# # 163 I Built the ULTIMATE AI Second Brain (Karpathy's LLM Wiki Setup Guide) Page: https://stenobird.com/podcast/build-with-ai-6407453/163-i-built-the-ultimate-ai-second-brain-karpathy-s-llm-wiki-setup-guide Text version: https://stenobird.com/podcast/build-with-ai-6407453/163-i-built-the-ultimate-ai-second-brain-karpathy-s-llm-wiki-setup-guide.md Podcast: [Build With AI](https://stenobird.com/podcast/build-with-ai-6407453) Published: 2026-05-08T04:15:00+00:00 Episode link: https://share.transistor.fm/s/3e92bab2 Audio file: https://media.transistor.fm/3e92bab2/d1eb8a0c.mp3 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/build-with-ai-6407453/episodes/163-i-built-the-ultimate-ai-second-brain-karpathy-s-llm-wiki-setup-guide Duration seconds: 1121 ## Resource šŸ”— Deploy your own Hermes agent on Hostinger -10% off any plan with code COREY10: http://hostinger.com/corey10 (use code COREY10)Grab the free step-by-step Hermes Second Brain setup guide here: https://corey-ganim.kit.com/60fc0fe6d9In this solo episode, I walk through exactly how I built the ultimate AI second brain using Hermes and its built-in LLM Wiki skill ā€” inspired by Karpathy's wiki setup. I break down the three core operations of the Hermes agent (ingest, query, lint), the three layers of the knowledge base (raw sources, the wiki, schema/tags), and why I chose Hermes over Claude Code, OpenClaw, or Obsidian for this build. From there, I show the full one-click deploy on a Hostinger VPS, the OpenAI model setup, the Telegram bot integration via BotFather, and the Markdownload Chrome extension trick I use to feed any tweet, article, or webpage straight into the wiki. By the end of this episode, you'll have a clear, step-by-step path to deploy your own self-improving second brain that gets smarter the more you use it.Key PointsHermes ships with a built-in LLM Wiki skill that handles the second brain function out of the box ā€” your job is to curate sources, the agent's job is to summarize, tag, and file them away.The knowledge base has exactly three layers: raw sources you give it (read-only), the agent-owned wiki of markdown files, and the schema/tags Hermes builds to make querying low-friction.Run the Lint command roughly once a month ā€” it audits your wiki for contradictions, sources older than 90 days, and oversized files that should be split for more accurate retrieval.Deploy on a Hostinger VPS instead of locally ā€” it's a one-click install with no terminal, cheaper than a Mac mini, always-on, and your data stays private.The simplest workflow for feeding the wiki: uā€¦ ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/build-with-ai-6407453/episodes/163-i-built-the-ultimate-ai-second-brain-karpathy-s-llm-wiki-setup-guide/transcription-requests` ā€” Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/build-with-ai-6407453/163-i-built-the-ultimate-ai-second-brain-karpathy-s-llm-wiki-setup-guide.md` ā€” Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.