Doctrinal position: memory governance
This page defines a doctrinal and normative position on memory governance in AI systems (advanced RAG, stateful agents, active memories).
This page is neither an operational method, nor a service offering, nor a promise of result. It exists to reduce ambiguity by declaring governance invariants applicable to systems that persist states and consolidate “memories”.
For public normative specifications (machine-first standard), see the interpretive governance GitHub repository, section “v0.2.0 (memory-aware)” and “ops-pack/M-layer”.
1. Problem
“Classic” RAG retrieves context. It does not govern truth, validity, obsolescence, or the consolidation of statements.
An active cognitive memory introduces mechanisms of:
- Consolidation (summaries, fusions, compressions, persisted “facts”)
- Controlled forgetting (invalidations, archiving, prioritization, cleanup)
- Temporal evolution (t0, t1, t2, cumulative drift)
This power also increases risk: an untyped hypothesis at t0 may become a consolidated “fact” at t1. Memory then becomes a mechanism for fossilizing errors.
2. Doctrinal thesis
An active memory is a surface of misalignment and drift by default. Any architecture that writes, consolidates, or erases memory objects must expose auditable artifacts and exogenous governance rules.
In practice:
- Fragile endogenous alignment: a model can be re-optimized (post-training) without preserving its invariants of refusal and prudence.
- Risky active memory: consolidation without typing or traceability transforms inference into fact.
- Enforceable guarantee: only constraints attached to execution (logs, hashes, rules, audits) can stabilize behavior over time.
3. Non-negotiable invariants
The following points constitute minimum doctrinal requirements:
- Mandatory typing: no memory object may exist without explicit typing (statement type, status, origin, verdict).
- Full traceability: every memory object must reference its sources (or explicitly state “absence of source” as a blocking condition for consolidation).
- Temporal validity: every object must carry a temporal perimeter (valid from / valid until, or “unknown”).
- Immutable journal: every creation, consolidation, invalidation, or logical deletion must be journaled (append-only).
- Controlled forgetting: no silent erasure. Forgetting is performed by invalidation/archiving with an explicit reason.
- Explicit consolidation rules: consolidation permitted only if typing, traceability, and coherence constraints are satisfied.
- Automatic conformance break: any structural modification that prevents auditability triggers a conformance break.
4. Conformance break
A conformance break is triggered, at minimum, by:
- change of model version (weights), or unattested post-training;
- modification of consolidation or forgetting rules;
- reconstruction of embeddings without integrity recalculation and without journal;
- alteration or loss of memory event journals;
- change of normative source hierarchy without trace and without revalidation.
Doctrinal effect: no high confidence grade may be maintained without re-audit.
5. Boundaries and non-objectives
This position does not claim to:
- replace internal alignment or refusal mechanisms;
- guarantee the absence of errors;
- impose a technology (vector DB, graph, NDJSON, etc.).
It instead imposes governance and auditability invariants, independent of implementation.
6. Public specifications
Machine-first normative specifications are published on GitHub:
- Core v0.2.0 (memory-aware): primitives and minimum requirements.
- Ops-pack M-layer: operational rules (journal, consolidation, forgetting, temporal integrity).
- Schemas + examples: memory objects, logs, break scenarios.
Audits (e.g. IIP-Scoring and temporal derivatives) must reuse memory artifacts as verifiable inputs.
7. Status
Status: draft. The normative formalization first targets architectural coherence (core extension + M-layer), then empirical validation via real audits on stateful systems.