Chapter 2 -- The 50-Day Plan For Building A Personal Assistant Agentic System (PAAS)

PHASE 2: API INTEGRATIONS (Days 11-25)

In this phase, you'll build the data collection foundation of your PAAS by implementing integrations with all your target information sources. Each integration will follow a similar pattern: first understanding the API and data structure, then implementing core functionality, and finally optimizing and extending the integration. You'll apply the foundational patterns established in Phase 1 while adapting to the unique characteristics of each source. By the end of this phase, your system will be able to collect data from all major research, code, patent, and financial news sources.

Day 23-25: Email Integration with Gmail API

These three days will focus on developing the agentic email and messaging capabilities of your PAAS, enabling it to communicate with key people in the AI ecosystem. You'll learn how Gmail's API works behind the scenes, understanding its authentication model, message structure, and programmatic capabilities. You'll build systems that can send personalized outreach emails, process responses, and maintain ongoing conversations. You'll develop sophisticated email handling capabilities that respect rate limits and privacy considerations. You'll also create intelligence gathering processes that can extract valuable information from email exchanges while maintaining appropriate boundaries.

• Morning (3h): Learn Gmail API and Rust HTTP clients

  • Authentication and permissions with OAuth: Master Gmail's OAuth authentication flow, understanding scopes, token management, and security best practices for accessing email programmatically. Implement secure credential storage using Rust's strong encryption libraries, and create refresh token workflows that maintain continuous access while adhering to best security practices.
  • Email composition and sending with MIME: Study MIME message structure and Gmail's composition endpoints, learning how to create messages with proper formatting, attachments, and threading. Implement Rust libraries for efficient MIME message creation, using type-safe approaches to prevent malformed emails and leveraging Rust's memory safety for handling large attachments securely.
  • Email retrieval and processing with Rust: Explore Gmail's query language and filtering capabilities for efficiently retrieving relevant messages from crowded inboxes. Create Rust-based processing pipelines for email content extraction, threading analysis, and importance classification, using Rust's performance advantages for processing large volumes of emails efficiently.

• Afternoon (3h): Build email interaction system

  • Programmatically send personalized emails: Implement systems that can create highly personalized outreach emails based on recipient profiles, research interests, and recent activities. Create templates with appropriate personalization points, and develop Rust functions for safe text interpolation that prevents common errors in automated messaging.
  • Process email responses with NLP: Build response processing components that can extract key information from replies, categorize sentiment, and identify action items or questions. Implement natural language processing pipelines using Rust bindings to libraries like rust-bert or native Rust NLP tools, optimizing for both accuracy and processing speed.
  • Implement conversation tracking with Rust data structures: Create a conversation management system that maintains the state of ongoing email exchanges, schedules follow-ups, and detects when conversations have naturally concluded. Use Rust's strong typing and ownership model to create robust state machines that track conversation flow while preventing data corruption or inconsistent states.