# 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**