Karpathy's LLM Wiki - AI Build & Learn #8

Welcome to AI Build & Learn a weekly AI engineering stream where we pick a new topic and learn by building together.

​​​​This event is about building an LLM-maintained Wiki, a pattern from Andrej Karpathy for turning raw sources into a persistent, compounding knowledge base instead of re-retrieving from documents on every query.

​We'll explore how this differs from traditional RAG, the three-layer stack (sources, wiki, schema), and the core operations (ingest, query, lint) that keep the wiki healthy as it grows.
​Some things to look up to get started:

• ​Karpathy's LLM Wiki gist: https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f
• ​Community implementations linked in the gist comments (SwarmVault, Kompl, Link, OmegaWiki, etc.)

​​​Resources

• ​​​GitHub: https://github.com/sagecodes/ai-build-and-learn
• ​​​Events Calendar: https://luma.com/ai-builders-and-learners
• ​​​Slack (Discuss during the week): https://slack.flyte.org/
• ​​​Hosted by Sage Elliott: https://www.linkedin.com/in/sageelliott/

​​In this stream

• Intro to topic
• ​​​​Community Discussion
• Practical examples

​​​Community challenge (optional)
​​​Try spending 30–90 minutes during the week learning or building something related to the topic, then share what you’re working on in Slack.

​​​Note on Flyte / Union
​​​You may see Flyte used in some demos. Flyte is an open-source AI orchestration platform maintained by Union (where I work) for building scalable, durable, and observable AI workflows. You do not need to use Flyte to participate.

• ​​​Union: https://www.union.ai/
• ​​​Flyte: https://flyte.org/

​​​Drop a comment with ideas for future topics (agents, RAG, MLOps, robotics, frameworks, and more).