Decision
AI Agent Memory: Local vs Cloud
Choose between local-first memory and hosted memory based on privacy, portability, collaboration, and operational needs.
Article packet
Concepts
Developers and teams choosing a memory architecture
5 min read
01
Local memory keeps project context on your machine by default.
02
Cloud memory can simplify multi-device collaboration but changes the trust boundary.
03
Origin optimizes for local control, readable artifacts, and MCP portability.
01
Quick answer
Use local-first memory when the context is private, project-specific, or needs human-readable control. Use a hosted memory service when centralized collaboration and managed infrastructure matter more than local ownership.
Origin chooses the local-first side. It keeps the daemon, database, Markdown projection, and git history on your machine unless you opt into external model/API paths for richer maintenance.
02
When this problem appears
Memory contains the parts of work that matter: decisions, preferences, debugging lessons, client context, and project constraints. The storage boundary is therefore a product decision, not an implementation detail.
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Choose the boundary
Decide based on the sensitivity and collaboration shape of the work.
- Choose local-first for private repos, client work, personal preferences, and inspectable artifacts.
- Choose hosted memory when many users need central access with account-level governance.
- Use MCP when you want many clients to talk to one memory boundary.
- Document what leaves the machine before adding API keys or cloud sync.
- Compare backup, export, deletion, offline access, team sharing, and lock-in before deciding.
04
What to check next
Local-first keeps Origin's memory layer local by default, but connected AI tools may still send prompts and retrieved context to their own model providers. You still need backup, migration, and delete habits if the memory becomes important.
Try the local memory loop
Install Origin, connect your AI client, and verify that capture, recall, and handoff work on your machine.
FAQ