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ACORN / CASE STUDY

A fresh chat. The same memory.

  • Memory architecture
  • Retrieval
  • Recovery
TESTED

Problem

Useful context was scattered across conversations and tied to whichever AI held the chat.

My design choice

Give memory its own record outside the chat. Keep the source and corrections with it, then prove a new session can recover it.

What I built

Independent, event-based memory with source records, decisions, corrections and explicit inference labels.

How it works

Selected records are saved outside the AI provider. A fresh authorised controller retrieves relevant context; a local cache can be rebuilt from the canonical copy.

Verification

A real private decision was saved through the remote controller, read back from Drive, restored into a temporary fresh cache and retrieved by a separate controller process.

Limitations

Sensitive records are excluded by default. Controllers must actively capture meaningful changes. This is not automatic recording of every conversation.

What I learned

Continuity depends on attribution and recovery, not the length of a chat window.

This is a sanitised account of Chris’s own system. Private memory, account details and research data are not connected to this website.

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