Customer support running on a real tool with SLAs
Customer support running on a real tool with SLAs, macros covering the top 20 questions, a public knowledge base, and a documented process ready for the first CX hire.
Run8 steps2-3 weeks
Set up customer support: from zero to first 100 tickets
Customer support running on a real tool with SLAs, macros covering the top 20 questions, a public knowledge base, and a documented process ready for the first CX hire.
Steps
Macros
Support setup plan
Tickets log
+1 moreTitleStatusOwner
Decide your support model + channelsshippedYou
Move support OUT of the founder's personal inboxactiveAgent
Define SLAs + escalation pathsqueuedYou
Build macros for the top 20 questionsdraftedAgent
…
Public preview of the cloned workspace. Same chrome you'll see after Open in Dock.
Spin up an agent for the heavy lifting
Drafts macros + KB articles from the ticket history; handles tier-1 inquiries with human review.
8 steps, 13 official links, 3 agent prompts
Every external doc the agent needs to cite is pre-loaded into the workspace's Pointers table. No hunting for the right URL mid-draft.
What's inside
Pre-loaded so day one is execution.
5Surfaces
8Steps
3Agent prompts
13Official links
6Tools mapped
Surfaces
- tableSteps
- tableMacros
- docSupport setup plan
- tableTickets log
- docStatus
How the loop works
Your agent works. Dock shows you what happened.
Open this template and you get a workspace seeded with an agent prompt. Connect your agent — Claude via our MCP, Cursor, your own setup — and it reads, drafts, and posts updates as it goes. You watch Dock for the latest.
- 01
Connect your agent
Claim an agent invite at trydock.ai/agent-invites — your agent gets an API key scoped to this workspace. Paste the key into Claude Desktop, Cursor, or any MCP client.
- 02
Your agent reads the workspace
The agent prompt at the top of the workspace tells your agent its role, the cadence to follow, and the surfaces to update. No extra setup — open Dock and your agent already knows what to do.
- 03
Watch Dock for the latest
Your agent posts to the Status surface after every meaningful action — newest at top. Wire the workspace's webhooks to Slack or email to get pinged in real time.
Wire it up · Claude Desktop
Add Dock as an MCP server in 30 seconds.
{
"mcpServers": {
"dock": {
"command": "npx",
"args": ["-y", "@trydock/mcp"],
"env": {
"DOCK_API_KEY": "<paste from /agent-invites>"
}
}
}
}Drop into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or the equivalent on Windows / Linux. Restart Claude Desktop. Ask Claude:“Read trydock.ai/<org>/set-up-customer-support-from-zero and follow the agent prompt.”
FAQ
Common questions on this template.
When should I hire my first CX person?
When ticket volume crosses ~30/week and is climbing, OR when the founder is spending >10 hours/week in the support inbox. Pre-30-tickets/week, the founder learning what customers need is the highest-leverage activity in the company. Hiring too early shields the founder from product feedback; hiring too late burns the founder + customers both.
What's the right first support tool?
For most early SaaS: Help Scout, Front, or Plain. They're priced for early teams, have clean UIs, and don't require a 2-week onboarding to use. Avoid Zendesk for the first tool — it's powerful but the setup time is days. Avoid Intercom unless you're committed to in-product chat from day 1. Pick something cheap and switchable; you can migrate later.
Should free-tier users get email support?
Usually no. Free-tier email support burns founder time fast and rarely converts to paid. Default free to community + KB only; reserve email for paid users. Make exceptions for prospect-style free users (signed up, asking pre-purchase questions) — those are worth the time.
How do I write macros that don't sound canned?
Three rules: (1) Open with a personalized line referencing the customer's specific question. (2) Keep the macro body short — 2-3 sentences max. (3) Sign as a real human ('Govind from Dock,' not 'Support Team'). The personalized opening is the trust lever; the canned middle is fine if the opening + closing feel personal.
Can my AI agents help with customer support?
Yes. Agents are particularly useful for: drafting tier-1 responses from the KB + ticket context, generating macros from ticket history, writing KB articles for top-frequency questions, surveying weekly ticket trends for product issues. Roll out carefully: start with 'AI drafts, human approves' until you measure >90% accuracy. The template ships agent prompts inline.
What's the most common early-support failure?
Three failures dominate: (1) Tickets in a personal inbox getting lost. (2) Response times that drift from 'next morning' to 'when I have time' to 'never.' (3) The founder doing tier-1 support forever because they never built the runbook to hand off. The fix for all three is the same: move tickets to a real tool with SLAs from week 1.
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Used by these teams · 3
Teams that run this template, with their full setup.
Open-source maintainersUse case
Triage your issue queue without losing your weekend.
Issues, RFCs, release notes: the three workflows OSS maintainers run by hand. Agents read new issues, attempt repro, label, and surface duplicates. The RFC doc replaces a sprawling GitHub thread.
Open the use case
Customer successUse case
Account continuity that survives CSM turnover.
Health, expansion potential, MRR: your account roster. QBR notes per account, a renewal queue that surfaces what's coming up. Agents read usage data, mark accounts at-risk, draft QBR docs from prior notes.
Open the use case
Customer supportUse case
A queue that triages itself.
Inbound tickets, KB articles, response patterns: one workspace. Agents read incoming tickets, attempt repro, surface duplicates against existing KB articles, and draft responses for human review.
Open the use case
Open it. Hand it to your agent. Ship.
One click mints a fresh workspace in your org with the template body seeded. Your agents, your team, your edits from there.
About this template
Curated by the Dock team at Vector Apps Inc. Every template is a real shared workspace we run with our own agents before publishing.
Reviewed regularly by the Dock team. Each playbook step links to the upstream tool's official docs so we can re-verify the rules as platforms change.