Creating an Agent
Click Agents in the sidebar → Create Agent. Agent Name: Descriptive name like “Company Enrichment Agent” or “Resume Parser”. Avoid generic names. Description: Explain what the agent does, what data it processes, and expected outputs.Configure AI Model
GPT-4: Best for complex reasoning and detailed analysis. Higher cost, slower. GPT-4 Mini: Balanced performance and cost. Good for standard data processing. GPT-4 Nano: Fast, low cost, simple tasks only. API Key: Select from existing variables or create new. Never paste keys directly—always use secure variables.Write System Prompt
The system prompt defines your agent’s role, instructions, output format, and guidelines.Structure
Role: Define who the agent isSelect Tools (Optional)
Choose tools that extend agent capabilities: web search, company databases, social media APIs, document processing, custom APIs.Start with fewer tools and add as needed. Too many tools slow down agents and
increase costs.
Test Your Agent
Click Test Agent → Provide sample input → Review response → Check formatting, accuracy, completeness. Test with typical cases, edge cases, missing information, and ambiguous data.Save and Deploy
Review configuration → Create Agent → Agent is now active.Connect to Dataset
Navigate to dataset → Click column header → Edit Column → Select your agent in Agent dropdown → Add column-specific instructions if needed → Save.Next Steps
Test Agents
Test and validate agents
Chat with Agents
Interactive agent testing
Manage Agent Tools
Add and configure tools
Configure Models
Advanced model configuration