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AISA Architecture
This document outlines the layered architectural model introduced in AISA — Agentic AI Systems Architecture.
AISA models agentic AI systems as composed systems in which behavior emerges from the interaction between reasoning, execution, infrastructure, evaluation, and governance.
Layered Model
AISA defines seven architectural layers, each responsible for a distinct system concern.
1. LLM Foundation Layer
Provides language understanding and reasoning capabilities. This layer focuses on interpreting inputs and generating outputs, independent of execution or control logic.
2. Tool & Environment Layer
Defines how the agent interacts with external systems. It mediates actions through controlled interfaces, separating reasoning from execution.
3. Cognitive Agent Layer
Handles goal-directed behavior, including planning, decision-making, and memory access. This layer represents the core agent logic.
4. Agentic Infrastructure Layer
Supports execution, orchestration, and coordination. It manages workflow state, failures, and scalability.
5. Evaluation & Feedback Layer
Monitors and evaluates agent behavior over time. It enables comparison, analysis, and continuous assessment.
6. Development & Deployment Layer
Governs system evolution through versioning, experimentation, and deployment control.
7. Governance, Ethics & Policy Layer
Defines system-wide constraints, oversight, and accountability mechanisms.
Architectural Principles
- Separation of Concerns across system layers
- Explicit Boundaries between responsibilities
- System-Level Evaluation of agent behavior
- Governance by Design
- Implementation Independence