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Insight
What an AI agent should and should not answer in support
About 70 % of tickets can close on their own. The other 30 % is where the setup matters.
2 Sep 2026 · 6 min read

Insight
What an AI agent should and should not answer in support
About 70 % of tickets can close on their own. The other 30 % is where the setup matters.
2 Sep 2026 · 6 min read

Insight
What an AI agent should and should not answer in support
About 70 % of tickets can close on their own. The other 30 % is where the setup matters.
2 Sep 2026 · 6 min read
An AI agent in your helpdesk can answer most of what arrives. The question is which messages it should answer, which it should draft, and which it should never touch.
Answer outright
Questions with a factual answer that exists in your own material: delivery times, how to reset a password, what the returns window is, where an order is. The agent reads the order record and the help centre, answers in your voice and closes the ticket. We measure these at about 70 % of volume for online retailers.
Draft for a person
Anything that involves a decision: a goodwill refund, a change to a contract, a complaint about a person. The agent prepares the reply and the context; a human reads it and presses send. The reading takes 20 seconds. The writing used to take five minutes.
Never touch
- Legal threats and anything mentioning a regulator
- Safety issues
- A customer who has written three times about the same thing
These go to a named person within minutes, with everything attached.
Give it the facts, not the internet
An agent that answers from your help articles and your order data is accurate. One that answers from general knowledge is confident and wrong. The difference is the setup, not the model.
Every answer the agent sends is logged with the source it used. If a customer disputes it, you can see exactly why it said what it said.
Measure three things
Tickets closed without a person, the reopen rate on those tickets, and the satisfaction score on them compared with human replies. If the second number climbs, narrow what the agent is allowed to answer.
Something in your week that should run itself?
Tell us what eats the hours. A 20-minute call, a map of the first workflow, no deck.
Keep reading
Two more from the night shift.
01Guide19 Aug 20265 min readThe Monday report: eight numbers, one page
Built overnight from every system, read in a minute, and nobody builds it.Read the article
02Report4 Aug 20266 min readWhat manual admin costs a 20-person company
190 hours a month, measured across 38 audits. Where the hours hide and what the first three workflows recover.Read the articleAn AI agent in your helpdesk can answer most of what arrives. The question is which messages it should answer, which it should draft, and which it should never touch.
Answer outright
Questions with a factual answer that exists in your own material: delivery times, how to reset a password, what the returns window is, where an order is. The agent reads the order record and the help centre, answers in your voice and closes the ticket. We measure these at about 70 % of volume for online retailers.
Draft for a person
Anything that involves a decision: a goodwill refund, a change to a contract, a complaint about a person. The agent prepares the reply and the context; a human reads it and presses send. The reading takes 20 seconds. The writing used to take five minutes.
Never touch
- Legal threats and anything mentioning a regulator
- Safety issues
- A customer who has written three times about the same thing
These go to a named person within minutes, with everything attached.
Give it the facts, not the internet
An agent that answers from your help articles and your order data is accurate. One that answers from general knowledge is confident and wrong. The difference is the setup, not the model.
Every answer the agent sends is logged with the source it used. If a customer disputes it, you can see exactly why it said what it said.
Measure three things
Tickets closed without a person, the reopen rate on those tickets, and the satisfaction score on them compared with human replies. If the second number climbs, narrow what the agent is allowed to answer.
Something in your week that should run itself?
Tell us what eats the hours. A 20-minute call, a map of the first workflow, no deck.
Keep reading
Two more from the night shift.
01Guide19 Aug 20265 min readThe Monday report: eight numbers, one page
Built overnight from every system, read in a minute, and nobody builds it.Read the article
02Report4 Aug 20266 min readWhat manual admin costs a 20-person company
190 hours a month, measured across 38 audits. Where the hours hide and what the first three workflows recover.Read the articleAn AI agent in your helpdesk can answer most of what arrives. The question is which messages it should answer, which it should draft, and which it should never touch.
Answer outright
Questions with a factual answer that exists in your own material: delivery times, how to reset a password, what the returns window is, where an order is. The agent reads the order record and the help centre, answers in your voice and closes the ticket. We measure these at about 70 % of volume for online retailers.
Draft for a person
Anything that involves a decision: a goodwill refund, a change to a contract, a complaint about a person. The agent prepares the reply and the context; a human reads it and presses send. The reading takes 20 seconds. The writing used to take five minutes.
Never touch
- Legal threats and anything mentioning a regulator
- Safety issues
- A customer who has written three times about the same thing
These go to a named person within minutes, with everything attached.
Give it the facts, not the internet
An agent that answers from your help articles and your order data is accurate. One that answers from general knowledge is confident and wrong. The difference is the setup, not the model.
Every answer the agent sends is logged with the source it used. If a customer disputes it, you can see exactly why it said what it said.
Measure three things
Tickets closed without a person, the reopen rate on those tickets, and the satisfaction score on them compared with human replies. If the second number climbs, narrow what the agent is allowed to answer.
Something in your week that should run itself?
Tell us what eats the hours. A 20-minute call, a map of the first workflow, no deck.
Keep reading
Two more from the night shift.
01Guide19 Aug 20265 min readThe Monday report: eight numbers, one page
Built overnight from every system, read in a minute, and nobody builds it.Read the article
02Report4 Aug 20266 min readWhat manual admin costs a 20-person company
190 hours a month, measured across 38 audits. Where the hours hide and what the first three workflows recover.Read the article
Book a call
Tell us what eats your week. We'll automate it.
Pick what fits. On the call we map the first workflow, the tools it touches and the week it goes live.

Book a call
Tell us what eats your week. We'll automate it.
Pick what fits. On the call we map the first workflow, the tools it touches and the week it goes live.

Book a call
Tell us what eats your week. We'll automate it.
Pick what fits. On the call we map the first workflow, the tools it touches and the week it goes live.