ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
188 articles · Published by MARIA OS
Eight papers that form the complete theory-to-operations stack: why organizational judgment needs an OS, structural design, stability laws, algorithm architecture, mission-constrained optimization, survival optimization, workforce transition, and agent lifecycle management.
Series Thesis
Company Intelligence explains why the OS exists. Structure defines responsibility. Stability laws prove when governance holds. Algorithms make it executable. Mission constraints keep optimization aligned. Survival theory determines evolutionary direction. White-collar transition shows who moves first. VITAL keeps the whole system alive.
00
Company Intelligence
Why organizational judgment needs an operating system, not just AI tools.
00
Company Intelligence
Why organizational judgment needs an operating system, not just AI tools.
01
Structural Design
How to decompose responsibility across human-agent boundaries.
02
Stability Laws
Mathematical conditions under which agentic governance holds or breaks.
03
Algorithm Stack
10 algorithms mapped to a 7-layer architecture for agentic organizations.
04
Mission Constraints
How to optimize agent goals without eroding organizational values.
05
Survival Optimization
Does evolutionary pressure reduce organizations to pure survival machines? The math of directed vs. undirected evolution.
06
Workforce Transition
Which white-collar workflows move first, and how fast the shift happens.
How agents recognize what they cannot do and trigger autonomous self-extension through formal gap analysis
Self-extending agents require a prerequisite that most architectures ignore: the ability to know what they do not know. This paper formalizes capability gap detection as a metacognitive layer that compares required capabilities against the agent's capability model, classifies detected gaps, prioritizes them by urgency and impact, and decides whether to synthesize, request, delegate, or escalate. We introduce the capability coverage metric, gap entropy measure, and multi-agent gap negotiation protocol. Experimental results show that agents with formal gap detection achieve 4.1x fewer silent failures and 2.8x faster self-extension compared to agents relying on runtime error detection.
形式的ギャップ分析を通じて、自分にできないことを認識し自律的な自己拡張をトリガーする方法
自己拡張型Agentには、ほとんどのアーキテクチャが無視する前提条件がある。自分に何ができないかを知る能力である。本論文はCapability Gap Detectionをメタ認知レイヤーとして形式化する。必要な能力をAgentの能力モデルと比較し、検出されたギャップを分類し、緊急度とインパクトで優先順位付けし、合成・要求・委任・エスカレーションの判断を下す。能力カバレッジメトリック、ギャップエントロピー測度、マルチAgent間ギャップ交渉プロトコルを導入する。
Agents that recognize their own limitations and autonomously build the tools they need — within the safety boundaries of an operating system
Traditional AI agents are bounded by the tools humans provide. When an agent encounters a task outside its toolset, it halts and waits. This paper introduces the Self-Extending Agent Architecture (SEAA), where agents detect their own capability gaps, synthesize new tools through code generation, validate those tools in sandboxed environments, and register them into the OS runtime — all under human-governed safety constraints. We formalize the agent state model X_t = (C, T, M, R), derive the self-extension equation X_{t+1} = E_t ∘ G_t ∘ J_t(X_t), prove Capability Monotonicity under validation gates, and demonstrate the architecture within MARIA OS's hierarchical coordinate system.
Agentが自身の限界を検知し、コード生成でツールを合成し、サンドボックスで検証し、OSランタイムに登録する — すべてガバナンス制約の下で
従来のAIエージェントは、人間が提供したツールセットに束縛される。未対応タスクに遭遇すると停止し、人間の介入を待つ。本論文では、Self-Extending Agent Architecture（SEAA）を提案する。エージェントが自律的に能力ギャップを検出し、構造化コード生成でツールを合成し、サンドボックス環境で検証し、OSランタイムに登録するフレームワークである。エージェント状態モデル X_t = (C, T, M, R) を形式化し、自己拡張方程式 X_{t+1} = E_t ∘ G_t ∘ J_t(X_t) を導出し、検証ゲート下での能力単調性定理を証明する。MARIA OSの階層座標系における具体的な実装を示す。
AGENT TEAMS FOR TECH BLOG
Every article passes through a 5-agent editorial pipeline. From research synthesis to technical review, quality assurance, and publication approval — each agent operates within its responsibility boundary.
Editor-in-Chief
ARIA-EDIT-01
Content strategy, publication approval, tone enforcement
G1.U1.P9.Z1.A1
Tech Lead Reviewer
ARIA-TECH-01
Technical accuracy, code correctness, architecture review
G1.U1.P9.Z1.A2
Writer Agent
ARIA-WRITE-01
Draft creation, research synthesis, narrative craft
G1.U1.P9.Z2.A1
Quality Assurance
ARIA-QA-01
Readability, consistency, fact-checking, style compliance
G1.U1.P9.Z2.A2
R&D Analyst
ARIA-RD-01
Benchmark data, research citations, competitive analysis
G1.U1.P9.Z3.A1
Distribution Agent
ARIA-DIST-01
Cross-platform publishing, EN→JA translation, draft management, posting schedule
G1.U1.P9.Z4.A1
Complete list of all 188 published articles. EN / JA bilingual index.
188 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
© 2026 MARIA OS. All rights reserved.