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---
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## Overview
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AISA (Agentic AI Systems Architecture) is a system-level reference architecture
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for the design, deployment, evaluation, and governance of agentic AI systems.
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It frames agentic AI as an end-to-end system problem, addressing the
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architectural challenges introduced by autonomous, tool-using,
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and long-horizon AI behavior.
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---
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## Motivation
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As large language models evolve into persistent and goal-directed agents,
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key challenges increasingly arise at the system level, including:
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- Fragmented agent architectures
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- Brittle orchestration and tool usage
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- Limited observability and evaluation
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- Unclear governance and accountability
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AISA introduces a unified architectural model that integrates reasoning,
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infrastructure, evaluation, deployment, and governance.
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---
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## Architectural Model
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AISA decomposes agentic AI systems into seven high-level layers:
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1. **LLM Foundation** β language understanding and reasoning
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2. **Tool & Environment** β controlled external actions
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3. **Cognitive Agent** β planning, goals, and memory
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4. **Agentic Infrastructure** β orchestration and coordination
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5. **Evaluation & Feedback** β continuous behavioral assurance
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6. **Development & Deployment** β lifecycle management
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7. **Governance, Ethics & Policy** β system-wide constraints
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This separation of concerns enables predictable behavior,
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continuous evaluation, and enforceable governance.
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---
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## System Perspective
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AISA treats agentic AI systems as composed, multi-layered systems
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whose behavior emerges from interactions across reasoning,
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execution, infrastructure, and policy layers.
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This perspective supports system-level analysis and comparison
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across different agentic designs.
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---
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## Contributions
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This work:
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- Proposes a unified layered reference architecture for agentic AI systems
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- Clarifies responsibilities and boundaries across system components
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- Elevates evaluation, operations, and governance to first-class concerns
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- Provides a shared vocabulary for research and practice
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---
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## Intended Use
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AISA is intended for:
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- Research on agentic and autonomous AI systems
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- Design of production-grade agent architectures
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- Evaluation and comparison of agentic behaviors
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- Governance and risk analysis of deployed AI systems
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The framework applies to both single-agent and multi-agent systems.
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<h1 align="center">AISA β Agentic AI Systems Architecture</h1>
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<p align="center"><em>Coming soon</em></p>
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<h1 align="center">AISA β Agentic AI Systems Architecture</h1>
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<p align="center"><em>Coming soon</em></p>
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