Resource
Agent Task Template
A reusable AI agent task template with variables for objective, context, available tools, constraints, success criteria, failure handling, and output format.
Customer Support Reply Template
A reusable support response template with variables for customer issue, policy boundary, account context, resolution steps, tone, escalation condition, and follow-up action.
Overview
Support replies fail in one of two ways: they acknowledge the problem without actually solving it, or they solve the immediate issue while ignoring the customer's emotional state. Good support replies acknowledge first, resolve second, and end with a clear next step. This template builds that structure in — the policy boundary prevents over-promising, the resolution steps force specificity, and the escalation condition defines when this reply is not enough.
How to use this resource
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Define the policy boundary clearly
The policyBoundary variable is the most important constraint in this template. Be explicit: 'We can offer a refund within 30 days. We cannot refund after 30 days regardless of circumstance.'
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Fill in the template variables
Open in Prompt Template Builder. Variables: customerIssue, accountContext, tone, agentName, policyBoundary, resolutionSteps, escalationCondition, followUpAction.
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List resolution steps in sequence
Write resolutionSteps as numbered actions the customer needs to take, not a description of what you will do. Specific steps reduce follow-up tickets.
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Review and personalize before sending
The AI draft is a starting point. Adjust for the specific customer tone, add any account-specific detail that wasn't in the template, and verify all steps are accurate.
Why This Works
- Encoding the policy boundary prevents agents from over-promising in the moment and creating exceptions that become precedents
- Requiring numbered resolution steps produces replies that resolve issues in one contact rather than generating a back-and-forth thread
- Separating tone as a variable means the same issue can be handled empathetically for a frustrated long-term customer and matter-of-factly for a first-contact inquiry
- The escalation condition variable forces the agent to think about failure cases before writing the reply, not after the customer escalates
Best for
- Issue categories that repeat often and benefit from a consistent reply structure
- Situations where the policy boundary needs to be enforced without alienating the customer
- Replies that need to balance empathy with specific technical resolution steps
- Teams where multiple agents respond to similar issues and quality varies
Not for
- Fully automated replies sent without human review — always review before sending
- Legal or compliance-sensitive issues that require legal team input
- Highly personalized situations with significant account-specific context not captured in the template
Use cases
- Drafting first-response replies for common support categories at scale
- Handling escalated tickets where tone, policy, and resolution need careful coordination
- Onboarding new support agents with a structured drafting process
- Building a reply template library for recurring issue categories
FAQ
How does this template stop a support reply from over-promising?
Through the {{policyBoundary}} variable paired with the rule "Do not promise outcomes that fall outside the policy boundary." You fill it explicitly — e.g. "refund within 30 days, cannot refund after 30 days regardless of circumstance" — and the draft stays inside it. Step 1 calls it the template's most important constraint. It shapes the AI draft; the notFor line is clear that a human reviews before sending.
How do I reuse this same template for both a frustrated and a first-time customer?
By changing the {{tone}} variable while keeping the rest fixed — separating tone means "the same issue can be handled empathetically for a frustrated long-term customer and matter-of-factly for a first-contact inquiry." The structure — acknowledge first, {{resolutionSteps}}, one clear next step — stays constant. You fill the variables in the Prompt Template Builder, generate the draft, then personalize before sending.
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Guides for this resource
Guide
How to Create an AI QA Checklist Before Using Generated Content
AI hands you a polished email, landing page, or support reply that looks ready to send — and only after you send it do you find the claim you can't back or the audience you got wrong. Here's how to build a reusable QA checklist and review generated content against it first.
Guide
How to Make AI Generate Cleaner First Drafts With Fewer Revisions
"Write a professional email" comes back smooth, generic, and aimed at the wrong reader — so you burn three rounds feeding in details you should have led with. Here's how to write a short first-draft brief up front, so the draft lands closer to what you needed.
Guide
How to Draft Consistent Support Replies With AI
The risk with support tickets is not that AI answers similar ones differently — it is that it answers them all the same confident way when only one has a verified answer. Here is how to draft consistent support replies with AI: one policy and one promise boundary, held steady while the case facts move.