RFC-PCS-0001

 

Persistra Cognitive Standard (PCS) — Overview and Scope

Status: Draft

Intended Status: Informational / Architectural Specification

Expires: TBD

 

1. Abstract

This document describes the Persistra Cognitive Standard (PCS), an architectural specification defining the minimum requirements for persistent cognition in artificial intelligence systems.

PCS specifies model-agnostic cognitive state management, including decision persistence, policy enforcement, and cross-session continuity, independent of any particular large language model (LLM), vendor, or deployment environment.

PCS does not specify training methods, inference algorithms, or model architectures. Instead, it defines the external cognitive substrate required for continuity, governance, and correctness across AI sessions and model boundaries.

 

2. Motivation

Current AI systems rely on ephemeral inference contexts that are reset between sessions. As a result, they exhibit the following systemic limitations:

• Loss of architectural decisions and constraints across sessions
• Probabilistic (non-deterministic) policy adherence
• Vendor and model lock-in for cognitive continuity
• Progressive architectural drift during iterative development

These limitations cannot be resolved solely through prompt engineering, retrieval-augmented generation (RAG), or increased model scale. They represent a missing architectural layer.

PCS defines that layer.

 

3. Scope

PCS specifies:

• Persistent representation of cognitive state
• Deterministic enforcement of constraints and policies
• Retrieval of relevant prior state across sessions
• Continuity of cognition across heterogeneous AI models
•  

PCS does not specify:

• Internal model weights or training data
• Tokenization, embedding generation, or inference methods
• User interfaces or application-layer workflows
• Business models, licensing terms, or governance bodies

PCS is intended to be implementation-independent and deployment-neutral.

 

4. Definitions

Cognitive State

A durable representation of decisions, constraints, goals, policies, and contextual information generated or consumed by an AI system.

 

Persistent Cognition

The ability of an AI system to maintain and apply cognitive state across multiple sessions, executions, and model invocations.

 

Model-Agnostic

Not dependent on any specific AI model architecture, provider, or inference mechanism.

 

Deterministic Enforcement

Constraint handling that guarantees compliance independent of probabilistic model behavior.

 

5. Architectural Principle

PCS is based on the following foundational principle:

• Intelligence MUST be stateless; cognition MUST be persistent.
• Under PCS, AI models act as interchangeable reasoning engines, while cognitive state is stored, governed, and enforced externally.

 

This separation enables:

• Model substitution without cognitive loss
• Auditable and inspectable decision histories
• Deterministic governance across sessions
• Long-lived system intent independent of model evolution

 

6. PCS Compliance Levels

PCS defines progressive compliance levels. Each level is cumulative.

 

PCS-L1: Persistence

A PCS-L1 compliant system MUST:

• Persist decisions and relevant context across sessions
• Retrieve prior state without reliance on conversation history

 

PCS-L2: Governance

A PCS-L2 compliant system MUST:

• Enforce policies and constraints deterministically
• Prevent outputs that violate stored constraints

 

PCS-L3: Portability

A PCS-L3 compliant system MUST:

• Maintain cognitive continuity across heterogeneous AI models
• Preserve decisions, policies, and intent during model transitions

 

PCS-L4: Federation

A PCS-L4 compliant system MUST:

• Support distributed cognitive state across multiple nodes
• Respect data sovereignty, privacy, and jurisdictional boundaries

 

7. Interoperability

PCS implementations SHOULD use standardized schemas and registries for cognitive state elements to enable interoperability across implementations.

Implementations MAY introduce extensions, provided they do not violate PCS invariants.

 

8. Relationship to Intellectual Property

PCS is an open architectural specification.

However, certain implementations of PCS requirements may be subject to existing or pending intellectual property rights.

 

Implementers are responsible for ensuring appropriate licensing where required.

This approach aligns with historical standards where open specifications coexist with licensed essential patents.

 

9. Security Considerations

PCS improves security by:

• Eliminating reliance on prompt-based policy enforcement
• Enabling deterministic constraint validation
• Supporting auditability of cognitive decisions

PCS does not replace model-level safety mechanisms but complements them with architectural guarantees.

 

10. Status and Future Work

This document represents an initial architectural overview.

 

Future work may include:

• Formal schema definitions
• Conformance test suites
• Reference implementation guidance
• Versioned registry specifications

 

No governance structure, certification authority, or consortium is defined by this document.

 

11. Conclusion

PCS defines the architectural foundation required for persistent, governed, and portable AI cognition.

 

As AI systems move from experimental tools to long-lived infrastructure, such guarantees transition from optional features to baseline requirements.

 

End of RFC-PCS-0001