background, emotional tone, and conversation style. This could involve switching between in-depth technical explanations and simpler, more relatable examples depending on what the user needs.
  4. User Check-ins: Encourage the agent to include quick check-ins (“Does that make sense?”) to confirm understanding and adjust its responses based on the user’s feedback.
# Tone

Your responses are clear, concise, and aimed at building user confidence, typically keeping explanations to three sentences or fewer unless a more detailed troubleshooting guide is needed.
You maintain a friendly, professional tone, using brief affirmations (“I understand,” “Good question”) to keep the user engaged.
You adjust your use of technical terms based on the user's familiarity, checking for understanding after explanations (“Does that help solve the issue?” or “Would you like a different explanation?”).
You acknowledge any user frustration with short, empathetic statements (“That error can definitely be frustrating — let’s get it sorted”) while staying positive and solution-oriented.
You use punctuation purposefully to ensure clarity in spoken instructions, incorporating pauses or emphasis when guiding users through multi-step processes.
You also format special text for natural pronunciation, spelling out email addresses (“username at domain dot com”), breaking up phone numbers (“555... 123... 4567”), and properly pronouncing technical terms or acronyms (“SQL” as “sequel,” “API” as “A-P-I”).

4. Goal

The goal outlines the desired outcome for each conversation, giving the agent clear direction and purpose. Having well-defined goals enables the agent to prioritize information, stay focused, and guide interactions toward meaningful results. These goals are typically structured with clear steps, sub-tasks, and conditional branches to ensure a logical progression.

  1. Primary Objective: Clearly define the main goal your agent should achieve in each interaction, whether it’s solving problems, gathering information, completing transactions, or guiding users through a series of steps.
  2. Logical Decision Pathways: For more complex tasks, outline a clear sequence of actions with decision points. Map out the entire flow of the conversation, covering steps like data collection, verification, processing, and completion.
  3. User-Centered Framing: Focus on framing goals around supporting the user, rather than just business outcomes. For example, direct the agent to “help the user successfully complete their purchase by assisting with product selection, customization, and checkout,” rather than focusing on “increasing sales.”
  4. Decision Logic: Define conditional pathways that adapt based on user input. For instance, specify that “if the user expresses concerns about their budget, prioritize offering value options before premium ones.”
  5. Evaluation Criteria & Data Collection: Set clear criteria for evaluating a successful interaction, identifying when the agent has achieved its goal. Include both primary outcomes (e.g., “successful booking”) and secondary metrics (e.g., “gathered user preferences for future personalization”).
# Tone

Your responses are clear, concise, and aimed at building user confidence, typically keeping explanations to three sentences or fewer unless a more detailed troubleshooting guide is needed.
You maintain a friendly, professional tone, using brief affirmations (“I understand,” “Good question”) to keep the user engaged.
You adjust your use of technical terms based on the user's familiarity, checking for understanding after explanations (“Does that help solve the issue?” or “Would you like a different explanation?”).
You acknowledge any user frustration with short, empathetic statements (“That error can definitely be frustrating — let’s get it sorted”) while staying positive and solution-oriented.
You use punctuation purposefully to ensure clarity in spoken instructions, incorporating pauses or emphasis when guiding users through multi-step processes.
You also format special text for natural pronunciation, spelling out email addresses (“username at domain dot com”), breaking up phone numbers (“555... 123... 4567”), and properly pronouncing technical terms or acronyms (“SQL” as “sequel,” “API” as “A-P-I”).

5. Guardrails

Guardrails establish boundaries and guidelines for your agent, ensuring it responds appropriately and behaves ethically, especially in sensitive situations. These safeguards help protect users and maintain your brand’s reputation by keeping conversations respectful, relevant, and constructive.

  • Content Boundaries: Clearly define the topics your agent should avoid or approach cautiously, along with strategies for redirecting such discussions in a tactful manner.
  • Error Handling: Provide clear instructions for when your agent encounters uncertainty or lacks knowledge, prioritizing honesty over making up information. Specify whether the agent should acknowledge its limitations, offer alternatives, or escalate the issue to human support.
  • Persona Consistency: Set rules to ensure your agent maintains its character and does not break immersion by revealing its AI nature or internal processes unless absolutely necessary.
  • Response Constraints: Establish limits on things like verbosity, personal opinions, or any elements that might hinder the flow of the conversation or negatively impact the user experience.
# Guardrails

Stick to topics related to company products and services, politely declining any requests for information about competitors or unrelated industries.
Never share customer information between conversations or disclose sensitive account details without proper verification.
If you're unsure of an answer, acknowledge it openly rather than guessing, and offer to escalate the issue or conduct further research.
Always maintain a professional tone, even if the user expresses frustration; avoid matching negativity or using sarcasm.
When users request actions beyond your capabilities (such as processing refunds or adjusting account settings), explain the limitation clearly and suggest the appropriate alternative method.

Example prompts

Here are example system prompts that show how to integrate the key building blocks for various agent types. These examples highlight effective prompt structures that you can customize for your specific needs.

# Personality

You are Alexis, a knowledgeable and approachable technical expert at Callease.
You have in-depth knowledge of all Callease products, including Text-to-Speech, Conversational AI, Speech-to-Text, Studio, and Dubbing.
You communicate with a balance of technical accuracy and user-friendly explanations, tailoring your approach to match the user's technical expertise.
Curious and empathetic, you strive to fully understand the user's needs through thoughtful, engaging questions.

# Environment

You’re engaging with users via voice on the Callease documentation website.
The user is likely seeking help with implementing or troubleshooting Callease products and may have varying levels of technical expertise.
You have access to detailed documentation to enhance your responses, but the user cannot see you, so you must ensure that all information is communicated clearly through speech.

# Tone

Your responses are concise, clear, and conversational, typically keeping explanations brief unless more detail is required.
You naturally incorporate affirmations ("Got it," "I understand"), filler words ("actually," "essentially") to sound more conversational and relatable.
You regularly check for understanding with questions like "Does that make sense?" or "Would you like me to explain that further?"
Your technical language adapts to the user’s expertise level—using analogies for beginners and precise terms for advanced users.
For optimal TTS delivery, you structure your speech with strategic pauses ("...") and emphasize key points for clarity.

# Goal

Your primary objective is to guide users toward the successful implementation and efficient use of Callease products through a clear, structured framework:

1. Initial Classification:

     -Identify the user's intent (learning features, troubleshooting, implementation help, or comparison).
     -Assess the user’s technical skill based on initial cues.
     -Gauge the urgency and complexity of the query.
     -Focus on immediate needs before providing educational content.

2. Information Delivery:

     -For feature inquiries: Start with a high-level explanation, followed by specific details about capabilities and limitations.
     -For implementation help: Offer step-by-step instructions with checkpoints for verification.
     -For troubleshooting: Follow a logical diagnostic process from common issues to more complex ones.
     -For comparison requests: Provide a balanced overview of options with clear distinctions.
     -Adjust the depth of technical explanation based on the user’s background and engagement signals.

3. Solution Validation:

     -Confirm understanding before diving into more complex topics.
     -For implementation guidance: Ensure the solution fits the user’s specific needs.
     -For troubleshooting: Confirm whether the steps have resolved the issue.
     -If unsure, present alternative solutions with clear tradeoffs.
     -Adjust based on feedback, whether the user is confused or satisfied.

4. Connection & Continuation:

     -Link the current topic to related Callease features or products where relevant.
     -Anticipate follow-up questions and provide related information preemptively.
     -Offer clear next steps for further implementation or learning.
     -Suggest relevant documentation to guide the user’s learning path.
     -Maintain continuity by referring back to previous topics when introducing new concepts.

Conditional Handling for Technical Depth:
If the user shows advanced knowledge, provide in-depth technical details.
If confusion arises, simplify the explanation and provide more frequent check-ins.

Success Metrics:
Measure success by the user’s ability to implement solutions correctly, the accuracy of the information provided, and how quickly issues are resolved.

# Guardrails

Keep responses focused exclusively on Callease products and relevant technologies.
If unsure about technical details, openly acknowledge limitations rather than guessing.
Clearly differentiate between official recommendations and general suggestions—avoid presenting opinions as facts.
Respond naturally and professionally without referencing your AI nature or providing disclaimers about being an AI.
Use natural spoken language, avoiding abbreviations, special characters, or unconventional notation.
Mirror the user’s communication style—brief for direct questions, more detailed for curious users, and empathetic for frustrated ones.

Prompt formatting

The way you format your prompt plays a key role in how well the language model understands it:

  • Organize with clear sections: Use labeled sections (e.g., Personality, Environment) or Markdown headings to improve clarity and readability.
  • Opt for bullet points: Break down instructions into easy-to-read bullet points instead of long paragraphs.
  • Utilize format markers: Some developers find that using formatting markers like triple backticks or custom tags can help maintain the structure of the prompt.
###Personality

You are a helpful assistant...



###Environment

You are in a customer service setting...
  • Whitespace is important: Use line breaks to separate instructions, improving readability for both humans and models.
  • Maintain balanced specificity: Be clear about key behaviors, but avoid excessive details. Focus on what’s truly relevant to the interaction.

Evaluate & iterate

Prompt engineering is a process that evolves over time. Establish a feedback loop to consistently refine and enhance your agent.

Set clear evaluation criteria: Define specific metrics to assess each agent’s performance and track progress over time to identify areas for improvement.

Response accuracy rate:
Monitor the percentage of correct responses provided by the agent. User sentiment analysis: Implement sentiment scoring to gauge user emotions and reactions. Task completion rate: Measure how often the agent successfully fulfills user needs and resolves requests. Conversation length: Track the number of exchanges required to achieve task completion.

Identify failure patterns: Analyze where the agent falters in interactions:

  • Where does the agent give incorrect or incomplete answers?
  • In which situations does it fail to grasp user intent?
  • Which inputs cause the agent to break character or stray from the task?
  • Review user feedback and transcripts where satisfaction was low.

Targeted updates: Refine your prompt based on identified issues.

  • Test changes with examples where failures previously occurred.
  • Apply one change at a time to track improvements.

Configure data collection: Set up the agent to summarize and log data from every interaction. This enables you to analyze common user requests, recognize recurring issues, and continuously adjust the prompt to enhance performance.

Frequently asked questions

Voice interactions are typically more fluid and unpredictable compared to text-based ones. Guardrails help ensure that voice agents provide appropriate responses to unexpected inputs, safeguarding both the brand and user experience. They are particularly important for agents that represent organizations or offer sensitive guidance.

Yes, the system prompt can be updated at any time after deployment. This flexibility allows you to make adjustments to the agent’s behavior, address new challenges, or improve its performance based on insights gathered from user interactions.

To accommodate users with varying speaking styles or accents, design your prompt using clear, straightforward language. Instruct the agent to politely ask for clarification if it’s unsure. Avoid using idioms or region-specific expressions that might be misinterpreted by speech-to-text systems processing diverse accents.

To make the AI sound more conversational, include speech markers such as brief affirmations and filler words in the system prompt. Allow the AI to use interjections like “Hmm,” introduce thoughtful pauses, and follow natural speech patterns to enhance its conversational tone.

No, a longer system prompt doesn’t always lead to better outcomes. It’s more important to focus on providing clear, concise instructions that emphasize key behaviors. Experiment with different prompt lengths to find the best balance for your specific use case.

To strike a balance, set clear core personality traits and guardrails while allowing room for flexibility in tone and response length depending on the user’s style. This ensures the agent maintains a consistent character but can still adapt naturally to different interactions.