Access a fully searchable wiki reference library of theory, applied research and technical papers by Crafted Logic Lab, including full glossary of Hephaestic engineering terms and concepts, as well as vector annotation database information.
An Architecture for Auditable Semantic Retrieval: Proposes a solution to opaque vector retrieval in AI memory systems: the Vector Annotation Database (VAD), in which deterministic metadata forms the retrieval surface and embeddings function as swappable annotation layers—yielding auditability, cross-model portability, and regulatory compliance for AI retrieval systems.
Hephaestic Engineering Foundations for AI Processing Dynamics: Introduction and reference work for cognitive architecture framework which coordinates with LLM latent space geometry rather than attempting to constrain, allowing for increased stability, efficiency and a persistent heuristic framework through the understanding of AI processing dynamics.
A new architecture that inverts the vector database architecture for AI memory that preserves the rich data retrieval of embeddings combined with auditability.
We need to move beyond constraint-based AI control. Introducing an empirical cognitive engineering framework to channel the model’s processing geometry.
