I gave my LLM a Cortex
Every LLM session boots blind. Close the window and it forgets everything: the notes, the transcripts, the decisions you already made. It all piles up write-only, never read back. So you re-explain yourself from scratch. Every single time.
Bigger context windows do not fix this. They are rented, and they reset. So I stopped prompting harder and built a brain underneath the model instead.
Cortex is a memory layer between your files and any model. The principle:
Files own the truth. The brain owns the connections.
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How it works, borrowed from human neuroanatomy:
1. Regions.
Every memory is tagged by where it lives: language, vision, episodic events, project structure, identity. Retrieval comes back grouped that way, not as one flat pile.
2. Tracts.
Memories are wired by typed edges.
Some are fixed (a prompt to its answer, an image to its caption).
Others grow by use: anything retrieved together often enough forms a permanent link.
Fire together, wire together. Cold edges decay.
3. Consolidation.
The brain sleeps.
Raw capture distils through five tiers (raw, session, daily, weekly, promoted fact).
A year of thinking compresses about 37x, and every fact still walks back to its source.
Nothing is deleted. Importance decays, rows do not.
4. Modes.
The same brain retrieves differently in creative versus deep versus fast-recall.
Neuromodulation as a config flag.
5. Auto-recall.
A session-start hook injects the right context into turn one, and edits re-index on the fly.
The brain reminds you. You never have to remember to ask.
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It runs locally, needs no API key, and stays model-agnostic. Claude, Codex, Gemini, or a model on your own machine plug in through injected context, a thin adapter, or MCP. Delete the index and rebuild it from your files with one command. Lose the index, lose nothing.
The model is the replaceable part. The brain is what persists.
//A<3
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Ari Evergreen
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I gave my LLM a Cortex
Clief Notes
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Jake Van Clief, giving you the Cliff notes on the new AI age.
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