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How to use AI agents better than 99% of people
Omnigraph implements Git-style branching and atomic commits for shared AI agent memory using standard cloud object storage.
What: Neo Kim outlines how Omnigraph uses AWS S3 and a schema-based graph approach to solve memory fragmentation among multiple AI agents. It leverages Apache Lance, Arrow, and DataFusion to allow agents to propose changes in isolated branches, which are then merged via policy-governed commits to prevent conflicting writes or hallucinations from polluting shared context.
Why it matters: This represents a necessary evolution for multi-agent systems, shifting from unstructured vector databases or flat files toward structured, audit-ready data models that mimic modern software development workflows.
Deep dive
- Memory Fragmentation: Standard setups have agents using disconnected files or simple vector databases, leading to context loss.
- Graph Structure: Uses nodes and edges to maintain relationships between entities like users, services, and deployments.
- Atomic Commits: Uses a manifest-based versioning system on object storage to ensure all-or-nothing writes, preventing partial state corruption.
- Isolation: Agents work in branches; changes are only merged to main after approval or policy validation.
- Conflict Handling: Implements compare-and-swap (CAS) logic to detect and block clashing concurrent writes.
- Unified Retrieval: Combines graph traversal, BM25 keyword search, and vector similarity via Reciprocal Rank Fusion (RRF) for consistent context retrieval.
- Policy Engine: Uses AWS Cedar for access control, ensuring only authorized actors can perform specific graph operations.
Decoder
- Vector database: A storage system that indexes data as high-dimensional mathematical vectors to allow for semantic rather than keyword-based search.
- RAG (Retrieval-Augmented Generation): A technique where an AI model retrieves relevant documents from an external source before generating a response to reduce hallucinations.
- Object storage: Scalable cloud storage (e.g., AWS S3) that manages data as objects rather than a file system, often used for massive datasets.
- Compare-and-Swap (CAS): An atomic instruction that updates a memory location only if its current value matches a provided expected value, used to prevent race conditions.
- Reciprocal Rank Fusion (RRF): A method for merging multiple search results by calculating scores based on the items' rankings in separate lists.
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