System Architecture

How Executive AI Works

A hierarchical agent system where an Executive AI layer manages, delegates, and supervises specialized agents. Full control over memory, context, and tool access.

USER / APPLICATION
GOALS & CONSTRAINTS
EXECUTIVE LAYER

Executive AI Agent

Goal understanding • Task decomposition • Agent coordination • Quality assurance

PlanningDelegationMonitoringValidation
DELEGATES TO
AGENT

Code Agent

Code generationRefactoring
AGENT

Research Agent

Information retrievalSynthesis
AGENT

Data Agent

Data queryingTransformation
AGENT

Ops Agent

Workflow executionAutomation
Governance Layer
Memory Control
Context Management
Tool Governance

Executive Agent

Responsibilities

The Executive Agent operates as the central coordination layer, handling high-level planning and oversight while specialized agents execute discrete tasks.

Task Decomposition

Breaks down complex goals into discrete, parallelizable sub-tasks that can be assigned to specialized agents.

Agent Supervision

Monitors agent execution in real-time, validates outputs, and intervenes when quality thresholds are not met.

Resource Allocation

Manages compute budgets, token limits, and execution priorities across the agent workforce.

Quality Assurance

Validates agent outputs against acceptance criteria before aggregating results and reporting completion.

Specialized Agents

Purpose-Built Executors

Each specialized agent is optimized for a specific domain, with curated tool access and domain-specific knowledge.

Code Agent

Capabilities

  • Code generation
  • Refactoring
  • Code review
  • Testing

Tool Access

  • IDE integration
  • Git operations
  • Build systems
  • Linters

Research Agent

Capabilities

  • Information retrieval
  • Synthesis
  • Fact verification
  • Citation

Tool Access

  • Web search
  • Document parsing
  • Knowledge bases
  • APIs

Data Agent

Capabilities

  • Data querying
  • Transformation
  • Analysis
  • Visualization

Tool Access

  • SQL databases
  • Data warehouses
  • Python runtime
  • BI tools

Ops Agent

Capabilities

  • Workflow execution
  • Automation
  • Monitoring
  • Alerting

Tool Access

  • CI/CD pipelines
  • Cloud APIs
  • Monitoring systems
  • Runbooks

Governance

Memory, Context, and Tool Control

The governance layer ensures safe, auditable, and controllable agent execution through explicit controls over what agents can access and do.

Memory Control

Each agent operates with scoped, persistent memory. The Executive controls what context each agent can access, enabling secure multi-tenant execution and preventing context pollution across tasks.

Per-agent memory isolation
Controlled context sharing
Automatic memory pruning
Audit trail for all memory access

Context Management

Explicit context passing ensures agents receive only the information they need. The Executive manages context windows, handles summarization, and maintains coherent state across long-running workflows.

Selective context injection
Automatic summarization
State persistence
Context window optimization

Tool Governance

Dynamic tool permissions prevent unauthorized actions. Each agent has an allowlist of tools with configurable rate limits, approval workflows, and automatic revocation on policy violations.

Per-agent tool allowlists
Rate limiting and quotas
Approval workflows
Automatic policy enforcement