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  # AISA Architecture
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- This document outlines the layered architectural model introduced in
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- **AISA — Agentic AI Systems Architecture**.
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- AISA models agentic AI systems as composed systems in which behavior
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- emerges from the interaction between reasoning, execution,
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- infrastructure, evaluation, and governance.
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- ![Agentic AI Systems Architecture (AISA)](https://cdn-uploads.huggingface.co/production/uploads/676bac31dd95830fd9adf3cf/N6mUf5D7FzV5PXOl2Bm3z.png)
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  ---
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- ## Layer Responsibilities (Summary)
 
 
 
 
 
 
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  ### Governance, Ethics & Policy Layer
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  - AI policies and transparency standards
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  ## Architectural Principles
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- ![AISA Architectural Principles](https://cdn-uploads.huggingface.co/production/uploads/676bac31dd95830fd9adf3cf/NZACvevXzxQR2dye4PNh_.png)
 
 
 
 
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- **1. Separation of Concerns**
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- Clear separation between system responsibilities to prevent mixing reasoning, permissions, and orchestration logic.
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- **2. Assurance-by-Design**
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- Evaluation, monitoring, and governance are built into the architecture from the start, not added after deployment.
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- **3. Dual-Plane Design**
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- A clear distinction between the data plane (runtime execution) and the control plane (policies, permissions, and budgets).
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- **4. Contract-Driven Interfaces**
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- Structured and machine-checkable interfaces reduce ambiguity and improve testing and auditability.
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- **5. Continuous Improvement Loop**
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- Agent behavior evolves continuously through feedback-driven updates to prompts, tools, and policies.
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- **6. Practical Deployability**
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- The architecture accounts for real-world constraints such as cost, latency, observability, access control, and versioning.
 
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  # AISA Architecture
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+ AISA models agentic AI systems as composed systems in which behavior emerges from the interaction between reasoning, execution, infrastructure, evaluation, and governance.
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  ---
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/676bac31dd95830fd9adf3cf/N6mUf5D7FzV5PXOl2Bm3z.png"
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+ alt="Agentic AI Systems Architecture (AISA)"
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+ width="800"/>
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+
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+ ---
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+
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+ ## Layer Responsibilities
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  ### Governance, Ethics & Policy Layer
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  - AI policies and transparency standards
 
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  ## Architectural Principles
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/676bac31dd95830fd9adf3cf/NZACvevXzxQR2dye4PNh_.png"
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+ alt="AISA Architectural Principles"
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+ width="700"/>
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+
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+ ---
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+ **1. Separation of Concerns** :Clear separation between system responsibilities to prevent mixing reasoning, permissions, and orchestration logic.
 
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+ **2. Assurance-by-Design** :Evaluation, monitoring, and governance are built into the architecture from the start, not added after deployment.
 
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+ **3. Dual-Plane Design** :A clear distinction between the data plane (runtime execution) and the control plane (policies, permissions, and budgets).
 
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+ **4. Contract-Driven Interfaces** :Structured and machine-checkable interfaces reduce ambiguity and improve testing and auditability.
 
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+ **5. Continuous Improvement Loop** :Agent behavior evolves continuously through feedback-driven updates to prompts, tools, and policies.
 
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+ **6. Practical Deployability** :The architecture accounts for real-world constraints such as cost, latency, observability, access control, and versioning.