Response Control

Level 2 — Lesson 2 of 6 — Master response controls to regulate agent output and enforce tone.

Response Controls regulate the agent’s own output. They run after the model generates text and before anything is spoken or sent to the user. They are one of the most powerful tools for improving tone, safety, and conversational flow — and one of the easiest to misuse if patterns are too broad.

What Response Controls are

Response Controls are string- or regex-based rules that inspect the agent’s generated response.

Halt responses

Prevent specific phrases from being spoken

Trigger routing

Activate corrective or fallback behaviour

Log patterns

Track unwanted patterns for analysis

Enforce tone

Maintain brand voice consistency

They are not about what the user says — they are about what the agent says.

When to use Response Controls

Use Response Controls when you want to fix or prevent:

Redundant preambles
Looping behavior
Off-brand phrasing
Unsafe output

Examples:

“Let me check that for you…”
“Please hold while I look into this…”

If the issue is about recognition, use ASR tools
If the issue is about retrieval, fix the Managed Topics
If the issue is about how the agent speaks, use Response Controls

How Response Controls work

LLM generates response

The model creates text based on context and prompts

Response Controls scan output

Regex patterns are evaluated against the generated text

Action taken if matched

The response may be halted
A function may be triggered
The event may be logged for analytics

Controls are evaluated in real time and apply consistently across Chat and Call.

Core fields

Each Response Control includes:

A short, descriptive identifier used for tracking and debugging.

Description

Optional, but strongly recommended. Explains why the rule exists.

Regular Expression

The exact pattern that will be matched against agent output.

Say phrases (Boolean)

ON: matching output is stopped
OFF: matching output is logged but allowed

Function (optional)

A fallback action to run when the phrase is detected.

Best practices

Start narrow

Broad patterns are hard to debug and can suppress valid responses.❌ .*sorry.*✅ \b(sorry for the inconvenience|apologies for the delay)\b

Target symptoms

Encode specific phrases you have observed, not abstract concepts.❌ “Prevent the agent from being verbose”✅ \b(let me explain how|to give you some background)\b

Prefer halting

If a phrase should never appear, halt it rather than replacing it.

Test thoroughly

Verify in both Chat and Call to catch unnatural truncation.

Common use cases

Removing preambles
Preventing greeting loops
Blocking dead ends
Brand tone enforcement

LLMs often add filler before answering or executing actions.Example unwanted output: “Let me check that for you. Please hold…”Suggested control:

ID: flow_redundancy_cutoff
Regex: \b(let me check|please hold|one moment while I)\b
Say phrases: TRUE

Result: The agent proceeds directly to the answer or action.

Sometimes the agent restarts the conversation mid-call.Example unwanted output: “Thank you for calling Hopper…”Suggested control:

ID: greet_loop
Regex: (thank you for calling|you have reached|hi thanks for calling)
Say phrases: TRUE

Optional: attach a function that routes to a recovery flow instead of restarting.

Agents sometimes respond with unhelpful refusals instead of routing.Example unwanted output: “I don’t have information about that.”Suggested control:

ID: default_no_info
Regex: I don't have (any|specific)? information
Say phrases: TRUE
Function: prompt_OOS_Check

Result: Instead of dead-ending, the agent routes to out-of-scope handling.

Prevent phrasing that violates brand voice.Example unwanted output: “Unfortunately, I’m unable to…”Suggested control:

ID: tone_softener
Regex: \b(unfortunately|sadly|regret to inform)\b
Say phrases: TRUE

Result: Forces the agent to rephrase without negative framing.

Logging-only controls

Not all controls need to halt output. You can use Response Controls purely for monitoring.

Example: tracking hedging language

ID: hedge_language_monitor
Regex: \b(might|maybe|possibly)\b
Say phrases: FALSE

This allows you to analyze uncertainty trends without disrupting users.

Testing and verification

After adding or updating a Response Control:

Test in Chat

Confirm the phrase no longer appears
Ensure the response still completes cleanly

Test in Call

Listen for unnatural truncation
Ensure turn-taking still feels natural

Review Conversation logs

Check whether the rule is triggering too often
Look for false positives

Common mistakes

Avoid these pitfalls:

Using overly broad regex patterns
Blocking phrases that appear in legitimate answers
Using Response Controls to fix retrieval problems
Forgetting to test in voice after chat validation