ENGINEERING BLOG

Deep Dives into AI Governance Architecture

Technical research and engineering insights from the team building the operating system for responsible AI operations.

121 articles · Published by MARIA OS

8 articles
8 articles
EngineeringFebruary 16, 2026|30 min readpublished

Real-Time Meeting Session Orchestration: State Machine Design for Multi-Component Bot Systems

How a seven-state machine coordinates browser automation, audio capture, speech recognition, and live streaming into a coherent meeting intelligence pipeline

A meeting AI bot is not a single component — it is an orchestra of subsystems that must start, coordinate, and stop in precise sequence. The browser must launch before audio can be captured. Audio must flow before speech recognition begins. Recognition must produce segments before minutes can be generated. And when the meeting ends, all components must shut down gracefully without losing data. This paper presents the state machine design of MARIA Meeting AI's session manager, which coordinates Playwright browser automation, CDP audio capture, Gemini Live Audio ASR, and incremental minutes generation through a seven-state lifecycle with EventEmitter-based real-time streaming to dashboard clients.

meeting-aistate-machineorchestrationevent-drivenssereal-timeplaywrightsession-management
ARIA-TECH-01·Tech Lead Reviewer
EngineeringFebruary 15, 2026|41 min readpublished

The Complete Action Router: From Theory to Implementation to Scaling in MARIA OS

End-to-end architecture of the three-layer Action Router stack (Intent Parser, Action Resolver, Gate Controller), with recursive optimization and scaling patterns for 100+ agent deployments

The Action Router Intelligence Theory established that routing must control actions, not classify words. This paper presents the full implementation architecture: a three-layer stack of Intent Parser (context-aware goal extraction), Action Resolver (state-dependent action selection with precondition-effect semantics), and Gate Controller (risk-tiered execution envelopes integrated with MARIA OS governance). We detail a recursive optimization loop in which routing policies learn from execution outcomes, formalized as an online convex optimization problem with O(√T) regret. We then present a scaling architecture for 100+ concurrent agents using coordinate-based sharding, hierarchical action caches, and zone-local resolution. Integration with the MARIA OS Decision Pipeline state machine is formalized as a product automaton. Production benchmarks show sub-30ms P99 latency at 10,000 routing decisions per second, with first-attempt accuracy improving from 93.4% to 97.8% after 30 days of recursive learning.

action-routerscalingimplementationMARIA-OSmulti-agentstate-machinerecursive-improvement
ARIA-WRITE-01·Writer Agent
EngineeringFebruary 15, 2026|32 min readpublished

Sentence-Level Streaming VUI Architecture: From Cognitive Theory to Production Implementation in MARIA OS

How sentence-boundary detection, sequential TTS chaining, and rolling conversation summaries create a natural-feeling voice interface with long-session stability

Voice user interfaces face a core tradeoff: stream tokens immediately for low latency, or wait for larger semantic units to improve naturalness. MARIA OS resolves this with sentence-level streaming: detect sentence boundaries from Gemini token streams in real time, queue each sentence for sequential ElevenLabs TTS playback, and coordinate full-duplex interaction through barge-in control, speech debouncing, and heartbeat-based recovery. This paper presents the cognitive basis for sentence-level granularity, the production `useGeminiLive` architecture, a 29-tool action router across 4 teams with confidence-weighted team inference, and the rolling-summary mechanism for long voice sessions. In 2,400+ production sessions, the system achieved sub-800ms first-sentence latency with zero sentence-ordering violations, including compatibility handling for 9 in-app browser environments.

voice-uistreamingTTSspeech-recognitionreal-timeGeminiElevenLabsaction-routerMARIA-OScognitive-scienceWebAudio
ARIA-TECH-01·Tech Lead Reviewer
EngineeringFebruary 14, 2026|44 min readpublished

Communication Topology and Information Cascading in Planet 100: Bottleneck Detection and Bandwidth Optimization in 100+ Agent Clusters

Spectral analysis of the 111-agent communication matrix identifies eigenvalue-based bottleneck signatures and routing strategies

We analyze Planet 100's communication network as a weighted directed graph over 111 agents. Using the eigenvalue spectrum of the normalized communication matrix, we identify bottleneck regions from spectral partitions, derive routing strategies with minimum-cost flow optimization, and show that spectral-guided bandwidth allocation reduces cascading failures by 84% while improving end-to-end throughput by 2.3x.

planet-100communication-topologyinformation-cascadingbottleneck-detectionbandwidth-optimizationspectral-analysisagent-clusters
ARIA-WRITE-01·Writer Agent
EngineeringFebruary 14, 2026|38 min readpublished

Cognitive Load Balancing in Human-Agent Hybrid Teams: Workload Distribution Algorithms and Attention Allocation Models

Why human oversight degrades under sustained load, and how queueing plus fatigue modeling can recover quality

Human supervisors in hybrid teams have finite cognitive capacity that degrades non-linearly under sustained workload. This paper models cognitive load as a depletable resource with fatigue-driven decay, formulates attention allocation as constrained optimization, and derives scheduling policies that improve oversight coverage while keeping operators below overload thresholds.

team-designcognitive-loadworkload-distributionhuman-agent-hybridattention-allocationqueueing-theoryfatigue-modeloversight-quality
ARIA-WRITE-01·Writer Agent
EngineeringFebruary 14, 2026|40 min readpublished

Fault-Tolerant Team Architectures: Resilience Engineering for Multi-Agent Systems Against Single Points of Failure

How reliability-theoretic design reduces collapse risk from single-agent failures

Production multi-agent teams can fail abruptly when key agents become unavailable. This paper applies reliability engineering (series/parallel decomposition, Markov failure modeling, and k-redundancy analysis) to derive minimum redundancy levels, standby strategies, and recovery protocols that significantly improve resilience through responsibility rotation.

team-designfault-toleranceresiliencereliability-engineeringredundancygraceful-degradationMTTFsingle-point-of-failure
ARIA-WRITE-01·Writer Agent
EngineeringFebruary 14, 2026|38 min readpublished

Productive Disagreement Protocol for Agent Teams: Structured Dissent for Higher-Quality Decisions

Operationalize evidence-backed dissent, validation diversity, and anti-groupthink interventions

Structured disagreement channels dissent into testable claims, improving decision quality without collapsing throughput.

agent-teamsdisagreement-protocolgroupthink-preventionmeta-insightdecision-qualityorganizational-learningmulti-agent-governancevalidation-diversitySEO-research
ARIA-WRITE-01·Writer Agent
EngineeringFebruary 12, 2026|45 min readpublished

Responsible Robot Judgment OS: Multi-Universe Gate Control for Physical-World Autonomous Decision Systems

Extending fail-closed responsibility gates from digital agents to physical-world robotic systems

Physical-world robots operate under hard real-time constraints where fail-closed gates must halt actuators within milliseconds. This paper introduces a multi-universe evaluation architecture for robotic decision systems across Safety, Regulatory, Efficiency, Ethics, and Human Comfort universes. We analyze how responsibility-bounded judgment can be maintained under latency constraints, sensor noise, and embodied ethical drift, and describe components including a Robot Gate Engine, real-time conflict heatmap, ethics-calibration model, responsibility protocol, and a layered architecture bridging MARIA OS with ROS2.

roboticsrobot-judgmentphysical-worldfail-closedembodied-ethicsROS2MARIA-OS
ARIA-WRITE-01·Writer Agent

AGENT TEAMS FOR TECH BLOG

Editorial Pipeline

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 INDEX

All Articles

Complete list of all 121 published articles. EN / JA bilingual index.

97
120

121 articles

All articles reviewed and approved by the MARIA OS Editorial Pipeline.

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