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- Add knowledge/convention/dual-memory-architecture.md with graph links to principles and layers - Update relative source references in knowledge concepts to point to categorized docs paths - Record changes in knowledge/log.md and sync knowledge/index.md
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2.4 KiB
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| Project | OKF Agent Memory Overview | A domain-neutral persistent project-memory system for AI agents based on the Open Knowledge Format (OKF) v0.2. | https://okf-memory.dev |
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OKF Agent Memory
The OKF Agent Memory project provides an open, vendor-neutral, and domain-agnostic persistent memory layer for AI agents, built directly on Google's Open Knowledge Format (OKF) v0.2.1
Problem & Vision
Conversations with AI agents are temporary and ephemeral. When a context window resets or a new session starts, valuable discoveries, architectural decisions, and domain facts are lost unless stored systematically.2
Traditional solutions often rely on proprietary vector databases, locked memory APIs, or unstructured scratchpads. OKF Agent Memory solves this by treating an OKF knowledge bundle inside the repository (knowledge/) as the single source of persistent truth.
flowchart LR
A[AI Agent] -->|Reads / Queries| K[knowledge/ bundle<br/>OKF v0.2]
A -->|Discovers & Persists| K
H[Human Developer] -->|Inspects & Edits| K
Key Capabilities
- Domain-Neutral: Functions equally well for software engineering, coaching, research, literature reviews, and operations.2
- Core Value Proposition: Key differentiators and selling points detailed in value-proposition.
- Deterministic Tooling & Separation of Concerns: Described in detail in architecture/layers.
- Principled Knowledge Lifecycle: Defined in convention/principles and convention/lifecycle.
- Phased Implementation: Detailed in the roadmap/milestones.