Lesson 41 of 1550
Ticket Triage With LLMs: Routing Without The Backlog
Support and ops queues drown teams in repetitive sorting work. A well-prompted LLM classifier can do 80% of that triage with confidence-aware handoff.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1Triage is a classification problem in disguise
- 2triage
- 3classification
- 4confidence threshold
Concept cluster
Terms to connect while reading
Section 1
Triage is a classification problem in disguise
Every ticket queue is doing the same job: read text, decide a category, decide a priority, decide an owner. That's a three-axis classification problem. LLMs are great at it — until they aren't. The trick is knowing when to trust the model and when to fall back to a human.
The triage prompt skeleton
Confidence thresholds matter more than accuracy
- 1Pick a confidence threshold based on the cost of being wrong, not the average accuracy
- 2Route low-confidence tickets to a human triage queue, not the destination queue
- 3Track confidence calibration over time — if 'high confidence' is wrong 10% of the time, the threshold is broken
- 4Sample 5% of high-confidence routings for human audit anyway
- 5Surface the model's reasoning in the ticket comment so humans can challenge it
Key terms in this lesson
The big idea: triage automation lives or dies on confidence calibration. Optimize for the cost of being wrong, not for the demo.
End-of-lesson quiz
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