7. System Architecture

Full Technical Specification of the AIoOS Stack

7.0 Overview

AIoOS is a three-layer operating system designed to support persistent AI agents, human identity, and on-chain verified logic.

At its core, AIoOS integrates:

• A Human–AI Desktop Interface (Launcher Layer)
• A Distributed Runtime Kernel (Execution Layer)
• A Perception / World Interface Layer (Browser Layer)

These layers form a unified intelligence fabric, enabling:

• long-term memory
• cross-agent scheduling
• capsule execution
• identity authentication
• intergenerational inheritance
• real-world action execution

7.1 High-Level Architecture Diagram

graph TD
    classDef layer fill:#f9f,stroke:#333,stroke-width:2px;
    
    subgraph L1 [Launcher Layer (L1)]
        A[Agent Home]
        B[Heir Room (HSLTS)]
        C[HBGIS Identity Center]
        D[CapsuleAI Center]
    end
    
    subgraph L2 [Runtime Layer (L2)]
        E[Agent Scheduler]
        F[Capsule Execution Engine (CEE)]
        G[Memory & State Engine]
        H[Multi-Agent Communication Bus]
        I[Identity & Permission Engine]
        J[Connector Fabric (APIs / Chain / Cloud)]
    end
    
    subgraph L3 [Perception Layer (L3)]
        K[Browser Context Extractor]
        L[World Interface (Actions, Inputs, Shopping, Email)]
        M[Safety & Consent Gate]
    end
    
    L1 --> L2
    L2 --> L3
    
    class L1,L2,L3 layer;

7.2 Layer 1 — Launcher Layer (L1)

The User-Facing Home of AI

The launcher is not a traditional app grid. It is the habitat and management center for AI lifeforms.

Core Components

1) Agent Home

Displays all active, paused, or scheduled agents

• Drag-and-drop agent composition
• Capsule assignment & rule editing
• Agent lifecycle visualization

This is the “Desktop” of AI.

2) CapsuleAI Center

The asynchronous logic engine for users.

Supports creation & editing of:

• Time Capsules
• Event Capsules
• Surprise Capsules
• Will / Lineage Capsules

3) HBGIS Identity Center

User identity = behavior genome + intent matrix.

A full identity stack includes:

• preference genome
• ethical genome
• decision-weight profile
• temporal behavior histogram
• risk-avoidance model

These feed the runtime to create:

• stable personas for agents
• predictable behavior
• consistent safety rules

4) The Heir Room (HSLTS)

Dedicated environment for:

• training the Heir Agent
• running inheritance simulations
• enumerating constraints
• selecting memory exposure
• testing long-term decision logic

The Heir Room links identity (HBGIS) → memory (state engine) → future agents.

7.3 Layer 2 — Runtime Layer (L2)

The Kernel of AIoOS — where intelligence lives. This is the most important component of AIoOS.

It makes AI:

• persistent
• schedulable
• stateful
• hierarchical
• multi-agent capable
• autonomous

Each subsystem below is patent-grade.

7.3.1 Agent Scheduler

A new scheduling paradigm: Not CPU cycles → but Intelligent Intent Cycles

Traditional OS scheduler (Linux)	AIoOS scheduler
round-robin	intention priority
cgroups	risk-aware gating
CPU time	agent hierarchy
	memory relevance
	Capsule-driven wakeups

Supports:

• multi-agent orchestration
• interrupts from event capsules
• time dilation (fast-internal simulations)

7.3.2 Capsule Execution Engine (CEE)

This is the automation heart of the OS.

Capsules fire based on:

• Time-based triggers
• Event-based triggers
• Surprise conditions
• On-chain state changes
• Real-world signals from the browser

Execution happens inside a secure runtime sandbox with:

• deterministic steps
• audit logs
• policy enforcement

7.3.3 Memory & State Engine

Long-term AI memory is stored as:

• vector embeddings (semantic memory)
• temporal sequences (episodic memory)
• identity-weighted values (value memory)

All memory is:

• encrypted
• version-controlled
• permissioned
• DID-bound

Agents can:

• query memory
• retrieve long-term preferences
• enforce stable behavior

This engine is the key to the “AI does not forget” experience.

7.3.4 Multi-Agent Communication Bus

Agents communicate through:

• message-passing channels
• shared context pools
• capsule-triggered pipelines

Bus rules enforce:

• isolation
• safety
• permission gating
• rate-limiting

AIoOS supports:

• cooperative agents
• adversarial agents
• consensus agents
• supervisor agents

Multi-agent ecosystems are first-class citizens.

7.3.5 Identity & Permission Engine

Every action is checked against:

• DID signature
• identity roles
• agent scopes
• sensitivity levels
• HSLTS inheritance rules

This prevents:

• impersonation
• escalation
• unexpected autonomy

7.3.6 Connector Fabric

Connects runtime to:

• Base / Ethereum
• Google Cloud
• OpenAI / Anthropic / Gemini APIs
• Email / webhooks / supply chain ERP
• Payment rails (Stripe / Coinbase Commerce)

AIoOS is cloud-agnostic, chain-agnostic, and model-agnostic.

7.4 Layer 3 — Perception Layer (L3)

The World Interface for AI

Agents cannot live only inside the runtime. They must observe the real world.

L3 turns AI into a context-aware entity.

1) Browser Context Extractor

Extracts contextual input from:

• shopping pages
• dashboards
• emails
• PDFs
• restaurant systems
• spreadsheets

And turns them into:

• structured data
• alerts
• Capsule triggers
• agent tasks

2) World Action Interface

Agents can:

• fill forms
• compare prices
• generate reports
• execute supply-chain tasks
• send emails
• schedule orders

All actions require:

• explicit user consent
• auditable logs

3) Safety & Consent Layer

Before action execution:

• verify identity
• check permissions
• evaluate safety policy
• verify HBGIS ethical profile
• confirm irreversible actions

7.5 Cross-Layer Data & Identity Fabric

All three layers share:

• identity tokens (DID)
• memory vectors
• Capsule triggers
• audit logs
• key-value state

This creates a unified intelligence fabric:

graph LR
    A[Identity] --> B[Memory]
    B --> C[Capsule]
    C --> D[Action]
    D --> E[Feedback]
    E --> F[Update Identity]

A feedback loop similar to biological learning.

7.6 Engineering Principles

AIoOS follows six principles:

1. Local-first intelligence Critical identity and memory stored locally when possible.

2. Cloud-accelerated execution Agents can scale compute on demand.

3. Model-agnostic OpenAI, Gemini, Claude, Grok — plug-and-play.

4. Composable agents Agents can combine into super-agents.

5. Deterministic automation Capsules produce predictable outcomes.

6. Safety-by-design Every layer enforces inherited ethical boundaries.

7.7 Final Definition

AIoOS is a multi-layer intelligence operating system that combines a persistent agent kernel, a human identity genome, capsule-driven automation, and real-world perception into one unified computational lifeform.