A neurocognitive governance model formalizes a Pre-Action Governance Reasoning Loop that consults global, workflow, agent, and situational rules before each action, yielding 95% compliance accuracy with zero false escalations in a retail supply-chain implementation.
Agentsway–software development methodology for ai agents- based teams
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
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2026 7verdicts
UNVERDICTED 7roles
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Agentic Consensus replaces code as the main artifact with a typed property graph world model that maintains commitments and evidence through synchronization operators, shifting evaluation to alignment fidelity and consensus entropy.
The paper introduces an agentic AI platform to train and support recovered soldiers as peer facilitators providing mental health triage and interventions in austere battlefield environments.
Proposes ten design principles for an agent-first web with changes to access (agent identification and dual content), economics (intent-based tiers and tokens), and content (ATML and provenance chains) to address blocking and epistemic recursion.
A cross-platform mobile application deploys an ensemble of quantized open-source LLMs for fully local, DSM-5-aligned psychiatric decision support with claimed accuracy comparable to prior cloud versions.
Flowr is an agentic AI framework that decomposes retail supply chain workflows into coordinated LLM-based agents with human-in-the-loop oversight to automate operations in large supermarket chains.
AI Trust OS is a proposed always-on operating layer that discovers undocumented AI systems via telemetry and produces continuous zero-trust compliance artifacts for regulations including ISO 42001, EU AI Act, SOC 2, GDPR, and HIPAA.
citing papers explorer
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Think Before You Act -- A Neurocognitive Governance Model for Autonomous AI Agents
A neurocognitive governance model formalizes a Pre-Action Governance Reasoning Loop that consults global, workflow, agent, and situational rules before each action, yielding 95% compliance accuracy with zero false escalations in a retail supply-chain implementation.
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Scaling Human-AI Coding Collaboration Requires a Governable Consensus Layer
Agentic Consensus replaces code as the main artifact with a typed property graph world model that maintains commitments and evidence through synchronization operators, shifting evaluation to alignment fidelity and consensus entropy.
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Train the Trainers -- An Agentic AI Framework for Peer-Based Mental Health Support in Battlefield Environments
The paper introduces an agentic AI platform to train and support recovered soldiers as peer facilitators providing mental health triage and interventions in austere battlefield environments.
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Towards an Agent-First Web: Redesigning the Web for AI Agents
Proposes ten design principles for an agent-first web with changes to access (agent identification and dual content), economics (intent-based tiers and tokens), and content (ATML and provenance chains) to address blocking and epistemic recursion.
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Toward Zero-Egress Psychiatric AI: On-Device LLM Deployment for Privacy-Preserving Mental Health Decision Support
A cross-platform mobile application deploys an ensemble of quantized open-source LLMs for fully local, DSM-5-aligned psychiatric decision support with claimed accuracy comparable to prior cloud versions.
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Flowr -- Scaling Up Retail Supply Chain Operations Through Agentic AI in Large Scale Supermarket Chains
Flowr is an agentic AI framework that decomposes retail supply chain workflows into coordinated LLM-based agents with human-in-the-loop oversight to automate operations in large supermarket chains.
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AI Trust OS -- A Continuous Governance Framework for Autonomous AI Observability and Zero-Trust Compliance in Enterprise Environments
AI Trust OS is a proposed always-on operating layer that discovers undocumented AI systems via telemetry and produces continuous zero-trust compliance artifacts for regulations including ISO 42001, EU AI Act, SOC 2, GDPR, and HIPAA.