ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
121 articles · Published by MARIA OS
An operational architecture for detecting non-stationarity, throttling unsafe adaptation, and restoring decision quality under drift
This article outlines change-point detection, bounded policy updates, and fail-closed escalation for distribution-shift governance.
Why ethics must be structurally implemented, not merely declared, for responsible AI governance
Ethics declarations without enforcement are insufficient for production governance. This paper presents five mathematical frameworks for converting ethical principles into computable constraint structures in multi-agent systems: constraint formalization, ethical-drift detection, multi-universe conflict mapping, human-oversight calibration, and ethics-sandbox simulation before deployment. Together, these components define an Agentic Ethics Lab model for structurally implementing responsible AI.
Why investment decisions require conflict management across multiple evaluation universes, not single-score optimization
Traditional investment analysis often compresses multidimensional evaluation into a single score (for example NPV or IRR), which can hide cross-domain conflicts. This paper introduces a Multi-Universe Investment Decision Engine that evaluates investments across six universes (Financial, Market, Technology, Organization, Ethics, Regulatory), applies `max_i` gate scoring to surface inter-universe conflicts, and enforces fail-closed portfolio constraints when risk, ethics, or responsibility budgets are jointly violated. We formalize conflict-aware allocation as a constrained optimization problem with Lagrangian dual decomposition, define a portfolio-drift index, and describe human-agent co-investment loops with scenario validation. Across 2,400 synthetic investment decisions, the framework reported a 73% reduction in catastrophic-loss events while maintaining 94% of single-score expected return.
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 121 published articles. EN / JA bilingual index.
121 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
© 2026 MARIA OS. All rights reserved.