second-brain-karpathy-applying-or-just-fomo

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− The past few days I've seen Twitter, Reddit, Hacker News, and even Vietnamese dev groups all talking about a gist by **[Andrej Karpathy](https://karpathy.ai/)**. It's about how he built a personal wiki using LLMs to manage knowledge. Many people are calling it "Karpathy's Second Brain."
+ The past few days I've seen Twitter, Reddit, Hacker News, and even Vietnamese dev groups all talking about a gist by **[Andrej Karpathy](https://karpathy.ai/)**. It's about how he built a personal wiki using <TermNote id="llm">LLMs</TermNote> to manage knowledge. Many people are calling it "Karpathy's Second Brain."
   
  I was curious so I read the original gist. Then read further analysis from Vi (Mod Nghien AI) on Facebook and a piece by [Goon Nguyen](https://goonnguyen.substack.com/) on Substack.
   
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  The foundation is just a folder on his machine, Markdown, GitHub, and an LLM.
   
− He doesn't want to use **RAG** in the traditional sense: querying raw documents each time, stuffing context into a prompt, letting the model synthesize from scratch. That's useful, but it doesn't create accumulated knowledge. Each query is almost starting over.
+ He doesn't want to use <TermNote id="rag">**RAG**</TermNote> in the traditional sense: querying raw documents each time, stuffing context into a prompt, letting the model synthesize from scratch. That's useful, but it doesn't create accumulated knowledge. Each query is almost starting over.
   
  Karpathy wants to build a **wiki with accumulation**. Meaning the LLM doesn't just answer questions. It also maintains a layer of processed, linked, updated knowledge.
   
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  I think the best way is to try small for 2 weeks. Don't over-setup from the start.
   
− 1. **Create your ground**: a local folder or GitHub repo. Don't start inside a closed app. The folder is the foundation.
+ 1. **Create your ground**: a local folder or GitHub <TermNote id="repository">repo</TermNote>. Don't start inside a closed app. The folder is the foundation.
  2. **Throw documents into `raw/`**: articles, PDFs, transcripts, raw notes. Prioritize sources you genuinely want to learn from, not links saved out of fear of missing out.
  3. **Use AI to process into `wiki/`**: ask AI to summarize, explain concepts, link to related notes, record open questions.
  4. **Ask the wiki, not individual files**: ask synthesis questions, comparisons, contradictions, gaps. If the answer is good, save it back into the wiki.
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