Agentic information architectures for efficient AI systems.
Architectural Gravity is a research and engineering program focused on the information structures surrounding model execution. The central premise is that capable models spend a significant portion of their finite inference capacity reconstructing what could instead be represented explicitly.
Architectural Gravity explores externalizing these relationships to reduce overhead, enabling increased model capacity to be directed toward reasoning, verification, and execution.
Architectural Gravity is a cross-model Agent Control Language for explicitly representing context, relationships, constraints, references, operations, and workflow structure inside ordinary model input
Architectural Gravity Studio provides language tooling for static analysis, validation, navigation, and diagnostics of ArcGrav composed artifacts
Architectural Gravity Benchmark is an evidence-first prompt benchmarking system for comparing registered prompt treatments under controlled execution boundaries with retained evidence and reconstruction verification
The broader Architectural Gravity research program around Model-Native Structural Representation (MNSR), including terminology, hypotheses, observational evidence, and experimental proposals