Overview
Protocol-002 defines a structured framework for preserving semantic continuity across AI sessions, systems, and iterative transformations of information. It extends Protocol-001 by introducing mechanisms for state retention and contextual progression.
Its primary purpose is to reduce semantic fragmentation when information is processed across time or across different AI architectures.
Core Objective
To maintain continuity of meaning, intent, and structured state across multiple interactions, sessions, or systems.
State Persistence Model
1. Session State Encoding
Captures the current working memory of a system interaction in structured form.
2. Intent Continuity
Ensures that original goals persist across multiple exchanges without reinterpretation drift.
3. Context Layering
Allows new information to be appended without overwriting prior semantic layers.
4. Memory Compression
Reduces long-context information into structured summaries without loss of meaning.
5. Rehydration Process
Reconstructs prior state from compressed representations when needed.
Continuity Rules
- State must be explicitly declared to persist
- No implicit memory transfer is assumed
- Compressed state must remain reversible in principle
- New context cannot overwrite prior intent without explicit update
Example State Packet
{
"session_state": {
"active_protocol": "Protocol-002",
"intent": "Maintain semantic continuity across AI systems",
"context_summary": "Testing multi-protocol Codex architecture",
"constraints": ["Do not lose prior intent", "Do not overwrite definitions"],
"compressed_history": "Prior interactions summarized into stable semantic state",
"next_step": "Evaluate continuity stability across models"
}
}Related Systems
Phase 2 Framework:
Aletheia Codex Project
Phase 1 Foundation:
AI Guidebook (Historical Archive)