The Behavior tab
Conversation memory
Controls how much of the past conversation the agent reads before replying. More history means better continuity but higher cost per message.
Short support exchanges rarely need more than the recent messages. Turn on Summarize older
messages when customers come back over days and expect the agent to remember what happened —
a long-running sales thread, or a complaint that’s been through several rounds.
Every message you include is read again on every reply, so raising Recent messages to include
raises the cost of each reply. Raise it because the agent is forgetting things, not by default.
Hand off to a human
Rules that pause the AI and bring a human into the conversation.There are three independent triggers, and you can use any combination.
Pause when the customer says…
A list of phrases. Type one and press Enter (or a comma), or click Add. Each phrase becomes a chip you can remove.Case-insensitive. If the customer’s message contains any of these phrases, the AI pauses and a human is notified.This is the blunt, reliable trigger. Good candidates:
speak to a human, agent, manager,
cancel my account, complaint, legal. Match how your customers actually write — including the
languages they write in.
Let the agent escalate on its own
When on, the AI can decide to hand off to a human itself (e.g. when it’s unsure or the customer is upset).Turn this on when your conversations vary too much to cover with a phrase list. The agent judges for itself when it is out of its depth.
Pause when the AI is unsure
Switch this on and you get a confidence threshold between 0 and 1, defaulting to0.5.
Confidence threshold from 0 to 1. If the AI’s confidence drops below this, it pauses for a human. Leave off to disable.A higher number makes the agent more cautious and hands off more often. A lower number lets it push on through uncertainty. Start at the default and move it only after you’ve read a batch of real handoffs and decided there were too many or too few.
File into folders
Let the AI move conversations into the right inbox folder as it works.When on, the AI can move a conversation into one of your inbox folders once it understands what it’s about — for example filing a billing question into Billing without a rule or a person having to move it there first. Off by default. Turning it on reveals a Filing rules list — one row per rule, each pairing a free-text condition with a folder, for example:
+ Add rule adds a row, both sides edit inline, and a row can be removed at any time. Folder
is a dropdown of your workspace’s real, non-system folders, so a rule can never point at one that
doesn’t exist. These rules tell the agent when to file and where — you no longer need to
spell out a filing policy in the agent’s prompt.
A condition is read for meaning, not matched literally — the agent understands rephrasings and
other languages, so “customer is asking about branch JLT” also matches “where is your JLT
office?”. That is the strength of filing rules, and also why they are the wrong tool for exact,
deterministic routing — a specific sender, a specific channel, or an AI-assigned tag. Use
inbox routing rules for those instead.
- It doesn’t stop the AI replying. Filing a conversation and escalating it to a human are two separate things — an agent can file the conversation into the right folder and still hand off to a person afterwards.
- It doesn’t compete with a transfer to a teammate. An agent on a team can file the conversation and still transfer it to a colleague in the same conversation.
Filing only ever happens while the conversation is still unfiled, sitting in Unrouted. Neither
a filing rule nor the agent’s own judgment ever overrides a folder a person or a
routing rule already chose.
Objective
Give the agent a concrete goal to collect structured information from the customer and act on it at the end.An objective turns an open conversation into a job with a finish line: gather these fields, then do something. Use it for lead capture, ticket intake, booking details, or any hand-off where the next person needs facts rather than a transcript.
1
Turn on Enable objective
The helper text switches between “Active” and “Off”.
2
Write the Objective description
For example: “Collect the customer’s name, email, and issue description for a support ticket.”This text is added to the agent’s instructions, so it knows what it is working towards.
3
Add the variables to collect
“Each variable is a piece of information the agent must gather from the customer.” Click
+ Add variable for each one and fill in:
Use Remove variable to drop one.
4
Choose what happens when the objective is complete
Two checkboxes, and you can tick both, one, or neither:
- Close the conversation automatically — the agent has what it needs, so the thread closes.
- Hand off to a human agent — a person takes over with the collected details already in hand.
Use Multiple choice (enum) whenever the answer should be one of a fixed set. It stops the
agent from recording “billing issue I think” when you wanted
billing.Next steps
Prompt, knowledge and tools
What the agent knows and what it can do.
Teams
Hand off to another agent instead of a person.
Folders, rules and the blacklist
Route conversations into folders with rules, including on AI-assigned tags.

