Welcome to Agents 365! This guide will walk you through building your first AI agent from scratch. By the end, you'll have a working agent that can perform real tasks.
What is an AI Agent?
An AI agent is an autonomous system that can:
- Understand natural language instructions
- Use tools to interact with external systems
- Make decisions based on context
- Complete multi-step tasks
Think of it as a specialized AI assistant that you can configure for specific workflows.
Step 1: Define Your Agent's Purpose
Before building, ask yourself:
- What problem should this agent solve?
- What tools does it need access to?
- What decisions should it make autonomously?
Example: A customer support agent that can:
- Read support tickets
- Search knowledge base
- Generate responses
- Escalate complex issues
Step 2: Choose Your Model
Agents 365 supports multiple AI models:
- GPT-4 - Best for complex reasoning and creativity
- Claude 3.5 Sonnet - Excellent for analysis and writing
- GPT-3.5 Turbo - Fast and cost-effective for simple tasks
- OpenRouter Models - Access to 100+ models
For your first agent, we recommend Claude 3.5 Sonnet for its balance of capability and cost.
Step 3: Configure Your Agent
Basic Configuration
- Name: Give your agent a descriptive name
- Description: Explain what your agent does
- System Prompt: Define the agent's personality and behavior
- Model: Select your AI model
System Prompt Example
You are a helpful customer support agent for Agents 365. Your role is to:
- Answer user questions accurately and politely
- Search the knowledge base when needed
- Escalate complex issues to human support
- Always maintain a professional and friendly tone
Step 4: Connect Tools (MCP Integration)
Agents 365 uses Model Context Protocol (MCP) to connect tools. You can connect:
- Databases (PostgreSQL, MySQL)
- APIs (REST, GraphQL)
- File Systems
- Cloud Services (AWS, GCP, Azure)
- Communication Tools (Slack, Email)
Example: Connecting a Database
- Go to Settings → Integrations
- Add a new MCP server
- Configure connection details
- Your agent can now query the database
Step 5: Test Your Agent
Use the "Run Now" feature to test your agent:
- Enter a test input
- Watch the agent's reasoning process
- Review tool calls and responses
- Iterate based on results
Step 6: Deploy and Monitor
Once your agent is working:
- Deploy it to your organization
- Monitor its performance in Analytics
- Iterate based on real-world usage
- Scale by creating agent teams
Common Pitfalls to Avoid
1. Overly Broad Prompts
Keep your agent focused. A "do everything" agent is less effective than specialized agents.
2. Insufficient Tool Access
Make sure your agent has access to all necessary tools and data.
3. No Error Handling
Define what your agent should do when things go wrong.
4. Ignoring Feedback
Regularly review agent outputs and refine prompts.
Next Steps
- Read our MCP Integration Guide to connect external tools
- Check out Team Management for Customer Support examples
- Explore the Agents 365 catalog to discover pre-built agents
- Learn more about Model Context Protocol from the official documentation
Ready to build? Create your first agent now or start chatting with existing agents!