Internet Draft Specifications for Agentic AI Communication

[muscariello]

Internet Draft Specifications for Agentic AI Communication

Two new Internet Draft specifications have been published that address infrastructure requirements for agentic AI systems:

Draft Specifications

1. An Overview of Messaging Systems and Their Applicability to Agentic AI

Document: draft-agntcy-messaging-ecosystem
Scope: Comparative analysis of messaging protocols for generative AI agent systems

This document provides a technical evaluation of messaging protocols for generative AI agent deployments. It analyzes six protocols (AMQP, MQTT, NATS, AMQP over WebSockets, Kafka, and AGNTCY SLIM) across the following criteria:

• Real-time collaboration and high-volume streaming capabilities
• Security models including post-compromise protection and quantum-safe encryption
• Dynamic group coordination across distributed networks
• Performance characteristics for different deployment scenarios

Key findings include:

• Traditional protocols have limitations regarding security requirements for autonomous agents
• Requirements for quantum-safe end-to-end encryption in sensitive AI deployments
• Analysis covers scenarios from lightweight edge computing to large-scale multi-organizational collaborations

2. Secure Low-Latency Interactive Messaging (SLIM)

Document: draft-agntcy-slim
Scope: Protocol specification for agentic AI communication

SLIM defines a messaging protocol that combines gRPC with publish-subscribe capabilities for interactive AI applications:

Architecture:

• Messaging nodes functioning as message queues with routing capabilities
• Message Layer Security (MLS) integration for quantum-safe end-to-end encryption
• Hierarchical DID-based naming system for globally unique, secure channels
• Distributed control plane for scalable deployment and centralized management

Features:

• End-to-end encryption that maintains security through TLS termination and untrusted intermediaries
• OAuth-based authentication with dynamic group membership support
• Optimization for token-by-token streaming and real-time agent collaboration
• Separation of control and data planes for large-scale deployments

Technical Motivation

Multi-agent AI systems require messaging infrastructure that addresses:

Security Requirements:

• Post-compromise security to maintain future communication security
• Quantum-safe encryption for post-quantum cryptography readiness
• Zero-trust architectures for multi-organizational AI collaborations

Performance Requirements:

• Low latency for real-time agent coordination
• High-throughput streaming for continuous token generation
• Efficient many-to-many communication patterns

Scalability Requirements:

• Support for distributed agent networks
• Compatibility with existing gRPC deployments
• Centralized management with distributed execution

Intended Audience

These specifications are relevant for:

• AI framework developers (LangGraph, AutoGen, LlamaIndex)
• Enterprise AI architects designing multi-agent systems
• Security engineers implementing zero-trust AI infrastructures
• Protocol implementers building messaging systems
• Standards organizations working on AI communication protocols

Document Access

Documents:

• Messaging Ecosystem Analysis: https://spec.slim.agntcy.org/draft-agntcy-messaging-ecosystem.html
• SLIM Protocol Specification: https://spec.slim.agntcy.org/draft-agntcy-slim.html

Resources:

• GitHub Repository: agntcy/slim-spec
• Specification Site: https://spec.slim.agntcy.org

Community Participation

These draft specifications represent initial work toward standardizing communication protocols for agentic AI systems. Community input is requested for:

• Technical review and feedback on specifications
• Implementation experience and test results
• Use case documentation and deployment scenarios
• Standards development participation

Comments and feedback can be posted in the GitHub repository: https://github.com/agntcy/slim-spec

[tiswanso]

As mentioned above, comments and discussions are welcome!

For additional methods of community engagement, refer to https://github.com/agntcy/governance/blob/main/CONTRIBUTING.md#community-engagement

and, specifically, the core working group: https://github.com/agntcy/governance/blob/main/working-groups/WORKING-GROUPS.md#core