Lecture Notes: Ultimate Personal Assistant

Overview

• Introduction to the "Ultimate Personal Assistant"
• The build consists of four main agents integrated within a system called NADN:
  • Email Agent
  • Calendar Agent
  • Content Creator Agent
  • Contact Agent
• Additional tool: Tavali for web search functionality

Agents and Their Functionalities

1. Email Agent

• Capabilities:
  • Send, reply to, label, create drafts, get emails, get labels, mark emails as unread
• Demonstration:
  • Scheduling a meeting and sending a confirmation email
  • Modifying meeting times and automatically notifying participants
  • Responding to emails within the same thread
  • Labeling emails as high priority

2. Calendar Agent

• Capabilities:
  • Update, create, get, and delete events
• Demonstration:
  • Scheduling a team sync meeting
  • Adjusting meeting times based on participant feedback

3. Content Creator Agent

• Capabilities:
  • Searches the web and creates blog posts
• Demonstration:
  • Creating a blog about Deep Seek and drafting it for email

4. Contact Agent

• Capabilities:
  • Get, add, or update contacts in Airtable database
• Demonstration:
  • Modifying contact details in the database

Tavali Tool

• Provides web search functionality
• Used by the content creator agent to gather information for blog posts

Workflow and Demonstration

• Use of Telegram for input (voice or text)
• The assistant transcribes voice inputs and processes them
• Workflow download available through Free School Community
• Option for deeper learning through paid Community

Building the Ultimate Assistant

Workflow Inputs and Outputs

• Utilizes Telegram for triggers
• Handles both text and voice inputs, converting voice to text
• Outputs responses through Telegram

Ultimate Assistant Prompt

• Simple prompts for delegating tasks to the correct agent
• Rules for actions requiring contact information

Integration with Other Workflows

• Uses the "Call NN Workflow as a Tool" feature
• Assigns workflows to specific functions (Email, Calendar, etc.)

Agent-Specific Prompts and Tools

• Each agent has a specific set of responsibilities and tools
• Utilizes the "from AI" function for filling data dynamically

Community and Learning Resources

• Free and paid community options for further exploration and learning
• Opportunities for hands-on learning and networking

Conclusion

• Encouragement to join the community and explore further learning opportunities
• The importance of specialized, simple prompts for building efficient AI agents