I define my product philosophy around AI memory as a set of explicit guiding principles that put the user at the center, demand explicit consent, ensure every stored item is provably linked to evidence, make corrections frictionless, and embed trust and provenance directly into the architecture.
- User‑Owned Memory – Memory data belongs to the individual user, not the AI provider.
- Consent‑First – Explicit user consent is required before any memory is recorded, accessed, or used.
- Traceable to Evidence – Every stored memory item must be linkable to verifiable evidence (timestamp, source identifier, or audit log).
- Easy to Correct – Users can edit, update, or delete memory entries without undue friction.
- Trust & Provenance as First‑Class Capabilities – Trustworthiness and provenance tracking are built into the core system architecture.
These principles drive the concrete decisions I make when designing AI memory services.
- Decision 1 – Make memory ownership explicit to guarantee user control and comply with data‑rights regulations.
- Decision 2 – Require consent before any memory operation to prevent inadvertent capture and respect autonomy.
- Decision 3 – Include immutable evidence links with each memory entry for verification and auditability.
- Decision 4 – Provide user‑friendly correction interfaces to reduce friction and improve data hygiene.
- Decision 5 – Design trust and provenance as core system services to ensure consistent application across all memory interactions.