AI Companion Memory Correction UX: Fixing Wrong Memories Without Resetting the Relationship
How AI companions can let users correct, downgrade and replace wrong memories without wiping an entire relationship history.
Long-Term Memory
AI Companion Memory Write Policies: What Should Be Saved Automatically?
A practical framework for deciding which AI companion memories can be saved automatically, which need confirmation and which should never…
AI Companion Memory Consent: Designing Temporary, Session and Long-Term Memory
A practical framework for deciding what an AI companion should remember for minutes, sessions or months—and how users should control…
AI Companion Memory Decay: Why Some Personalization Should Fade Over Time
A practical framework for deciding which AI companion memories should persist, weaken or expire as relationships and preferences change.
AI Companion Memory Portability: What Should Move When Users Switch Platforms?
A practical framework for portable AI companion memory: what users should be able to export, what should stay private, and…
AI Companion Memory Confidence: How Systems Should Decide What to Remember
A practical framework for assigning confidence to AI companion memories so uncertain, stale or conflicting details do not quietly become…
AI Companion Conversation Recovery: How to Repair Awkward, Repetitive or Off-Character Chats
A product framework for detecting and recovering from repetitive, awkward, contradictory or off-character AI companion conversations.
AI Companion Context Windows: What Should Stay in the Prompt—and What Belongs in Memory?
A practical architecture guide to deciding what belongs in an AI companion's active context, long-term memory and retrieval layer.
AI Companion Memory Controls: What Users Should Be Able to See, Edit and Forget
A practical product guide to user-facing AI companion memory controls: visibility, correction, deletion, sensitivity rules, retention and trust.
AI Companion Memory Failure Modes: How to Detect, Repair and Prevent Bad Memories
A practical guide to AI companion memory failures including false recall, stale preferences, duplicate facts, over-retrieval and privacy mistakes—and how…
AI Companion Relationship Stages: Designing Progression Without Manipulative Engagement
How AI companion products can design relationship progression around trust, continuity and user choice without turning intimacy into a manipulative…
AI Companion Personalization: How to Adapt Without Losing a Stable Identity
A practical framework for AI companion personalization that adapts to users while preserving a coherent, recognizable personality over time.