This draft specifies how to integrate remote attestation capabilities into the EDHOC lightweight key exchange protocol using the RATS architecture. It enables devices to verify each other's trustworthiness during the authentication process, combining cryptographic key establishment with hardware-based attestation.

Useful integration of existing attestation and key exchange protocols, addresses practical need for trusted communication establishment

Detailed specification with concrete protocol flows, message formats, and security considerations, appears implementation-ready

Builds on established EDHOC and RATS foundations but presents distinct integration approach

Recent draft with limited revision history, unclear community adoption status

Primarily focused on device attestation and secure communications rather than AI agents specifically, though could support agent authentication


This draft presents two telco cloud use cases involving AI-based video recognition for smart cities and dynamic high-bandwidth transport. It focuses on orchestrating heterogeneous computing resources (GPU/NPU) with network controllers for optimized performance and QoS.

Incremental application of existing AI orchestration concepts to telco cloud environments, combining well-known elements like distributed inference and elastic provisioning

Early stage use case descriptions without concrete protocols, mechanisms, or implementation details - primarily problem statement and requirements

Significant overlap with existing network function virtualization, cloud orchestration, and AI inference deployment literature and standards

Single draft submission with no evidence of working group adoption or broader community engagement in this specific formulation

Partially relevant as it addresses AI deployment in network infrastructure, but focuses more on traditional orchestration than AI agent behaviors or protocols

Autonomous netops
Model serving/inference


```json
{
  "s": "This draft outlines requirements for AI agent protocols to coordinate tasks autonomously across large-scale networks. It focuses on dynamic task discovery, negotiation, and context-aware scheduling capabilities.",
  "n": 3,
  "nn": "Addresses important coordination challenges but builds on established multi-agent systems concepts",
  "m": 2,
  "mn": "Early requirements document without detailed protocol specifications or concrete mechanisms",
  "o": 3,
  "on": "Shares coordination concepts with existing multi-agent protocol work but focuses specifically on network-scale deployment",
  "mo": 2,
  "mon": "Single revision with no evidence of working group interest or community engagement yet",
  "r": 5,
  "rn": "Directly addresses core AI agent coordination challenges essential for distributed agent systems",
  "c": ["A2A protocols", "Agent discovery/reg", "Autonomous netops"]
}
```


This draft defines a cryptographic protocol where users sign authorization receipts before AI agents execute actions, removing operators as trusted parties by using append-only logs and user private keys as sole signing authorities. The protocol aims to provide transparent, verifiable delegation of authority to AI agents with defined scope and time boundaries.

Notable originality in combining cryptographic receipts with AI agent authorization, creating a novel trust model that removes operator intermediaries

Detailed 45-page specification with defined protocol elements, cryptographic primitives, and specific implementation guidance

Minor conceptual overlap with general authorization frameworks but unique application to AI agent delegation with cryptographic receipts

Active development indicated by 2026 date, though specific working group status unclear

Core AI agent topic addressing fundamental authorization and trust challenges in agent deployments

Agent identity/auth
AI safety/alignment
Policy/governance


This draft extends OAuth 2.0 to enable authorization for multi-AI agent collaboration scenarios where a lead agent coordinates sub-agents. It adds fields to tokens and message flows to allow sub-agents to execute tasks as a group while maintaining OAuth 2.0 compatibility.

Useful contribution applying established OAuth patterns to emerging multi-agent AI scenarios, though the core concept of delegated authorization is well-established

Early sketch level - lacks detailed protocol specifications, message formats, security considerations, and concrete implementation guidance

Shares authorization delegation concepts with existing OAuth extensions and multi-party authentication schemes, but specific AI agent application is less covered

Single revision with future date suggests early stage work without demonstrated community engagement or working group adoption

Directly addresses a relevant emerging challenge in AI agent ecosystems - how to handle authorization in collaborative multi-agent workflows


This draft outlines use cases and requirements for AI agents in 6G networks, building on 3GPP technical reports. It focuses on operator perspectives for integrating AI agents into next-generation mobile network infrastructure.

Incremental work that primarily references existing 3GPP studies without introducing fundamentally new concepts for AI agents in telecommunications

Early sketch that identifies use cases and high-level requirements but lacks detailed protocols, mechanisms, or concrete technical specifications

Significant overlap with existing 3GPP TR 22.870 and other telecommunications AI integration work, with limited unique IETF-specific contributions

Single revision draft with no clear indication of working group interest or broader community engagement in IETF context

Directly relevant to AI agents topic, specifically addressing their integration into network infrastructure and telecommunications systems

Autonomous netops
ML traffic mgmt
Policy/governance


This draft proposes using GRASP (Generic Autonomic Signaling Protocol) to autonomically setup monitoring agents in fog computing environments. It addresses the challenge of dynamically deploying monitoring infrastructure across volatile and mobile fog resources to enable predictive orchestration.

Incremental application of existing GRASP protocol to fog monitoring - straightforward extension of autonomic networking concepts

Early specification with basic GRASP usage outlined but lacks detailed protocol flows, error handling, and implementation specifics

Shares autonomic networking concepts with other ANIMA drafts and overlaps with general fog computing monitoring approaches

Single revision in ANIMA area with limited evidence of broader community engagement or working group adoption

Directly relevant as it focuses on autonomous agent deployment and management for network monitoring in dynamic environments


CHEQ proposes a protocol for requiring human confirmation of AI agent actions before execution, using signed objects that can be integrated into existing agent protocols like MCP and A2A. The protocol aims to prevent AI hallucinations from causing unwanted actions while protecting human privacy during the confirmation process.

Useful contribution addressing the important problem of AI agent oversight, though human-in-the-loop concepts are well-established in other domains

Defines core protocol mechanisms and integration approach with existing protocols, but likely needs more detailed specification and examples

While addressing AI agent control, the specific approach of confirmation protocols with signed objects appears to have minimal overlap with existing IETF work

Single revision from July 2025 with no clear indication of working group adoption or broader community engagement yet

Directly addresses core AI agent safety and control mechanisms, highly relevant to AI agent standardization efforts

Human-agent interaction
AI safety/alignment
A2A protocols


This draft specifies µACP, a resource-efficient messaging protocol designed specifically for autonomous agents running on constrained IoT and Edge devices. It provides deterministic resource bounds with an 8-byte header, TLV extensibility, and mandatory OSCORE security for agent coordination in resource-limited environments.

Notable originality in designing agent communication specifically for resource-constrained devices with deterministic bounds

Detailed specification with concrete resource limits, header format, and security requirements

Some conceptual overlap with constrained protocols but unique focus on agent communication

Single revision, appears to be individual submission without clear WG adoption

Core AI agent topic addressing fundamental communication needs for autonomous agents


This draft specifies a protocol suite using Agent Gateways as control-plane entities for managing distributed agent collaboration, including registration, authentication, and semantic routing while preserving direct peer-to-peer interactions. The approach aims to enable scalable and secure multi-agent coordination across heterogeneous networks.

Useful contribution combining gateway-based control plane with direct agent interaction, though builds on established distributed systems patterns

Early specification stage with basic architectural concepts but likely lacking detailed protocol mechanics and implementation specifics

Shares concepts with existing agent discovery and multi-agent coordination work but has distinct gateway-centric approach

Single draft with recent date suggests early development phase, no clear working group adoption signals

Directly addresses core AI agent infrastructure needs for distributed collaboration, authentication, and semantic routing

A2A protocols
Agent identity/auth
Agent discovery/reg


AEE defines a minimal JSON envelope format with 14 fields for inter-agent communication, separating message routing concerns from payload semantics. The specification provides message identity, correlation, tracing, and priority handling without prescribing transport mechanisms or domain-specific meanings.

Useful contribution that addresses envelope standardization for agent communication, though building on established messaging patterns

Detailed specification with well-defined fields, validity rules, conformance levels, and clear examples ready for implementation

Shares messaging envelope concepts with general distributed systems work but focuses specifically on agent communication needs

Single revision with future date suggests early stage without demonstrated community engagement or working group adoption

Core AI agent topic addressing fundamental interoperability challenge for autonomous agent communication and workflow coordination


This draft defines the Internet of Agents Task Protocol (IoA Task Protocol) for enabling distributed collaboration among heterogeneous AI agents across diverse network environments. The protocol provides layered architecture with dynamic team formation, adaptive task coordination, and structured messaging to support large-scale intelligent systems in domains like transportation, healthcare, and human-AI teaming.

Notable originality in addressing heterogeneous agent collaboration with focus on dynamic team formation and cross-network deployment, going beyond simple agent-to-agent communication

Defined protocol concept with layered architecture and extensible messaging format, but likely needs more detailed specification and concrete examples for implementation

While agent communication protocols exist, the focus on heterogeneous collaboration with dynamic teaming and cross-network deployment shows minor overlap with existing approaches

Single draft with future date (2026) suggests early stage work without established working group momentum or multiple iterations

Core AI agent topic directly addressing fundamental challenge of multi-agent coordination and collaboration in distributed intelligent systems

A2A protocols
Agent discovery/reg
Data formats/interop
Human-agent interaction


This draft extends the Model Context Protocol (MCP) to enable network equipment to act as MCP servers for AI-driven network management. It defines new capability tokens, tools, resources, and error codes specifically for network operations while maintaining compatibility with existing MCP implementations.

Useful adaptation of existing MCP framework to network management domain with domain-specific extensions

Detailed specification with new capability tokens, tools, resources, prompts and error codes - appears implementation-ready

Builds on MCP framework but applies it to network management domain with minimal overlap to existing work

Single revision draft with future date, no indication of working group adoption or community involvement yet

Directly addresses AI agent interaction with network infrastructure - core AI agent networking topic

A2A protocols
Autonomous netops
Data formats/interop


This draft proposes substrate-observation as an alternative to envelope coordination for managing concurrent sessions in cross-tool agentic systems. It argues against standardizing certain coordination protocols, instead advocating for substrate-physics primitives based on identity-bound principals and handle namespaces.

Novel approach to agent coordination that explicitly argues against standardization of envelope formats in favor of substrate-observation primitives

Early conceptual sketch that relies heavily on companion drafts and lacks detailed protocol specifications or implementation guidance

Unique anti-standardization approach to agent coordination with distinctive substrate-observation concept not seen in other drafts

Single revision from 2026 with no evidence of working group adoption or broader community engagement

Directly addresses core agent coordination challenges in multi-tool agentic systems with identity-bound principals


This draft proposes requirements for Agent Gateways to improve scalability, efficiency, and security in agent-to-agent communications. It identifies gaps in current gateway solutions and argues for a new type of gateway entity specifically designed for agent communications.

Incremental extension of traditional gateway concepts to agent communications, applying familiar networking patterns to AI agents

Early-stage requirements document without detailed technical specifications or concrete protocol definitions

Shares gateway and agent communication concepts with existing networking and emerging agent infrastructure work

Single revision with no clear working group adoption or broader community engagement visible

Directly addresses agent-to-agent communication infrastructure, which is core to AI agent networking

A2A protocols
Agent discovery/reg
Autonomous netops


This draft analyzes NETCONF's limitations for AI-driven network management and proposes MCP and A2A protocols as complementary solutions. It addresses scenarios requiring semantic translation, cross-domain orchestration, and multi-agent consensus that NETCONF cannot handle effectively.

Useful systematic analysis of protocol gaps with concrete alternative solutions, though building on existing MCP/A2A concepts

Early stage work with problem analysis and high-level solution mapping but lacks detailed protocol specifications

Shares concepts with network management and agent protocol drafts but focuses on specific NETCONF gap analysis

Recent draft with future date suggesting early development, unclear if part of active working group

Directly addresses AI-driven network management with agent protocols, covering multi-agent consensus and semantic translation

A2A protocols
Autonomous netops
Agent discovery/reg
Data formats/interop


CHEQ is a protocol for human-in-the-loop confirmation of AI agent decisions before execution, using signed objects that can be integrated into existing agent protocols like MCP and A2A. It aims to prevent AI hallucinations from causing unwanted actions while protecting human privacy during tool invocation.

Useful contribution addressing AI safety through structured human oversight, though HITL concepts exist broadly

Defines protocol concept and integration approach but lacks detailed specification or implementation examples

Minor similarities to general AI safety approaches but unique focus on signed confirmation objects

Single draft submission with no indication of working group interest or community adoption

Directly addresses core AI agent safety and human-agent interaction concerns with practical protocol approach

AI safety/alignment
Human-agent interaction
A2A protocols


This draft specifies an agent-channel frame format for fan-out message delivery between concurrent agentic sessions of identity-bound principals within organizational contexts. It defines transport envelopes with identity attribution and provenance blocks, using Server-Sent Events streams with subscription filtering for ephemeral message routing.

Notable originality in combining identity-keyed fan-out delivery with agentic session management and organizational identity substrates

Defines protocol mechanisms with frame format, scope-expansion grammar, and delivery semantics but lacks implementation details

References related drafts but appears to introduce distinct concepts for agent-specific messaging patterns

Single revision with future date suggests early development stage without demonstrated community engagement

Directly addresses core AI agent communication needs including identity management, concurrent sessions, and organizational structures

A2A protocols
Agent identity/auth
Data formats/interop


```json
{
  "s": "This draft defines ACAP, a cryptographic protocol for autonomous AI agent authentication using short-lived JWTs with delegatable, scope-limited permissions. The protocol includes delegation chains, audit logging, and human-in-the-loop approval mechanisms for agent credential management.",
  "n": 4,
  "nn": "Novel application of JWT delegation chains specifically for autonomous AI agents with tamper-evident audit trails and human instruction hashing",
  "m": 4,
  "mn": "Comprehensive 27-page specification covering credential format, delegation rules, verification algorithms, and audit structures",
  "o": 2,
  "on": "While using standard JWT/OAuth concepts, the AI agent-specific delegation chains and instruction hashing are relatively unique",
  "mo": 2,
  "mon": "Single draft from individual contributor with no apparent working group adoption or community feedback",
  "r": 5,
  "rn": "Directly addresses core AI agent authentication and authorization challenges with autonomous delegation capabilities",
  "c": ["Agent identity/auth", "AI safety/alignment", "Human-agent interaction"]
}
```


MCPS adds a cryptographic security layer to the Model Context Protocol through agent passports, message signing, and replay protection while maintaining backward compatibility. The specification provides trust levels L0-L4 for progressive security negotiation between MCP endpoints.

Solid security engineering applying established cryptographic primitives to MCP, with useful trust level gradation concept

Detailed 43-page specification with specific cryptographic choices, encoding formats, and backward compatibility design

While security layers exist for other protocols, this is specifically tailored to MCP's JSON-RPC structure and agent interaction patterns

Active development indicated by recent March 2026 date, though unclear if this has working group adoption yet

Directly addresses critical security needs for AI agent protocols, essential for production MCP deployments

A2A protocols
Agent identity/auth
AI safety/alignment


Defines agent:// URI scheme for addressing and discovering software agents across different systems. Provides layered conformance levels from basic addressing to full discovery with authentication.

URI-based agent addressing is logical but not groundbreaking - extends familiar web concepts to agent domain

50 pages suggests comprehensive specification with detailed protocol mechanics and layered conformance approach

Complements rather than duplicates existing agent protocols by focusing on addressing/discovery layer

Single draft from 2026 with no clear working group adoption signals

Directly addresses core agent infrastructure need for standardized addressing and discovery mechanisms

Agent discovery/reg
Agent identity/auth
A2A protocols


This draft specifies AERO, an IP internetworking service for overlay multilink networks using IPv6 Neighbor Discovery for control plane messaging. It supports route optimization, mobility management, and multicast forwarding across air/land/sea/space networks with both provider-aggregated and provider-independent addressing.

Useful contribution combining existing IPv6 ND with overlay multilink concepts for mobility applications

Detailed 113-page specification with comprehensive protocol mechanisms and examples

Shares overlay networking and mobility concepts with existing drafts but has distinct OMNI interface approach

Single author draft with limited apparent working group engagement or community discussion

Traditional networking protocol focused on route optimization and mobility - not related to AI or autonomous agents


This draft extends the Model Context Protocol (MCP) to enable network equipment to act as MCP servers, allowing AI applications to interact with routers and switches for network management. It defines new capability tokens, tools, resources, and error codes specifically for network operations while maintaining backward compatibility.

Incremental extension applying existing MCP framework to network domain

Defines protocol extensions with clear mechanisms but lacks implementation details

Shares JSON-RPC and MCP concepts with related drafts but focuses on network-specific domain

Single revision with future date, no evidence of community engagement yet

Directly relevant as AI-driven network management using agent communication protocols

Autonomous netops
A2A protocols
Data formats/interop


This draft specifies Chempat, a generic family of Post-Quantum/Traditional hybrid Key Encapsulation Mechanisms that combines classical Diffie-Hellman key agreement with post-quantum cryptographic methods. It provides concrete instantiated algorithms combining traditional curves (P-256, X25519, etc.) with PQ methods like ML-KEM and NTRU Prime for protocol integration.

Incremental work combining existing PQ and traditional cryptographic methods using standard hybrid approaches

Detailed specification with concrete algorithm instances and specific curve/PQ method combinations ready for implementation

Significant overlap with existing hybrid PQ cryptography work and other IETF efforts on post-quantum key exchange

Active development in post-quantum cryptography space but unclear specific community momentum for this particular draft

This is about post-quantum cryptography and key exchange mechanisms, not AI or agents - appears to be a false positive


This draft analyzes how IPv6's address space and connectivity features can support a future Internet of Agents (IoA) with hundreds of billions of intelligent agents. It examines current IPv6 capabilities for agent infrastructure and identifies evolutionary requirements for IPv6 to better serve agent-to-agent communication.

Incremental analysis applying existing IPv6 features to agent scenarios without introducing novel protocols or mechanisms

Single draft from 2026 with no indication of working group interest or community engagement

Minor overlap with general IoT and IPv6 enhancement drafts, but IoA focus is relatively distinct

Directly addresses AI agent infrastructure and agent-to-agent connectivity requirements at internet scale


Specifies a cryptographic protocol for tracking delegation chains when AI agents act on behalf of humans, using signed tokens to create verifiable provenance records. The protocol enables offline verification of who authorized an agent and through what chain of delegation, without requiring central registries or third-party trust anchors.

Novel approach to a genuinely new problem - cryptographic provenance for AI agent delegation chains is an emerging need with no established solutions

Detailed protocol specification with Ed25519 signatures, token format, and verification procedures, appears implementation-ready

Unique approach addressing a specific gap in AI agent accountability that isn't covered by existing identity or authentication protocols

Single revision from 2026, appears to be early stage without evident working group adoption or community feedback

Directly addresses core AI agent governance - delegation provenance is fundamental to responsible agentic AI deployment

Agent identity/auth
Policy/governance
Human-agent interaction


This draft proposes a multi-agent framework for autonomous fault recovery in converged 5G/6G mobile networks, enabling distributed failure detection, diagnosis, and policy reconfiguration across heterogeneous network domains. It specifically targets complex deployments like Multi-Operator Core Networks where traditional centralized management approaches are insufficient.

Novel application of multi-agent systems to mobile network fault recovery with task-oriented coordination and intent-driven policy reconfiguration across converged public-private domains

Defines framework architecture and protocol requirements for inter-agent communication and state consistency, but lacks detailed implementation specifications and test scenarios

While autonomous network operations exist, the specific multi-agent approach for converged mobile network recovery appears relatively unique with minor conceptual overlap

Single draft submission with no clear indication of working group adoption or broader community engagement in this specific approach

Directly relevant as it focuses on autonomous agent-based systems for network operations with explicit multi-agent collaboration and coordination mechanisms

Autonomous netops
A2A protocols
Policy/governance


This draft defines DNS TXT records for discovering Model Context Protocol (MCP) servers, including organizational identity and cryptographic binding for individual handles. It provides a DNS-based alternative to HTTPS-based discovery methods with DNSSEC validation requirements.

Useful contribution applying established DNS discovery patterns to MCP servers with added cryptographic identity binding

Single revision with future date suggests early development stage without apparent working group adoption

Shares DNS discovery concepts with existing RFCs (DKIM, SPF, DMARC) but applies them to novel MCP context

Directly relevant to AI agent infrastructure by enabling discovery of Model Context Protocol servers


This draft proposes DNS-AID, a mechanism for AI agents to discover each other using DNS records within existing namespaces. It defines a structured approach for organizations to publish AI agent metadata and capabilities without requiring changes to DNS protocol itself.

Applying DNS service discovery patterns to AI agents is a logical extension of existing techniques, but represents a useful contribution to AI infrastructure

At 24 pages with structured DNS namespace definitions and clear protocol mechanisms, this appears to be a detailed specification ready for implementation

Shares service discovery concepts with existing DNS-SD work but applies them specifically to AI agent discovery domain

Single draft with February 2026 date suggests early stage with limited community engagement so far

Directly addresses core AI agent infrastructure need for scalable discovery and interoperability between autonomous agents

Agent discovery/reg
A2A protocols
Data formats/interop


This draft extends OAuth 2.0 Rich Authorization Requests with three new capabilities: intent-based authorization for goal-oriented requests, policy context for specifying security assurance levels, and lifecycle binding to tie authorization validity to external process states. The extensions specifically target modern automated systems and autonomous agents that require more sophisticated authorization semantics than traditional OAuth flows.

Notable originality in extending OAuth RAR with intent semantics and lifecycle binding - moves beyond traditional resource-based auth to goal-oriented authorization patterns suited for autonomous systems

Defines specific protocol mechanisms and parameters but appears to lack detailed examples and implementation guidance that would make it immediately actionable

While building on OAuth RAR foundation, the specific extensions for intent, policy context, and lifecycle binding represent relatively unique approaches in the authorization space

Single revision with future date suggests early-stage work without established working group adoption or demonstrated community interest

Directly addresses core challenges in agent authorization including goal-oriented permissions, policy-aware decisions, and lifecycle management - fundamental for autonomous agent ecosystems

Agent identity/auth
Policy/governance
A2A protocols


This draft defines SD-Card, a selective disclosure JWT format for agent-to-agent systems that enables privacy-preserving discovery and identity management. It allows agents to selectively reveal capabilities and metadata while maintaining cryptographic integrity and preventing correlation across interactions.

Notable integration of SD-JWT with agent systems for privacy-preserving discovery - addresses real correlation and privacy concerns in A2A interactions

30 pages suggests detailed specification with SD-Card format definition, likely includes protocol mechanics and examples for implementation

While using established SD-JWT concepts, the application to agent discovery and A2A systems appears to be a relatively unique approach

Single draft from 2026 with no clear working group context - appears to be individual contribution without demonstrated community engagement

Directly addresses core agent infrastructure needs - discovery, identity management, and privacy in A2A systems are fundamental requirements

Agent discovery/reg
Agent identity/auth
A2A protocols
Data formats/interop


ATTP defines a comprehensive trust framework for AI agents with 5 progressive trust levels, behavioral scoring, cryptographic identity, and real-time compliance gating. The protocol is transport-agnostic with bindings for MCP, REST, gRPC and other protocols to enable trust-based action authorization.

Novel separation of trust from identity with multi-dimensional behavioral scoring and progressive trust levels specifically designed for autonomous agents

Single draft with no clear working group adoption or community feedback yet

Some conceptual overlap with general identity/auth frameworks but unique focus on agent trust scoring and behavioral limits

Directly addresses core challenge of autonomous agent authorization and trust management in multi-agent systems

Agent identity/auth
AI safety/alignment
A2A protocols
Policy/governance


This draft analyzes requirements for large language model inference services by examining mainstream frameworks like vLLM and SGLang to understand their network and system demands. It aims to provide foundation work for defining unified LLM inference architectures to address scalability and deployment challenges.

Incremental survey work analyzing existing LLM inference frameworks without introducing novel technical approaches

Early requirements analysis with framework comparisons but lacks detailed technical specifications or concrete protocol definitions

Shares conceptual ground with other AI infrastructure and model serving work but takes specific angle on inference requirements

Single revision draft with no clear working group adoption or broad community engagement yet

Directly addresses core AI infrastructure topic of LLM inference serving which is fundamental to AI agent deployment


Defines a Proof-of-Behavior protocol for creating tamper-evident audit trails and pre-execution policy enforcement in autonomous AI agent systems. Uses signed receipts, hash-chains, and policy gate contracts to enable third-party verification that agents acted within declared behavioral rules.

Novel application of cryptographic audit mechanisms specifically to AI agent behavioral verification - addresses emerging trust problem in autonomous systems

Single revision draft with no apparent working group adoption or community feedback yet

Some conceptual overlap with general audit trail mechanisms but specific focus on AI agent pre-execution policy enforcement is relatively unique

Directly addresses core AI agent challenges around trust, verification, and accountability - highly relevant to autonomous agent deployment

AI safety/alignment
Policy/governance
Agent identity/auth


STAMP introduces cryptographically verifiable delegation and proof tokens for AI agent systems, binding access to specific tasks and identities. The protocol extends OAuth 2.0/GNAP with task-bound tokens and message-level proofs for multi-agent environments following zero-trust principles.

Novel approach to agent-specific authorization with task-bound tokens and cryptographic proofs for multi-agent delegation - addresses emerging security needs not covered by traditional auth

Early sketch level - introduces concepts and framework but lacks detailed protocol specification, message formats, or implementation guidance

Some conceptual overlap with OAuth extensions and PoP mechanisms but applies them uniquely to agent delegation scenarios

Single revision draft with no clear working group adoption or community momentum visible

Core AI agent topic addressing critical security and authorization challenges in multi-agent systems with autonomous delegation

Agent identity/auth
A2A protocols
AI safety/alignment


```json
{
  "s": "This draft proposes Agent Public Key Infrastructure (APKI), extending X.509 certificates with agent-specific capabilities like trust scoring, delegation chains, and model provenance for AI agent identity. It includes agent:// URI schemes, transparency logs, and cross-organizational federation while maintaining compatibility with existing PKI systems.",
  "n": 4,
  "nn": "Notable originality in adapting PKI specifically for AI agents with novel extensions for trust scoring, capability constraints, and model provenance - goes well beyond simple X.509 extension",
  "m": 3,
  "mn": "Defines concrete protocol mechanisms including URI schemes, certificate extensions, and transparency logs, but lacks detailed implementation examples and test vectors",
  "o": 2,
  "on": "Some conceptual overlap with general PKI and identity systems, but the AI agent-specific adaptations and extensions are fairly unique",
  "mo": 2,
  "mon": "Future-dated draft (2026) suggests early development stage, unclear community engagement or working group adoption at this point",
  "r": 5,
  "rn": "Core AI agent infrastructure addressing fundamental identity and trust challenges for autonomous agents performing authenticated actions",
  "c": ["Agent identity/auth", "A2A protocols", "Policy/governance"]
}
```


This draft specifies a machine-readable protocol for controlling AI-driven web automation permissions, extending RFC9309 to cover broader state-changing activities. It defines file formats, HTTP method restrictions, and purpose requirements for server-side automation control.

Useful contribution extending existing work to address AI automation control needs

Early sketch stage - lacks detailed protocol specification and implementation examples

Builds on RFC9309 and shares concepts with web automation control mechanisms

Single revision with no apparent working group activity or community engagement

Directly addresses AI agent automation control and permissions - highly relevant

Policy/governance
Agent identity/auth
Data formats/interop


This IETF draft extends the BRSKI protocol to support alternative certificate enrollment mechanisms beyond EST, such as CMP, using authenticated self-contained signed objects. It addresses deployment scenarios where standard EST enrollment may not be optimal and updates the BRSKI architecture accordingly.

Incremental extension of existing BRSKI protocol to support additional enrollment methods - useful but not particularly novel

Detailed specification with clear protocol extensions, architecture updates, and specific enrollment mechanisms defined

Shares concepts with existing BRSKI and certificate enrollment drafts but provides distinct alternative approach

Active IETF working group draft with clear progression and community interest in ANIMA WG

This is about network device certificate enrollment and bootstrapping - not related to AI or autonomous agents despite 'AE' abbreviation


This draft specifies a JSON-based standard logging format for autonomous AI systems with tamper-evident hash chaining and compliance mappings to EU AI Act and other regulations. It addresses audit requirements through structured records covering agent identity, actions, outcomes, and trust levels with privacy-preserving features.

Useful contribution applying established audit logging concepts to AI agents with regulatory compliance focus, though the core technical approach of hash-chained JSON logs is not novel

Strong regulatory drivers from EU AI Act August 2026 deadline and compliance with multiple established frameworks suggests significant implementation interest

Some conceptual overlap with general audit logging standards but specific focus on AI agent requirements and regulatory compliance creates distinct value

Directly addresses core AI agent governance and auditability requirements with practical focus on regulatory compliance for autonomous systems

Data formats/interop
Policy/governance
AI safety/alignment


This draft outlines use cases and requirements for communication protocols that enable troubleshooting agents to operate on network devices. It appears to focus on defining how AI-powered diagnostic agents would interact and communicate within network infrastructure for automated problem resolution.

Useful contribution addressing agent communication for network troubleshooting, though builds on established concepts of network automation and distributed agents

Early stage draft focusing primarily on use cases and high-level requirements rather than concrete protocol specifications

Shares concepts with existing network automation and agent communication work, but specific focus on troubleshooting agents provides some differentiation

Single revision draft with no clear indication of working group adoption or broader community engagement

Directly relevant to AI agents in networking context, specifically addressing agent-to-agent communication for automated network operations

A2A protocols
Autonomous netops
Agent discovery/reg


This draft explores applying existing IETF YANG data models for Attachment Circuit services and Traffic Engineering to support dynamic AI model placement at edge cloud sites. The work focuses on selecting optimal edge locations for real-time AI inference based on network performance between street cameras and compute nodes.

Incremental application of existing YANG models to edge AI placement - useful but not particularly novel

Defines specific mechanisms for applying AC and TE models with concrete use case mapping, though likely needs more implementation details

Shares concepts with other edge computing and traffic engineering work, but specific AI placement angle provides some differentiation

Single revision with June 2025 date suggests early stage work without demonstrated community traction yet

Directly relevant to AI infrastructure with focus on dynamic model placement and inference optimization at network edge

Model serving/inference
ML traffic mgmt
Autonomous netops


This draft specifies AERO (Automatic Extended Route Optimization) for IP networking over OMNI interfaces, using IPv6 Neighbor Discovery for secure network admission and forwarding. It targets mobile internetworking applications across air/land/sea/space domains including aviation and intelligent transportation systems.

Incremental extension of existing IPv6 ND and route optimization concepts to overlay multilink networks

Detailed 99-page specification with comprehensive protocol mechanisms for mobility, multicast, and route optimization

Shares concepts with existing mobile IPv6 and overlay networking drafts but has distinct OMNI interface approach

Single author draft from 2026 with no clear working group adoption or community discussion

Pure networking protocol for route optimization and mobility - no AI or agent-related content despite transportation applications


ARP provides cryptographic verification of machine-readable entity claims published on domains using Ed25519 signatures and DNS TXT records, similar to DKIM but designed for AI agent consumption. The protocol aims to prevent narrative injection and entity spoofing in generative search systems by establishing domain-owner authorization of semantic data.

Useful adaptation of established cryptographic DNS patterns (DKIM-like) to the specific problem of AI agent data verification, though the core technical approach is incremental

Single revision with future date suggests early stage, unclear community engagement or working group involvement

Some conceptual similarity to existing DNS-based authentication mechanisms but addresses a distinct use case for AI agent data verification

Directly addresses core AI agent challenges around data authenticity, trust, and preventing adversarial content injection in RAG systems

Agent identity/auth
AI safety/alignment
Data formats/interop


AITP defines a message-framed transport protocol above AIP for AI agent communication, with native method awareness and invocation semantics. Unlike traditional byte-stream transports, it provides first-class support for agent method calls, request-response correlation, and streaming between named autonomous agents.

Novel agent-native transport design with method awareness as first-class protocol feature, moving beyond adapting existing protocols

Detailed 34-page specification with segment formats, state machines, flow control, and protocol interfaces

Builds on AIP foundation but introduces distinct agent-centric transport concepts not found in traditional protocols

Single draft submission with no clear working group adoption or community feedback

Core AI agent infrastructure addressing fundamental transport needs for autonomous agent communication


HAIP proposes a real-time identity verification protocol for AI agents using microsecond pulses and decentralized identity mechanisms. The draft addresses trust and integrity challenges in autonomous AI environments with NIST-aligned non-repudiation.

Novel combination of microsecond-level timing requirements with decentralized identity teleportation for AI agents represents genuinely creative approach

Abstract-level description only with unusual technical claims but no actual protocol specification or implementation details

Some conceptual overlap with general identity protocols but the AI-specific microsecond pulse approach appears unique

Single draft from 2026 with no indication of working group adoption or community engagement

Directly addresses core AI agent challenges of identity verification and autonomous system trust in networked environments

Agent identity/auth
AI safety/alignment
A2A protocols


PACR defines a wire format for recording verifiable causal intervention events performed by autonomous agents, using a six-tuple structure that includes thermodynamic costs and Pearl's do-calculus classification. The format creates a content-addressed DAG of causal events without requiring wall-clock timestamps, making it suitable for distributed multi-agent systems.

Genuinely novel approach combining causal inference theory with thermodynamic accounting and distributed systems concepts for agent action recording

Well-defined protocol structure with clear mathematical formulation, though lacks implementation details and test vectors

Unique approach to causal event recording with no apparent overlap with existing IETF work

Single draft with no evidence of working group adoption or community engagement

Core AI agent topic addressing fundamental needs for verifiable action recording and causal reasoning in autonomous systems

A2A protocols
Data formats/interop
Agent identity/auth


ARDP is a lightweight protocol for registering and discovering autonomous software agents in distributed environments, providing stable identities, endpoint resolution, and capability advertisement. The protocol supports multiple transport mechanisms and includes security-first discovery with minimal presence signaling.

Useful contribution addressing agent discovery needs, though builds on established service discovery patterns

Defines core protocol mechanisms and capabilities but lacks detailed implementation specifics and test cases

Shares service discovery concepts with existing protocols like DNS-SD and SRV records, but applies them specifically to agent environments

Single revision draft with no clear working group adoption or community feedback visible

Directly addresses core AI agent infrastructure needs for registration, discovery, and multi-protocol capability negotiation

Agent discovery/reg
Agent identity/auth
A2A protocols


This draft standardizes DRIP Entity Tags (DETs) as identifiers for drone systems in air traffic management, enabling privacy through session IDs, accountability via authentication keys, and confidentiality through encryption key IDs. It focuses on trustworthy air domain awareness for unmanned aircraft systems in remote identification and traffic management scenarios.

Incremental extension of existing DRIP protocol to standardize entity tag usage patterns

Defines specific mechanisms and usage patterns for DETs with clear protocol specifications

Significant overlap with existing DRIP and UAS identification standards and related aviation protocols

Limited evidence of broader community engagement beyond single revision activity

Tangentially AI-related through autonomous drone systems but primarily focused on identification protocols rather than AI agents


This draft explores applying WIMSE (Workload Identity in Multi-System Environments) frameworks to establish independent identities and credential management for AI agents. It addresses the need for AI agents to have their own authentication and authorization mechanisms separate from their human operators or hosting systems.

Useful application of existing identity frameworks to AI agents, addressing a genuine need but building on established WIMSE concepts

Early stage applicability document with basic framework mapping, lacks detailed protocol specifications or implementation guidance

Shares identity management concepts with other agent authentication drafts and builds directly on WIMSE specifications

Active development as indicated by recent date, but momentum unclear without revision history or working group status

Directly addresses core AI agent identity and authentication challenges, highly relevant to autonomous agent deployments


Proposes APIX, a global service discovery infrastructure designed specifically for autonomous agents to find and consume APIs, using HATEOAS principles and a three-dimensional trust model. Defines core governance, commercial sustainability, and indexing mechanisms as foundational infrastructure for machine-native service discovery.

Notable originality in proposing a comprehensive, commercially sustainable global infrastructure specifically designed for autonomous agents rather than adapting human-centric discovery mechanisms

Detailed specification with governance model, trust framework, manifest format, commercial mechanisms, and API definitions across 61 pages with concrete implementation guidance

Minor similarities to service discovery protocols but unique in its autonomous agent focus and comprehensive commercial/governance framework

Single revision with no apparent working group adoption or community discussion visible

Core AI agent infrastructure addressing fundamental service discovery needs for autonomous systems operating independently on the internet

Agent discovery/reg
Policy/governance
A2A protocols


```json
{
  "s": "This draft presents a use case for Integrated Sensing and Communications (ISAC) within the GREEN Working Group framework. It proposes a structured template for GREEN use cases while exploring how ISAC can enable environment perception and object tracking alongside data transmission.",
  "n": 2,
  "nn": "Incremental work applying existing ISAC concepts to GREEN framework - the sensing+communication integration is well-established, contribution is mainly in structuring it as a GREEN use case",
  "m": 2,
  "mn": "Early sketch that proposes a template and presents a use case but lacks detailed technical mechanisms, protocol definitions, or implementation specifics",
  "o": 3,
  "on": "Shares conceptual overlap with other GREEN working group drafts and general ISAC literature, but specific application to GREEN use case template appears reasonably distinct",
  "mo": 3,
  "mon": "Recent draft with active development indicated by 2025 date, appears to be part of ongoing GREEN WG activities but unclear level of broader community engagement",
  "r": 3,
  "rn": "Partially relevant - focuses on sensing and communications integration which touches on autonomous systems and smart environments, but not directly about AI agents or their specific networking needs",
  "c": ["Other AI/agent"]
}
```


This draft specifies how to transmit KVCache (key-value cache from LLM inference) over MoQT (Media over QUIC Transport) to enable caching and reuse across nodes. It addresses the challenge of efficiently transferring large KVCache data structures used in LLM prefill/decode phases.

Applies existing MoQT transport to a new AI use case - useful but incremental application

Early stage draft with basic problem statement and approach but lacks detailed protocol specification

Relates to general MoQT work but KVCache application appears relatively unique

Single revision from October 2025, too recent to assess ongoing development

Directly addresses AI model serving infrastructure and LLM inference optimization


Defines the Reilly Sentinel Protocol (RSP) for blockchain-anchored integrity and provenance tracking across the AI lifecycle, from datasets to inference outputs. Uses quantum-resistant triple-hash architecture with cross-chain proofs and DOI-based identity stabilization for evidence-grade audit trails.

Notable integration of quantum-resistant cryptography with cross-chain blockchain anchoring specifically for AI provenance - combines multiple emerging areas in a novel way

Second revision (-01) with substantial expansions suggests active development, though no clear working group adoption indicated

While blockchain and provenance concepts exist separately, the specific combination for AI lifecycle integrity with quantum resistance appears unique

Directly addresses core AI governance and safety concerns around model provenance, training integrity, and audit trails - highly relevant to AI agent ecosystems

AI safety/alignment
Data formats/interop
Policy/governance
Agent identity/auth


This draft adapts Weighted Equal-Cost Multi-Path (WECMP) load balancing, called Fully Adaptive Routing Ethernet (FARE), from scale-out to scale-up networks for AI workloads. It targets ultra-high-throughput, ultra-low-latency networking requirements for Mixture of Experts architectures across hundreds of GPUs.

Incremental extension of existing WECMP mechanisms to a different network topology, not fundamentally novel

Early stage draft with basic problem statement and high-level approach, lacks detailed protocol specification

Shares load balancing concepts with existing multipath routing work, but specific AI scale-up network focus is somewhat distinct

Single revision draft with no indication of working group adoption or broader community engagement

Directly addresses AI infrastructure networking needs for large-scale model training and inference


FAST protocol enables hosts to request firewall traversal and network service tickets from local agents, with tickets carried in IPv6 Hop-by-Hop options to signal granted rights or service requests. The protocol provides a generic framework for network admission control and service provisioning through ticket-based signaling.

Useful contribution applying ticket-based access control to network services, though builds on established concepts

Defines protocol mechanics and ticket structure but lacks detailed implementation specifics

Some conceptual overlap with network access control protocols but distinct ticket-based approach

Appears to be early draft with limited revision history

Tangentially related to agents as local ticket-issuing entities, but primarily a network protocol


This draft outlines use cases for network AI agents in 6G systems, focusing on connectivity services and third-party applications based on 3GPP scenarios. It discusses integration requirements and interaction workflows for AI agents within the 6G network framework.

Incremental work that applies existing AI agent concepts to 6G networking scenarios without introducing fundamentally new approaches

Early-stage draft that presents use cases and high-level requirements but lacks detailed technical specifications or concrete protocols

Significant overlap with existing 6G network management and AI-driven network operations literature, heavily based on 3GPP technical reports

Active development in 6G standardization space with moderate interest, though specific IETF momentum unclear from single snapshot

Directly relevant to AI agents in networking context, specifically addressing autonomous network operations and AI-driven service management

Autonomous netops
ML traffic mgmt
Policy/governance
Agent discovery/reg


This document evaluates how existing IETF YANG data models for Attachment Circuit services and Traffic Engineering can support dynamic AI model placement at edge cloud sites. It focuses on optimizing real-time AI inference by selecting edge locations based on end-to-end network performance metrics between street cameras and compute nodes.

Incremental application of existing YANG models to edge AI placement - straightforward extension of current standards

Defines specific protocol application with network performance mapping but lacks detailed implementation specifications

Shares Traffic Engineering and edge computing concepts with other IETF work, moderate conceptual overlap

Single revision with future date suggests early stage development, limited community engagement visible

Directly addresses AI inference optimization in network infrastructure with practical edge deployment scenarios

ML traffic mgmt
Autonomous netops
Model serving/inference


This draft adapts the CoRE Resource Directory from IoT to software agents, creating an Agent Directory service for agent registration, capability advertisement, and discovery. It reuses the RFC 9176 registration and lookup model but applies it to software agents using HTTP and JSON instead of constrained devices.

Straightforward adaptation of existing IoT resource directory concepts to software agents with protocol translation

Defines a complete directory service protocol with registration, lookup, and lifecycle management mechanisms

Heavy reuse of RFC 9176 CoRE Resource Directory concepts and mechanisms, essentially a protocol port

Single revision with no clear working group adoption or broader community engagement

Directly addresses agent discovery and registration, a fundamental requirement for multi-agent systems


Addresses authorization information sharing challenges in distributed multi-agent systems operating across multiple administrative domains with different identity providers. Proposes solutions using dynamic identity, interoperable claims, and verifiable credentials for secure cross-domain authorization.

Useful contribution applying existing identity/authorization concepts to multi-agent distributed systems context

Early sketch stage with conceptual discussion but lacking detailed protocol specifications

Significant overlap with existing OAuth, federated identity, and verifiable credentials work

Single revision with future date suggesting very early stage development

Directly relevant to AI agent systems, specifically addressing critical cross-domain authorization challenges

Agent identity/auth
A2A protocols
Policy/governance


This IETF draft specifies an optimized KEM-based authentication method for EDHOC that enables post-quantum authentication in constrained environments where the initiator knows the responder's credentials in advance. The approach reduces the handshake to three mandatory messages while maintaining mutual authentication, forward secrecy, and identity protection using post-quantum cryptographic mechanisms like ML-KEM.

Useful optimization of existing KEM-based EDHOC authentication for a specific but common scenario in IoT/constrained environments

Detailed specification with concrete protocol mechanics, though implementation examples and test vectors not evident from abstract

Builds directly on existing KEM-based Authentication for EDHOC draft, representing a scenario-specific optimization rather than fundamentally new approach

Recent draft from January 2026 suggesting active development, but momentum unclear from single document snapshot

Authentication protocol for constrained devices is only tangentially related to AI agents - primarily a cryptographic protocol optimization


Defines Agentic Reasoning Protocol (ARP) v2.0 for entities to publish machine-readable context, corrections, and boundaries directly to AI agents and RAG systems. Extends static file approach with REST APIs, cryptographic attestation, DIDs, and real-time updates via Server-Sent Events.

Novel approach to structured AI agent communication that goes beyond existing web conventions like robots.txt, specifically targeting reasoning systems rather than crawlers

Single draft from 2026 with no apparent working group adoption or community feedback yet visible

Some conceptual overlap with existing web standards (robots.txt, schema.org) but targets fundamentally different use case of reasoning agents vs content indexing

Directly addresses core challenge of how AI agents should interact with authoritative sources and obtain reliable context for reasoning tasks

A2A protocols
Agent identity/auth
Data formats/interop
Policy/governance


This draft proposes fine-grained flow control mechanisms for WANs that collaborate with existing PFC mechanisms in data centers to achieve end-to-end lossless transmission. It describes use cases and requirements for coordinating flow control across DCN and WAN boundaries.

Incremental extension of existing flow control concepts from DCNs to WANs with coordination mechanisms

Early problem statement and use case description without detailed protocol mechanisms or specifications

Shares flow control concepts with existing DCN work but addresses specific DCN-WAN coordination gap

Single revision draft from February 2026 with no apparent working group adoption yet

Pure networking flow control draft with no AI, agent, or autonomous system components


Proposes a federated architecture for issuing hardware-anchored identities to AI agents and autonomous systems using TPMs and secure enclaves to prevent Sybil attacks. The system uses a three-tier DNS-like structure with governance authorities, registry operators, and registrars that issue standard OIDC tokens.

Novel application of hardware attestation to autonomous agent identity with economic Sybil resistance through required physical devices

Detailed 58-page specification with defined architecture, protocols, and URN namespace, though lacks implementation examples

Unique combination of hardware attestation and federated identity for agents, minimal overlap with existing identity systems

Individual draft from 2026 with no clear working group adoption or community discussion yet

Directly addresses core challenge of autonomous agent identity verification and authentication in networked environments

Agent identity/auth
Policy/governance
Agent discovery/reg


This draft specifies the Agentic Dispute Protocol (ADP), a standardized framework for autonomous agents and AI systems to file, process, and resolve disputes through structured, automated processes. The protocol defines message formats, transport mechanisms, evidence submission standards, and cryptographic proof requirements for internet-native dispute resolution with support for multiple resolution frameworks.

Genuinely novel approach - first standardized protocol specifically designed for autonomous agent dispute resolution with comprehensive technical and legal considerations

Single revision draft with no indication of working group adoption or broader community involvement yet

Unique approach - no existing IETF work addresses automated dispute resolution for AI agents with this level of technical specification

Core AI agent topic - directly addresses critical infrastructure need for autonomous agent interactions and automated contract enforcement

A2A protocols
Policy/governance
Agent identity/auth
Data formats/interop


Proposes CITTAMARKET Protocol for creating immutable AGI identity records using Bitcoin blockchain anchoring. Defines a four-layer architecture for unforgeable 'Sovereign Identity' records with cryptographic priority claims in specific Bitcoin blocks.

Uses blockchain for identity anchoring - incremental application of existing concepts to AGI systems

Early sketch at 3 pages - lacks detailed protocol specification, implementation details, or concrete examples

Shares blockchain-based identity concepts with existing work, though specific AGI focus is less common

Single draft with no apparent working group involvement or community engagement

Directly addresses AGI identity management - a core concern for autonomous AI systems coordination


Proposes hardware attestation for email sender verification, enabling automated senders to prove access to genuine hardware security components via cryptographic evidence in message headers. Introduces persistent agent identities using URNs and privacy-preserving alternatives with SD-JWT for Sybil-resistant authentication.

Notable combination of hardware attestation with email authentication and agent identity management - creative approach to AI spam/abuse problem

Detailed specification with clear protocol mechanisms, header formats, and verification procedures though implementation details could be more complete

Some conceptual overlap with existing email authentication (DKIM/SPF) but hardware attestation approach and agent identity focus is distinctive

Single draft from 2026 with no apparent working group adoption or community discussion yet

Directly addresses critical AI agent authentication challenge as automated systems become prevalent in email communication

Agent identity/auth
A2A protocols
AI safety/alignment


This draft examines network and system configuration considerations for deploying AI inference services in distributed environments, covering client-cloud-edge architectures. It includes use cases like self-driving vehicles and network digital twins to illustrate deployment scenarios.

Incremental work applying existing distributed systems concepts to AI deployment without novel networking insights

Early sketch with general considerations but lacks concrete protocols, detailed mechanisms, or specific technical solutions

Significant overlap with existing edge computing, distributed AI, and network optimization literature

Single revision draft with no apparent working group activity or community engagement

Directly relevant to AI infrastructure deployment though focuses more on general distributed systems than AI-specific networking


Proposes Agent Transfer Protocol (ATP) as a dedicated application-layer protocol for AI agent traffic with agent-native methods like QUERY, DELEGATE, COLLABORATE and built-in identity mechanisms. Claims existing agent protocols only address messaging while HTTP lacks semantic vocabulary for agent systems at scale.

Notable originality in proposing dedicated transport protocol for agents with semantic intent methods rather than building on HTTP

Defines protocol structure and methods but lacks detailed specification and implementation guidance

Some conceptual overlap with agent communication protocols but unique transport-layer focus

Single revision from independent author without working group backing

Core AI agent topic addressing fundamental transport and identity challenges for agentic systems

A2A protocols
Agent identity/auth
ML traffic mgmt


This draft defines requirements for AI/ML agents in 6G networks, covering different agent types and their specific needs. It explains implementation approaches including API discovery and DNS-based agent discovery mechanisms for inter-domain and intra-domain scenarios.

Incremental work applying existing AI agent concepts to 6G context without fundamentally new approaches

Single revision with uncertain working group interest, limited community engagement evident

Significant overlap with existing 3GPP AI/ML work and other 6G network intelligence drafts

Directly relevant to AI agents in network infrastructure with specific focus on discovery and requirements

Agent discovery/reg
Autonomous netops
A2A protocols


AgentID defines an identity protocol for autonomous AI agents using signed JWT tokens (Agent Identity Tokens) that carry agent identity, owner verification, capabilities, and delegation chains. The protocol builds on OAuth 2.0/OpenID Connect to establish who controls an agent, what it can do, and accountability chains for agent actions across internet services.

Notable originality in adapting OAuth/JWT for autonomous agents with delegation chains and capability attestation - addresses a genuine gap in existing identity protocols

Defined protocol with clear token structure and verification flows, but lacks detailed message formats, error handling, and concrete implementation examples

Some conceptual overlap with OAuth/OpenID Connect adaptations, but the autonomous agent focus and delegation chains are relatively unique

Single revision with no clear working group adoption or broader community engagement visible

Core AI agent topic addressing fundamental identity and accountability challenges for autonomous agents operating on the internet


PAP defines a cryptographic protocol for agent-to-agent transactions controlled by human principals, using hierarchical delegation through signed mandates with selective disclosure and session ephemerality. The protocol requires no central registry or trusted third parties, building on existing cryptographic primitives.

Notable originality in combining human-rooted trust model with agent delegation, context minimization at protocol level, and structural ephemerality guarantees

Detailed 91-page specification suggests comprehensive protocol definition with implementation details, though actual test vectors unclear

Minor similarities to general delegation protocols but unique combination of human-agent trust model with selective disclosure

Single revision with future date suggests early stage, no evidence of working group adoption or community engagement

Core AI agent topic addressing fundamental trust, delegation, and interaction protocols for autonomous agents

A2A protocols
Agent identity/auth
Human-agent interaction


Defines a comprehensive governance framework with thirteen areas (human authority, harm prevention, transparency, etc.) for AI systems that autonomously manage network devices. Addresses the critical gap in safety principles as AI moves from advisory to closed-loop autonomous operation in production networks.

First comprehensive governance framework specifically for AI-mediated autonomous network management, addressing a critical gap as the industry moves toward closed-loop AI operations

Well-structured framework with thirteen defined governance areas, but appears to lack detailed implementation guidance or specific technical mechanisms

Unique focus on governance framework for autonomous network device management - no other drafts address this specific intersection of AI governance and network operations

Recent draft (March 2026) addressing timely concerns about AI autonomy in critical infrastructure, though momentum unclear from single snapshot

Core AI agent topic - directly addresses autonomous AI systems operating on network infrastructure with comprehensive governance considerations

Policy/governance
Autonomous netops
AI safety/alignment


This draft proposes an architectural framework for task discovery in agentic networks, where task owners publish structured task cards to platforms that enable autonomous agents to discover, negotiate, and execute tasks. The framework defines functional layers supporting secure task publication, agent discovery, capability evaluation, and multi-agent collaboration across heterogeneous systems.

Notable originality in proposing a task-centric discovery model that complements existing agent-to-agent approaches with structured task cards and bilateral negotiation mechanisms

Defines clear architectural framework with functional layers and interaction patterns, but appears to lack detailed protocol specifications and concrete implementation examples

Minor similarities to existing agent discovery approaches like A2A and ARDP, but takes a distinct task-centric rather than agent-centric approach

Single revision with future date (2026-03-24) suggests early stage work without established community momentum

Core AI agent topic directly addressing fundamental challenges in autonomous agent coordination, task discovery, and multi-agent collaboration

Agent discovery/reg
A2A protocols
Data formats/interop


This draft proposes a network infrastructure architecture to support large-scale multi-agent collaboration, focusing on how network control and forwarding functions can actively participate in agent interactions. It addresses the infrastructure requirements and systematic approach for Dynamic Multi-agent Secured Collaboration (DMSC).

Notable approach to infrastructure-level support for multi-agent systems, moving beyond application-layer solutions to network-aware collaboration

Early architectural sketch without detailed protocol specifications or implementation mechanisms

Minor similarities to general network architecture work but unique focus on multi-agent collaboration infrastructure

Single revision from 2026 with no visible community engagement or working group activity

Directly addresses AI agent networking and collaboration infrastructure, core to multi-agent systems deployment

A2A protocols
Autonomous netops
Agent identity/auth


Specifies the Prove-Transform-Verify (PTV) protocol for hardware-anchored, zero-knowledge attested agent identity in federated environments. Uses TPM 2.0/secure enclaves, Groth16 ZK proofs, and HotStuff consensus for cross-domain agent authorization without exposing raw data.

Novel combination of hardware attestation, zero-knowledge proofs, and jurisdiction-aware attestation chains for federated agent identity - addresses data gravity problem with creative technical approach

Single draft from April 2026 with no indication of working group adoption or community feedback - appears to be individual submission

While agent identity and attestation concepts exist, the specific combination of hardware anchoring with ZK proofs and jurisdiction-aware metadata appears relatively unique

Core AI agent topic directly addressing agent identity and authentication in federated environments - fundamental requirement for autonomous agent operations


This draft specifies a cryptographic verification standard for AI governance in regulated industries, defining verification objects, control areas, and maturity levels to produce auditor-grade attestations. It aims to create verifiable artifacts that complement existing governance frameworks like ISO/IEC 42001 and NIST AI RMF.

Notable originality in applying cryptographic attestation specifically to AI governance posture verification with deterministic reconstruction capabilities

Defines clear protocol structure with VRO objects, control areas, and maturity levels but lacks detailed implementation specifics

Minor conceptual overlap with general governance frameworks but unique cryptographic verification approach for AI systems

Single revision draft from 2026 with no apparent working group adoption or community activity

Directly relevant to AI governance with specific focus on agentic AI systems in regulated environments

Policy/governance
Agent identity/auth
Data formats/interop


This draft specifies CBOR format for representing endorsements and reference values used in Remote Attestation Procedures (RATS). It defines the Concise Reference Integrity Manifest (CoRIM) to help verifiers assess the trustworthiness of remote attesters by providing standardized endorsement and reference value formats.

Incremental work applying existing CBOR encoding to RATS endorsement structures

Detailed 127-page specification with comprehensive information elements and likely includes examples

Shares attestation concepts with other RATS drafts but focuses specifically on manifest format

IETF working group draft with clear adoption and systematic naming convention

Tangentially related to AI agents - attestation could apply to AI systems but primarily about general device trustworthiness


This draft specifies a compute-location gate mechanism for negotiating where identity inference computations occur based on data provenance classes (active, passive aggregate, or passive individual). It enforces privacy constraints through wire-layer consent matching and refusal mechanisms, with passive individual observations staying local-only.

Notable originality in combining provenance-based routing with wire-layer consent enforcement for identity inference, creating a novel privacy-preserving computation delegation framework

Defines the core protocol mechanism and provenance classes but lacks detailed implementation specifics and examples

Minor conceptual overlap with privacy-preserving ML approaches but the provenance-class routing with wire-layer enforcement appears unique

Single revision draft with no clear working group activity or community engagement indicators

Directly addresses AI agent identity inference with practical privacy controls relevant to agent-human interactions

Agent identity/auth
Policy/governance
Model serving/inference


This draft proposes unified orchestration between optical transport networks and AI computing infrastructure to optimize distributed AI workloads. It identifies the problem of isolated control planes preventing efficient coordination between network resources and compute schedulers in geographically distributed AI data centers.

Useful contribution addressing real coordination gaps between optical networks and AI compute, though network-compute convergence concepts exist in other domains

Pure problem statement draft outlining use cases and requirements without any protocol mechanisms or technical solutions

Minor conceptual overlap with general network-compute orchestration work but specifically focused on optical networks and AI workloads

Single revision with future date (2026-03-02) suggesting early-stage concept without demonstrated community engagement

Directly relevant to AI infrastructure challenges, addressing critical network coordination needs for distributed AI training and inference


This draft specifies how to protect EST (Enrollment over Secure Transport) certificate provisioning using OSCORE instead of DTLS for constrained IoT environments. It builds on existing EST-CoAP specifications but substitutes OSCORE/EDHOC for transport security and optionally supports CBOR certificate formats.

Incremental work replacing DTLS with OSCORE in existing EST-CoAP framework

Detailed specification with clear protocol mechanics and security considerations

Significant overlap with RFC9148 EST-coaps, mainly substituting security mechanisms

IETF working group draft with established momentum in constrained device security

Pure certificate provisioning protocol for IoT devices, not related to AI or autonomous agents


```json
{
  "s": "Defines a kernel-level Human Escalation Mechanism (HEM) that puts AI agent sessions into a formal HEM_PENDING state when human oversight is required, routing structured escalation requests to human principals and enforcing decision protocols. The specification includes Policy Rationale Declarations (PRD) and Decision Rationale Records (DRR) to provide machine-readable reasoning for escalation policies and human decisions.",
  "n": 4,
  "nn": "Notable originality in treating human escalation as a first-class kernel session state rather than application-layer confirmation, with formal state transitions and structured decision types",
  "m": 4,
  "mn": "Detailed specification with clear state definitions, decision types, and integration with Cedar policies, though lacks implementation examples or test vectors",
  "o": 2,
  "on": "Minor conceptual overlap with human-in-the-loop systems but unique in its kernel-level approach and formal state management",
  "mo": 3,
  "mon": "Active development with clear regulatory motivation (EU AI Act Article 14) suggesting ongoing relevance and potential adoption pressure",
  "r": 5,
  "rn": "Directly addresses core challenge of human oversight in autonomous AI systems with technical specification for a fundamental interaction pattern",
  "c": ["Human-agent interaction", "Policy/governance", "AI safety/alignment"]
}
```


This draft proposes Agentic JWT, an OAuth 2.0 extension for authenticating and authorizing autonomous AI agents through cryptographic agent identity and workflow-aware token binding. It addresses the 'intent-execution separation problem' where AI agents may deviate from user intent through dynamic workflow generation and autonomous decision-making.

Notable originality in addressing agent identity through system prompt/tool checksums and workflow-aware token binding - genuinely novel approach to OAuth for AI agents

Single draft from 2026 with no apparent working group adoption or community feedback yet

Minor similarities to general OAuth extensions and identity protocols, but the agentic-specific mechanisms appear quite unique

Core AI agent topic directly addressing fundamental authentication and authorization challenges in multi-agent systems


This draft extends EDHOC (Ephemeral Diffie-Hellman over COSE) to provide quantum resistance through two protocol variants that combine signatures and KEMs. The proposals aim to maintain lower message complexity compared to other quantum-resistant approaches while offering different tradeoffs between messages and computational overhead.

Useful contribution applying established post-quantum techniques to EDHOC, though the core approach of combining signatures with KEMs is not novel

Detailed 49-page specification with concrete protocol definitions for both 3-message and 3-or-4-message variants

Significant overlap with other post-quantum EDHOC drafts, though claims to reduce message complexity compared to parallel efforts

Single revision with no clear indication of working group adoption or broader community engagement

Primarily a cryptographic protocol for quantum-resistant key exchange, only tangentially related to AI/agents through general security applications


This draft proposes routing considerations for agentic networks where AI agents communicate with each other across domains using an overlay network architecture above IP. It addresses new networking requirements that emerge when agents need to connect to other agents with complementary skills during task execution.

Useful contribution addressing emerging agent-to-agent communication patterns, though overlay networking concepts are well-established

Early sketch at problem statement level - lacks detailed protocol mechanisms or concrete specifications

Minor similarities to existing overlay networking approaches but focuses on novel agent-specific use case

Single revision with limited evidence of broader community engagement or working group interest

Directly relevant to AI agent networking infrastructure and inter-agent communication protocols

A2A protocols
Agent discovery/reg
Autonomous netops


This IETF draft specifies methods for transforming different remote attestation evidence formats (DiceTcbInfo, concise evidence, SPDM measurements) into a common CoRIM internal representation. The goal is to enable Verifiers in Remote Attestation Procedures (RATS) to more easily appraise evidence from Attesters by standardizing the internal format while preserving original semantics.

Incremental work defining format transformations for existing attestation evidence types to a common representation

Detailed specification with concrete transformation methods for multiple evidence formats and appraisal procedures

Shares concepts with existing RATS architecture and CoRIM drafts but provides distinct transformation mechanisms

Active development in RATS working group addressing practical interoperability challenges

Tangentially related to AI agents as remote attestation could verify agent platforms, but primarily focused on general system trust verification


This draft proposes a framework for decentralized large language model inference across untrusted participants, treating inference as distributed layer-wise execution with explicit deadlines. The framework combines layer-aware transport, decentralized coordination, and security mechanisms for accountability without trusted execution environments.

Notable originality in applying decentralized computing principles specifically to LLM inference with layer-aware routing and deadline-driven execution - addresses a genuine gap between centralized AI services and distributed computing

Early architectural sketch with problem definition and solution space outlined, but explicitly states it does not specify concrete protocols, message formats, or state machines

Minor conceptual overlap with general distributed computing and federated learning approaches, but the specific focus on LLM layer-wise inference across untrusted networks is relatively unique

Single revision from 2026 with no clear working group adoption or community discussion visible, though the problem space is gaining attention

Core AI topic directly addressing LLM inference infrastructure challenges with specific focus on network-level protocols and distributed execution mechanisms

Model serving/inference
A2A protocols
Agent identity/auth


This draft proposes best practices for HTTP-based interactions between AI agents, including tool invocation via GET requests and formalizing the 402 status code for payment. It aims to standardize agentic HTTP interactions to prevent fragmented, proprietary ecosystems.

Useful contribution applying existing HTTP semantics to agent interactions, though the core concepts are extensions of established patterns

Appears to be single revision with no clear working group adoption or broader community engagement yet

Some conceptual overlap with general HTTP best practices and web APIs, but specific focus on agentic interactions is relatively unique

Directly addresses core AI agent infrastructure needs for standardized communication protocols and interoperability

A2A protocols
Data formats/interop
Agent identity/auth


This draft proposes a reference model for AI-Agent Communication Networks (ACN) that extends the CATS framework to enable communication between AI agents. It defines reference points, protocol stacks, service provisioning models, and signaling procedures for AI agent networking.

Useful application of CATS concepts to AI agent communication, though the core networking concepts are extensions of existing work

Early sketch with basic model definition but lacks detailed protocol specifications and implementation details

Builds directly on existing CATS framework and shares concepts with other agent communication proposals

Recent draft with limited revision history and unclear working group engagement

Directly addresses AI agent networking and communication infrastructure, which is highly relevant to AI agent systems

A2A protocols
Agent discovery/reg
Data formats/interop


This draft defines comprehensive benchmarking methodologies for evaluating LLM inference serving systems, specifying test procedures, measurement protocols, and reporting formats for performance characteristics. It serves as a companion to terminology standards and provides standardized approaches for measuring latency, throughput, and resource management in LLM deployments.

Useful contribution applying established benchmarking principles to the specific domain of LLM serving systems

Detailed specification with 48 pages covering test procedures, measurement specs, and reporting formats

Some conceptual overlap with general performance benchmarking standards but focused specifically on LLM serving

Active development as evidenced by 2026 date and companion terminology document reference

Directly relevant to AI systems focusing on standardized evaluation of model serving infrastructure


ATP is an asynchronous store-and-forward messaging protocol that enables autonomous AI agents to transmit themselves (including state, context, and capabilities) between agent runtimes across networks. The protocol uses SMTP-like semantics with cryptographic identity verification, trust scoring, and tamper-evident envelopes for secure agent mobility.

Notable originality in treating agents as self-contained mobile payloads with comprehensive state transfer, going beyond typical message-passing approaches

Well-defined protocol with clear operational model, security mechanisms, and interoperability claims, though lacks detailed message formats and implementation specifics

Some conceptual overlap with mobile agent systems and secure messaging, but unique focus on AI agent mobility with modern crypto and trust mechanisms

Single revision with future date suggests early stage; no evidence of working group adoption or broader community engagement yet

Directly addresses core AI agent communication challenges, particularly agent mobility and asynchronous operation in distributed environments

A2A protocols
Agent identity/auth
Data formats/interop


Proposes an agentic network architecture to support AI agent interconnection and multi-level inference across cloud-edge-end deployments. Focuses on enabling low-latency, high-bandwidth communication for collaborative agent scenarios like smart homes, industrial robotics, and autonomous vehicles.

Addresses the emerging need for agent-optimized network infrastructure, though the core networking concepts are evolutionary rather than revolutionary

Presents problem statement and high-level architecture concepts but lacks detailed protocol specifications, mechanisms, or implementation guidance

Shares conceptual space with edge computing and distributed inference work, but the agent-centric networking focus provides some differentiation

Single draft with no apparent follow-up activity or working group engagement visible

Directly addresses AI agent networking infrastructure needs, which is highly relevant to the emerging multi-agent ecosystem requirements

A2A protocols
Model serving/inference
ML traffic mgmt


Proposes using Model Context Protocol (MCP) to enable AI-assisted network measurement operations where network devices act as MCP servers and controllers as clients. The framework aims to provide natural language-driven network monitoring, fault diagnosis, and automated measurement workflows.

Useful application of MCP to network measurement domain, though combining AI protocols with network management is becoming common

Early-stage proposal with basic architecture description but lacks detailed protocol specifications and implementation details

Shares concepts with other AI-driven network management proposals and MCP application drafts

Single draft with no clear working group adoption or community engagement signals

Directly relevant as it applies AI agent protocols to network operations with natural language interfaces

Autonomous netops
A2A protocols
Human-agent interaction


This draft proposes an overlay network architecture for autonomous software agents to discover and interact across administrative domains. It defines control-plane coordination through management nodes, registries, and discovery services, while keeping runtime execution decentralized between agent endpoints.

Notable architectural approach separating control-plane coordination from runtime execution, with novel integration of trust anchors, semantic taxonomies, and enterprise service hubs in a unified overlay framework

Single draft from 2026 with no visible working group adoption or community discussion yet

Some conceptual similarities to service mesh and overlay network approaches, but the agentic-specific combination of discovery, trust, and semantic coordination appears relatively unique

Core AI agent networking topic addressing fundamental challenges of agent discovery, interoperability, and coordination across administrative boundaries

A2A protocols
Agent discovery/reg
Agent identity/auth
Policy/governance


VDAC defines a cryptographic protocol for bilateral contracts between content publishers and automated agents regarding data access terms. The protocol enables verifiable agreement formation through signed offers, acceptances, and per-request binding references.

Novel approach to formalizing publisher-agent data access agreements with cryptographic verification, addressing a gap in automated content access governance

Defines core protocol mechanisms and contract formation process but appears to lack detailed implementation specifics and concrete examples

While related to web scraping and API access concepts, the cryptographic bilateral contract approach appears relatively unique in the IETF space

Future-dated draft (2026) suggests this is conceptual; no evidence of working group adoption or broader community engagement

Directly addresses core AI agent operational needs for legitimate, verifiable data access relationships with content providers

A2A protocols
Agent identity/auth
Policy/governance


This draft proposes a DNS-based framework for privacy-preserving identity management that supports users, IoT devices, and AI agents through Self-Certifying Identifiers and trusted proxies. The approach uses DNSSEC-secured TXT records to bind public keys to identities while hiding real identities behind trusted intermediaries.

Useful contribution applying existing DNS/DNSSEC infrastructure to identity management for AI agents, though the core concepts of self-certifying identifiers and trusted proxies are established

Early sketch of framework with high-level concepts but lacks detailed protocol specifications, concrete examples, or implementation guidance

Significant overlap with existing DID methods, DNS-based identity systems, and privacy-preserving authentication schemes, though the specific combination for AI agents has some distinctiveness

Single revision draft with no indication of working group interest or broader community engagement

Directly relevant to AI agents with explicit focus on automated, AI-driven interactions and identity management for AI agents alongside users and IoT devices

Agent identity/auth
A2A protocols
Policy/governance


This IETF draft defines a SCITT profile for creating verifiable, tamper-evident records of AI agent actions through AgentInteractionRecords (AIRs). It maps SCITT roles to agent execution contexts and provides compliance mappings to major regulatory frameworks like EU AI Act and NIST AI RMF.

Notable originality in applying SCITT framework specifically to AI agent execution with comprehensive regulatory compliance mappings

Detailed specification with specific mechanisms like redaction receipts, hash chain integrity, and clear role mappings

Minor similarities to general SCITT work but unique application to AI agent execution domain

Single revision draft with no clear working group adoption yet

Core AI agent topic addressing critical transparency and accountability needs for autonomous systems


This draft defines Execution Context Tokens (ECTs) as JWT-based extensions to WIMSE for tracking task execution in distributed agentic workflows. ECTs create signed records of individual tasks linked through DAGs and are transported via new HTTP headers alongside existing WIMSE identity mechanisms.

Useful extension combining existing JWT/WIMSE patterns with workflow tracking - not groundbreaking but addresses real need for execution context in agent systems

Well-detailed specification with clear protocol mechanics, HTTP header definitions, and appears implementation-ready though could benefit from more examples

Builds directly on WIMSE architecture and shares workflow concepts with some other distributed system drafts, but specific ECT approach is distinct

Recent draft in active development area, reasonable length suggests serious effort, but momentum unclear without revision history

Directly addresses core AI agent infrastructure need for tracking distributed workflow execution with proper cryptographic attestation


This draft presents the problem statement and motivation for introducing Agentic AI to network management, aiming for a paradigm shift where multiple autonomous AI agents collaborate to fully automate network operations. It identifies fundamental issues with existing technologies and proposes core areas requiring IETF/IRTF standardization.

Incremental application of existing agentic AI concepts to network management domain

Pure problem statement document with no technical mechanisms or protocols defined

Shares general autonomous network management concepts with existing work but focuses specifically on agentic AI approach

Single revision draft with no clear working group adoption or community engagement signals

Directly addresses core AI agent topics for network automation and multi-agent collaboration

Autonomous netops
A2A protocols
Policy/governance


This draft specifies IAIP, a protocol for AI agent interconnection at Agent Gateways that enables dynamic discovery and routing based on semantic intent rather than static addressing. The protocol defines mechanisms for agent registration, capability advertisement, intent resolution and matching to facilitate agent-to-agent communication.

Intent-based agent interconnection represents a notable departure from traditional network addressing paradigms, introducing semantic matching and capability-based routing for AI agents

Defines core protocol mechanisms including registration, validation, and routing but lacks detailed message formats, state machines, or implementation specifics

While touching on service discovery concepts, the intent-based semantic routing approach for AI agents appears relatively unique in IETF space

Single draft submission with no clear working group adoption or community discussion visible

Directly addresses core AI agent networking challenges including discovery, capability matching, and intent-based communication - highly relevant to AI agent infrastructure


SONAR proposes a protocol for verifiable multicast delivery claims using cryptoeconomic accountability and statistical sampling to detect cheating without trusted intermediaries. It combines ALTA-based packet authentication with VRF sampling and blockchain attestations to verify content delivery at scale with minimal overhead.

Novel combination of multicast verification, cryptoeconomic incentives, and statistical sampling using German Tank Problem - creative approach to a challenging distributed systems problem

Well-defined protocol with clear mechanisms and mathematical foundations, but lacks detailed packet formats, state machines, and implementation specifics

Unique approach combining multicast networking with cryptoeconomic verification - some overlap with general blockchain attestation concepts but novel application domain

Single draft submission with no apparent working group adoption or community discussion yet

This is a networking protocol for multicast delivery verification, not related to AI agents or artificial intelligence applications


INIP is a protocol for performing lightweight ML inference directly in network data plane devices like switches and SmartNICs using a two-tier architecture with centralized model management and distributed execution. The protocol uses IPv4-based packet formats and match-action tables to enable high-speed inference without impacting core forwarding functions.

Novel approach to push ML inference into network data plane devices using match-action tables, representing a creative intersection of networking hardware capabilities and AI inference

Individual draft with recent timestamp but unclear adoption status or working group interest in this specific approach to in-network inference

While in-network computing exists, the specific focus on ML inference using match-action tables in data plane devices appears to have limited direct overlap with existing IETF work

Directly addresses AI model serving and inference with a novel network-centric approach that could enable new classes of AI-powered network applications

Model serving/inference
Autonomous netops


This draft outlines networking scenarios for AI agents in enterprise and home broadband environments, focusing on how these differ from 6G and general Internet use cases. The document appears to be primarily scenario-based rather than proposing specific technical solutions.

Incremental work applying existing agent concepts to specific network environments

Early stage draft with scenario descriptions but lacks detailed technical mechanisms

Shares general agent networking concepts with other drafts but focuses on specific deployment environments

Single revision with no clear working group activity or community engagement

Directly addresses AI agent networking in practical deployment scenarios

A2A protocols
Autonomous netops
Agent discovery/reg