Show HN: Architectural Gravity – Cross-Model Agent Control Language

A project called Architectural Gravity has launched as a research and engineering program built around a cross-model Agent Control Language for explicitly representing context, relationships, constraints, references, operations, and workflow structure inside ordinary model input. The program's premise is that capable models spend a significant portion of their finite inference capacity reconstructing information that could instead be represented explicitly, and that externalizing these relationships reduces overhead so more capacity goes to reasoning, verification, and execution. The release includes Architectural Gravity Studio, which provides language tooling for static analysis, validation, navigation, and diagnostics of ArcGrav composed artifacts, and the Architectural Gravity Benchmark, an evidence-first prompt benchmarking system for comparing registered prompt treatments under controlled execution boundaries with retained evidence and reconstruction verification, all under a broader Model-Native Structural Representation (MNSR) research program.

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