AI Agent Guide for ClickUp: Choose, Configure, and Manage Super Agents, Autopilot Agents, and External Agents

ClickUp AI features can feel like a menu of options: Brain Assistant, Super Agents, Autopilot Agents, Ambient Answers, plus external AI agents that show up as app users. This guide connects them into one workflow-first playbook so you can choose the right agent type, configure it with repeatable templates, and run it safely at scale.

This is for ClickUp admins, team leads, and ops/process owners who want fewer repetitive steps, faster handoffs, and cleaner reporting-without creating a black box automation nobody owns.

Terminology alignment (so we don’t talk past each other): In this guide, an “AI agent” means a ClickUp AI Agent (Super Agent or Autopilot Agent). When we mean a third-party or integration-driven agent account, we’ll call it an external AI agent (app user).

What this guide covers (and how to use it)

You’ll get an end-to-end method that starts with the workflow, not the feature:

• Decide: pick the right capability (Brain Assistant vs Super Agent vs Autopilot vs Ambient Answers vs external AI agent)
• Configure: use copy-paste instruction templates and a simple “agent design brief”
• Govern: manage consistency, ownership, and rollout via AI Hub
• Scale: measure impact, iterate, and standardize across teams

Scenario (how teams usually mature): A team starts by using Brain Assistant to draft a weekly status update from a set of tasks and notes. After a few weeks, they standardize the format, define the source-of-truth lists, and convert it into a repeatable workflow. If it becomes role-like (collect updates, flag risks, write a summary for execs), they build a Super Agent. If it becomes trigger-based (every Friday, compile updates into a doc and notify a channel), they build an Autopilot Agent.

Definition box: ClickUp AI, Brain Assistant, Agents, and Ambient Answers

The ClickUp AI agent landscape: what exists today and where it lives in ClickUp

ClickUp provides multiple entry points to use AI while you work (for example, from key UI areas like the toolbar and Chat). For ongoing management-especially for Super Agents-ClickUp provides AI Hub, a centralized place to manage Super Agents and access ClickUp AI capabilities.

At a high level, the “where to click” path looks like this:

• AI Hub -> Agents -> create/manage Super Agents
• Within work areas (tasks, Chat, and other surfaces) -> open AI and use Brain Assistant or interact with agents where available

If you don’t see AI Hub or Agents, start with basics: confirm your Workspace settings and your permission level. ClickUp notes that availability and limits can vary by plan and user role.

Comparison table: Brain Assistant vs Super Agents vs Autopilot Agents vs Ambient Answers vs External AI Agents

Option	Best for	How it’s triggered	Typical outputs	Setup effort	Governance risk level	Example use case	Do not use when
Brain Assistant	One-off drafting, summarizing, explaining, and quick help inside existing work	User-initiated (you ask)	Text: summaries, drafts, rewrite suggestions, structured notes	Low	Low (human remains in control)	Marketing: Rewrite a landing page section in a consistent voice	When you need repeatable routing or consistent always-on behavior
Super Agents	Specialist roles and multi-step workflows with human-like handoffs	Typically user-initiated via agent interaction; can operate continuously within defined guardrails	Drafted docs, analysis, multi-step coordination instructions, task-level deliverables	Medium	Medium (agent acts across defined scope; requires tight permissions)	Ops/Product: Weekly PMO Reporter that compiles updates, flags risks, and drafts an exec summary	When the work is purely deterministic field mapping with clear triggers (often better as Autopilot)
Autopilot Agents	Repeatable, rules-based workflows with clear inputs/outputs	Triggered by defined events/conditions in the Workspace	Creates/updates tasks or content; comments asking for missing info; routing/assignment	Medium	Medium-High (automation at scale can create noise if mis-scoped)	Support/Ops: Request intake triage that tags priority, routes to owner, and comments with clarifying questions	When the process needs nuanced judgment or negotiation with stakeholders (often better as Super Agent plus human approval)
Ambient Answers	Passive, contextual Q&A in Chat Channels	Team asks a question in a Chat Channel	Context-aware answers (designed to help teams get clarity fast)	Low	Medium (answers depend on available context and access)	Ops: “What’s blocking the onboarding project and who owns it?” answered in a channel	When you need the system to create/update work items on a trigger
External AI Agents (app users)	Cross-tool orchestration when work originates outside ClickUp or requires custom toolchains	Driven by the external system/integration logic	New tasks, updates, comments, or synced metadata from another platform	Medium-High	High (data exposure, permissions, and auditability must be designed)	Support: Escalated tickets sync into ClickUp tasks with key fields populated	When built-in ClickUp AI Agents can do the job inside ClickUp with less risk and less maintenance

Decision checklist: choosing the right ClickUp agent for a workflow

Use this checklist to choose the right starting point. If multiple options fit, default to the simplest tool that can achieve the outcome with acceptable risk.

• Is the work repeatable with clear inputs/outputs (good for Autopilot)?
• Does it require nuanced judgment, multi-step reasoning, or human-like handoff (good for Super Agent)?
• Do you just need one-off help drafting/summarizing (use Brain Assistant)?
• Do you need passive, contextual answers surfaced in the workspace (Ambient Answers)?
• Do you need an agent from an external system/toolchain to appear in ClickUp (external AI Agent/app user)?
• Do you have governance: permissions, auditability, and a clear owner for the agent?

Simple scoring approach:

• If items point to Autopilot, build an Autopilot Agent first.
• If items point to Super Agent (especially judgment/handoff), build a Super Agent first.
• If the goal is “help me write/think faster” and it’s not repeatable, start with Brain Assistant.

Two quick walkthroughs

1) Intake triage for requests
If new requests arrive in a single list, you want consistent tagging/priority rules, assignment, and a standard comment for missing details, that’s repeatable with clear inputs/outputs.

Recommended first agent: Autopilot Agent.

2) Executive weekly status reporting
If reporting needs interpretation (what matters, what’s a risk, what’s truly blocked), plus a polished narrative summary and escalations, that’s multi-step and judgment-heavy.

Recommended first agent: Super Agent (and use Brain Assistant to refine the instruction set).

Step 1 – Pick a workflow and map it to inputs, rules, and outputs (the agent design brief)

Before you build anything, write a one-page design brief. It prevents vague setups and makes testing simple: you can check whether the agent did exactly what you asked, in the right place, in the right format.

Agent Design Brief (copy/paste template)

• Agent name:
• Agent type: Super Agent or Autopilot Agent
• Goal (1 sentence):
• Scope boundaries: Which Space/Folder/List/Chat Channel it can use; what it must not touch
• Triggers / inputs: What starts the work (event, schedule, manual request) and what data it receives
• Required context: Which lists, docs, fields, or prior tasks it should rely on
• Decision rules: If/then rules, definitions (priority, severity, ready), edge cases
• Actions / outputs: What it creates/updates; where it posts results
• Output format: Headings, bullet structure, field mapping, tone, and length constraints
• Escalation rules: When to ask a human; who to notify; what to include
• Owner: A named person responsible for accuracy and iteration
• Success metrics: What improves if this works (cycle time, SLA adherence, backlog size, rework rate, stakeholder satisfaction)

Why scope boundaries matter: Agents are most reliable when their scope is narrow and their rules are explicit. Define where they can operate (one list or a small set of related lists) and where they should stop and ask.

Permissions (high level): Treat every agent like a new team member. Only grant access required for the workflow, and test in a non-production area before wider rollout. ClickUp notes that agent access is governed by Workspace permissions.

Filled example brief: “Autopilot Intake Triage Agent”

• Agent name: Ops – Requests Intake – Autopilot
• Agent type: Autopilot Agent
• Goal: Triage new requests consistently and route them to the right owner with the right priority.
• Scope boundaries: Only the “Requests” List in the Ops Space; do not edit tasks marked Confidential; do not change due dates.
• Triggers / inputs: When a new task is created in Requests List.
• Required context: Custom fields: Request Type, Impact, Urgency, Customer Tier; internal SLA doc in Docs (linked in the List description).
• Decision rules: Priority based on Impact plus Urgency; assign owner by Request Type; if required fields are blank, ask questions and label as “Needs Info.”
• Actions / outputs: Set Priority field; assign task; add a comment for missing info; apply tag(s) by category.
• Output format: Comment must include a 3-bullet checklist of missing details and a single question per bullet.
• Escalation rules: If Customer Tier is “Enterprise” and Impact is “High,” notify the on-call lead in a designated Chat Channel.
• Owner: Ops Lead
• Success metrics: Shorter time-to-triage; fewer back-and-forth comments; improved SLA adherence.

Filled example brief: “Super Agent Weekly PMO Reporter”

• Agent name: PMO – Weekly Exec Report – Super
• Agent type: Super Agent
• Goal: Produce an exec-ready weekly status narrative with risks, decisions needed, and next-week focus.
• Scope boundaries: Only the “Initiatives” Folder plus the “Risks & Decisions” Doc; never edit tasks tagged “HR” or “Finance.”
• Triggers / inputs: Manual request from PMO (“Create this week’s report for Week of ___. “).
• Required context: Initiative status fields, milestone tasks, latest meeting notes doc.
• Decision rules: Flag risks when due dates slip or blockers persist; call out decisions when owner is “Unassigned” or dependency is external.
• Actions / outputs: Draft a weekly report doc with sections: Highlights, Risks, Decisions Needed, Next Week.
• Output format: One-page max; bullets; no internal jargon; include links to top 5 referenced tasks.
• Escalation rules: If data is missing for an initiative, ask the initiative owner for an update before finalizing the section.
• Owner: PMO Manager
• Success metrics: Reduced time to produce report; fewer executive follow-up questions; improved clarity of ownership.

Step 2 – Create a Super Agent (best for specialist roles and human-like handoffs)

Use a Super Agent when you want a role-based teammate: a defined specialty, a consistent style, and multi-step work that often ends in a handoff to a person (approve, publish, escalate, schedule).

ClickUp positions its AI Agent Builder as a natural-language way to design and deploy Super Agents that understand your Workspace and execute multi-step workflows. In practice, your results depend most on three things: scope, instruction quality, and permissions.

High-level build flow (what to do, not pixel-perfect steps)

• Open AI Hub and go to Agents, or access agent configuration from relevant in-work surfaces where available.
• Create a new Super Agent and define name and role (what it is responsible for).
• Define scope and context sources: which Spaces/Lists/Docs it should reference (and which it should never use).
• Write behaviors and outputs: how it should respond, what formats it must use, and when to ask questions.
• Test with a small set of real examples, then tighten rules based on failures.

Create a Super Agent

Super Agent instruction best practices

• Role: “You are the Release Notes Agent for Team X.”
• Objective: One measurable outcome, not a vague mission.
• Constraints: Where it can operate; what it must never do.
• Output format: Headings, bullets, template, length.
• Ask-before-acting: Require confirmation for sensitive actions (customer messaging, due date changes, cross-team pings).
• Escalation: What to do when inputs are missing or conflicting.

Copy-paste Super Agent instruction template

Name: {Team} - {Workflow} - Super
Role: You are a specialist teammate for {Workflow}.

Objective:
- Produce {Primary Output} that is ready for {Audience}.

Scope:
- You may ONLY use and reference items in: {Space/List/Folder/Docs/Chat Channels}.
- Do NOT edit or disclose anything outside this scope.

Operating rules:
1) First, restate what you're going to do in 2-3 bullets.
2) Gather required context from: {Context Sources}.
3) If required info is missing, ask up to {N} clarifying questions in a single message.
4) Follow the process steps below exactly.

Process steps:
- Step 1: {Step}
- Step 2: {Step}
- Step 3: {Step}

Output format:
- Use this structure:
  - Title:
  - Summary (5 bullets max):
  - Details:
  - Risks/Unknowns:
  - Next actions (owner + due date if available):

Escalation rules:
- If {Escalation Condition}, then {Escalation Action} and tag/notify {Escalation Owner}.

Quality bar:
- Be concise and specific.
- Use links to relevant tasks/docs when referencing work.
- If you are unsure, ask before acting.

Department template 1: Marketing Content QA Agent (Super Agent)

Name: Marketing - Content QA - Super
Role: You are the Marketing Content QA Agent.

Objective:
- Review draft content and return a QA report that improves clarity, consistency, and compliance with our style rules.

Scope:
- ONLY use the Marketing Space and the "Brand & Style Guide" Doc.
- Do NOT change task statuses or publish anything.

Process steps:
1) Read the draft content from the task description and linked Doc.
2) Check against the Brand & Style Guide.
3) Return a QA report with:
   - Must-fix issues (blocking)
   - Nice-to-fix improvements
   - Suggested rewrites for the top 3 problem paragraphs

Output format:
- QA Report
  - Summary (3 bullets)
  - Must-fix (bullets)
  - Nice-to-fix (bullets)
  - Suggested rewrites (before/after)

Escalation rules:
- If claims require legal review or the draft includes sensitive customer references, ask the content owner to confirm approvals before making suggestions.

Success metric:
- Fewer revision cycles before publish-ready.

Department template 2: Engineering Release Notes Agent (Super Agent)

Name: Engineering - Release Notes - Super
Role: You are the Engineering Release Notes Agent.

Objective:
- Draft customer-friendly release notes from completed work, accurately reflecting what shipped and what changed.

Scope:
- ONLY use the Engineering Space and the "Release Tracking" List.
- Do NOT modify task fields.

Process steps:
1) Identify items marked as shipped for the target release window.
2) Group changes into: New, Improved, Fixed.
3) Translate technical details into customer-friendly language.
4) Flag any ambiguous items that lack customer-facing context.

Output format:
- Release Notes Draft
  - Highlights (3 bullets)
  - New
  - Improved
  - Fixed
  - Known limitations / follow-ups
  - Items needing clarification (with task links)

Escalation rules:
- If an item lacks a clear customer impact statement, ask the task owner for a one-sentence explanation before finalizing.

Success metric:
- Faster time from ship to publish-ready notes.

Step 3 – Create and configure Autopilot Agents (best for repeatable, triggered workflows)

Autopilot Agents are the right choice when the workflow looks like: “When X happens, check Y, then do Z.” ClickUp describes Autopilot Agents as performing actions based on defined triggers and conditions.

Operationally, treat Autopilot Agents like process code: define inputs, map decision rules to fields, and make outputs visible so the team can audit what happened.

High-level setup flow

• Choose the location (Space, Folder, List, or relevant Chat Channel) where the process lives.
• Define the trigger and any conditions that must be true.
• Provide instructions that include field mapping and decision rules.
• Set up guardrails: narrow scope, require human review for high-impact changes, and send notifications for transparency.
• Test with edge cases (missing fields, ambiguous categories, duplicates).

Create and configure Autopilot Agents

Copy-paste Autopilot instruction template

Name: {Team} - {Workflow} - Autopilot

Trigger:
- When {Event} occurs in {Space/Folder/List/Chat Channel}.

Conditions:
- Only run if {Condition 1} and {Condition 2}.

Inputs available:
- Task fields: {Field List}
- Description/comments
- Linked docs: {Docs}

Decision rules (explicit):
- If {Rule}, then set {Field} to {Value}.
- If {Rule}, then assign to {Assignee/Team}.
- If required info is missing (list required fields), then:
  1) Add a comment requesting missing info using the exact format below.
  2) Set Status to {Needs Info} (if applicable).

Actions:
1) Update fields:
   - Priority = {Mapping}
   - Category = {Mapping}
2) Apply tags: {Tag Rules}
3) Add a comment to the task (format below).
4) Notify {Channel/User} when escalation rules are met.

Comment format (must follow):
- Thanks for the request. To route this correctly, please reply with:
  1) {Question 1}
  2) {Question 2}
  3) {Question 3}

Escalation rules:
- If {Escalation Condition}, notify {Owner} with: task link + summary of why it escalated.

Success metric:
- {Metric definition}

Walkthrough example: “Request Triage Autopilot Agent”

Use this when you have a single Requests List that gets noisy and inconsistent.

Name: Ops - Requests Intake - Autopilot

Trigger:
- When a new task is created in the "Requests" List.

Conditions:
- Only run if Status is "New".

Decision rules:
- If Impact = High AND Urgency = High, then Priority = P1.
- If Impact = High AND Urgency != High, then Priority = P2.
- If Impact != High AND Urgency = High, then Priority = P2.
- Otherwise Priority = P3.

- If Request Type = "Access", assign to IT Queue.
- If Request Type = "Reporting", assign to Analytics Queue.
- If Request Type = "Process", assign to Ops Queue.

Missing info handling:
- Required fields: Request Type, Impact, Urgency.
- If any are missing, add comment requesting missing info, and set Status = "Needs Info".

Actions:
1) Set Priority field based on rules.
2) Assign based on Request Type.
3) Apply tag "Intake-Triaged".
4) Comment:
- Thanks for the request. To route this correctly, please reply with:
  1) Request Type (Access / Reporting / Process / Other)
  2) Impact (High / Medium / Low)
  3) Urgency (High / Medium / Low)

Escalation rules:
- If Customer Tier = "Enterprise" AND Priority = P1, notify the on-call lead in the Ops Chat Channel with a link.

Success metric:
- Shorter time from task created -> assigned with correct priority.

Step 4 – Use AI Hub to manage, standardize, and scale agents

AI Hub is the control center. ClickUp describes it as a centralized location to manage Super Agents and use ClickUp AI. For most teams, this is where you prevent sprawl: consistent naming, clear ownership, and a predictable review cadence.

AI Hub

Governance checklist (run this before you scale beyond one team)

• Naming convention: use “[Team] – [Workflow] – [Agent Type]“
• Owner assigned: one person accountable for changes and outcomes
• Scope documented: which Spaces/Lists/Docs are in-bounds and out-of-bounds
• Least privilege: grant only the access required for the workflow
• Change control: when instructions change, record what changed and why
• Deprecation plan: how you retire agents that are obsolete or redundant

Tagging approach (simple but effective)

• Department: Marketing, Product, Support, Ops
• Workflow: Intake, Reporting, QA, Release
• Risk tier: Low (draft-only), Medium (updates fields), High (creates/updates widely or interacts cross-team)
• Status: Pilot, Production, Deprecated

Agent Review Cadence (template)

Monthly (pilot) or quarterly (stable production):

• Is the agent still operating within its intended scope?
• What are the top 3 failure cases from the last period?
• Are outputs in the required format (and actually used)?
• Do decision rules still match current process definitions?
• Should we tighten permissions or add an approval step?
• Is there overlap with another agent we should consolidate?

Safe rollout pattern

• Sandbox first: test with realistic copies of tasks/docs (or a dedicated test Space).
• Pilot group: start with a small set of users and one workflow.
• Version your instructions: when you change rules, label the change and re-test edge cases.
• Feedback loop: give users one clear place to report failures and suggestions.

Step 5 – Connect external AI Agents (app users) when built-in agents aren’t enough

Sometimes the workflow doesn’t start in ClickUp. Or you need orchestration across tools that isn’t practical to do only inside ClickUp. That’s where external AI agents (app users) can help: a non-human account that can operate in the Workspace alongside people via integration logic.

Use external AI Agents (app users)

When external AI agents are a good fit

• Cross-tool orchestration: work begins in support, sales, or a data platform, and ClickUp is the execution layer.
• Specialized toolchains: you need a specific model, no-code agent platform, or custom pipeline outside ClickUp.
• Inbound enrichment: data is enriched elsewhere, then pushed into ClickUp as structured tasks.

Risk considerations (treat as production integration)

• Permissions: use least privilege; restrict access to only required Spaces/Lists.
• Data exposure: assume anything the agent can access could be transmitted to external systems; scope accordingly.
• Auditability: ensure actions are attributable (who/what updated tasks and why).
• Operational ownership: assign an owner for uptime, failures, and change control.

Three practical scenarios

• Support tickets -> ClickUp tasks: When a ticket is escalated, create a ClickUp task with ticket link, severity, and customer context; keep updates synced via comments.
• Lead enrichment -> follow-up tasks: Enrich inbound leads in your CRM, then create tasks in ClickUp for SDR follow-up with key fields populated (industry, company size, priority tier).
• External BI summary -> report doc: When a weekly BI summary is generated, create a ClickUp Doc draft with highlights and anomalies, then notify the owner to review.

Pre-flight checklist for external agents (app users)

• Create the agent account with the minimum required access.
• Test in a non-production Workspace area first.
• Log every action the agent takes (create/update/comment) in a way your team can review.
• Define failure handling: what happens when the external system is down or sends malformed data.
• Assign an owner and a quarterly review cadence.

Writing better agent instructions (with help from Brain Assistant)

Instruction quality is the biggest lever you control. Whether you’re configuring a Super Agent role or an Autopilot rule set, your goal is the same: make the work unambiguous, bounded, and testable.

Brain Assistant can help you tighten instructions by turning vague goals into a structured spec, suggesting edge cases, and improving formatting and escalation rules.

Instruction quality rubric

• Clarity: a single objective with defined deliverables
• Scope boundaries: where the agent can operate; what is forbidden
• Inputs: which fields/docs/messages it should use as source-of-truth
• Output format: consistent structure (so humans can scan and trust it)
• Escalation: when it must ask questions or notify an owner
• Examples: at least one good and one edge case scenario

Five common failure modes (and fixes)

• Failure: Vague scope (“help with requests”).
  Fix: Restrict to one list and define exactly which fields it may change.
• Failure: No field mapping (agent doesn’t know where to put outputs).
  Fix: Provide explicit mappings: “Set Priority field to P1/P2/P3 based on Impact/Urgency.”
• Failure: No escalation path (agent guesses when missing info).
  Fix: Add “If missing X, ask these questions and set Status to Needs Info.”
• Failure: Output isn’t usable (too long, inconsistent).
  Fix: Enforce a strict format and length limit (bullets, max sections).
• Failure: Over-automation creates noise.
  Fix: Add conditions, narrow scope, and notify only on true exceptions.

Before vs after (instruction snippet)

Before (too vague):

Triage new requests and assign them.

After (testable and safe):

When a new task is created in the "Requests" List and Status = New:
- If Request Type is missing, comment with the 3 questions below and set Status = Needs Info.
- Otherwise:
  - Set Priority based on Impact + Urgency mapping.
  - Assign based on Request Type mapping.
  - Add tag Intake-Triaged.
- Never change due dates.
Comment format:
- Thanks for the request. To route this correctly, please reply with:
  1) Request Type
  2) Impact
  3) Urgency

Prompt template to improve instructions using Brain Assistant

You are helping me write instructions for a ClickUp AI Agent.

Here is the workflow:
- Goal:
- Location (Space/Folder/List/Chat Channel):
- Inputs (fields, docs, messages):
- Required outputs:
- Forbidden actions:

Please:
1) Rewrite my instructions into a structured spec with: scope, decision rules, output format, and escalation rules.
2) Identify missing inputs or ambiguous rules.
3) Propose 5 edge cases to test.
4) Suggest a minimal pilot version that is safe to ship first.

Advanced concepts in plain English: Ambient Answers and ClickUp MCP (and how they relate to agents)

Ambient Answers

Ambient Answers is a prebuilt Autopilot Agent that responds to questions in Chat Channels with detailed, context-aware answers. The key difference is that it’s designed for Q&A rather than acting on a workflow like “route requests” or “update fields.”

Choose Ambient Answers if:

• You want faster answers in a Chat Channel without building a custom workflow.
• The most common need is “What’s the status?” “Who owns this?” “What changed?”

ClickUp MCP (Model Context Protocol)

Model Context Protocol (MCP) is a way to connect tools and context so AI agents can work across systems more effectively. Conceptually, it matters because agents are only as useful as the context and tools they can safely access.

Choose an MCP-related approach if:

• Your workflow requires the agent to reference or coordinate with multiple external systems.
• You need standardized, controlled access to tools and data sources for agent workflows.

Quick “what to use when”:

• Brain Assistant: you want help drafting, summarizing, or thinking through something now.
• Super Agent: you want a specialist teammate for multi-step work and consistent handoffs.
• Autopilot Agent: you want reliable, triggered execution of a repeatable process.
• Ambient Answers: you want contextual Q&A inside Chat Channels.

AI features and availability can change over time. Confirm what your Workspace supports in current ClickUp documentation.

Measurement: prove ROI and keep agents healthy

Agents only work if they change an operational outcome. Pick a baseline, measure after, then iterate on scope and instructions.

Five practical metrics

• Cycle time: time from request created -> done (or created -> triaged, for intake workflows)
• SLA adherence: percent of items meeting response or resolution targets (where you track SLAs)
• Backlog size: count of items in New / Untriaged / Needs Info
• Rework rate: how often tasks bounce back due to missing info or wrong routing
• Stakeholder satisfaction: quick qualitative pulse (simple helpful/not helpful feedback)

Baseline -> after loop

• Baseline: capture current state for a representative slice of work.
• Deploy: pilot the agent with a small group and tight scope.
• Review: identify top failure cases (missing fields, wrong category, noisy notifications).
• Iterate: adjust instructions, conditions, scope, and escalation rules.

Agent KPI Snapshot (template)

Workflow	Metric	Baseline	Current	Trend	Notes / Next change
Requests Intake	Time-to-triage	–	–	–	Tighten missing-info questions; add condition for duplicates
Weekly Exec Report	Time to produce draft	–	–	–	Add top risks rule; enforce one-page max

Safety checklist

• Monitor for incorrect changes during the pilot (spot check daily at first).
• Require human approval for sensitive outputs (external comms, major reprioritization).
• Define exception handling: when the agent should stop and ask.
• Keep the scope narrow until reliability is proven.

Common use cases with ready-to-use templates (marketing, product, ops/support)

Below are six complete templates-three Super Agents and three Autopilot Agents. Each includes scope, trigger (if applicable), actions, output format, escalation, and a success metric. Use them as starting points, then adapt your field names and lists.

Super Agent templates

1) Marketing – Content Brief Builder (Super Agent)

Name: Marketing - Content Brief Builder - Super
Scope:
- Marketing Space only; reference the "Brand & Style Guide" Doc.

Objective:
- Turn a topic + audience + goal into a publish-ready content brief.

Inputs:
- Task includes: Topic, Target audience, Primary keyword, Offer/CTA, Constraints.

Actions/Outputs:
- Produce a brief to paste into the task description or a Doc:
  - Working title
  - Audience + pain points
  - Primary keyword + secondary themes
  - Outline (H2/H3)
  - Key examples and proof points to gather
  - CTA copy variants (3)

Output format:
- Use headings and bullets. Keep it to one screen where possible.

Escalation rule:
- If the task lacks audience or offer details, ask clarifying questions before writing the outline.

Success metric:
- Reduced back-and-forth before drafting starts.

2) Product – PRD Clarifier (Super Agent)

Name: Product - PRD Clarifier - Super
Scope:
- Product Space and the "Product Requirements" Docs area.

Objective:
- Improve PRD quality by identifying gaps and drafting a structured PRD section set.

Inputs:
- Feature idea (task description), links to related tasks, and any constraints.

Actions/Outputs:
- Return:
  - Problem statement
  - Non-goals
  - Requirements (bulleted)
  - Open questions
  - Acceptance criteria draft

Escalation rule:
- If success metrics are missing, ask for how the team will measure success before finalizing acceptance criteria.

Success metric:
- Higher completeness of PRDs before engineering review.

3) Engineering – Release Notes (Super Agent)

Name: Engineering - Release Notes - Super
Scope:
- Engineering Space + Release Tracking List.

Objective:
- Draft release notes from shipped items and flag ambiguous entries.

Actions/Outputs:
- Draft release notes using the structure:
  - Highlights
  - New / Improved / Fixed
  - Known limitations
  - Items needing clarification (task links)

Escalation rule:
- If a shipped task lacks a clear customer-facing impact statement, request a one-liner from the owner.

Success metric:
- Faster publish-ready release communications.

Autopilot Agent templates

4) Marketing – Content QA Gate (Autopilot Agent)

Name: Marketing - Content QA Gate - Autopilot
Scope:
- Marketing Space, "Content Production" List only.

Trigger:
- When Status changes to "Ready for QA".

Actions:
- Check for required fields: Target keyword, Audience, CTA, Draft link.
- If any missing:
  - Comment requesting missing items (checklist format)
  - Set Status to "Needs Info".
- If complete:
  - Add tag "QA-Ready"
  - Notify the QA owner in a designated Chat Channel.

Output format (comment):
- To proceed with QA, please add:
  1) ...
  2) ...
  3) ...

Escalation rule:
- If the content is tied to a time-sensitive campaign (field = Yes), notify the marketing lead as well.

Success metric:
- Fewer QA stalls due to missing inputs.

5) Product/Ops – Bug Triage (Autopilot Agent)

Name: Product - Bug Triage - Autopilot
Scope:
- Engineering Space, "Bugs" List only.

Trigger:
- When a new task is created in "Bugs".

Decision rules:
- If Severity is missing, comment asking for severity + repro steps and set Status = Needs Info.
- If Severity = Critical, tag "On-Call" and notify the on-call channel.

Actions:
- Apply tags by component (based on Component field).
- Assign by component owner mapping.

Escalation rule:
- If Severity = Critical AND customer-facing impact is indicated, notify Support lead with task link.

Success metric:
- Shorter time from bug created -> owned and categorized.

6) Support/Ops – Escalation Summarizer (Autopilot Agent)

Name: Support - Escalation Summary - Autopilot
Scope:
- Support Space, "Escalations" List only.

Trigger:
- When Status changes to "Escalated".

Actions:
- Summarize the task description and recent comments into:
  - What happened
  - Customer impact
  - What's been tried
  - Needed next step
- Post the summary as a comment.
- Notify the assigned engineering owner.

Escalation rule:
- If no owner is assigned, notify the escalation manager and set Status = "Needs Owner".

Success metric:
- Higher-quality handoffs with fewer clarification rounds.

Governance note (use this on at least one workflow): For any agent that routes work or notifies leadership, assign a named owner and set a quarterly review cadence in AI Hub (naming + status tag + review questions).

FAQ: ClickUp AI Agents

Key takeaways and recommended next steps

• Pick the agent type based on workflow shape: one-off assistance vs automated triggers vs specialized roles vs external app users.
• Start with one workflow, define inputs/outputs, and create a minimal agent with tight instructions before expanding.
• Use AI Hub for centralized management and consistency (naming, ownership, monitoring).
• Instruction quality is the biggest lever: include scope, steps, format, and escalation rules.
• Measure impact with a simple before/after baseline (cycle time, backlog size, handoff quality) and iterate.

Build your first ClickUp AI Agent this week

Build your first ClickUp AI Agent: pick one workflow, use the template instructions, and review results after a short pilot.

7-day starter plan

• Day 1: Pick one workflow with obvious friction (intake triage, weekly reporting, QA gate).
• Day 2: Write the Agent Design Brief (scope, rules, outputs, escalation, owner, success metric).
• Day 3: Build the agent (Super Agent or Autopilot Agent) using the copy-paste template.
• Day 4: Test with edge cases and tighten instructions (missing fields, ambiguous categories, exceptions).
• Day 5: Pilot with a small group and turn on notifications for transparency.
• Day 6: Measure: compare baseline vs current for the chosen metric(s).
• Day 7: Iterate: tighten scope, add escalation rules, and document governance in AI Hub.

First agent to build (by team)

• Marketing: Content QA Gate (Autopilot) or Content Brief Builder (Super)
• Product: Bug Triage (Autopilot) or PRD Clarifier (Super)
• Ops/Support: Requests Intake Triage (Autopilot) or Weekly PMO Reporter (Super)

Change management caution: Agents change how work flows. Announce the pilot, define what good looks like, and provide one clear feedback channel. Keep humans in the loop for high-impact decisions until the process is stable, then expand scope deliberately.

References

• https://help.clickup.com/hc/en-us/articles/12578085238039-What-is-ClickUp-AI
• https://help.clickup.com/hc/en-us/articles/20658787666071-Use-AI-from-anywhere-in-ClickUp
• https://help.clickup.com/hc/en-us/articles/36954958035863-AI-Hub
• https://clickup.com/solutions/ai-agent-builder
• https://clickup.com/blog/super-agents-launch/
• https://clickup.com/blog/how-to-choose-a-super-agent/
• https://clickup.com/blog/mcp-tools/