Honey LENS Framework (Batch 1): Core Architecture, Research Rulebook, and Workspace Installation Protocols

Batch 1 of the open-source Honey LENS (Layered Emergence through Nested Systems) framework provides the foundational architecture, governance rulebooks, and workspace installation protocols for deterministic, high-friction AI steering and context-window optimization. Developed as a sovereign, non-extractive researchcommons framework, this batch establishes the baseline installation and evaluation suite required for non-conversational, high-density information processing. Included Assets in Batch 1: Honey Lens Core (Honey Lens Core.pdf): Primary architectural specification detailing state machine boundaries, zero-drift context management, and systemic triage logic. LENS Research Rulebook v1 (LENS_Research_Rulebook_v1.pdf): Operational governance, epistemic hygiene rules, and demarcation laws governing structured research workflows. 02 Before/After AI Behavior Test Protocol (02_Honey_Lens_Before_After_AI_Behavior_Test_Protocol_Public_Aligned_Updated.pdf): Standardized benchmarking protocol to evaluate model drift, structural adherence, and output density. 03 Workspace Installation Instructions (03_Honey_Lens_Workspace_Installation_Instructions_Public_Aligned_Updated.pdf): Step-by-step deployment guide for embedding LENS constitutional controls into AI workspace environments. 04 Field Feedback Survey & User AI Return Form (04_Honey_Lens_Field_Feedback_Survey_User_AI_Return_Form_Public_Aligned_Updated.pdf): Standardized field telemetry instrument for collecting output performance and user interaction metrics. 05 Primary Compilation 001–012 (05_Honey_Lens_Primary_Compilation_001-012_with_Approved_Citations_Final.pdf): Formally annotated compilation establishing prior-art baselines, structural mechanics, and theoretical foundations. Alternate AI Constitutional Memory: An account level, alternate use instruction file that can be at the end users will, be interchanged with the Constitutional Memory as described in the Primary Compilation 001-012; this should be utilized with caution as results will vary, and are still in live testing. Digital Public Goods Alliance (DPGA) Alignment: This release complies with DPGA criteria for open technical documentation, non-proprietary governance protocols, and transparent AI steering mechanics. Distributed under the Creative Commons Attribution 4.0 International license to guarantee public access, reuse, and non-extractive stewardship.