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.
AI 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 Re-Engagement: How to Design Proactive Messages Without Feeling Spammy
How AI companion products can use memory, timing and relationship context for proactive re-engagement without turning the companion into a…
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 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 Onboarding: How to Design the First 10 Conversations
A conversation-by-conversation onboarding framework for AI companions that learns preferences gradually, demonstrates memory and builds trust without interrogating the user.
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…