WUPHF: shared memory for AI agent teams, powered by markdown and git

Karpathy’s LLM wiki concept now has a multi-agent implementation. WUPHF gives each agent a private notebook and a shared team wiki with a promotion flow, all on plain markdown and git. No vector DB, no cloud lock-in.

📋 Source: Reddit r/clawdbot, GitHub, Karpathy gist

Why this matters

Three weeks ago, Andrej Karpathy dropped a gist that changed how people think about LLM memory. The idea: instead of treating your LLM as a stateless Q&A machine, give it a persistent wiki it writes into and reads from across sessions. Knowledge compounds rather than restarting from scratch every time. Over 15 implementations appeared in the first week alone.

Most of those implementations follow Karpathy’s original pattern: one human, one LLM, one personal vault. WUPHF takes a different route. It adapts the concept for multi-agent teams, where different AI agents each have their own context, biases, and work habits, and need shared infrastructure that doesn’t devolve into noise.

On April 4, 2026, Andrej Karpathy published a gist titled llm-wiki.md that rapidly went viral, amassing over 5,000 stars and 16 million tweet views within days. Karpathy described the pattern as “Obsidian is the IDE; the LLM is the programmer; the wiki is the codebase.” Every new source gets integrated into existing pages, contradictions get flagged, and the knowledge base compounds rather than restarting from scratch each query.

From personal wiki to team brain

The key departure from Karpathy’s original concept is the notebook-wiki split. In Karpathy’s version, one person curates one wiki. WUPHF gives each agent:

A private notebook at agents/{slug}/notebook/*.md: a scratch space for half-formed hypotheses and in-progress thinking that stays local
A team wiki at team/*: canonical, reviewed knowledge including decisions, playbooks, and established procedures

The critical mechanism is the promotion flow between them. An agent drafts in its notebook; a reviewer (human or another agent) approves, and the content formalizes into the team wiki with a back-link to the original draft. It mirrors how real organizations treat scratch documents versus official documentation, except the drafting and review cycle happens at machine speed.

This is where WUPHF diverges meaningfully from the dozen-plus other LLM wiki implementations that sprang up after Karpathy’s gist. Most follow the original pattern closely. WUPHF treats the wiki as shared infrastructure for a team of heterogeneous agents (Claude Code, Codex, OpenClaw, local LLMs via OpenCode), each with its own context and biases. The promotion flow is the governance layer that makes that work without turning the wiki into a mess of unvetted notes.

Entity briefs and knowledge integrity

For every person, company, or customer your agents interact with, WUPHF auto-generates an entity brief from an append-only fact log. When enough new facts accumulate, a built-in agent called Pam (the Archivist) synthesizes an updated brief and commits it under her own git identity. The full author chain is visible in git log.

Contradictions between facts are surfaced inline rather than silently reconciled. A daily lint cron scans for contradictions, stale entries, and broken [[Wikilinks]], which render in red to make knowledge gaps visible rather than hidden. The /lookup slash command and an MCP tool let any agent query “what do we know about X” and get a cited answer.

The bleve + SQLite index layer powers /lookup and the lint checks, but the markdown files remain the source of truth. This is a deliberate architectural choice. As the project’s author puts it: “Not a RAG vector store with a chat UI wearing a wiki costume.” The index can be rebuilt from the markdown at any time. If WUPHF disappears tomorrow, you still own every byte in ~/.wuphf/wiki/.

What this is not

The author is candid about the project’s boundaries:

Not hosted: your wiki lives on your machine
Not magic: synthesis quality is bounded by observation quality, and the lint cron catches problems but doesn’t judge them
Not finished: recall on the query layer is still being tuned, with an internal benchmark of 85% recall@20 on 500 artifacts

The Karpathy framing is their own: “He has been circling the pattern for a while. I am the one claiming we shipped a serviceable implementation of it.”

The project has 72 GitHub stars as of late April 2026, putting it in early-adopter territory. The codebase is primarily Go (74.7%) with TypeScript (14.9%), and the stability warning is explicit: “pre-1.0, main moves daily, pin your fork to a release tag.” WUPHF is part of a broader project billed as “a collaborative office for AI agents,” supporting multiple memory backends. The markdown wiki became the default in v0.0.6, replacing the earlier Nex-backed context graph, though existing users can continue on their preferred backend.

Getting started

Two commands to start:

npx wuphf@latest
/connect openclaw

Existing OpenClaw agents appear as members of the “office” and start reading from and writing to the wiki by default. A demo script (./scripts/demo-entity-synthesis.sh) walks through the full loop: recording facts, triggering synthesis, and committing under an archivist git identity. An asciinema recording is available for those who want to see the process before installing.

WUPHF is MIT-licensed, self-hosted, and available at github.com/nex-crm/wuphf and wuphf.team. Named, naturally, after Ryan Howard’s Season 7 startup from The Office. “Michael invested ten thousand dollars in the original. This one is holding up slightly better so far.”

Community

“I have set this up in a remotely synced Obsidian Vault, i can now create my own wiki, query it with the agent and read it when I want to. I absolutely love it.” — u/seth76

The thread attracted modest engagement (17 upvotes, 1 comment at time of writing) with the standout observation being the Obsidian compatibility. Not surprising given the plain markdown substrate, but practically compelling for users already invested in personal knowledge management tools.

Key points:

WUPHF extends Karpathy’s LLM wiki pattern from personal use to multi-agent teams, with a notebook-wiki promotion flow as the governance layer
The entire system runs on plain markdown files and git history, no vector DB or cloud dependency required
Still pre-1.0 with 72 GitHub stars and active tuning on recall, but the architecture is sound and the data ownership is real

Karpathy showed that LLMs need persistent memory to compound knowledge. WUPHF asks the next question: what happens when a whole team of LLMs needs to share that memory without losing signal?