RUNE Protocol: Save AI Session Memory Across Platforms

RUNE (Relational User Notation for Entities) is an open-source protocol that lets you save your entire AI relationship to a single encrypted file, solving the cold-start problem where AI assistants start each session with zero memory of previous interactions.

What RUNE Does

The protocol addresses the issue where every new Claude session requires re-introducing yourself, re-explaining preferences, and re-establishing communication style. With RUNE, you can save your identity profile and conversation history to one small encrypted file that works across platforms.

Key Features

• Saves identity profile and conversation history to encrypted .rune file
• Works across platforms (created with Claude, loadable on GPT, and vice versa)
• Two modes: LOAD FULL (resume everything) or LOAD FRESH (fresh topic but AI still knows you)
• Encrypted with your passphrase - nobody else can read it
• You own the file, not the platform

How It Works

At the end of a session, you ask Claude to create a .rune file. In the next session, you upload it and provide your passphrase. Claude instantly knows who you are, how you communicate, what you've been working on, and everything from previous sessions.

Development Details

The project was built with Claude Opus 4.6 as the primary collaborator over thousands of hours of sessions. Claude helped design:

• The JSONL file structure
• The identity kernel concept
• The append-only memory ledger
• The encryption layer
• The MAKE/LOAD/APPEND lifecycle

Claude also wrote the research paper, created the README, validated cross-platform compatibility, and discovered an emergent self-healing property where drift corrections in one session automatically fix errors in subsequent loads. GPT-5.4 served as peer reviewer.

Technical Specifications

• Tested on Claude Opus 4.6, Claude Sonnet 4.6, GPT-5.2, and GPT-5.4
• Cross-platform verified
• Free and open source with no paid tiers
• GitHub repository includes copy-paste prompts for immediate use
• Includes plain-language PDF explainer alongside research paper

Resources

• GitHub: https://github.com/TooCas/RUNE
• Paper: https://doi.org/10.5281/zenodo.19378687