Results for “storage-engines”

Prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.

Designs persistent memory architectures for AI agents, covering cross-session knowledge retention, entity tracking, temporal validity, graph/vector retrieval, and memory consolidation.

Provides a persistent, queryable virtual filesystem backed by SurrealDB for AI agents, with a Rust core and a Python agent interface.