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His support agent closes 78% of tickets, but a recount says a quarter of them still needed a human

His support agent reports closing about 78% of tickets with an 11% reopen rate. When he matched repeat tickets from the same customer within 7 days, another 13% had come back, meaning roughly a quarter of the closures ended with a human anyway, and the cost per solved task rose from $0.54 to $0.71.

This only partly worked. Read what happened before you try it.

How it works

  1. The agent closes tickets and reports a 78% close rate
  2. He matches closures against repeat tickets within 7 days
  3. Another 13% had returned
  4. The true solved cost works out to $0.54 to $0.71 per task

Why it’s worth knowing

The agent was grading its own homework. The recount used the customers' behaviour instead of the agent's label.

Where it’s from

Summarized from a public post on reddit.com. See the original ↗

Upgraded prompt

A ready-to-use prompt for this idea, built from research on what makes AI agents do the job right: who the AI should be, the exact steps, and a check to make sure it was done the way you wanted.

1Who the AI should be
2The prompt, with the steps
3The check when it’s done
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Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.