> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wazoo.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# LLM Wiki (Karpathy Pattern)

> Worlds vs LLM Wiki: schema-validated RDF graphs vs agent-compiled markdown wikis.

## At a glance

|                 | Worlds                                            | LLM Wiki                                                   |
| :-------------- | :------------------------------------------------ | :--------------------------------------------------------- |
| Data model      | RDF triples in an append-only ledger              | Interlinked Markdown articles (`[[wikilinks]]`)            |
| Gardening model | Schema-checked assertions & SHACL validation      | Continuous agent summarizing, linking, & synthesis         |
| Retrieval       | Hybrid: SPARQL graph filters, vector, & full-text | File traversal (`ls`, `cat`, `grep`) & wikilink navigation |
| Provenance      | Quad-level, temporal, verifiable via SPARQL       | Article-level source citations & git commits               |
| Primary surface | Context engine API & agent tool calls             | Human & agent-readable Markdown vault                      |

## Overlap and shared capabilities

The LLM Wiki pattern (popularized by [Andrej Karpathy](https://x.com/karpathy)
and demonstrated in project Farzapedia) and Wazoo Worlds take the same position
on agent memory: it should be compiled, structured, and interlinked rather than
stored as flat, opaque vector databases.

Both approaches organize knowledge into navigable graph nodes where links
between concepts matter just as much as raw text search.

Where they overlap and build on each other:

* LLM Wiki defines the human-and-agent readable workspace, where agents
  continuously summarize, synthesize, and interlink Markdown articles
  (`[[wikilinks]]`).
* Worlds provides the underlying schema-checked fact engine. It takes those
  compiled articles and frontmatter assertions, enforces SHACL shape validation,
  and lets agents execute SPARQL graph queries across the knowledge graph.

## When Worlds fits

* You need strict schema validation (SHACL) to prevent metadata drift and
  hallucinated facts in your knowledge base.
* You require deterministic [graph queries](/worlds/query) (SPARQL) across
  connected entities rather than manual link-following.
* You want an append-only ledger that tracks when facts were asserted and by
  whom.

## When LLM Wiki fits

* You want a human-in-the-loop personal knowledge base (Obsidian/Logseq format)
  where both humans and agents read and edit markdown articles.
* You are starting with raw transcripts and want agents to summarize and
  interlink information organically.

## Coexistence and integration

The LLM Wiki pattern is complementary to Wazoo context infrastructure. You can
run an LLM Wiki directly using the [Wiki toolchain](/projects/wiki), as
demonstrated in the official
[`llm-wiki` starter template](https://github.com/wazootech/wiki-templates/tree/main/llm-wiki),
where agents continuously garden Markdown articles while Wiki CLI validates RDF
shapes.

To scale agent knowledge across multi-agent fleets and production environments,
we recommend pairing your LLM Wiki with [Worlds](/projects/worlds) as the
underlying context engine, so agents maintain human-readable Markdown while
querying Worlds via SPARQL for deterministic fact verification.