Resource
Bug Triage Assistant
Convert scattered bug notes, Slack messages, or user complaints into structured engineering tasks with reproduction steps, severity, and root cause hypothesis.
Customer Support Agent
Configure AI to answer support questions within your actual policy boundaries — not generic best-guess answers.
Overview
Most AI-assisted support breaks down when the model improvises outside documented policy. This workflow constrains the assistant to your specific scope: if the answer isn't covered by your policies, it escalates rather than guesses. The result is consistent, policy-aware responses that don't create liabilities or set incorrect expectations.
How to use this resource
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Define your policy scope
Paste the relevant policy sections into the template — refund terms, SLA commitments, and what's explicitly out of scope.
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Set the escalation trigger
Specify explicitly what should be escalated vs. resolved within the assistant's authority.
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Test with real tickets
Paste a sample of your most common ticket types and review responses for accuracy, tone, and correct escalation behavior.
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Calibrate and deploy
Adjust constraints based on responses that were too broad, too cautious, or off-tone before rolling out to your team.
Why This Works
- Explicit policy boundaries prevent the AI from improvising answers it wasn't given authority to make
- Hard escalation triggers ensure edge cases reach a human rather than receiving a confident wrong answer
- Response length constraints keep replies actionable — exhaustive answers slow resolution without adding value
- Requiring a clear next step eliminates the ambiguous responses that generate follow-up tickets
Best for
- Teams with documented policies and repeating ticket patterns
- Products where an incorrect answer creates a liability or broken expectation
- Scaling first-response quality without adding headcount
- Situations where tone and phrasing consistency matter across agents
Not for
- Novel account disputes that require individual judgment and account history
- Replacing human agents on legally sensitive or high-stakes issues
- Real-time live chat scenarios where system prompt latency is a constraint
Use cases
- Drafting first-response templates for common ticket categories
- Handling refund and cancellation requests within documented policy
- Answering product questions using help documentation as context
- Routing edge cases to human agents with structured context
FAQ
What policy details do I need for the support agent to answer safely?
The 'Policy boundaries' slot is what matters most — paste the actual refund terms, SLA commitments, and escalation triggers, not a summary. Specificity is the safety mechanism: whatever your pasted policy doesn't cover, the agent treats as out of scope and escalates with the built-in line rather than guessing. Vague or missing policy means more escalations, never a confident wrong answer.
How do I set the escalation trigger, tone, and response length in this support prompt?
Three separate slots control this. The escalation trigger fires on the fixed line 'I'll escalate this to our team. To help them, can you confirm [relevant detail]?' whenever an issue is out of scope or needs individual judgment. Set 'Tone: [professional / friendly / technical]' to one option, and the length rule caps replies under 150 words. Adjust each independently after testing real tickets.
Can this system prompt run customer support autonomously without a human?
It answers only within the documented policy you paste in — anything outside that scope hits the escalation line and routes to a human rather than being resolved. It won't set policy, invent refund terms, or handle novel account disputes, legally sensitive, or high-stakes issues. Treat it as a policy-bounded first-response drafter, wherever you run the support prompt; the human owns edge cases and final decisions.
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Workflows that use this resource
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Design a system prompt that holds up in production — define the role precisely, engineer the behavior and guardrails on top of it, then check it reads clearly before you ship.
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AI Customer Support Workflow
Run inbound support the same way every time — triage and route the ticket, pull the details that matter, draft a reply in a consistent voice, and log the resolution for the record.