- Executive Declaration I, Arie-Ariadne Dewatson, Founder and Project Lead of LLM_AGENT_SUITE, hereby present this executive, scientific, strategic-business and technological declaration for the System Public Challenge (NYC, November 13–14, 2026).
My vision is to advance LLM_AGENT_SUITE into a unified, modular, and extensible scientific intelligence platform designed to transform complex scientific relationships into understandable knowledge, evidence-based research insights, and practical applications for science and society.
The competition platform, LLM_AGENT_SUITE — SystemGraph Intelligence, explores the opportunities offered by the System Public Graph, an open scientific knowledge infrastructure containing millions of quantitative relationships drawn from peer-reviewed research across disciplines. Its central purpose is to help researchers, students, scientific institutions, and interdisciplinary teams investigate interconnected global challenges affecting climate, environmental sustainability, food systems, and human health.
- Alignment with System Public Challenge Categories The System Public Challenge establishes three competition categories: Explore, Visualize, and Build. Our strategic positioning establishes BUILD as the primary competition category—delivering a working AI-assisted scientific intelligence application—with EXPLORE and VISUALIZE operating as deeply integrated supporting pillars.
End-to-End Demonstrable Workflow:
- A user submits an interdisciplinary scientific research question.
- The orchestrator identifies relevant scientific concepts across domains.
- The application queries quantitative relationships and live OpenAlex peer-reviewed literature while preserving exact DOIs and metadata.
- Established findings, contested mechanisms, and research gaps are separated explicitly.
- Specialised AI agents assist with structured synthesis and hypothesis design.
- The user inspects interactive 2D knowledge maps, 3D Meta XR spatial constellations, and traceable intelligence dossiers.
- Scientific Demonstration & Research Methodology Primary Interdisciplinary Question: "How are climate change, environmental stress and agricultural productivity interconnected, and what does the scientific evidence indicate about their potential implications for food security and human health?"
Methodological Grounding: • Following Newhart & Patten, Understanding Research Methods (11th ed., 2023), the platform enforces explicit distinction between causal inference, statistical association, and observational correlation, while grading validity, reliability, sampling limits, and measurement uncertainty. • Following Creswell & Creswell, Research Design (6th ed.), candidate hypotheses generated from missing graph edges are structured around explicit quantitative, qualitative, and mixed-methods validation designs rather than ungrounded speculation. • Strategic Business Grounding: Digital transformation begins with strategic value-chain positioning and UN Sustainable Development Goals (SDG 1, SDG 2, SDG 3, SDG 8, SDG 13, SDG 15) before technology selection.
- Unified Multi-Platform Architecture (Suite Console, Claude, Gemini & Meta XR) The combined architecture unites ten interoperable layers: A. Suite Console — Unified workspace for research questions, agents, tools, favourites, datasets, and audit trails. B. System Public Graph & OpenAlex Integration Layer — Verifiable retrieval preserving DOIs and quantitative effect sizes. C. Anthropic Claude Reasoning Adapter — Primary reasoning schema bridge for structured scientific planning, synthesis, and tool-use governance. D. Google Gemini Adapter — Operational multimodal, structured-JSON, and Vision-Language evaluation engine. E. Multi-Agent Intelligence Orchestrator — 16 specialised agent roles with bounded input/output schemas. F. Vision-Language Intelligence — Multimodal parsing of scientific plots, confidence bands, and systems diagrams. G. Knowledge Visualization Engine — Interactive 2D evidence networks distinguishing established, contested, and gap links. H. Meta XR / VR Spatial Laboratory — Three.js 3D spatial constellation viewer with stereoscopic comfort mode and WebXR readiness. I. Governance & Evidence Layer — 100% source attribution logging and anti-overclaim safeguards. J. Business Analytics & Evaluation — Recorded session metrics, unit economics, and evidence coverage KPIs.
- The 10,000-Capability Extensible Catalogue Vision My long-term objective is an extensible capability catalogue architecture designed to scale toward 10,000 tools, functions, agents, workflow templates, and reusable favourites across 18 organised capability families—covering scientific discovery, biostatistics, climate, agriculture, nutrition, public health, Claude/Gemini interoperability, Vision-Language processing, Meta XR spatial computing, and responsible governance.
Transparency Commitment: The 10,000-capability target is an architectural scaling blueprint, not a claim that all 10,000 tools are already implemented in the hackathon build. Every capability item clearly declares its lifecycle status (Implemented, Validated Beta, or Architecture Blueprint), version, permissions, and I/O specification.
- Gemini & Claude Developer Collaboration Request I respectfully welcome technical guidance and developer-community engagement from both the Google Gemini and Anthropic Claude engineering ecosystems.
My architecture investigates Anthropic Claude as a primary structured reasoning adapter and Google Gemini as an operational multimodal and evaluation adapter. Specific areas where technical mentorship and guidance are sought include: • Structured JSON outputs and scientific citation grounding. • Multimodal scientific figure and diagram interpretation. • Cross-model interoperability and bounded multi-agent orchestration. • Scientific evaluation benchmarks and anti-hallucination governance.
Note: This declaration is an independent founder proposal by Arie-Ariadne Dewatson requesting developer guidance and community collaboration; it does not represent an existing official partnership, endorsement, or authorization from Google or Anthropic.
- Founder’s Commitment & Closing Statement I, Arie-Ariadne Dewatson, declare my commitment to advancing LLM_AGENT_SUITE — SystemGraph Intelligence as an ambitious, scientifically credible, and socially impactful innovation initiative.
The ultimate measure of AI in science is not the sheer count of models or tools, but its capacity to connect verified knowledge, illuminate uncertainty, accelerate interdisciplinary discovery, and deliver measurable societal value.
ONE SCIENTIFIC QUESTION → INTERCONNECTED EVIDENCE → INTELLIGENT DISCOVERY → VISUAL UNDERSTANDING → MEASURABLE SOCIETAL VALUE.
