123 lines
7.2 KiB
Markdown
123 lines
7.2 KiB
Markdown
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# Video Synthesis — The 6 Levels of Claude Code Memory
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Synthesis of the YouTube video "The 6 Levels of Claude Code Memory" plus the referenced
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articles (John Connelly / Pawel Huryn). This is background: the source of several ideas in our
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design. Our system borrows from Levels 1–3 and deliberately ignores 4–6.
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## The framing
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Every memory system answers the same question: **when you give Claude Code a task, how does it
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pull the right context at the right time?** Each level differs on just two axes:
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- **Where memory lives** — the storage mechanism and file structure (markdown vs vectors,
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local vs cloud).
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- **How Claude gets it** — the retrieval stage (auto-injected into context, searched on
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demand in a DB, etc.).
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The recurring enemy is **context rot**: as you load more context, the model recalls less of it
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reliably. The cure throughout is **progressive disclosure** — load a small *index*, pull the
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detail only when needed.
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## The levels
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### Level 1 — What ships natively (CLAUDE.md + memory.md / automemory)
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- **CLAUDE.md**: plain markdown in the project, always loaded every session like a system
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prompt. Hierarchical (project-folder → root → individual project); lower levels inherit the
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parent but local rules win on conflict.
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- **Common mistake**: stuffing it full (brand guide, tone doc, client list) → burns context →
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context rot. **Rule of thumb: keep CLAUDE.md under 200 lines**; push larger context into
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separate files *referenced* from CLAUDE.md so they load only when needed.
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- **memory.md / automemory**: `/memory` shows imported/project/user memory. Auto-memory keeps a
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per-project `memory.md` that acts as an **index of pointers** to many small memory files —
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Claude quietly takes notes in the background and builds the index.
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- Anthropic is clearly working on this natively (leaked references to an unreleased always-on
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consolidation daemon, "Chyros"). Native memory will only get better.
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### Level 2 — Forcing reliable recall (Connelly hook / Huryn structure)
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- Paste a memory-management prompt + rules into CLAUDE.md. Structured memory rooted at
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`~/.claude/memory/`: `memory.md` (index), `general.md` (cross-project facts/prefs/env),
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`domain/<topic>.md` (one file per topic), `tools/<tool>.md` (one file per tool, e.g.
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`slack.md` with config/workarounds/edge cases).
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- A **session-start hook** auto-injects the **index** (not full content) into every session and
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sub-agent — not relying on Claude choosing to read it.
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- A **"reorganize memory"** command periodically reads all memory files, removes
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duplicates/outdated entries, merges related ones, splits overloaded files, sorts by date,
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and rebuilds the index.
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- Huryn's updated post (productcompass.pm) adds **active hypothesis tracking**, a **catalog of
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"false beliefs,"** and an **AI-proposes-reorganization / human-keeps-editorial-control**
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loop. The transferable mechanic (not the content-writing domain) is the hypothesis/
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false-belief log + propose-and-approve loop — useful for per-client "what we tried / decided
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/ what didn't work."
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- **Author's take: most people should stop here.**
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### Level 3 — Search by meaning, not keywords (memsearch; OpenClaw template)
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- Add only if you've used Claude Code > 1 month, have many memory files, and have asked
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something you *know* is in your notes that Claude couldn't find.
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- **OpenClaw memory design (3 layers)**: (1) `memory.md` = long-term durable facts, loaded at
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session start; (2) **daily note files** = one per date, a running log, today+yesterday
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auto-loaded, older left on disk; (3) optional **"dreaming"** = background process that scores
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daily notes and promotes recurring ones into long-term memory, forgetting stale stuff.
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- **memsearch** (by Zilliz): ports this into Claude Code as a two-line plugin. Markdown-first,
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same chunking/structure. Chunks into semantic vectors; a **user-prompt-submit hook
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auto-injects the top-3 semantic matches** into every prompt. Plain-readable markdown.
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- Alternative **claude-mem**: MCP-based, 3-tier storage (summaries/timeline/observations),
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dashboard/team/cost features. Author's view: overkill, and MCP-based means Claude must
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actively call the search tool; stores opaque blobs vs memsearch's readable markdown.
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### Level 4 — Verbatim conversation recall (MemPalace)
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- Local RAG, free, claims highest published benchmark. Stores words **verbatim** (nothing
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summarized) indexed in a dense symbolic dialect ("memory palace": wings → rooms → closets →
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drawers). Two DBs: SQL (entities/relationships) + Chroma (vector chunks). Background hooks on
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session-end/pre-compaction. ~42ms retrieval.
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- **Downsides**: storage is **not readable markdown**; drawers are **isolated** (knowledge not
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interconnected); local-only.
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### Level 5 — Self-organizing knowledge base (Karpathy LLM wiki; Recall; LightRAG)
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- Karpathy's **LLM wiki**: `raw/` (you drop sources, Claude reads, never writes) + `wiki/`
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(Claude owns entirely). Plain markdown, Obsidian graph. **Recall** is a hosted done-for-you
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version (you don't own the data). **LightRAG** is enterprise knowledge-graph overkill.
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- **Author's take**: these are for **content knowledge bases / deep research**, NOT operational
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memory ("what did we decide about client X's landing page in March"). Skip for our use case.
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### Level 6 — One brain for all AI tools (OpenBrain; Mem0)
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- **OpenBrain**: memory in a **Postgres DB you own** (Supabase), one `thoughts` table (text +
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embedding + tags + timestamp), MCP server fronting it so any AI tool shares the same memory.
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Most portable/future-proof. **Downsides**: longer/harder setup; **always remote → latency on
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every query**; small monthly cost. **Mem0**: cross-tool layer, fast setup, but data lives on
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their servers permanently.
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- **Author's take**: only if you live across many AI tools and want real-time shared memory.
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## Author's recommendation
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- Just starting → Level 1 done right.
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- A bit in → Level 2 (Connelly hook). **Most should stop here.**
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- Lots of context, losing old decisions → Level 3 (memsearch) or Level 4 (MemPalace).
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- Levels 5–6 are a different realm for specific use cases.
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- **Levels 1+2+3 stack** (similar folder structures). The author personally runs up to Level 3:
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OpenClaw conventions + semantic search + injection hooks.
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## What we took / left (see ADRs for why)
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- **Took**: progressive-disclosure index (L1/L2), per-tool/per-domain granularity + reorganize
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command + session hooks (L2), Huryn's propose-and-approve reorg loop, OpenClaw daily-notes +
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dreaming and memsearch (L3).
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- **Replaced**: L2's **folders** with **namespaced tags** in a flat vault.
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- **Left**: MemPalace (opaque, isolated), Recall/LightRAG (content KB, not operational),
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OpenBrain/Mem0 (always-remote, fights local-fast).
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## Reference links
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- John & Pawel's system — youngleaders.tech/p/how-i-finally-sorted-my-claude-code-memory
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- Pawel Huryn (updated) — productcompass.pm/p/self-improving-claude-system
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- memsearch — github.com/zilliztech/memsearch
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- MemPalace — github.com/MemPalace/mempalace
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- Karpathy LLM wiki — gist.github.com/karpathy
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- Recall — recall.it · Mem0 — mem0.ai · OpenBrain — github.com/NateBJones-Project
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- QMD (our deferred semantic layer) — github.com/tobi/qmd
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