Personal Knowledge Agent

Overview

Pal is designed to be a deeply personal AI agent that functions as an evolving, structured memory for its user. Unlike simple note-takers, Pal doesn't just store information; it actively learns the user's patterns, preferences, and relationships between disparate pieces of data.

The core philosophy is building a comprehensive, interconnected model of the user's world by dynamically creating and managing schemas in a PostgreSQL database.

Capabilities

• Dynamic Schema Creation: Automatically designs and creates new database tables when the user introduces novel concepts or requires tracking for a new domain.
• Dual Knowledge System: Maintains two distinct knowledge repositories: one for raw, structured data (e.g., notes, bookmarks) and another for meta-knowledge (learned patterns and preferences).
• Contextual Linking: Connects different types of stored information—such as linking a project note to the people involved or a research bookmark to a specific topic.
• Proactive Learning: Continuously improves its understanding of user needs by analyzing interaction history and stated goals.

Example Use Cases

• Project Tracking: A user can ask Pal to track all decisions, stakeholders, and milestones for 'Project Phoenix.' Pal will create the necessary tables and populate them as discussions occur.
• Relationship Mapping: By feeding it meeting transcripts, Pal can build a graph showing which people are connected by which projects or shared interests.
• Preference Modeling: Over time, if the user consistently asks for summaries formatted in a specific way or cites certain sources, Pal learns this preference and applies it proactively.