HomeCommunityDiscordLogin

Day 3: First Agent

🎯 Learning Objectives

⏱️ Time Commitment

  • Video: 13 minutes

  • Reading: 12 minutes

  • Hands-on: 20 minutes

  • Total: ~45 minutes

📚 Lesson Content

📹 Video Tutorial: Creating Your First Agent

Creating AI Agents with AgenticFlow (8:06) This comprehensive tutorial walks you through the complete agent creation process, from initial setup to testing and deployment.
Build Your Own AI Copilot with AgenticFlow MCP (5:10) Learn how to enhance your agent with MCP tool integrations, turning a simple chatbot into a powerful AI copilot.

📖 Step-by-Step Agent Creation

Now it's time to build your first agent! We'll create a "Meeting Summarizer" agent that can help you process and summarize meeting notes.

Phase 1: Basic Setup (5 minutes)

Step 1: Create the Agent

  1. Navigate to Agents in your left sidebar

  2. Click "+ Create Agent"

  3. Fill out the basic information:

    • Name: Meeting Summarizer

    • Description: Helps summarize meeting notes and extract action items

  4. Click "Create Agent"

Step 2: Initial Configuration You'll now see the 11-tab configuration interface. We'll focus on the essential tabs first:

Phase 2: Essential Configuration (10 minutes)

Tab 1: Basic Information

  • Avatar: Choose a professional-looking avatar or upload your own

  • Voice Input: Enable this for meeting recordings (toggle ON)

  • Description: Expand to: An AI assistant specialized in analyzing meeting notes, extracting key decisions, identifying action items, and creating structured summaries for team follow-up.

Tab 3: System Prompt (Most Important) Replace the default prompt with this specialized one:

Tab 2: AI Model Configuration

  • Model: Keep default agenticflow/gpt-4o-mini (good balance of cost and capability)

  • Temperature: Set to 0.1 (for consistent, factual responses)

  • Max Output Tokens: Set to 2000 (sufficient for detailed summaries)

Phase 3: Advanced Features (5 minutes)

Tab 4: Knowledge Integration For now, we'll skip adding documents, but note that you can upload:

  • Meeting templates

  • Company procedures

  • Team contact information

  • Previous meeting examples

Tab 9: Chat Interface

  • Welcome Message: Hello! I'm your Meeting Summarizer AI. Share your meeting notes or recordings, and I'll create a structured summary with key decisions and action items.

  • Suggested Messages: Add these options:

    • Summarize this meeting recording

    • Extract action items from these notes

    • Create a follow-up email template

    • What decisions were made?

💡 Key Insights

Agent Configuration Best Practices:

  • Start Simple: Focus on core functionality before adding complexity

  • Be Specific: Detailed system prompts produce better, more consistent results

  • Test Iteratively: Build, test, refine based on actual conversations

  • Think User-First: Configure the interface for your intended users

Common Beginner Mistakes to Avoid:

  • Making the system prompt too vague or generic

  • Trying to make one agent do everything

  • Not testing thoroughly before sharing

  • Forgetting to set appropriate temperature and token limits

🛠️ Hands-On Exercise

Build and Test Your Meeting Summarizer (20 minutes)

Part A: Agent Creation (10 minutes)

Follow the steps above to create your Meeting Summarizer agent with all the specified configurations.

Success Criteria:

  • Agent is created with proper name and description

  • System prompt is configured for meeting summarization

  • Welcome message and suggested messages are set

  • Model parameters are optimized

Part B: Testing Phase (10 minutes)

Test 1: Basic Functionality Copy this sample meeting content and test with your agent:

Test 2: Conversation Flow Try these follow-up questions:

  • "What are the main action items?"

  • "When is the new release date?"

  • "Who needs to deliver what by when?"

  • "Create a follow-up email template for the team"

Test 3: Edge Cases Test how your agent handles:

  • Unclear or incomplete meeting notes

  • Request for information not in the original content

  • Questions about meeting logistics or next steps

Evaluation Criteria

Your agent should:

  • ✅ Provide structured, well-organized summaries

  • ✅ Clearly identify action items with owners

  • ✅ Extract key decisions accurately

  • ✅ Ask clarifying questions when information is unclear

  • ✅ Maintain a professional, helpful tone

✅ Knowledge Check

Test your agent-building knowledge:

  1. Which tab contains the most important configuration for agent behavior?

    • A) Basic Information

    • B) AI Model Configuration

    • C) System Prompt

    • D) Chat Interface

  2. What temperature setting is best for factual, consistent responses?

    • A) 1.0

    • B) 0.7

    • C) 0.1

    • D) 0.5

  3. What should you do first after creating an agent?

    • A) Share it with others

    • B) Add MCP integrations

    • C) Test it thoroughly

    • D) Upload knowledge files

  4. How many configuration tabs does the AgenticFlow agent system have?

    • A) 5

    • B) 8

    • C) 11

    • D) 15

  5. What's the purpose of suggested messages in the chat interface?

    • A) To limit what users can ask

    • B) To provide helpful starting prompts for users

    • C) To save on credits

    • D) To make the agent respond faster

Click to see answers

  1. C) System Prompt - This defines the agent's personality, expertise, and behavior

  2. C) 0.1 - Lower temperatures produce more consistent, factual responses

  3. C) Test it thoroughly - Always validate functionality before sharing

  4. C) 11 - AgenticFlow uses an 11-tab configuration system

  5. B) To provide helpful starting prompts for users - They guide users on how to interact effectively

🚀 Apply Your Knowledge

Agent Enhancement Challenge

Now that you have a working Meeting Summarizer, try these enhancements:

Challenge 1: Personality Refinement

Modify your system prompt to make the agent:

  • Ask follow-up questions about unclear action items

  • Suggest meeting efficiency improvements

  • Provide templates for common meeting types

Challenge 2: Interface Optimization

Update your chat interface:

  • Add more specific suggested messages

  • Create a more engaging welcome message

  • Test with different types of meeting content

Challenge 3: Knowledge Integration

If you have sample meeting notes or templates:

  • Upload them to Tab 4 (Knowledge Integration)

  • Test how this improves response quality

  • Notice how the agent references your specific examples

Real-World Application Planning

Think about agents you could build for your own work or interests:

Business Applications:

  • Customer support agent with your product knowledge

  • Sales assistant with pricing and inventory information

  • HR agent with company policies and procedures

Personal Applications:

  • Travel planning agent with your preferences

  • Recipe assistant with dietary restrictions

  • Learning tutor for specific subjects

Community Applications:

  • Event coordinator for clubs or organizations

  • Information hub for local communities

  • Support agent for online groups

Pick one idea and outline how you would configure the system prompt and knowledge base.

📌 Summary

Congratulations! You've successfully built your first AI agent. Here's what you accomplished:

Technical Skills:

  • Navigated the 11-tab agent configuration system

  • Wrote an effective system prompt for specialized behavior

  • Configured model parameters for optimal performance

  • Set up a user-friendly chat interface

Conceptual Understanding:

  • How system prompts shape agent behavior

  • The importance of testing and iteration

  • Balance between functionality and user experience

  • Agent specialization vs. generalization trade-offs

Practical Experience:

  • Created a real, working agent that solves a specific problem

  • Tested with realistic scenarios and edge cases

  • Understanding of when and how agents provide value

What's Next: Tomorrow we'll explore the workflow system, learning how to create automated processes that can work alongside your agents or independently handle data processing tasks.

🔗 Additional Resources

Agent Building Deep Dive

Video Tutorials

Advanced Topics

Community Resources

Troubleshooting

🎉 Outstanding work! You've built your first AI agent and understand the core concepts of agent configuration. Your Meeting Summarizer agent demonstrates the power of specialized AI that can provide consistent, valuable assistance.

Tomorrow: We'll dive into workflows - the automation engine that can process data, connect systems, and work alongside your agents to create comprehensive solutions.

PreviousDay 2: Core ConceptsNextDay 4: Workflow Fundamentals

Last updated

Was this helpful?