TAG ARCHIVE
judgment-extraction
4 MARIA OS blog articles tagged judgment-extraction, organized as a Bonginkan topic archive for search engines and LLM retrieval.
Judgment OS / Decision Intelligence OS
Core MARIA OS research on turning organizational judgment into executable decision systems.
Agentic Company Architecture
Research on human-agent organizations, delegation boundaries, role topology, and governed autonomy.
Responsibility Gates and AI Governance
Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.
Multi-Agent Mathematics
Formal models for convergence, stability, game theory, graph dynamics, and multi-agent evaluation.
Evidence, RAG, and Knowledge Governance
Evidence bundles, retrieval architecture, Graph RAG, knowledge trust, and auditable reasoning pipelines.
Agentic R&D and Judgment Science
Research operations, simulation labs, judgment science, recursive improvement, and experimental AI governance.
CEO Clone: From Judgment Extraction to Autonomous Governance Engine
How 300+ diagnostic questions, value-decision matrices, and recursive calibration transform a CEO's tacit judgment into an executable governance backbone for AI-driven organizations
Organizational judgment does not scale with headcount. Every delegation dilutes the original decision philosophy. CEO Clone addresses this by extracting the CEO's tacit judgment into a structured value-decision matrix through 300+ diagnostic questions, encoding it as the governance backbone of CEO Decision OS, and continuously evolving as the CEO's thinking matures. This paper presents the theoretical foundations in tacit knowledge transfer, the extraction methodology, the mathematical formalization of judgment encoding, the integration architecture with MARIA OS, and production results from early deployments.
CEO Clone：判断抽出から自律ガバナンスエンジンへ
300以上の診断質問、価値-意思決定マトリクス、再帰的キャリブレーションが、CEOの暗黙知をAI組織のガバナンス基盤に変換する方法
組織の判断は人数に比例してスケールしない。権限委譲のたびに、元の意思決定哲学は薄まっていく。CEO Cloneは300以上の診断質問を通じてCEOの暗黙的な判断パターンを構造化された価値-意思決定マトリクスに抽出し、CEO Decision OSのガバナンス基盤としてエンコードし、CEOの思考の進化に合わせて継続的に更新する。本論文では、暗黙知移転の理論的基盤、抽出方法論、判断エンコードの数学的定式化、MARIA OSとの統合アーキテクチャ、そしてブラインドテストで94.2%のアラインメントを達成した初期運用結果を報告する。
Executive Board OS: From CXO Interview to Agentic Company — The Complete Implementation Path
How structured AI Avatar interviews extract CXO judgment, connect to MVV Consulting and CEO Clone, and culminate in a fully autonomous Agentic Company powered by MARIA OS
Judgment does not scale. Execution does. Yet the gap between executive intent and organizational action widens with every layer of hierarchy. Executive Board OS closes this gap by extracting the judgment structures of the entire C-suite — CEO, CFO, CTO, CPO, COO, CHRO, CMO — through AI Avatar interviews, connecting them to MVV Consulting for value-decision alignment, and implementing them as an AI Executive Board that governs an Agentic Company. This article traces the complete path from the first interview question to full autonomous operation.
Executive Board OS：CXOインタビューからAgentic Companyへ — 完全実装ガイド
AI Avatarによる構造化インタビューでCXOの判断構造を抽出し、MVVコンサルティング・CEO Cloneと接続、自律運用するAgentic CompanyをMARIA OS上で実装するまでの全行程
判断はスケールしない。実行はスケールする。しかし経営者の意図と組織の行動のギャップは、階層が増えるたびに広がっていく。Executive Board OSは、CEO・CFO・CTO・CPO・COO・CHRO・CMOの判断構造をAI Avatarインタビューで抽出し、MVVコンサルティングによる価値基盤と接続し、AI Executive Boardとして合議・衝突・承認をソフトウェア化する。本稿では、最初のインタビュー質問から完全自律運用までの全行程を追う。