Ceria

Overview

Ceria is a modular workspace platform designed to support long-term learning, reflection, and project organization across multiple personal contexts. The system separates academic, startup, and personal workspaces while maintaining a unified interaction layer.

Architecture and System Design

I designed a workspace isolation model that cleanly separates data and state across contexts while still enabling a shared agent infrastructure. This allows the same agent framework to operate safely across different personal and professional domains.

The interaction layer is built around a LangGraph-powered command interface that supports agentic task creation and semantic search through a spotlight-style command bar. This enables fast navigation, retrieval, and action execution across large personal knowledge bases.

Learning and Mastery Engine

A core component of Ceria is a mastery engine that tracks user performance and spaced-repetition metadata to support long-term learning. Agent workflows generate personalized journal and reflection prompts designed to promote deeper understanding rather than surface-level recall.

These workflows combine user history, performance signals, and contextual retrieval to produce structured, goal-driven reflection sessions.

What I Learned

Ceria strengthened my ability to design agent-oriented systems that operate over long-lived personal data, and to reason about isolation boundaries, personalization, and workflow orchestration in learning-centric applications.