How to Use Model-Based AI Agents in ClickUp

Model-based AI Agents in ClickUp let you connect a language model directly to your work so you can automate research, drafting, analysis, and more without building complex workflows. This guide walks you through everything you need to know to configure these agents and start using them in your workspace.

All instructions below are based on ClickUp’s current AI Agent capabilities and show you how to set up, customize, and manage model-based agents step by step.

What Are Model-Based AI Agents in ClickUp?

Model-based AI Agents in ClickUp are agents whose core behavior is driven by a specific language model. Instead of using only predefined actions, these agents rely on a selected AI model to respond to prompts, interpret context, and generate helpful outputs for your team.

These agents can be used to:

• Summarize project updates and task activity
• Draft content, messages, or documentation from context
• Analyze information stored in your workspace
• Help teammates interact with structured processes using natural language

Because they are model-based, you focus on choosing the right model, setting clear instructions, and providing the right context, while ClickUp handles the rest.

Before You Create a ClickUp AI Agent

Before building a model-based AI Agent in ClickUp, confirm that you:

• Have access to AI features in your workspace
• Understand which use case you want the agent to support
• Know which users or teams should be able to access and use the agent

Planning these details in advance makes configuration faster and helps ensure your AI Agent produces reliable, consistent outputs.

How to Create a Model-Based AI Agent in ClickUp

Creating a model-based AI Agent takes just a few steps inside ClickUp. Use the flow below to define the agent’s purpose and core settings.

Step 1: Open the AI Agents area in ClickUp

1. Sign in to your workspace.
2. Navigate to the section where AI Agents are managed (this is typically available to admins or users with appropriate permissions).
3. Choose the option to create a new AI Agent.

Once open, you will see options to pick the agent type and configuration mode.

Step 2: Select the model-based agent option

1. Choose Model-based as the agent type.
2. Confirm that you want the agent to respond primarily through a language model rather than a fully action-based automation.

This ensures the agent relies on a selected model to interpret instructions and handle user prompts.

Step 3: Name and describe your ClickUp AI Agent

1. Enter a clear, descriptive name for the agent, such as “Sprint Summary Assistant” or “Content Drafting Helper”.
2. Add a short description that explains the agent’s role and how teammates should use it.

Names and descriptions should be specific. This helps users quickly understand when to call the agent and what to expect from its responses.

Configuring the AI Model and Behavior in ClickUp

After you create the base agent, configure the model and core behavior so it can perform well in real workflows inside ClickUp.

Step 4: Choose the language model

1. In the configuration panel, locate the Model or Provider section.
2. Select the appropriate language model for your use case. This could be a general-purpose model or a more specialized option, depending on what is available in your workspace.

Consider the following when choosing a model:

• Complexity of tasks (simple Q&A vs. long-form drafting)
• Speed and cost trade-offs
• Need for nuanced reasoning or domain-specific knowledge

Step 5: Define system instructions and agent personality

1. Locate the instructions or system prompt area for the model-based agent.
2. Describe what the agent should do, how it should respond, and any constraints it must follow.

For example, you might specify:

• “Always summarize task updates in three bullet points.”
• “Use a professional, concise tone in all responses.”
• “If information is missing, ask a clarifying question instead of guessing.”

Clear instructions help the model behave consistently across your ClickUp workspace.

Step 6: Configure context and data access in ClickUp

1. Choose which parts of your workspace the agent can reference, such as tasks, docs, or custom fields.
2. Set any filters or limits (for example, only tasks within a specific Space or Folder).
3. Confirm that the agent respects existing permissions, so it only accesses data visible to the requesting user.

Good context selection ensures the agent uses relevant, recent information when generating answers.

Setting Actions and Triggers for Your ClickUp AI Agent

Although model-based AI Agents are driven by a language model, you can still configure how they are triggered and how they behave inside ClickUp.

Step 7: Decide how teammates will use the agent

Common options include:

• Calling the agent from a task or doc sidebar
• Triggering it through a slash command or prompt area
• Making it available as part of a workflow for specific teams

Define the primary entry points so people know exactly where they can interact with the agent.

Step 8: Configure allowed actions and limitations

1. Specify what the agent is allowed to do with workspace items, such as reading tasks, summarizing comments, or drafting content.
2. Limit sensitive actions where appropriate, so the agent focuses on analysis and generation rather than changes that should remain manual.

By balancing allowed actions and restrictions, you maintain control while still gaining the benefits of AI-driven support.

Testing and Improving Your ClickUp AI Agent

Testing is essential before rolling out a model-based AI Agent to your entire organization. ClickUp provides an environment where you can iterate safely and refine instructions.

Step 9: Run test prompts and review results

1. Use realistic prompts that match how your team will interact with the agent.
2. Check whether responses are accurate, concise, and aligned with your instructions.
3. Verify that the agent is pulling the right context from tasks or docs.

If the results are inconsistent, refine your instructions, adjust context, or try a different model and test again.

Step 10: Share the agent with selected users

1. Choose a pilot group of users or a single team to try the agent in their daily ClickUp workflows.
2. Gather feedback about clarity, speed, and usefulness.
3. Monitor common prompts and adjust instructions where misunderstandings appear.

Short pilot phases help you refine the agent before enabling it for the whole workspace.

Managing Access and Governance in ClickUp

Proper governance ensures that model-based AI Agents remain safe, predictable, and aligned with your organization’s policies.

Control who can create and edit agents

Restrict AI Agent creation and editing to admins or trusted power users. This helps maintain standardization and prevents a proliferation of overlapping or poorly configured agents in ClickUp.

Review data usage and compliance

Regularly review how agents use workspace data and confirm that their behavior aligns with your security and compliance requirements. If necessary, adjust context access or restrict certain locations inside ClickUp.

Best Practices for Model-Based AI Agents in ClickUp

To get the most out of model-based agents, follow these practical guidelines:

• Keep instructions short but explicit about format and tone.
• Use examples in the instructions to demonstrate ideal responses.
• Limit the agent to a clear, focused purpose instead of trying to make one agent do everything.
• Regularly update the agent as your processes evolve in ClickUp.

Well-scoped agents are easier to maintain and perform more reliably over time.

Additional Resources

To explore more details about model-based AI Agents, refer to the official product documentation at ClickUp model-based AI Agents. For broader workspace optimization and implementation support, you can also visit Consultevo for consulting services and best-practice guidance.

By following the steps in this guide and iterating based on real user feedback, you can build powerful, reliable model-based AI Agents in ClickUp that streamline routine work and improve how your team interacts with project data.

Need Help With ClickUp?

If you want expert help building, automating, or scaling your ClickUp workspace, work with ConsultEvo — trusted ClickUp Solution Partners.

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