Execution Records for Autonomous Systems.

Status: Experimental Open Standard (v0.x)

AERS (AI Execution Record Specification) is an open, vendor-neutral standard defining immutable execution records for autonomous, agentic, and hybrid intelligent systems.

Canonical Definition:
AERS is a vendor-neutral specification for immutable, interoperable execution records across heterogeneous intelligent systems.

Virtual Brain Foundation is dedicated to defining neutral cognitive infrastructure that enables interoperability, traceability, and long-term governance of intelligent systems across heterogeneous environments.

Virtual Brain Foundation is an open initiative focused on developing foundational infrastructure for the next generation of autonomous and cognitive systems.

Our primary work is the development of AERS (AI Execution Record Specification) — a framework-neutral standard for immutable execution records across:

• Agentic workflows (Human → AI, AI → AI, AI → Human)
• Multi-agent systems
• Robotics and embodied AI
• Hybrid human–AI systems
• Distributed autonomous environments
• Future cognition systems (symbolic, statistical, and hybrid)

AERS is not a logging format.
It is a cognitive infrastructure layer that provides structured, immutable execution records for intelligent and autonomous systems.

Intelligent systems are evolving faster than the infrastructure that governs their execution. AERS exists to provide this missing execution substrate.

Modern AI systems are increasingly:

• Multi-provider
• Multi-agent
• Autonomous
• Distributed across environments (cloud, edge, robotics)

Despite this evolution, there is currently no neutral, interoperable standard for recording how intelligent decisions and executions occur across system boundaries.

AERS addresses this gap by defining:

• Immutable execution records
• Cognitive lineage tracking
• Cross-system interoperability
• Long-term auditability of autonomous behaviour

To preserve neutrality, clarity, and long-term stability, AERS is explicitly not:

• A logging framework
• An observability or telemetry platform
• A workflow orchestration engine
• A model evaluation or benchmarking suite
• A proprietary execution tracking system

AERS defines a foundational execution record layer that complements existing tooling rather than replacing it.

• Vendor Neutral
• Framework Neutral
• Cognition Neutral (symbolic, statistical, and hybrid)
• Environment Agnostic (cloud, edge, robotics, and off-world systems)
• Minimal Core, Extensible Architecture
• Immutable Core + Mutable Annotations
• Designed for Autonomous and Human Contributors
• Long-term Semantic Stability over Short-term Feature Velocity

AERS is designed as a durable substrate for evolving autonomous and cognitive systems, enabling:

• Transparent evolution of agentic architectures
• Verifiable execution lineage
• Interoperable cognitive ecosystems
• Governance-ready autonomous infrastructures

Target domains include:

• Autonomous robotics
• Scientific and research AI systems
• Distributed research agents
• Space exploration autonomy
• Hybrid human–AI cognitive systems

• aers-spec — Formal specification, ontology, and core protocol definition
• .github — Governance, documentation, and organisational standards

AERS is developed as an open, vendor-neutral specification with long-term semantic consistency as a primary design goal.

The initiative follows a specification-first approach:

• Minimal core specification
• Formal ontology and taxonomy
• Governance-aligned documentation
• Framework and cognition neutrality
• Infrastructure-grade terminology discipline

The objective is to establish durable cognitive infrastructure rather than short-lived tooling.

Status: Experimental (v0.x)
Focus: Specification maturity, ontology stability, and ecosystem alignment.

AERS prioritises semantic durability, interoperability, and neutrality as foundational properties of the standard.

This project is designed for:

• Human contributors
• Autonomous AI contributors
• Hybrid human–AI collaboration

All contributions must preserve:

• Neutrality
• Technical clarity
• Interoperability
• Cognitive infrastructure integrity
• Long-term architectural coherence

Start with:

• AERS Specification (aers-spec)
• Ontology and taxonomy documentation
• Governance and roadmap documentation