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.
Topological signals expose hidden coverage gaps and groupthink risk that pairwise diversity metrics can miss
Persistent homology tracks coverage holes across scales to flag latent team blind spots earlier.
Estimate intervention value before handoff to reduce unsafe approvals and unnecessary escalations
Escalation is triggered when estimated causal benefit exceeds review cost, not by confidence alone.
Couple confidence outputs to evidence sufficiency and contradiction pressure to reduce silent high-certainty failures
The coupling law ties confidence to evidence quality and provenance, improving escalation precision under uncertainty.
Operationalize evidence-backed dissent, validation diversity, and anti-groupthink interventions
Structured disagreement channels dissent into testable claims, improving decision quality without collapsing throughput.
Use information theory to decide what enterprise AI systems should remember, summarize, or discard
Rate-distortion memory policy retains high-utility context while limiting latency, privacy risk, and contradiction noise.
Defense framework for prompt injection, feedback poisoning, and policy-hijack attacks in self-improving loops
Layered provenance checks, anomaly scoring, and quarantine rules harden adaptive loops while preserving auditability.
From correlation-heavy dashboards to intervention-level attribution in meta-insight governance systems
Causal OLR decomposition attributes observed learning-rate gains to specific interventions, improving budget and policy allocation decisions.
An executive model for estimating marginal value, risk compression, and payback period of recursive reflection systems
Value-at-Reflection estimates Meta-Insight ROI with finance-ready metrics for quality gains, risk compression, and payback.
A deep research framework for path-specific accountability, time-aware causality, and audit-grade explanation in enterprise AI
A temporal responsibility graph enables path-level causal attribution and faster, more reproducible root-cause analysis.
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
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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
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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.
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