What is Persistent AI Memory?

AI assistants like Claude, ChatGPT, and Gemini start every session with a blank slate. They have no memory of previous conversations, decisions, or user preferences. Persistent AI memory solves this by storing structured facts in a cloud database and retrieving them when relevant.

The problem

When you tell Claude “I prefer dark mode and vim keybindings,” it remembers for the rest of that session. Start a new session tomorrow, and it has no idea. Switch to ChatGPT, and your preferences are completely gone.

This is not a limitation of the models themselves — it is a limitation of the context window architecture. The model only knows what is in its current context.

How persistent memory works

Persistent memory systems sit outside the AI model and store facts in a structured database. When a new session starts, relevant memories are retrieved and injected into the context window before the model generates a response.

The key components are:

Extraction — raw conversation text is processed into structured facts (e.g., “user prefers dark mode” with category “preferences” and salience score 0.8)
Storage — facts are stored in a searchable database with metadata (category, timestamps, decay parameters)
Retrieval — when a new session starts or a relevant query is made, facts are retrieved by semantic similarity and recency
Decay — old facts gradually lose salience, mimicking how human memory works (skills are evergreen, events fade quickly)

How HippoDid implements this

HippoDid provides persistent memory as a cloud API. AI agents connect via MCP (Model Context Protocol) or REST API. Memories are scoped to characters — named memory namespaces that represent an agent, a project, or a persona.

Store: add_memory("User prefers dark mode and vim keybindings")
Recall: search_memories("UI preferences") returns relevant facts ranked by salience and recency
Cross-platform: a memory written in Claude Code is readable in ChatGPT, Cursor, or any MCP client

Why “character” memory?

The term “character” comes from HippoDid’s design philosophy — each AI agent has an identity (a character) with its own memories, personality, and context. This is more than a key-value store: characters have profiles, background knowledge, and category-specific decay curves.

See the Quick Start to create your first character and store a memory in under 5 minutes.