Creating Agents
This guide walks you through creating a new AI agent from scratch, covering configuration options and best practices.Prerequisites
- Access to Agent Studio
- Understanding of your use case and goals
- Knowledge of what tools the agent will need
Step 1: Start a New Agent
- Navigate to Agent Studio from the main navigation
- Click Agents in the sidebar
- Click Create Agent or the + button
Step 2: Basic Information
Agent Name
Choose a descriptive name that indicates the agent’s purpose:| Good Names | Poor Names |
|---|---|
| ”Account Health Analyzer" | "Agent 1" |
| "QBR Prep Assistant" | "Helper" |
| "Renewal Risk Monitor" | "AI Bot” |
Step 3: Write Instructions
Instructions (the system prompt) define how your agent behaves. This is the most important configuration.Structure Your Instructions
Example: Customer Health Agent
Step 4: Select the Model
Choose the AI model based on your needs:Model Options
| Model | Speed | Capability | Cost | Best For |
|---|---|---|---|---|
| Gemini Auto | Varies | Varies | Optimized | Most use cases |
| Gemini 3 Pro | Slower | Highest | Higher | Complex analysis, critical tasks |
| Gemini 3 Flash | Fastest | Good | Lower | Quick queries, simple tasks |
| Gemini 2.5 Flash | Fast | Very Good | Moderate | Balanced needs |
Recommendations
- Start with Gemini Auto - Let the system optimize model selection
- Use Pro for complex research, multi-step analysis, or critical decisions
- Use Flash for quick lookups, simple formatting, or high-volume tasks
Step 5: Configure Reasoning Level
Reasoning level controls how much the agent “thinks” before responding:Options
| Level | Behavior | Use When |
|---|---|---|
| Auto | Adapts to task complexity | You’re unsure what level is needed |
| Low | Quick, direct responses | Simple questions, factual lookups |
| Medium | Moderate analysis | Standard analysis, most tasks |
| High | Deep reasoning | Complex problems, nuanced analysis |
Higher reasoning = better analysis but slower responses and higher cost. Match the level to your actual needs.
Step 6: Enable Toolkits
Toolkits give your agent capabilities. Enable only what’s needed.Available Toolkits
| Toolkit | Capabilities | Enable When |
|---|---|---|
| Account Data | Get account details, health scores, custom fields | Agent needs account information |
| Activity Data | Fetch activities, emails, meetings | Agent analyzes engagement |
| Contact Data | Get contact details, roles, engagement | Agent works with people |
| Task Management | Create/update tasks, add comments | Agent manages follow-ups |
| Project Data | Get project status, tasks, timelines | Agent reviews implementations |
| Communication | Send emails, Slack messages | Agent takes outreach actions |
| CRM Integration | Salesforce/HubSpot operations | Agent syncs with CRM |
| Knowledge Base | Search documents, articles | Agent needs reference materials |
| Data Analysis | Run Python code for accurate counting, aggregation, and data calculations | Agent needs precise arithmetic or data analysis |
Guidelines
Less is more
Less is more
Each enabled toolkit adds complexity. An agent with 3 focused toolkits will often outperform one with 10 toolkits.
Match to purpose
Match to purpose
A health analysis agent needs Account + Activity data. It probably doesn’t need Task Management or Communication.
Consider the user
Consider the user
Will users expect the agent to take actions (create tasks, send messages) or just provide information?
Step 7: Set Scope
Define what data the agent can access:Scope Options
| Scope | Access | Use For |
|---|---|---|
| Global | All organization data | General-purpose agents |
| Account | Specific account context | Account-focused workflows |
Account Scope
When using account scope:- Agent can only access data for the specified account
- Useful for embedding agents in account-specific contexts
- Provides data isolation and relevance
Step 8: Add Datasets (Optional)
Connect specific data sources for the agent to reference:- Knowledge bases - Internal documentation
- Playbooks - Standard procedures
- Templates - Response templates
Step 9: Test Your Agent
Before deploying, test thoroughly.Test Scenarios
-
Typical request
- Ask something your users commonly would
- Verify the response is helpful and accurate
-
Ambiguous request
- Ask something vague
- Does the agent ask clarifying questions or make reasonable assumptions?
-
Edge case
- Ask about an account with missing data
- How does the agent handle incomplete information?
-
Out of scope
- Ask something outside the agent’s purpose
- Does it gracefully redirect or explain limitations?
Example Test Prompts
Step 10: Deploy
Once tested:- Click Save to save your agent
- Toggle Active to enable it
- The agent is now available for use
Configuration Examples
Research-Focused Agent
Action-Oriented Agent
Communication Agent
Best Practices Summary
Start simple
Start simple
Begin with minimal toolkits and instructions. Add complexity only when needed.
Be specific in instructions
Be specific in instructions
Vague instructions lead to inconsistent results. Be explicit about what you want.
Test with real data
Test with real data
Sample data doesn’t catch real-world issues. Test with actual accounts and scenarios.
Iterate based on feedback
Iterate based on feedback
Your first version won’t be perfect. Collect feedback and refine instructions.
Monitor performance
Monitor performance
Track how the agent is being used and whether responses are helpful.
Next Steps
Agent Best Practices
Advanced tips for agent optimization
Use Agents in Automations
Embed agents in workflow automations