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.)

​Reources

• ​GitHub: /sagecodes/ai-build-and-learn

• ​Events Calendar: https://luma.com/ai-builders-and-learners

• ​Slack (Discuss during the week): Flyte Slack Group

• ​Hosted by Sage Elliott: /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).