Core Topic / AI Agent Memory

AI Agent Memory is the context your future agent can call.

Short-term context disappears when a conversation ends. Personal agent memory should persist: your sources, choices, preferences, blind spots, and the way you connect ideas.

Memory model

Short-term context vs long-term memory

A model's context window is short-term memory. It is useful, but it is temporary and expensive to fill with everything you have ever saved.

Long-term agent memory is different. It is a durable index of the material and decisions that define your work. The agent can retrieve from it instead of asking you to repeat yourself.

Why personal

Private workflows need personal knowledge, not generic memory

Generic AI memory can remember preferences inside one product. Personal agent memory should represent your own knowledge base: notes, sources, projects, and the patterns that make your judgment yours.

For research, writing, coding, planning, or personal CRM, the value is not only what the model knows. It is whether it can call the context that belongs to you.

Walnut role

How Walnut can serve as a memory layer

Walnut keeps a local-first index of your knowledge. It separates capture, indexing, review, and AI suggestions so your second brain can become a stable memory substrate.

That memory layer can support future personal agents because it records not only documents, but also entities, concepts, links, edits, and the context behind decisions.

Use cases

Practical ways to use Walnut

Research memory

Remember papers, claims, sources, and unresolved questions.

Writing memory

Bring back old notes when a new draft touches the same topic.

Coding memory

Keep product decisions, architecture notes, and bug context callable.

Planning memory

Preserve why a project moved in one direction instead of another.

Personal CRM

Keep people, meetings, and promises connected to source notes.

FAQ

Questions people actually ask

Is AI agent memory just chat history?

No. Chat history is one signal. Useful agent memory also includes durable sources, concepts, relationships, preferences, and decisions that can be cited and reviewed.

Why should memory be local-first?

Personal memory contains private context. Local-first storage keeps the default boundary on your device and lets you choose when to sync, upload, or send AI requests.

Can Walnut train my personal agent today?

Walnut is building the second-brain and index layer that can become the foundation for a personal agent. We avoid claiming full agent training before those features exist.