TAG ARCHIVE
agent-operations
5 MARIA OS blog articles tagged agent-operations, 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.
Dynamic Workflow Agent Monitoring Harness: Mass-Producing Safe Operational Agents
Monitoring tools, quality and manufacturing-management harnesses, loop guards, and agent blueprints for scaling workflow agents inside MARIA OS
Dynamic Workflow Agents should not be mass-produced by cloning prompts. MARIA OS treats every operational agent as a monitored production unit with a blueprint, harness binding plan, quality observatory, settlement ledger, loop guard, and memory-backed improvement path.
Dynamic Workflow Agent監視Harness：安全な業務Agentを量産する方法
監視ツール、品質・製造管理Harness、Loop Guard、Agent BlueprintでDynamic Workflow Agentを量産するMARIA OS設計
Dynamic Workflow Agentはpromptの複製で量産してはいけない。MARIA OSでは、すべての業務AgentをBlueprint、Harness Binding Plan、Quality Observatory、Settlement Ledger、Loop Guard、Memory改善経路を持つ製造単位として扱う。
MARIA VITAL: The Life Support System for Agent Organizations — From Heartbeat Monitoring to Recursive Self-Improvement
Why agent organizations need an autonomic nervous system, and how 4-layer vital monitoring, behavioral health diagnosis, self-repair orchestration, and failure-to-improvement conversion keep AI agents alive, healthy, and evolving
Creating AI agents is easy. Keeping them alive is hard. When agents scale beyond a handful, the problem shifts from intelligence to operations: heartbeats stop silently, processing queues back up, memory references decay, judgment quality degrades, and failures cascade across dependencies. MARIA VITAL addresses this by implementing a biological metaphor — the autonomic nervous system — for agent organizations. This paper presents the theoretical foundations in biological self-monitoring, the 4-layer architecture (Vital Signal, Behavioral Health, Recovery Orchestration, Recursive Improvement), the Health Score formalization, the self-repair pipeline with shadow agent validation, and the connection to biological homeostasis through the Observe-Diagnose-Recover-Improve loop.
MARIA VITAL：Agent組織のための生命維持システム — Heartbeat監視から再帰的自己改善まで
なぜAgent組織には自律神経系が必要なのか、そして4層バイタル監視、行動健全性診断、自己修復オーケストレーション、障害→改善変換がAIエージェントの生存・健康・進化を維持する方法
AIエージェントを作るのは簡単だ。生かし続けるのが難しい。エージェントが少数を超えてスケールすると、問題は知能から運用に移る：Heartbeatが静かに停止し、処理キューが詰まり、記憶参照が劣化し、判断品質が低下し、障害が依存関係を通じて連鎖する。MARIA VITALは生物学的メタファー — 自律神経系 — をAgent組織に実装することでこれに対処する。本論文では生物学的自己監視の理論的基盤、4層アーキテクチャ、Health Scoreの定式化、シャドーエージェント検証による自己修復パイプライン、そしてObserve-Diagnose-Recover-Improveループを通じた生物学的恒常性との接続を報告する。
Homeostasis: The Operating System of Life
From Claude Bernard's milieu intérieur to allostasis — how closed-loop control sustains every living thing
Homeostasis — the maintenance of stable internal conditions despite external perturbation — is life's foundational operating system. This article traces the concept from its nineteenth-century origins through modern control theory and allostasis, connecting it to MARIA VITAL's 4-layer implementation architecture.