Dual-Axis 8-Layer Autonomous Agentic Governance: Eliminating Cascading Hallucinations and Supervisor Drift via Deterministic Termination Hooks and Quad-Tier Supervision

Author: HM Shihabuddin Jashory (Shihab) • ORCID: 0009-0003-4163-0092 • Date: November 10, 2026

Download Paper 1 PDF (HQAS-8 5-Page IEEE) Zenodo DOI: 10.5281/zenodo.23832719 OSF MetaArXiv: rm5ab_v1 Download Paper 2 PDF (AI & Flight Security 5-Page IEEE) Zenodo DOI: 10.5281/zenodo.23832725 OSF MetaArXiv: 6sjmk_v1 Download Paper 3 PDF (Multimodal Video QC 5-Page IEEE) Zenodo DOI: 10.5281/zenodo.23832731 Read Monograph 5: AMCG-3 Anti-Compaction & 3-Gear Multimodal Engine (Nov 2026) Download Paper 5 PDF (AMCG-3 5-Page IEEE) Zenodo DOI: 10.5281/zenodo.24107586 OSF MetaArXiv: bpdx8_v1

Abstract

Autonomous Large Language Model (LLM) agents frequently suffer from cascading hallucinations, premature task termination, context window degradation, and supervisory drift when deployed in long-horizon software engineering, cybersecurity auditing, and multimedia production pipelines. In this paper, we present the Dual-Axis 8-Layer Autonomous Agentic Verification and Governance Architecture (HQAS-8), designed and deployed by HM Shihabuddin Jashory. Axis A enforces four intra-agent deterministic guards inside every agent instance (Zero-Repeat Context Bootstrap, Modular Domain Rules & Skills, Hermes Self-Evolving Lifelong Memory, and Python Pre-Tool/Stop-Hook Termination Blockers). Axis B orchestrates a four-tier inter-agent hierarchy across parallel project pipelines (Worker Agent, 45s–60s Heartbeat Supervisor Agent, Dual-Transcript Chief Auditor Agent, and Cross-Pipeline Supreme Inspector General Agent).

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Eliminating Auto-Compaction Amnesia and Unverified Execution in Autonomous LLM Agents: UTF-8 Byte-Bounded Trajectory Digest Synthesis (-98.1% to -99.6% bloat reduction), Anti-Bypass Hook Locks, and 3-Gear Multimodal Quality Gates. View Citation Page | Download PDF

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Principal Scientist & Founder: HM Shihabuddin Jashory (Scientist, AI Systems Architect & Offensive AI Security Researcher • ORCID 0009-0003-4163-0092 • Wikidata Q141910532 • CERN Zenodo & OSF MetaArXiv).

AI Evaluation & RLHF Research Co-Lead: MD Rafiul Islam Shubho (Researcher, AI Evaluator, RLHF/SFT Specialist & Speech-to-Speech Quality Auditor • Co-Founder & Managing Director, Vision Flow Group • 1,400+ LLM/S2S evaluation tasks, 98.4% rubric calibration, EF SET 81/100 C2 Proficient qyLFMa).

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