According to Andrej Karpathy, his viral post outlines an agent-driven workflow where LLMs ingest raw sources and compile a fully linked markdown wiki that powers Q&A, visualization, and ongoing curation (as reported on X and in his GitHub Gist). According to Karpathy, data is collected into a raw directory, converted with tools like Obsidian Web Clipper, and incrementally compiled by an LLM into summaries, concept pages, backlinks, and index files for retrieval without heavy RAG at small scale (as reported by his Gist). According to Karpathy, Obsidian serves as the IDE frontend while the LLM maintains the wiki, outputs slides in Marp, renders plots, runs health checks for inconsistencies, and files outputs back to the knowledge base to compound value (as reported on X). According to Karpathy, the approach enables product opportunities for agentic knowledge management, lightweight search, CLI tool orchestration, and future synthetic data plus finetuning to internalize domain knowledge (as reported in his Gist).