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.
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Company Intelligence
Why organizational judgment needs an operating system, not just AI tools.
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Company Intelligence
Why organizational judgment needs an operating system, not just AI tools.
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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.
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Workforce Transition
Which white-collar workflows move first, and how fast the shift happens.
Eliminating the command registry in favor of goal decomposition, plan generation, and dynamic tool synthesis
Traditional agent architectures bind agents to pre-defined command sets — fixed APIs, registered tools, and enumerated actions. This paper presents the MARIA OS command-less architecture, where agents receive goals rather than commands, decompose them into hierarchical plans, detect capability gaps, and synthesize whatever tools are needed for execution. We formalize the morphisms between Goal space G, Plan space P, and Tool space T, prove convergence of the tool space under recursive planning, and demonstrate that command-less agents achieve 3.2x higher task completion rates on novel problem classes compared to command-bound architectures.
コマンドレジストリを排除し、Goal分解・Plan生成・動的Tool合成によるAgent自律実行を実現する
従来のAgentアーキテクチャは事前定義されたコマンドセットに束縛される。本論文はMARIA OSのコマンドレスアーキテクチャを提示する。AgentはコマンドではなくGoalを受け取り、階層的Planに分解し、能力ギャップを検出し、必要なToolを動的に合成して実行する。Goal空間G、Plan空間P、Tool空間T間の射を形式化し、再帰的計画のもとでTool空間が収束することを証明する。
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.
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