How to Learn from Projects in the AI Era: Vault Cross-Project Persistent Storage System

In the era of AI-assisted development, how can we help AI assistants better understand our learning resources? The HagiCode project implements a unified, AI-comprehensible knowledge storage abstraction layer through the Vault system, significantly improving learning efficiency when studying projects. Background In the AI era, the way developers learn new technologies and architectures is undergoing profound changes. "Learning from projects"—deeply studying and learning from excellent open-source projects' code, architecture, and design patterns—has become an efficient learning method. Compared to traditional reading books or watching videos, directly reading and running high-quality open-source projects helps you understand real-world engineering practices faster. However, this learning approach also faces several challenges. Learning materials are too scattered. Your notes might be in Obsidian, code repositories scattered across various folders, and AI assistant conversation history i