Catalog Systems Theoretical / informal — ideas without a paper LLM Wiki — compiled memory

LLM Wiki — compiled memory

https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f

Three-layer directory: raw/ (immutable sources), wiki/ (LLM-maintained compiled pages), CLAUDE.md (schema). LLM reads sources and integrates them into the wiki — updating pages, resolving contradictions — so knowledge compounds across sessions instead of being retrieved cold.

Research code · Verified 2026-10-28 · fresh as of 2026-10-28 · 15 cited facts, 0 with a third-party source · 1 recorded change · Suggest a correction

At a glance

Type
Compilation over RAG repo fix
Tier
T5
Section
Theoretical / informal — ideas without a paper
Created
see post date repo fix
Latest release
not applicable — informal artifact (gist/tweet/blog) repo fix
License
not applicable — informal artifact (no formal license) repo fix
GitHub
0★ no data — repo unreachable repo fix
Pricing
not applicable — theoretical / informal fix
Funding
not applicable — not commercial fix
Freshness
2026-10-28 fix
Layer
agent-infra repo fix

Memory taxonomy

storage
file
retrieval
injection
persistence
long-term
update
overwrite
unit
file
governance
editable
conflict
n/a

When to use

Optimised for: not applicable - theoretical / not a system

Anti-fit: not applicable - theoretical / not a system

Pros & cons

Pros

Three-layer compilation paradigm (raw / wiki / schema) directly challenges RAG orthodoxy — knowledge compounds across sessions instead of being retrieved cold.

Cons

GitHub Gist; conceptual sketch with minimal implementation guidance.

Claims & capabilities

Karpathy, April 2026 GitHub Gist. Challenges RAG orthodoxy; separates ingestion (compilation) from retrieval.

Technical surface

API surface
not applicable — theoretical / not a system
Backend storage
not applicable — theoretical / not a system
Deployment
not applicable — theoretical / informal
Embedding model
not applicable — theoretical / not a system
Multi-tenancy
not applicable — theoretical / not a system
MCP
not applicable — theoretical / informal idea
A2A
not applicable — theoretical / informal idea
OpenTelemetry
not applicable — theoretical / informal idea

Similar systems

Other theoretical / informal — ideas without a paper in the catalog, ranked by inbound references.

  • From Human Memory to AI Memory (survey) T4

    Eight-quadrant classification grid across personal/system, parametric/non-parametric, and short-term/long-term axes. Bridges cognitive-science memory taxonomy to LLM architecture choices, less common than purely engineering-oriented surveys. v2 revision April 23, 2025.

  • Context Engineering T5

    "+1 for 'context engineering' over 'prompt engineering' … the delicate art and science of filling the context window with just the right information for the next step." The LLM is "a coworker with anterograde amnesia" — cannot consolidate or build long-running knowledge once training ends.

  • Context Engineering — naming event T5

    Endorses "context engineering" as a distinct discipline from prompt engineering — what agents do with their context window (routing, compression, tool output formatting, memory retrieval injection) is engineering, not just prompting.

  • Context Expansion Law T5

    "Application context tends to expand to fill the context limits supported by the model." Treats agent memory as a first-class unresolved design problem rather than a solved component; explicitly defers a memory deep-dive to a future post.

  • Externalization in LLM Agents T4

    Traces the shift from weights-as-capability to harness-as-capability; analyzes memory, skills, and protocols as three coupled forms of externalization and examines how they interact. Memory is defined as the externalization of state across time. Covers self-evolving harnesses and shared agent infrastructure as emerging directions. April 9, 2026.

  • Files Are All You Need T5

    Coding agents (Claude Code, Cursor) converge on the filesystem as their primary memory abstraction: conversation histories as searchable files, skills as files, retrieval via file search rather than vector DBs. Argument: LLMs are fluent with filesystem concepts, so the filesystem is the right interface even if storage underneath is a database.

Sources (14 cited facts, 0 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-22
    • Lifecycle first recorded as “research-complete”
    #195