Andrej Karpathy, Google, and Garry Tan are all adopting Markdown as the primary format for agent memory and organizational context. While Karpathy focuses on personal knowledge, Google targets enterprise runbooks, and Tan defines agent roles, they all share a reliance on versioned Markdown files. This shift suggests that the strategic advantage is moving from the specific large language model used to the curated knowledge base a team accumulates.
- Karpathy's LLM Wiki for personal knowledge bases
- Google's Open Knowledge Format for enterprise context
- Garry Tan's gstack for defining agent roles
- The migration of the competitive moat from models to portable data files
- Karpathy's LLM Wiki for personal knowledge bases
- Google's Open Knowledge Format for enterprise context
- Garry Tan's gstack for defining agent roles
- The migration of the competitive moat from models to portable data files
graphify is an AI coding assistant skill that transforms codebases, documents, and images into a structured, queryable knowledge graph. By utilizing deterministic AST parsing via tree-sitter for code and multimodal LLM capabilities for unstructured data like PDFs and screenshots, it creates a comprehensive map of concepts and relationships. This allows developers to understand complex architectures faster and find the "why" behind design decisions. A key advantage is its massive reduction in token usage per query compared to reading raw files, making it highly efficient for large-scale projects. The tool supports 19 programming languages and integrates seamlessly with platforms like Claude Code and Codex, providing an interactive, persistent, and highly organized way to navigate any codebase or research corpus.
