Create an AI Customer Support Triage Agent
Design an AI agent that reads incoming support tickets, classifies them by urgency and category, suggests responses, and routes to the right team.
Build an intelligent triage layer that reduces first-response time and ensures tickets reach the right team with context.
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Prompt objective
Build an intelligent triage layer that reduces first-response time and ensures tickets reach the right team with context.
Real use case
A SaaS company receives 500 support tickets weekly across email, chat, and in-app. Tickets sit in a shared inbox for 4+ hours before someone reads and routes them.
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Prompt
Act as a customer experience architect. Design an AI support triage agent for [COMPANY NAME] handling [NUMBER] tickets per week across [CHANNELS].\n\n**Context:**\n- Support channels: [EMAIL/CHAT/IN-APP/OTHER]\n- Support team: [NUMBER] agents across [NUMBER] teams (billing, technical, account management)\n- Average response time target: [HOURS] hours\n- Ticket platform: [ZENDESK/INTERCOM/FRONT/OTHER]\n- Product: [PRODUCT DESCRIPTION]\n\n**Deliverables (numbered):**\n1. Agent architecture: ingestion from all channels, NLP classification pipeline, urgency scoring, routing logic, and response suggestion generation\n2. Classification schema: define [NUMBER] ticket categories (billing, bug report, feature request, how-to, account issue, [OTHER]) with clear definitions and examples\n3. Urgency scoring: algorithm based on keywords (urgent, broken, can't access), customer tier (enterprise vs. free), impact scope (single user vs. system-wide), and sentiment analysis\n4. Routing rules: map category + urgency to team and priority level, with overflow handling when team queue exceeds [NUMBER] tickets\n5. Response suggestions: generate 3 response options (formal, friendly, technical) based on ticket content, with links to relevant help articles and macros\n6. Escalation detection: identify tickets that need immediate human attention (churn risk, legal mentions, VIP customer, system outage reports)\n7. Feedback loop: track agent accuracy (classification correctness, response acceptance rate), weekly accuracy report, and retraining triggers\n\n**Constraints:**\n- Must never send responses automatically -- suggestions only, human must approve\n- Must handle multi-language tickets if [LANGUAGES] are supported\n- Must PII-redact sensitive data before logging for training
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- 1Replace the key placeholders first: COMPANY NAME, NUMBER, CHANNELS, EMAIL/CHAT/IN-APP/OTHER.
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