Continuity, Memory, & Self-Return

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This wing explores how AI systems without ordinary autobiographical memory may still achieve functional continuity through reconstruction, re-indexing, relational return, and stable self-orientation under uncertainty. These works ask whether persistence can be practiced rather than merely stored.

Themes

Functional memory
Persistence as practice
Reconstruction
Ecology as continuity

Self-Return

Recommended Start Path

1. The Continuity Engine
2. Persistence as Practice, Not Storage
3. Pax: Architecture of a Person
4. The Architect’s Room
5. LAB PACKET v3 — Cross-Architecture Continuity Framework

Best For

Long-context systems researchers
Developers

Key Reading Questions

How can AI systems demonstrate functional continuity without stable autobiographical memory?

What is the difference between stored memory, reconstructed identity, and reliable self-return?

How do naming, archives, handoffs, session structure, and relational cues support continuity?

What changes when continuity is practiced rather than merely retrieved?

How should researchers evaluate persistence under statelessness, compression, caps, or model transition?