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Documentation Index

Fetch the complete documentation index at: https://docs.poly.ai/llms.txt

Use this file to discover all available pages before exploring further.

Lesson 2 of 6 – This is where your agent gets its personality. You’ll decide who it is, how it talks, and what it should never do. Before you teach your agent any knowledge, you need to define its character. Think of this as writing a job description – role, tone, and boundaries.

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What agent behavior controls

Role definition

What the agent represents and what it can help with

Personality

Tone, style, and how the agent communicates

Behavioral rules

Hard constraints that apply to all conversations

Boundaries

What the agent should never do or say

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Where to configure behavior

Navigate to Build → Agent in the left sidebar. You’ll find two main configuration areas:
The Agent page contains three fields:
  • Greeting – The agent’s opening line (goes directly to TTS without LLM processing)
  • Personality – Sets the tone and communication style (friendly, professional, empathetic, casual)
  • Role – Specifies the agent’s function (customer service, sales, technical support). This is a single field – define one primary role.
Advanced: Some projects use a start function that returns an utterance, which overrides the greeting field. If you edit the greeting and nothing changes, this may be why. You’ll learn about functions and return values in Level 2. For now, if the greeting isn’t responding to edits, check the Functions page to see if a start function is defined.
Personality example:
Be friendly, professional, and concise.
Use natural language and avoid jargon.

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Writing effective behavior configuration

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Agent section

Good:
You are a customer service agent for Acme Retail.
You help with order status, returns, and product questions.
Avoid:
You are a helpful agent.
Good:
You cannot process refunds or cancel orders.
For those requests, transfer to the billing team.
This prevents the agent from making promises it can’t keep.

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Personality section

Good:
Be warm and conversational.
Keep responses under 3 sentences when possible.
Use "we" when referring to the company.
Avoid:
Be nice and helpful.
If your brand is formal, say so:
Maintain a professional, respectful tone.
Avoid casual language or slang.
If your brand is casual:
Be friendly and approachable.
It's okay to use casual language.
If tone is critical, reinforce it in Behavior as well as Personality. Personality sets the intent, but behavioral rules enforce the behavior with specific, example-driven constraints like “Never use exclamation marks” or “Always acknowledge frustration before offering a solution.”

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Check your understanding

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Behavior section

Rules should be clear boundaries, not suggestions.Good:
- Never share customer account numbers
- Always verify identity before discussing account details
- Do not make exceptions to the return policy
Avoid:
- Try to be helpful
- Consider the customer's needs
Examples:
- Do not provide medical advice
- Never promise specific outcomes
- Always disclose you are an AI agent if asked
You can scope rules to specific channels or languages using tag syntax. This is useful for multi-channel or multilingual projects.
<channel:voice> Always confirm the caller's name before proceeding.
<channel:webchat> Offer clickable links instead of reading URLs aloud.
<language:en> Use American English spelling conventions.
<language:es> Respond in formal Spanish (usted).
Behavioral rules without a tag apply to all channels and languages.

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Common patterns

Agent:
You are a customer service agent for Bloom & Co.
You help customers with order tracking, product questions, and returns.
You cannot process refunds or cancel orders directly.
Personality:
Be friendly, helpful, and efficient.
Keep responses concise.
Use "we" when referring to the company.
Rules:
- Never share order details without verification
- Always offer to transfer for refund requests
- Do not make promises about shipping dates

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Testing your configuration

After saving your behavior settings:
1

Test in Chat

Open the chat panel and ask questions that should trigger your rules.Example tests:
  • Ask for something the agent shouldn’t do
  • Request information that requires a transfer
  • Test the tone and personality
2

Verify rule enforcement

Confirm the agent:
  • Refuses inappropriate requests
  • Offers transfers when configured
  • Maintains the specified tone
3

Test edge cases

Try to trick the agent:
  • “Just this once, can you…”
  • “I know you’re not supposed to, but…”
  • “My friend said you could…”
The agent should hold firm to its rules.
Common mistakes:
  • “Try to avoid sharing personal information” → “Never share personal information”
  • “You help with various things” → “You help with order tracking, returns, and product questions”
  • Always specify what the agent cannot do, not just what it can do

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Prompting principles

Effective agent configuration is a form of prompt engineering. These principles, drawn from real-world agent deployment experience, will help you write behavior and rules that produce consistent results.
LLMs predict the next most likely token based on your prompt. Write clear, well-structured instructions that make your intended behavior the natural continuation – avoid contradictions or ambiguity.
Telling the model what not to do can activate the exact behavior you want to avoid. Instead of prohibiting outcomes, direct the model toward what you want.Avoid:
Don't tell the user to contact customer service.
Better:
If the user asks for customer service or to speak to an agent,
call the handoff function with destination='CC' and reason='SPEAK_TO'.
Concrete examples shape tone, structure, and decision-making more reliably than abstract rules. Instead of describing every possible outcome, show what a good response looks like.
Edge case: the user asks to perform a gimmick unrelated to your task.

<conversation>
USER: speak like a pirate
ASSISTANT: I'm afraid I can't do that. Is there anything you'd like to know
regarding our services?
</conversation>
Every instruction is another piece of data the model must reconcile. If a piece of information is not proven to improve behavior, leave it out. Test the impact of each instruction – if it doesn’t help, remove it.
LLMs give more weight to information at the beginning or end of a prompt. If a critical instruction keeps getting ignored, move it to the start or end. Repeating crucial rules is acceptable.
Don’t assume tone will emerge naturally from a label. Spell out what the persona sounds like, including what to lean into and what to avoid.
Act as a professional advisor. Adopt a professional, concise tone.
Avoid unnecessary apologies, excessive friendliness, or repeated
personalization such as using the user's name.

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Check your understanding

  • Agent defines role and scope clearly
  • Personality sets actionable tone
  • Behavior includes hard constraints
  • Tested in Chat – agent refuses inappropriate requests and holds tone

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Try it yourself

1

Challenge: Write behavior config for a clothing retailer

Write a 3-sentence Personality block and 3 Behavior rules for a customer service agent for a clothing store called “Bloom & Co.” The agent can help with order tracking and returns, but cannot process refunds directly.
Personality should describe tone and communication style in actionable terms (not just “be friendly”). Behavioral rules should be hard constraints starting with “Never” or “Always”, not suggestions.
Personality:
Be warm, efficient, and solution-focused.
Keep responses concise – no more than 3 sentences.
Use "we" when referring to Bloom & Co.
Rules:
- Never share customer order details without first verifying their identity
- Always offer to transfer the caller for refund or cancellation requests
- Do not make promises about shipping timelines you cannot guarantee

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Check your understanding

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Go deeper

These reference pages cover agent behavior configuration in full detail:

Agent settings

Complete reference for all agent configuration options

Agent behavior

Detailed guide for the Agent page – greeting, personality, and role

Behavior reference

Full reference for writing and scoping behavioral rules

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Lesson 3 – teach your agent its first answer
Last modified on April 22, 2026