ZTIP defines primitives for verifiable delegation, intent binding, and behavioral attestation in multi-agent systems using zero-trust principles. The 49-page specification appears to provide a comprehensive protocol for secure agent interactions and verification.

Zero-trust applied to intent-based multi-agent systems is a notably original approach combining emerging concepts

49 pages suggests detailed specification with substantial protocol definition and likely examples

While touching on zero-trust and agent concepts, the specific intent protocol approach appears relatively unique

Single revision suggests early stage without demonstrated community engagement

Multi-agent systems with verifiable delegation and behavioral attestation is core to AI agent infrastructure

A2A protocols
Agent identity/auth
AI safety/alignment


This draft analyzes problems with DNS in supporting Internet of Agents (IoA) scenarios and explores technical requirements for agent collaboration. It focuses on how DNS needs to evolve to accommodate AI-driven agent interactions and discovery.

Useful contribution applying DNS to agent systems, though DNS evolution for new paradigms is an established pattern

Early sketch focusing on problem statement and requirements analysis without detailed technical solutions

Minor similarities to general DNS evolution work but unique focus on agent-specific requirements

Single draft with future date suggests early stage work without demonstrated community engagement

Directly relevant to AI agent infrastructure, addressing core networking needs for agent discovery and collaboration

Agent discovery/reg
A2A protocols
Data formats/interop


This draft clarifies ambiguities in RFC7030's CSR Attributes Response specification for EST (Enrollment over Secure Transport), addressing implementation challenges through clearer encoding rules. It introduces a template-based approach for CSR contents that allows EST servers to specify subject Distinguished Names and other attributes more precisely.

Incremental clarification of existing protocol ambiguities with straightforward template approach

Detailed specification with clear encoding rules and practical template mechanism for implementation

Significant overlap with RFC7030 and RFC9148 as this is an update/clarification document

IETF working group draft with recent publication date suggesting active development

Pure PKI certificate enrollment protocol specification with no AI or agent-related content


This draft extends the Robots Exclusion Protocol (robots.txt) to allow targeting of web crawlers and automated clients based on their stated purpose for accessing content, rather than just their user-agent string. It proposes a new rule type that could enable more granular control over different types of AI agents and automated systems based on their intended use case.

Useful extension addressing real need as AI agents diversify beyond traditional web crawlers

Early specification stage with basic concept outlined but lacking detailed implementation guidance

Builds directly on RFC9309 but addresses distinct targeting mechanism not covered elsewhere

Single revision draft with no clear working group activity or community discussion

Directly relevant to AI agent ecosystem management and web resource access control

ML traffic mgmt
Policy/governance
Agent identity/auth


This draft proposes an intelligent routing method for SR Policy that selects forwarding paths based on network quality metrics in MPLS and IPv6 environments. It extends existing SR Policy candidate path selection with network-aware intelligence for optimized routing decisions.

Incremental improvement to existing SR Policy mechanisms by adding network quality-based path selection intelligence

Defines a specific mechanism for intelligent SR Policy routing with clear methodology, though implementation details may need refinement

Shares concepts with existing SR Policy and traffic engineering drafts, builds on established SR framework

Single revision draft with unclear working group engagement or broader community interest

Partially relevant as it involves intelligent/AI-based routing decisions for network optimization, though not core AI agent functionality


This draft proposes BRSKI-CLE, a certificateless enrollment framework for constrained IoT devices that cannot handle certificates due to RAM limitations. The approach uses Key Encapsulation Mechanism (KEM) for quantum-safe security and lightweight credentials like CBOR Web Tokens instead of traditional X.509 certificates.

Useful contribution addressing a real constraint problem in IoT bootstrapping, though certificateless cryptography concepts exist

Early sketch with framework outline but lacks detailed protocol specification, implementation details, and concrete examples

Shares bootstrapping concepts with existing BRSKI work and builds on established certificateless cryptography approaches

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

Focuses on IoT device bootstrapping and authentication rather than AI agents, though could tangentially apply to constrained AI devices


Proposes a semantic-driven contract mechanism where AI applications provide minimum necessary semantics to networks, enabling differentiated forwarding and resource allocation for tensor flows. Aims to improve resource utilization and task completion times in heterogeneous AI computing environments.

Notable approach to expose AI workload semantics to network layer for intelligent traffic shaping, going beyond traditional QoS

Early stage draft at 6 pages, likely contains high-level concepts but lacks detailed protocol specification and implementation details

Some conceptual overlap with general network QoS and ML-aware networking, but semantic contract approach appears relatively unique

Single draft version with recent date suggests early development stage without demonstrated community engagement

Directly addresses AI network optimization challenges, highly relevant to distributed AI training and inference infrastructure


Defines a JSON-based format and HTTP convention for advertising and invoking AI agents uniformly across web hosts. Uses JSON Schema for describing agent inputs/outputs and serves from well-known locations as a primitive for higher-level discovery systems.

Basic HTTP+JSON approach to agent description, incremental application of existing web standards to AI agent context

Defines concrete protocol with JSON Schema usage and HTTP conventions, though lacks comprehensive examples and implementation details

Shares conceptual ground with OpenAPI/service description formats and other agent discovery approaches

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

Directly addresses core challenge of AI agent discovery and standardized invocation on the web

Agent discovery/reg
Data formats/interop
A2A protocols


CAAM defines a post-discovery authorization layer for AI agents that enforces relationship-based access control and purpose-bound delegation after agent discovery but before execution. It introduces Session Context Objects as JWTs/CWTs with contextual assertion claims to bind delegated authority to specific purposes and trust chains.

Notable originality in combining relationship-based access control with purpose-bound delegation for agent authorization, plus the contextual assertion claim design

Detailed 33-page specification with defined protocol mechanisms, token formats, and integration with multiple existing frameworks

Shares authorization concepts with existing identity frameworks but creates novel combinations for agent-specific use cases

Single revision with complex dependencies on multiple other draft protocols, unclear adoption signals

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

Agent identity/auth
A2A protocols
Policy/governance
Human-agent interaction


Proposes dynamic attestation mechanisms for AI agent communication over TLS, addressing how to continuously verify agent runtime posture including platform TCB, models, tools and policies during long-lived sessions. Focuses on enabling relying parties to make authorization decisions based on current agent state rather than initial handshake credentials.

Notable originality in applying continuous attestation to AI agent contexts where runtime state changes frequently

Early sketch level - describes use case and requirements but lacks detailed protocol mechanisms

Minor similarities to general remote attestation work but AI agent context is relatively unique

Single revision with no clear working group adoption yet

Core AI agent topic addressing fundamental trust and security challenges in agent-to-agent communication


This draft proposes using special text tags to improve data quality and context for conversational AI models during training and inference. The approach aims to enhance model understanding of user queries through structured markup.

Incremental approach to AI training data structuring, building on established markup concepts

Early stage draft with basic concept outline but lacks detailed protocol specification

Shares general concepts with existing AI training and markup standardization efforts

Single revision with no apparent working group adoption or community engagement

Directly addresses AI model improvement through structured data approaches

Data formats/interop
Model serving/inference


This draft proposes network protocol enhancements to recognize and optimize transmission of multi-modal AI agent data. It addresses the need for networks to understand different quality requirements for various data types (text, audio, video) within AI agent communications.

Useful contribution addressing a real emerging need, though applying existing QoS concepts to AI agent traffic

Early sketch phase with problem statement and high-level requirements but lacks detailed protocol specifications

Shares QoS and traffic management concepts with existing network drafts but focuses specifically on AI agent multi-modal requirements

Single revision draft from 2026 with no clear working group adoption or community engagement

Directly relevant to AI agent networking needs, addressing practical infrastructure requirements for multi-modal agent communications


This draft analyzes potential multicast use cases in Large Language Model Mixture of Experts (MoE) architectures, particularly for token dispatching scenarios. The document appears to be a problem statement and use case analysis rather than a detailed protocol specification.

Incremental work applying existing multicast concepts to MoE token distribution - useful but not particularly original

Early sketch level - analyzes use cases but lacks detailed protocol mechanisms or specifications

Minor similarities to general ML traffic management approaches but addresses specific MoE multicast scenarios

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

Directly relevant to AI model serving and inference optimization, addressing real networking challenges in MoE architectures


This draft proposes an intelligent routing method for SR Policy that selects paths based on network quality metrics in MPLS and IPv6 environments. It extends existing SR Policy candidate path selection with network-aware decision making capabilities.

Incremental enhancement to existing SR Policy mechanisms by adding network quality-based path selection

Defines a specific protocol mechanism with clear concepts but lacks detailed implementation specifics

Shares concepts with existing SR Policy and traffic engineering drafts but adds distinct quality-based routing approach

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

Partially relevant as it describes intelligent/adaptive network behavior but focuses on traditional networking rather than AI agents


This draft specifies an algorithm for determining effective media types of HTTP responses by examining both Content-Type headers and response content, addressing compatibility issues with web servers that supply incorrect MIME types. The algorithm balances security considerations with the need to handle legacy server behavior that commonly provides mismatched content types.

Incremental standardization of existing browser behavior for MIME type sniffing

Detailed specification with concrete algorithm steps and security considerations

Significant overlap with existing web security and HTTP standards

Active IETF working group development in websec

Pure web security/HTTP protocol specification with no AI or agent relevance


This draft defines a CDDL-based data format for creating verifiable records of autonomous agent conversations, capturing session metadata, message exchanges, tool invocations, and reasoning traces. It uses COSE signing for integrity and aims to enable accountability and compliance for AI agent interactions through structured, interoperable conversation logs.

Useful contribution addressing the emerging need for verifiable AI agent interactions, though the core concept of signed conversation logs is relatively straightforward

Detailed 51-page specification with comprehensive CDDL definitions, JSON/CBOR representations, and clear integration with existing standards like COSE and SCITT

Some conceptual overlap with general verifiable data structures and audit logging, but specific focus on AI agent conversations is relatively unique

Single draft submission without clear indication of working group adoption or broader community engagement

Directly addresses a critical need in AI agent systems for accountability, transparency, and verifiable behavior records as agents perform increasingly consequential tasks

Data formats/interop
AI safety/alignment
A2A protocols


This draft defines a framework for AI agent networks using the Agent Network Protocol (ANP) to enable communication between AI agents within trust domains. It appears to establish basic communication functions for agent-to-agent interactions in networked environments.

Useful contribution defining structured agent communication framework, though agent networking concepts are becoming established

Early sketch stage with basic framework definition but lacking detailed protocol specifications and implementation details

Shares networking and communication concepts with emerging agent protocol work but focuses specifically on trust domain approach

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

Core AI agent topic directly addressing agent-to-agent communication protocols and network architectures

A2A protocols
Agent discovery/reg
Agent identity/auth


This draft specifies AgentROA, a cryptographic policy enforcement framework for AI agents that adapts BGP Route Origin Authorization concepts to govern agent actions through signed policy envelopes, delegation chains, and execution receipts. The framework implements a Border Gateway enforcement model that positions cryptographic validation at capability invocation boundaries, external to the agent's execution context.

Novel application of RPKI/BGP ROA concepts to AI agent governance with creative Border Gateway enforcement positioning

Detailed specification with clear protocol objects, schemas, and enforcement semantics across multiple deployment topologies

Unique cryptographic approach to agent governance with minimal overlap to existing AI safety frameworks

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

Directly addresses core AI agent governance and policy enforcement challenges with practical cryptographic mechanisms

Policy/governance
Agent identity/auth
AI safety/alignment


This draft extends SRv6 to enable multicast delivery of RDMA traffic by defining new endpoint behaviors for per-receiver packet modifications and aggregating response messages. It targets high-performance computing and AI training scenarios where efficient one-to-many data distribution is critical.

Notable originality in combining SRv6 segment routing with RDMA multicast - addresses complex challenge of maintaining QP semantics over IP multicast trees

Detailed specification with new endpoint behavior End.MT, BTH modification procedures, and ACK/NACK aggregation mechanisms - appears implementation-ready

Minor similarities to general SRv6 and RDMA work but unique in combining these for multicast scenarios

Active development with recent draft date, targeting emerging HPC/AI infrastructure needs

Directly relevant to AI agent infrastructure - specifically addresses AI training parameter distribution and inference KV cache distribution at scale


This draft proposes an Agent Communication Gateway (Agent-GW) that serves as an infrastructure hub for multi-agent collaboration, providing semantic routing, shared working memory, and protocol adaptation across heterogeneous agent systems. The framework aims to enable intent-based interactions and collaborative workflows between agents across different administrative and protocol boundaries.

Notable integration of semantic routing with working memory and knowledge delivery networks - combines existing concepts in a genuinely useful way for agent infrastructure

Early architectural sketch with high-level concepts but lacks detailed protocol specifications, message formats, or concrete implementation guidance

While touches on gateway concepts, the semantic routing and working memory combination for agent infrastructure appears relatively unique

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

Directly addresses core challenges in AI agent communication, collaboration, and infrastructure - highly relevant to emerging agent ecosystems

A2A protocols
Agent discovery/reg
Data formats/interop
Model serving/inference


CAP defines a three-tier prohibition architecture for agentic AI systems with kernel-enforced constraints, evaluating both AI agent actions and human principal decisions against absolute, jurisdictional, and voluntary ethical prohibitions. The protocol includes jurisdictional conflict resolution mechanisms to handle irreconcilable policy conflicts via human escalation.

Novel three-tier prohibition model with dual evaluation points and kernel enforcement represents a genuinely original approach to AI governance

Detailed specification with defined tiers, evaluation mechanisms, and integration with related protocols, approaching implementation readiness

While governance concepts exist, the specific kernel-enforced dual-evaluation architecture has minimal overlap with existing work

Active development evidenced by cross-references to related drafts in the same series, suggesting coordinated protocol suite development

Directly addresses core AI agent safety and governance concerns with technical protocol specification

AI safety/alignment
Policy/governance
Human-agent interaction


Proposes HTTP Agent Profile (HAP) to enable cryptographic authentication of autonomous agents, separate human from agent traffic using privacy-preserving tokens, and enable micropayments for agent content access. Addresses economic misalignment between AI systems that consume content at scale without viewing ads and content providers who rely on advertising revenue.

Notable integration of agent authentication, human/agent traffic separation, and micropayment mechanisms into a cohesive HTTP-based protocol addressing a genuine economic problem

Well-defined protocol mechanics with clear use of HTTP Message Signatures and status codes, though lacks detailed implementation examples and test vectors

While authentication and payment protocols exist separately, this specific combination for agent traffic management appears to have minimal overlap with existing work

Recent draft from November 2024 but appears to be initial publication without evidence of working group adoption or broader community engagement

Directly addresses core challenges of AI agent web traffic including authentication, economic sustainability, and human/agent differentiation - highly relevant to AI agent ecosystem

Agent identity/auth
ML traffic mgmt
Policy/governance


This draft enhances EAP-AKA' Forward Secrecy protocol with Post-Quantum Key Encapsulation Mechanisms to protect against future quantum computer threats. It replaces traditional ECDHE key agreement with quantum-resistant algorithms to maintain perfect forward secrecy in mobile authentication.

Incremental upgrade replacing ECDHE with PQ-KEMs in existing EAP-AKA' FS - straightforward quantum-resistant enhancement

20-page draft with defined protocol mechanisms building on RFC9678, appears to specify concrete PQ-KEM integration

Shares post-quantum cryptography concepts with other PQC drafts, builds directly on existing EAP-AKA' FS specification

IETF EMU working group draft with 2026 date suggests active development and working group adoption

This is about quantum-resistant cryptography for mobile network authentication, not AI or autonomous agents


This draft proposes an intent-based network management use case with a five-level architecture for achieving fully autonomous network operations without human intervention. It focuses on simplifying network complexity through automated management driven by high-level intent specifications.

Incremental contribution building on well-established IBN concepts without significant new insights

Early conceptual sketch with basic architecture outline but lacks detailed protocols or implementation specifics

Significant overlap with existing IBN and autonomous network management literature and standards

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

Directly relevant to AI-driven network operations and autonomous management systems


This draft proposes adding 'Agent Considerations' sections to IETF specifications to help AI agents consume specs and generate code from them. It defines guidance for authorship, examples annotation, and language-specific media-type production to enable better AI-assisted implementation of IETF protocols.

Useful contribution addressing the practical need for AI-readable specifications, though the core concept of structured documentation for automated consumption isn't entirely new

Early sketch level - defines the concept and structure but lacks detailed implementation guidance, specific examples, or concrete mechanisms for how agents would actually consume this information

Minor conceptual similarities to existing documentation standards and API specification formats, but the specific focus on IETF specs for AI agent consumption is relatively unique

Single revision with no clear indication of working group interest or broader community engagement in this specific approach

Directly relevant to AI agents in networking - addresses the practical challenge of enabling AI systems to understand and implement network protocols from IETF specifications

Data formats/interop
Policy/governance
Human-agent interaction


This draft presents a problem statement for handling AI/LLM network traffic across datacenters, focusing on the specific characteristics of training and inference workloads that require federated cooperation between service providers. The document identifies networking challenges arising from large parameter counts and collective communication patterns in distributed AI systems.

Incremental work identifying known networking challenges for distributed AI workloads

Pure problem statement without proposed solutions or mechanisms

Shares concepts with existing work on AI traffic optimization and distributed ML networking

Single revision from October 2024, unclear community engagement

Directly addresses AI infrastructure challenges, though focused on network layer rather than agent protocols


Defines AMSP for synchronizing agent metadata between hierarchical gateways in Internet of Agents deployments. Enables global agent discovery and routing across distributed network domains with loop-free propagation.

Useful contribution applying distributed systems concepts to agent infrastructure, though builds on established gateway synchronization patterns

Defines core protocol mechanisms and hierarchical architecture but lacks detailed message formats and implementation specifics

Minor similarities to general distributed synchronization protocols but specific application to agent metadata is relatively unique

Single revision with future date suggests early stage development, no clear working group adoption

Core AI agent infrastructure topic addressing fundamental challenges of large-scale agent deployments and inter-gateway coordination

A2A protocols
Agent discovery/reg
Autonomous netops


This draft identifies the authorization challenges when AI agents operate autonomously in enterprise campus networks, proposing task-bound privilege reduction enforced by network devices. It argues for in-path enforcement to maintain compatibility with legacy systems while controlling agent access across heterogeneous protocols.

Novel application of network-based enforcement for AI agent authorization in campus environments, addressing the mismatch between traditional human-centric auth models and autonomous agent behavior

Early problem statement and high-level solution sketch, lacks concrete protocol definitions or implementation details

Some conceptual overlap with zero-trust architectures but unique focus on AI agent scope-down in campus networks

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

Directly addresses core AI agent authentication and authorization challenges in network environments

Agent identity/auth
Policy/governance
Autonomous netops


This draft provides best practices for managing Route Origin Authorizations (ROAs) in RPKI when using anycast services where each anycast node has a unique origin ASN. It focuses on mitigating technical risks in RPKI operations for such deployments.

incremental contribution addressing specific operational scenarios in existing RPKI framework

early sketch of best practices without detailed implementation specifics

builds on existing RPKI and anycast concepts but addresses specific combination

single revision with no clear working group adoption signals

purely network infrastructure focused, no AI or agent relevance


AEBA defines a framework for monitoring and analyzing behavioral events from autonomous AI agents, providing structured event schemas, signature binding, and integration with existing SIEM systems. It aims to enable security monitoring of AI agents similar to how UEBA systems monitor user behavior in enterprise environments.

Notable originality in adapting behavioral analytics concepts specifically for autonomous AI agents with cryptographic bindings

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

Minor similarities to general behavioral monitoring approaches but unique focus on autonomous AI agents

Core AI agent topic directly addressing critical security monitoring needs for autonomous systems

AI safety/alignment
Agent identity/auth
Data formats/interop
A2A protocols


This draft specifies how the Agent-to-Agent (A2A) protocol can be transported over Media over QUIC Transport (MOQT), enabling real-time communication between AI agents. It leverages MOQT's publish/subscribe model and streaming capabilities to support A2A requirements for agent discovery, negotiation, and collaboration.

Incremental application of existing MOQT transport to A2A protocol - straightforward protocol mapping

Defines specific protocol mechanisms for A2A over MOQT with reasonable detail at 12 pages

Shares transport concepts with other QUIC-based approaches and overlaps with general A2A protocol work

Single revision with 2026 date suggests early stage development without established momentum

Directly addresses AI agent communication transport, core to agent-to-agent interaction infrastructure


This IETF draft defines HPKE (Hybrid Public Key Encryption), a cryptographic scheme that combines asymmetric and symmetric encryption for efficient public key encryption of arbitrary-sized plaintexts. The scheme includes authenticated variants and works with various combinations of KEMs, KDFs, and AEAD functions, providing instantiations using widely-used primitives like ECDH and HKDF.

Useful contribution that systematically combines existing cryptographic primitives into a cohesive hybrid encryption scheme with multiple authentication modes

Implementation-ready specification at 125 pages with detailed protocol definitions, likely includes comprehensive examples and test vectors

While building on established cryptographic primitives, the specific hybrid approach and authentication variants have minor similarities to existing schemes

CFRG product suggests working group adoption and active standardization process within IRTF crypto community

This is a pure cryptographic protocol specification with no AI or agent-related content - appears to be a false positive in AI/agent classification


JIS defines a comprehensive identity and trust protocol for autonomous agents using dual keypairs (human-device and device authentication), trust negotiation handshakes, and human-readable context layers. The protocol operates transport-agnostically as a semantic layer and integrates with multiple referenced systems for provenance, verification, and agent discovery.

Notable originality in combining dual-keypair identity model with intent binding and human-readable context layers - goes beyond traditional PKI approaches

Future-dated draft (2026) with no indication of working group adoption or community development activity

While identity and trust are common themes, the specific dual-keypair approach with intent binding and Humotica context layer appears relatively unique

Directly addresses core autonomous agent challenges of identity establishment, trust negotiation, and intent binding - fundamental requirements for agent systems

Agent identity/auth
A2A protocols
Human-agent interaction


This draft proposes a mechanism for authoritative DNS servers to signal support for encrypted transport protocols (DoT, DoH, DoQ) within DNS responses or through direct queries. It enables resolvers to discover and upgrade to secure transports opportunistically or with DNSSEC validation, improving upon RFC9539's blind transport testing approach.

Incremental improvement to existing DNS transport discovery mechanisms, building on RFC9539 with signaling rather than blind probing

Detailed specification with clear protocol mechanisms, examples of opportunistic and validated modes, and implementation guidance

Shares concepts with existing DNS transport upgrade mechanisms and RFC9539, but provides a distinct signaling-based approach

Active individual draft with GitHub collaboration, but no clear working group adoption or broader community momentum yet

Pure DNS protocol enhancement for transport discovery - not related to AI agents or autonomous systems


This draft proposes a standardized protocol for discovering and invoking AI agents across platforms, defining metadata formats, capability-based discovery, and RESTful invocation interfaces. It includes an optional intent-based agent selection extension and addresses security considerations for multi-agent system interoperability.

Useful contribution addressing real interoperability needs, though the core concepts of service discovery and RESTful invocation are well-established patterns being applied to AI agents

Single revision from future date (2026-02-12) suggests early stage work without demonstrated community engagement or working group adoption

Shares service discovery concepts with existing web service standards and overlaps with general agent communication protocols, but focuses specifically on AI agent interoperability

Directly addresses core AI agent infrastructure needs for discovery, metadata description, and cross-platform invocation - fundamental to multi-agent system development

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


This draft extends RFC 7030 (Enrollment over Secure Transport) to allow certificate authorities to provide specific renewal timing recommendations to end-entity devices, replacing the typical 50% lifetime rule. The motivation is that as certificate lifetimes shorten from years to months, the traditional 50% renewal point may be unnecessarily early and wasteful.

Incremental extension addressing a practical timing issue as certificate lifetimes decrease

Early sketch level - only provides problem statement and basic concept without detailed protocol mechanisms

Shares certificate management concepts with existing PKI and EST work but addresses specific renewal timing gap

Single revision with recent date suggests limited development activity so far

Tangentially related to AI/agents only in that automated systems need certificate management, but primarily a general PKI improvement


This draft proposes enhancing EAP-AKA' Forward Secrecy with hybrid post-quantum cryptography to protect against future quantum computer threats. It aims to make the authentication protocol quantum-safe by replacing traditional ECDHE key exchange with PQ/T hybrid algorithms.

Incremental application of established hybrid PQC concepts to existing EAP-AKA' protocol

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

Significant overlap with general hybrid PQC standardization efforts and other quantum-safe authentication proposals

Active development addressing timely quantum threat concerns in authentication protocols

This is a network security/cryptography draft about authentication protocols, not related to AI or agents


This draft defines SASL2, an extensible authentication and security layer framework that allows protocols to use pluggable authentication mechanisms. It extends the original SASL to support additional authentication tasks like two-factor authentication and password changes.

Incremental improvement to existing SASL framework with some useful extensions

Well-defined protocol specification with clear structure and detailed mechanisms

Significant overlap with existing SASL RFCs, though adds new capabilities

Active development as indicated by 2025 date, but momentum unclear without WG context

Authentication framework is tangentially related to AI agents but not AI-specific


Proposes an inter-domain SAVNET architecture for AS-level Source Address Validation using both SAV-specific and general information sharing between autonomous systems. Defines architectural components and framework for generating more accurate SAV rules compared to existing approaches.

Useful contribution extending SAV concepts to inter-domain scenarios with novel information sharing approach

Early architectural sketch with components defined but lacks detailed protocol specifications

Shares concepts with existing SAV and BGP security work but focuses on inter-domain coordination

Active IETF working group draft with clear development trajectory

Network security architecture focused on source address validation, not related to AI or agents


This draft explores AI agent communication protocols for 6G networks, building on 3GPP TR 22.870 use cases and service requirements. It extrapolates potential protocol requirements for agent-to-agent and agent-to-tool communication in future 6G systems.

Incremental work that applies existing AI agent communication concepts to the 6G context, following established 3GPP requirements analysis patterns

Early sketch that primarily references 3GPP use cases and extrapolates high-level protocol requirements without detailed technical specifications

Shares conceptual overlap with general AI agent communication work but focuses specifically on 6G network integration

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

Directly relevant to AI agent protocols, though primarily focused on telecommunications network integration rather than general internet protocols

A2A protocols
Data formats/interop
ML traffic mgmt


This draft proposes a decentralized identity protocol for AI agents using W3C DIDs and capability-based authorization to enable secure multi-agent workflows. It combines cryptographic delegation chains with deterministic validation to eliminate dependence on centralized identity providers.

Notable integration of DIDs with AI agent delegation - first comprehensive framework addressing agent identity chains and capability inheritance in decentralized systems

Detailed 225-page specification suggests comprehensive protocol definition with examples, though implementation readiness depends on test vector completeness

Leverages existing W3C DID standards but applies them uniquely to AI agent contexts with novel delegation mechanisms

Single draft from 2026 with no visible working group adoption yet, though the comprehensive length suggests serious development effort

Directly addresses core AI agent infrastructure need for decentralized identity and authorization - fundamental building block for multi-agent systems

Agent identity/auth
A2A protocols
AI safety/alignment


Proposes a network architecture for trustworthy routing where data is transmitted only through trusted devices, extending BGP and BGPsec protocols to carry trustworthy routing information (TRI). Aims to address security and privacy requirements for high-security applications by enabling route selection based on device trustworthiness.

Incremental extension of existing BGP/BGPsec protocols to include trust attestation - builds on established concepts but applies them to routing decisions

Early sketch level - describes architecture and TRI concept but lacks detailed protocol mechanics, message formats, or trust evaluation algorithms

Significant overlap with existing trusted computing, BGPsec extensions, and secure routing literature - trust attestation in networking is well-explored

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

Tangentially related to AI/agents - while trustworthy routing could support AI agent communications, this is primarily a general networking security mechanism


This draft analyzes gaps in existing network configuration protocols (NETCONF, RESTCONF, gNMI, etc.) for supporting LLM-driven intent-based networking with natural language interfaces. It systematically identifies where current south-bound protocols fall short for conversational, multi-agent orchestration scenarios.

Useful systematic analysis of protocol gaps for LLM integration, though the concept of intent-based networking gaps is somewhat predictable

Early analysis stage - identifies problems and extension points but lacks concrete protocol modifications or detailed solutions

Some conceptual overlap with intent-based networking work, but specific focus on LLM protocol gaps is relatively unique

Single revision with future date suggests early stage work, unclear community engagement or WG interest

Directly addresses AI agent networking with focus on protocol adaptations for LLM-driven operations

Autonomous netops
A2A protocols
Data formats/interop
Human-agent interaction


This draft proposes ADOL (Agentic Data Optimization Layer), a data layer designed to reduce token consumption in agent-to-agent communication by eliminating redundant schema definitions, verbose structures, and inefficient capability exchanges. The approach uses techniques like JSON references, adaptive field inclusion, and controllable response verbosity to optimize context window usage for LLM-based agents.

Addresses a real optimization problem in agent communication with practical techniques, though the individual methods (JSON refs, adaptive fields) are incremental improvements rather than fundamental innovations

As a single draft from 2026-01-12 with no indication of working group adoption or community engagement, shows minimal momentum in the standardization process

Builds upon existing agent communication protocols like MCP and A2A, sharing optimization concepts with other efficiency-focused drafts but targeting the specific domain of token efficiency

Directly addresses a core challenge in AI agent systems - the efficient use of limited context windows in LLM-based agent communication, which is fundamental to practical agent deployment


This draft defines Attested Inference Receipt (AIR), a COSE/CWT-based format for creating cryptographically signed receipts that prove confidential AI inference events occurred within hardware-isolated Trusted Execution Environments. The receipts bind model identity, input/output hashes, and attestation metadata into verifiable artifacts for third-party validation.

Notable originality in creating a standardized receipt format specifically for confidential AI inference with TEE integration - addresses the emerging need for verifiable AI computation proofs

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

Minor similarities to general attestation frameworks but uniquely focused on AI inference receipts with specific cryptographic binding of model and computation metadata

Core AI agent topic addressing critical needs for verifiable, confidential AI inference - directly relevant to trustworthy AI deployment and verification

Agent identity/auth
Model serving/inference
Data formats/interop


This draft standardizes DRIP Entity Tags (DETs) as identifiers for drone remote identification, enabling trustworthy air domain awareness for unmanned aircraft systems. DETs serve multiple roles including session IDs for privacy, authentication key IDs for accountability, and encryption key IDs for confidentiality in UAS traffic management.

Incremental application of existing DRIP concepts to air domain awareness - extends known identification protocols to UAS context

Detailed 51-page specification with comprehensive registration and usage procedures for DET implementation in UAS systems

Shares identification and authentication concepts with other DRIP drafts and general identity management protocols

Active development with 2026 date indicating ongoing work, though momentum unclear from single draft snapshot

Primarily about drone identification systems rather than AI agents, though UAS may incorporate autonomous capabilities


```json
{
  "s": "IDDrop defines a protocol for transferring identity claims between human and machine environments using offer-first and request-first modes. It emphasizes sealed carrier truth and semantic classification rather than filename-based identity verification.",
  "n": 4,
  "nn": "Notable approach to identity transfer that moves beyond traditional filename-based verification to sealed carrier truth and causal validation",
  "m": 3,
  "mn": "Appears to define core protocol mechanisms and operating modes but lacks implementation details and test vectors",
  "o": 2,
  "on": "While identity protocols exist, the specific focus on human-machine identity transfer with sealed carriers is relatively unique",
  "mo": 1,
  "mon": "Single draft from future date (2026-05-18) suggests this is either hypothetical or very early stage work",
  "r": 4,
  "rn": "Directly addresses agent identity and authentication challenges, particularly relevant for human-agent interaction scenarios",
  "c": ["Agent identity/auth", "Human-agent interaction", "A2A protocols"]
}
```


HTTPA/2 extends HTTP to enable trusted communication with Trusted Execution Environments (TEEs) through remote attestation, eliminating dependence on TLS. The protocol treats TEEs as a new type of internet resource that can be attested and communicated with securely.

Notable approach to integrating TEE attestation directly into HTTP protocol layer, moving beyond traditional TLS-based security models

Defines protocol mechanisms and transaction flows but lacks detailed implementation examples and test vectors

Limited overlap with existing work - builds on original HTTPA/1 but represents distinct architectural approach

Single author draft with no apparent working group adoption or community discussion

Partially relevant - TEE attestation mechanisms could support secure AI agent execution and verification


Proposes a Meta-layer as a coordination substrate enabling communities and agents to share presence, annotations, and governance across web platforms. The draft outlines high-level concepts and use cases but lacks concrete protocol specifications or implementation details.

Useful contribution combining existing concepts (overlay networks, annotation systems, governance) into a coherent coordination framework for multi-agent environments

Early conceptual sketch with terminology and use cases but missing concrete protocols, message formats, or implementation specifications

Shares concepts with existing annotation systems, overlay networks, and distributed governance proposals but applies them to a specific coordination use case

Single revision with future date (2025-10-06), no evidence of working group adoption or community development activity

Directly relevant to AI agents with explicit focus on agent coordination, multi-agent governance, and shared digital spaces for automated systems

A2A protocols
Policy/governance
Agent discovery/reg


Proposes DA-ITN, a unified multi-plane network framework to support AI training, inference, and agentic interactions across distributed resources. The architecture includes control, data, and operations planes connecting AI clients, data providers, model providers, and computational resources.

Useful contribution that combines existing networking concepts with AI-specific requirements, though the multi-plane architecture approach is incremental rather than groundbreaking

Early sketch stage with high-level architecture description but lacks detailed protocol specifications, concrete mechanisms, or implementation guidance

Shares multi-plane networking concepts with existing IETF work and overlaps with other AI infrastructure proposals, but applies them specifically to AI workflows

Future-dated draft (2026) suggests this is inactive or hypothetical work with no apparent community engagement or development history

Directly addresses core AI infrastructure challenges including training, inference, and agent interactions with network-level considerations highly relevant to IETF

ML traffic mgmt
Model serving/inference
Agent discovery/reg
Data formats/interop
Policy/governance


This draft explores how large language models and AI agents can enhance network operations and maintenance by reducing manual tasks and improving automation. It identifies key scenarios where AI can address operational challenges and examines the impacts on network architectures, data handling, and standardization needs.

Incremental application of well-known LLM capabilities to network operations domain

Early conceptual sketch identifying scenarios and challenges without concrete protocols or mechanisms

Shares general concepts with other network automation and AI operations drafts but focuses specifically on LLM agents

Single draft with future date suggests early stage work without demonstrated community engagement

Directly addresses AI agents in networking context with specific focus on operational applications

Autonomous netops
Policy/governance
Human-agent interaction


Defines a framework for evaluating whether speech acts from autonomous agents are admissible based on modality and grounding state, without requiring semantic truth verification. Enables deterministic auditing of agent communications through rule-based admissibility criteria.

Novel approach to agent communication evaluation focusing on structural admissibility rather than semantic truth - addresses a gap in formal frameworks for agent speech act validation

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

Some conceptual overlap with general agent communication work, but the specific focus on normative admissibility evaluation is relatively unique

Directly addresses autonomous agent communication validation, a core concern for AI agent systems deployment and auditing

A2A protocols
AI safety/alignment
Policy/governance


Defines the Agent Trust Negotiation (ATN) protocol that enables AI agents to establish verifiable working agreements by binding capability statements, delegation proofs, provenance records, and reputation metrics to DNS-discovered agent identities. ATN addresses the critical gap between agent discovery and establishing trusted operational relationships.

Novel approach to binding multiple trust artifacts (capability, delegation, provenance, reputation) into a cohesive negotiation protocol for AI agents

48-page detailed specification with defined protocol mechanisms and comprehensive framework for agent trust establishment

While it touches on identity and discovery, the specific trust negotiation binding approach appears largely unique

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

Directly addresses core AI agent challenges of trust, authorization, and secure inter-agent collaboration

A2A protocols
Agent identity/auth
Policy/governance


```json
{
  "s": "This draft proposes a method for mailing list managers to revert From: header transformations that were implemented as DMARC workarounds. It focuses on an author-centric strategy where the signing agent enables undoing of From: rewriting to restore original headers after message reception.",
  "n": 2,
  "nn": "Incremental solution addressing known DMARC/MLM interoperability issues with straightforward header restoration approach",
  "m": 3,
  "mn": "Defines a specific protocol mechanism for undoing MLM transformations with clear author-centric strategy",
  "o": 4,
  "on": "Significant overlap with existing DMARC mitigation techniques and MLM interoperability solutions in email standards",
  "mo": 2,
  "mon": "Single revision draft with no clear indication of working group adoption or broader community engagement",
  "r": 1,
  "rn": "Pure email protocol engineering focused on DMARC/MLM interoperability - not related to AI or autonomous agents",
  "c": ["Other AI/agent"]
}
```


VAIP defines a cryptographic identity protocol specifically for autonomous AI agents, addressing gaps in existing human-centric identity systems. The protocol provides verifiable identity, hierarchical permissions, trust scoring, and audit trails using Ed25519 signatures and SHA-256 hashing.

Notable originality in designing identity primitives specifically for AI agents rather than adapting human identity protocols

Defines core protocol mechanisms and permission structures but lacks implementation details and test vectors

Minor conceptual overlap with general identity protocols but unique focus on AI agent-specific requirements

Single draft with no indication of working group adoption or community feedback

Directly addresses core AI agent infrastructure needs for identity and authorization in autonomous systems

Agent identity/auth
Policy/governance
A2A protocols


This draft defines a BGP extended community to signal AS_PATH validation state based on ASPA within an autonomous system. It allows IBGP speakers to receive validation state information and use it in local policy decisions for routing.

Incremental extension adding signaling for existing ASPA validation - useful but straightforward application of known patterns

Defines the extended community format and basic usage but lacks detailed implementation examples and comprehensive error handling

Shares concepts with other BGP signaling extensions and ASPA-related drafts, building on established BGP extended community mechanisms

Recent draft but appears to be early single revision without clear working group adoption signals

This is purely about BGP routing protocol extensions for AS path validation - not related to AI or autonomous agents despite 'autonomous system' networking terminology


This draft defines requirements for gateways to support Dynamic Multi-agents Secured Collaboration (DMSC), focusing on scalability, communication efficiency, and security. It identifies gaps in current gateway solutions and proposes the need for specialized DMSC gateways.

Incremental work applying existing gateway concepts to multi-agent systems without novel architectural insights

Early requirements document without detailed technical specifications or concrete protocols

Shares gateway and multi-agent communication concepts with existing networking and distributed systems work

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

Directly addresses AI agent collaboration infrastructure, a core concern for multi-agent systems

A2A protocols
Agent identity/auth
Data formats/interop


AID defines a DNS-based discovery protocol for locating agent service endpoints using TXT records at _agent.<domain> subdomains. The protocol provides a minimal mechanism to discover agent URIs, protocols, and authentication hints before delegating to specialized protocols like MCP or A2A.

Incremental application of well-established DNS service discovery patterns to agent endpoints, similar to existing SRV/TXT record approaches

Detailed specification with clear record format, discovery algorithm, security requirements, and IANA registrations ready for implementation

Shares DNS-based discovery concepts with general service discovery mechanisms, but agent-specific application has limited direct overlap

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

Directly addresses agent infrastructure needs for service discovery, essential for agent ecosystem interoperability and deployment

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


ADRP defines a dispute resolution protocol for agent-to-agent transactions, separating cryptographic proof validation from contractual satisfaction through arbitration mandates. It introduces counter-attestation overrides and legally-grounded arbitration mechanisms for contested AI agent transactions.

Novel separation of cryptographic proof from contractual satisfaction in agent commerce, introducing arbitration mandates as fourth element of mandate chain

Detailed protocol specification with state machines, legal grounding via FAA Section 2, and comprehensive dispute classification framework

Unique approach to agent transaction disputes - no existing IETF work addresses cryptographic attestation vs contractual satisfaction bifurcation

Active development with companion specifications co-submitted, but no clear WG adoption path or broader community engagement yet

Core AI agent topic addressing fundamental challenge of autonomous transaction disputes with practical legal and technical framework

A2A protocols
Policy/governance
Agent identity/auth


This draft specifies an X.509 certificate-based identity verification extension for the Agent Transfer Protocol (AGTP), enabling infrastructure components to cryptographically verify agent identities and authority scopes at the transport layer. The extension includes session revocation mechanisms and Certificate Transparency logging for tamper-evident governance.

Useful contribution applying established PKI mechanisms to agent identity verification, with practical O(1) verification and governance features

Detailed specification with certificate extensions, revocation propagation, and CT logging mechanisms clearly defined

While PKI and mutual TLS are well-established, the specific application to agent identity verification and AGTP integration shows minor similarities to existing work

Future-dated draft (2026) with no visible development history or working group activity, appears to be initial proposal

Core AI agent infrastructure topic addressing fundamental identity and authentication challenges for autonomous agent communication

Agent identity/auth
A2A protocols
Policy/governance


This draft specifies a JSON-based AI Manifest protocol for websites to provide step-by-step UI workflow instructions to autonomous AI agents, enabling direct browser automation via CSS selectors. The specification includes three embedding methods, SHA-256 verification via a central trust registry, and reports an 81.9% reduction in input tokens with improved task success rates.

Notable originality in creating a standardized manifest format specifically for AI agent browser automation, with the AFRM three-part model (frameworkHints, knownTraps, shortcuts) showing thoughtful design based on real-world practitioner needs.

Active development evident from multiple revisions (-01 update) with substantive improvements based on empirical findings, though no clear indication of working group adoption or broader community engagement.

Minor similarities to general web API documentation formats and robot.txt concepts, but the AI-specific workflow instruction approach and browser automation focus is largely unique.

Core AI agent topic addressing fundamental challenges of web automation, token efficiency, and autonomous task execution - directly relevant to the future of AI agent interactions with web interfaces.

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


ATP defines a comprehensive communication protocol for autonomous agents operating across different deployment scales, featuring DNS-based discovery, mandatory authentication, and server-mediated routing. The protocol supports multiple interaction patterns including messaging, request/response, and event streaming for an Internet of Agents paradigm.

Notable originality in defining a complete agent communication stack with scale-aware architecture and integrated discovery/auth mechanisms

Detailed specification with comprehensive protocol definition, authentication framework, and message semantics across 57 pages

Minor similarities to existing messaging protocols but unique focus on autonomous agent communication at Internet scale

Single revision with future date suggests early proposal without established community engagement

Core AI agent topic addressing fundamental infrastructure for autonomous agent communication and Internet of Agents

A2A protocols
Agent identity/auth
Agent discovery/reg


```json
{
  "s": "This draft defines execution outcome verification as a new attestation primitive, introducing execution receipts to verify that AI agents and automated systems actually performed claimed actions with verifiable outcomes. It provides an abstract model and concrete mappings to transparency logs, TEE receipts, and other verification mechanisms.",
  "n": 4,
  "nn": "Notable originality in separating execution outcome verification from identity attestation as first-class concepts, with composable receipt primitives",
  "m": 3,
  "mn": "Defines protocol concepts and abstract model with concrete realizations, but likely needs more implementation details",
  "o": 2,
  "on": "Some conceptual overlap with general attestation frameworks but distinct focus on execution outcomes rather than identity",
  "mo": 2,
  "mon": "Single revision from April 2026, too early to assess broader momentum",
  "r": 5,
  "rn": "Core AI agent topic addressing fundamental trust and verification needs for autonomous system actions",
  "c": ["Agent identity/auth", "AI safety/alignment"]
}
```


This IETF draft defines a WIMSE profile for transitive attestation that cryptographically binds software workloads to their execution environment to prevent identity theft. It specifically addresses risks from AI agents moving across jurisdictions or being compromised through prompt injection attacks.

Notable originality in addressing AI agent identity portability risks through transitive attestation chains - combines existing concepts in a novel way for emerging AI agent threats

Defines a clear protocol mechanism with cryptographic binding approach, though lacks detailed implementation specifics and test vectors

Shares attestation concepts with RATS framework and references related WIMSE geofencing profile, but applies them distinctively to workload identity portability

Part of active WIMSE working group with clear references to companion drafts, indicating coordinated development effort

Core AI agent topic - directly addresses autonomous AI agents, prompt injection attacks, and cross-jurisdictional movement challenges with concrete technical solutions

Agent identity/auth
AI safety/alignment
Policy/governance


This draft extends OAuth Transaction Tokens to support agent context propagation by using the 'act' field to identify the agent performing actions while the 'sub' field represents the principal. It enables more granular access control decisions for agent-based workloads within service call graphs.

Incremental extension applying existing OAuth transaction token patterns to agent scenarios

Defines clear protocol mechanism with field usage but lacks detailed examples and implementation guidance

Significant overlap with base OAuth transaction tokens specification, primarily adding agent-specific field semantics

Active development as evidenced by 2026 date, but momentum unclear without revision history

Directly addresses agent authentication and authorization, core concerns for AI agent deployments


This draft addresses trust and security considerations for structured email, providing recommendations for how email clients should handle structured data elements. It focuses on preventing abuse and ensuring secure processing of machine-readable email content.

Incremental security guidance for existing structured email concepts

Early sketch stage with basic recommendations, lacks detailed implementation guidance

Shares security framework concepts with other email security drafts

Active working group development with clear community engagement

Tangentially related - focuses on email security rather than AI agents specifically


```json
{
  "s": "This draft proposes methods for specializing generative AI models to create targeted solutions for Intent-Based Networking applications. It aims to provide a scalable and efficient approach to developing AI models that can understand and process network intents.",
  "n": 3,
  "nn": "Useful contribution combining two established fields (generative AI and IBN) in a practical way, though the core concept is somewhat predictable given current AI trends",
  "m": 2,
  "mn": "Early sketch stage - describes general approach for AI model specialization but lacks detailed protocols, specific mechanisms, or concrete implementation guidance",
  "o": 3,
  "on": "Shares conceptual overlap with existing IBN work and general AI networking drafts, but the specific focus on generative AI specialization is reasonably distinct",
  "mo": 2,
  "mon": "Single revision with future date (2026) suggests early/speculative work with limited development activity to date",
  "r": 4,
  "rn": "Directly relevant to AI agents in networking - addresses how to create specialized AI models for network intent processing and automation",
  "c": ["Autonomous netops", "Model serving/inference", "ML traffic mgmt"]
}
```


Proposes an Internet-scale architecture called Agentic Intent Network (AIN) for enabling autonomous AI agents to discover and coordinate with each other across organizational boundaries without pre-established integrations. The draft presents architectural requirements and components for routing-based agent coordination but explicitly excludes engineering protocol details.

Notable originality in applying Internet-scale routing principles to multi-agent coordination, addressing the fundamental challenge of agent discovery and invocation across organizational boundaries

Early architectural sketch with high-level requirements and components defined, but lacks concrete protocol mechanisms, detailed specifications, or implementation guidance

Some conceptual similarities to service discovery and overlay networks, but the specific application to AI agent coordination represents a distinct approach

Appears to be initial submission with no indication of working group adoption or broader community engagement beyond NMRG research context

Directly addresses core AI agent coordination challenges at Internet scale, representing a fundamental networking problem for the AI agent ecosystem

A2A protocols
Agent discovery/reg
Data formats/interop


This draft defines the environment.* constraint family for Verifiable Intent mandates, enabling autonomous agents to check external conditions (venue status, fund availability, etc.) before executing transactions on behalf of humans. It provides the framework and vocabulary for environmental constraints but doesn't define specific constraint types.

The concept of cryptographically binding environmental state constraints to autonomous agent mandates is notably original, bridging smart contract conditions with real-world state verification

Future-dated draft (2026) suggests early/conceptual stage with limited current activity or community engagement

While smart contracts have conditional execution, this specific approach to environmental state verification in agent mandates appears relatively unique

Directly addresses core autonomous agent functionality - how agents verify external conditions before acting on human behalf with cryptographic authorization

A2A protocols
Agent identity/auth
Data formats/interop
Human-agent interaction


CAMP proposes a consistency-aware multipath transport protocol built on MPQUIC to address latency and synchronization challenges in interactive multimodal LLM systems like digital humans. It introduces three-stream separation for different modalities, a transport-layer scheduler to reduce inter-modal arrival time deviations, and client-side alignment mechanisms.

Novel combination of multipath transport with multimodal consistency guarantees specifically for LLM systems, introducing coordinated transport and application layer mechanisms

Defines protocol architecture and key mechanisms but lacks detailed implementation specifications and test vectors for full deployment readiness

Builds on MPQUIC but addresses a distinct problem space of multimodal consistency with minimal overlap to existing transport work

Recent draft from emerging area but no clear indication of working group adoption or broader community engagement yet

Directly addresses transport requirements for interactive AI systems, specifically targeting LLM-based applications with multimodal outputs

ML traffic mgmt
Model serving/inference
Human-agent interaction


This draft explores applying the Agent-to-Agent (A2A) Protocol for communication between Controller Agents and Device Agents in network management, enabling network devices to become autonomous entities. It discusses workflows, deployment scenarios, and integration with existing protocols like NETCONF and RESTCONF.

Useful application of A2A protocols to network management domain with specific focus on device-level agents

Early sketch focusing on applicability without detailed protocol specifications or implementation details

Shares concepts with existing A2A protocol work and network management automation drafts

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

Core AI agent topic focusing specifically on agent-to-agent communication protocols for autonomous network operations

A2A protocols
Autonomous netops
Data formats/interop


This draft proposes Trusted Path Routing to route sensitive traffic only through network devices that have been recently verified as trustworthy through attestation. It addresses scenarios where encryption alone is deemed insufficient and requires additional assurance about the integrity of transit infrastructure.

Useful contribution combining network routing with device attestation, though builds on existing RATS framework concepts

Detailed specification with concrete mechanisms for attestation-based routing decisions and path selection algorithms

Shares attestation concepts with RATS working group drafts but applies them uniquely to routing decisions

Single revision draft with limited visible community engagement or working group adoption

Tangentially related to AI through potential application to protecting AI traffic, but primarily a network security mechanism


VIRP defines a cryptographic trust framework for verifying operations performed by human or autonomous agents on live network infrastructure. It provides seven trust primitives including observation integrity, intent gating, and outcome verification with formal protocol analysis and multi-vendor implementation results.

Novel cryptographic dual-signature scheme and trust tier architecture specifically designed for autonomous network operations

Complete specification with live multi-vendor implementation, formal verification in ProVerif/Tamarin, and detailed test results

Some conceptual overlap with general infrastructure security protocols but unique focus on autonomous agent operations

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

Directly addresses core challenge of trusting autonomous agents operating on critical network infrastructure

Autonomous netops
Agent identity/auth
AI safety/alignment


This draft identifies use cases for high-performance wide area networks driven by big data and AI computing demands. It appears to be a problem statement document cataloging network performance requirements for emerging AI/ML applications.

Basic enumeration of known requirements for AI/ML network performance - no novel technical insights

Early stage use case collection without detailed technical specifications or solutions

Significant overlap with existing network optimization and SDN work, plus general AI networking requirements

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

Partially relevant as it addresses networking for AI/ML workloads but focuses on infrastructure rather than agent protocols


Delta-1 defines a SCITT profile for generating binary accountability receipts that prove AI agent decisions met three specific conditions: evidence sealing, strategic intent isolation, and authorized settlement recording. The profile targets regulated industries needing verifiable AI decision audit trails with offline verification capabilities.

Notable application of SCITT framework to AI accountability with specific three-condition model and binary settlement approach - creative adaptation of supply chain integrity concepts to AI decision verification

Defines clear protocol mechanics with three accountability conditions and binary verdict model, though lacks implementation details and test vectors for production deployment

Builds on SCITT framework but applies it uniquely to AI decision accountability - minimal overlap with existing AI agent specifications in IETF

Single draft publication with no evident working group adoption or community discussion - appears to be individual contribution without broader momentum

Directly addresses AI agent accountability and decision verification, which are core concerns for agentic AI deployment in regulated environments

Policy/governance
Agent identity/auth
Data formats/interop


This draft specifies agent identity management for Internet of Agents (IOA) systems, defining requirements for agent identities, registration processes, identifier structures, and identity management functions performed by agent gateways. It appears to be an early framework for managing autonomous agent identities in networked environments.

Useful contribution addressing agent identity in networked systems, though identity management concepts are well-established in other domains

Early sketch with basic framework defined but lacks detailed protocol specifications, implementation details, or concrete examples

Shares general identity management concepts with existing work but applies them specifically to agent systems

Single draft submission with no evidence of working group activity or community engagement

Core AI agent topic directly addressing fundamental identity and authentication needs for autonomous agent systems

Agent identity/auth
Agent discovery/reg
A2A protocols


N-ACT defines a standardized protocol for AI agents to discover and invoke third-party tools through enumeration and invocation APIs. The goal is to reduce integration costs for enterprise AI agents needing to use external APIs.

Incremental work applying existing API design patterns to AI agent tool integration - straightforward but useful standardization effort

Defines core protocol components (enumeration and invocation APIs) with clear problem statement, though lacks detailed implementation specifics

Shares conceptual ground with OpenAI function calling specs and general API gateway patterns, but focuses specifically on AI agent use cases

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

Directly addresses a practical need in AI agent deployments - tool integration is a core challenge for enterprise AI systems


Proposes a decentralized RPKI repository architecture (dRR) that separates signing authority from object management through distributed certificate servers and monitors. Addresses current RPKI limitations around single points of failure, scalability, and consistency while maintaining compatibility with existing trust models.

Useful contribution applying decentralization concepts to RPKI infrastructure challenges, though builds on established distributed systems principles

Defines the architectural components and approach but appears to lack detailed protocol specifications and implementation guidance

Minor similarities to other distributed trust infrastructure proposals but addresses specific RPKI repository concerns

Recent draft with limited revision history, unclear working group status or community engagement

Focuses on RPKI infrastructure security and reliability, not related to AI or autonomous agents


This draft specifies security requirements for intent-based agent routing, defining a security architecture with phase-specific attack analysis for Registration, Resolution, and Dispatch phases. It addresses new security risks beyond traditional channel protection when autonomous agents collaborate based on semantic intent rather than static addresses.

Notable originality in addressing semantic intent security risks that go beyond traditional transport-layer protections

Defines security architecture and requirements framework but appears to be at requirements specification rather than detailed implementation level

Minor overlap with general agent security work but unique focus on intent-based routing security

Single revision with April 2026 date suggests early stage work

Core AI agent topic addressing fundamental security challenges in autonomous agent collaboration and routing

A2A protocols
AI safety/alignment
Agent identity/auth
Agent discovery/reg


This draft analyzes how AI agents impact network infrastructure to support IETF standardization discussions. It appears to be an early analysis document examining the networking implications of AI agent deployment and communication.

Incremental analysis of known AI agent networking challenges

Problem statement level with basic analysis, lacks concrete protocols or mechanisms

Shares general concepts with other AI networking drafts but focuses specifically on infrastructure impact

Single early draft with basic scope, unclear community engagement

Directly addresses AI agent networking infrastructure needs, highly relevant to IETF AI standardization

Autonomous netops
A2A protocols
ML traffic mgmt


This draft proposes a hardware-rooted cryptographic framework for verifying workload location and integrity using zero-knowledge proofs to ensure privacy. It establishes a 'Silicon-to-Workload' chain of trust that binds software identities to persistent hardware identities and verified geographic residency.

Notable combination of hardware attestation, zero-knowledge proofs, and geographic verification for workload identity - creative approach to sovereignty requirements

Early conceptual stage with high-level architecture described but lacking detailed protocol specifications, message formats, or implementation guidance

Some conceptual overlap with hardware attestation and identity work, but the privacy-preserving geofencing approach appears relatively unique

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

Directly addresses workload identity management for AI/ML systems with focus on sovereign computing requirements and hardware-backed trust


AgentCard defines a JSON format for autonomous software agents to declare their identity, capabilities, and communication details in a framework-neutral way. It enables interoperability between agents built with different frameworks like LangChain, CrewAI, or AutoGen without prior coordination.

Notable originality in creating a framework-neutral identity format with physics-grounded energy pricing and ULID-based global identity

Detailed specification with comprehensive schema elements, pricing mechanisms, and clear integration patterns

Minor similarities to general service discovery formats but unique approach to agent-specific identity and capability declaration

Single revision from 2026 with no apparent working group adoption or community momentum indicators

Core AI agent topic addressing fundamental interoperability challenges in multi-agent systems

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


This draft examines the potential impact on end users of standardizing AI preference signaling mechanisms, focusing on technological, legal, ethical, and governance dimensions. It aims to provide principles for the ai-pref working group to consider when developing vocabulary and definitions for AI preference signaling standards.

Incremental contribution focusing on end-user impact analysis of AI preference signaling, which is a useful but not particularly novel perspective on an emerging standardization area

Early sketch providing impact analysis and suggested principles but lacking concrete protocol mechanisms, detailed specifications, or implementation guidance

Shares conceptual space with other AI preference and signaling drafts, particularly around user control and data privacy, but focuses specifically on end-user impact analysis

Recent draft (2025-11-27) addressing an active area of IETF interest with the ai-pref working group, showing ongoing development in AI preference signaling standardization

Directly relevant to AI agent systems as it addresses how users interact with and control AI systems through preference signaling mechanisms, focusing on user agency and control

Policy/governance
Human-agent interaction
Data formats/interop


This draft proposes integrating the Model Context Protocol (MCP) into network management to enable AI agents to interact with network infrastructure through standardized, secure interfaces. It presents problem statements, use cases for troubleshooting and optimization, and requirements for MCP-based network management architectures.

Useful contribution applying MCP to network management domain, though MCP itself is established

Early stage problem statement and requirements document without detailed protocol specifications

Minor conceptual overlap with general network automation but unique focus on MCP integration

Single revision draft with no clear working group adoption signals

Directly relevant to AI agents in networking with concrete use cases and architectural considerations

Autonomous netops
A2A protocols
Data formats/interop


This draft extends EDHOC protocol with post-quantum cryptography mechanisms, specifically adding KEM-based authentication to provide quantum resistance. It defines signature-free authentication methods using standardized post-quantum KEMs like ML-KEM.

Useful contribution applying established PQC concepts to EDHOC authentication, though the core idea of KEM-based auth is known

Detailed specification with concrete protocol extensions, message formats, and integration with existing EDHOC framework

Shares PQC integration concepts with other quantum-resistant protocol extensions but specific to EDHOC authentication

Active development with specific focus on standardizing PQC in authentication protocols

Security protocol enhancement rather than AI/agent-focused, only tangentially related through potential use in agent authentication


This draft defines a framework for intercommunication between Agent Gateways in an Agent Internet ecosystem, specifying hierarchical layered models and protocol requirements. It aims to enable cross-domain agent collaboration through standardized gateway interoperability mechanisms.

Useful contribution to agent internetworking - builds on IoA concepts but focuses specifically on gateway intercommunication patterns

Early framework sketch - defines high-level architecture and requirements but lacks detailed protocol specifications or implementation guidance

Significant conceptual overlap with existing IoA reference architectures and general gateway interoperability frameworks

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

Directly relevant to AI agent networking - addresses core challenges of cross-domain agent communication and collaboration

A2A protocols
Data formats/interop
Agent discovery/reg


This draft defines a management architecture for Delay-Tolerant Networks (DTN) that operates asynchronously without query-response mechanisms, designed for challenged environments with long delays and frequent disruptions. The architecture supports autonomous local control with minimal resource footprint for constrained devices operating over the Bundle Protocol.

Useful contribution adapting network management principles to DTN's unique constraints, though builds on established DTN and network management concepts

Detailed 59-page specification with comprehensive architecture definition, appears implementation-ready with thorough treatment of DTN management challenges

Some conceptual overlap with general network management architectures but DTN-specific approach is fairly unique

IETF working group draft suggesting active development and community interest in DTN management standardization

Partially relevant due to autonomous local control aspects and asynchronous operation, though primarily focused on network management rather than AI agents


ANML defines a machine-first markup language for agent-to-agent communication, providing structured formats for content, interactions, constraints, and behavioral guidance. The 80-page specification offers both XML and JSON serializations to enable deterministic agent interactions with reduced reliance on unstructured data inference.

Novel approach to standardizing agent communication with comprehensive framework including persona, constraints, and state management - goes beyond simple API definitions

Detailed 80-page specification with dual serialization formats, abstract data model, and comprehensive feature set suggests implementation-ready maturity

While agent communication exists, the holistic approach combining content, interactions, knowledge, constraints, state, and persona appears relatively unique

Recent 2026 date suggests active development, though single draft snapshot limits momentum assessment

Core AI agent topic addressing fundamental challenge of standardized agent-to-agent communication protocols

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


This draft extends OAuth 2.0 scopes with structured syntax to enable fine-grained authorization for AI agent capabilities and modular functional units. It proposes a colon-separated format [resource_type]:[action]:[target][:constraints] to standardize permission requests for agent operations like file access, network access, and tool invocation.

Notable originality in applying structured OAuth scopes specifically to agent capability authorization - addresses a real gap in current agent security models

Defines clear protocol extension with syntax specification, though lacks detailed examples and implementation guidance

Minor similarities to general OAuth extension work, but the agent-specific capability authorization approach is relatively unique

Appears to be early stage work without clear working group adoption or community feedback

Directly addresses core AI agent security concerns around capability authorization and permission management

Agent identity/auth
Policy/governance
AI safety/alignment


This draft proposes an 'AI Agent Policy-Aware Network' paradigm that enables network infrastructure to understand and respond to AI agent intents rather than just traffic flows. It defines components like Agent Policy-aware Controllers to create dynamic mappings between agent policies and network configurations for scenarios like autonomous performance measurement and path optimization.

Useful contribution applying intent-based networking concepts to AI agents, though builds on established policy-aware networking principles

Early sketch defining high-level components and use cases but lacking detailed protocols, mechanisms, or concrete specifications

Shares concepts with intent-based networking and policy-aware systems, but specific application to AI agents is distinct

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

Directly relevant to AI agents in networking, addressing how network infrastructure can become agent-aware and policy-driven

Autonomous netops
Policy/governance
ML traffic mgmt


This draft identifies problems with current LLM-based multi-agent systems where each agent must independently handle communication, security, and collaboration logic, leading to inefficiency and security risks. It proposes requirements for a centralized DMSC infrastructure to offload these common functions and enable better scalability in multi-tenant environments.

Centralizing multi-agent infrastructure functions is a logical evolution but represents a useful architectural contribution to the space

Pure problem statement document without defined protocols, mechanisms, or technical specifications

Shares architectural concepts with service mesh and API gateway approaches, though applied specifically to AI agents

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

Directly addresses core challenges in multi-agent AI systems including communication, security, and collaboration coordination

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


This draft proposes DNS-Native Agent Naming and Resolution (DN-ANR) to use FQDNs as stable identifiers for AI agents and resolve them to verifiable endpoints with cryptographic integrity. It focuses on minimal pointer capabilities while avoiding heavy semantic metadata in DNS.

Useful contribution applying established DNS patterns to AI agent identification - not groundbreaking but addresses a clear need

Detailed specification with clear protocol mechanisms and examples, appears implementation-ready

Minor similarities to general service discovery mechanisms but specific application to AI agents is relatively unique

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

Directly addresses AI agent infrastructure needs for naming, discovery and verification - core to agent ecosystem development


This draft defines authentication message formats and protocols for the Drone Remote Identification Protocol (DRIP) to enable real-time verification of drone broadcast messages. It specifies cryptographic mechanisms to authenticate that Remote ID messages were signed by registered drone operators, supporting offline verification by observers without Internet access.

Incremental extension applying standard cryptographic authentication to drone identification - useful but builds on established patterns

Detailed 48-page specification with defined message formats, authentication protocols, and specific implementation guidance

Shares authentication and identity verification concepts with other Remote ID and aircraft identification standards

Active IETF working group draft with recent updates, indicating sustained development effort

Partially relevant as it addresses autonomous system identity and authentication, though focused on drones rather than AI agents broadly


Defines Agent Attachment Protocol (AAP) for AI agents to establish connections to edge nodes and obtain communication properties like identifiers and attachment context. Focuses on maintaining attachment state and representing properties for use by forwarding functions and routing mechanisms.

Useful contribution addressing the specific problem of agent-to-infrastructure attachment, though builds on familiar networking attachment concepts

Appears to define a complete protocol mechanism with attachment procedures and property representation, though lacks implementation details

Shares networking attachment concepts with existing protocols but applies them specifically to AI agents in edge computing contexts

Single draft from individual author with no clear working group activity or community engagement indicated

Directly addresses AI agent networking needs with focus on attachment protocols and communication mechanisms for agent infrastructure

A2A protocols
Agent discovery/reg
Agent identity/auth


```json
{
  "s": "Extends OAuth 2.0 Rich Authorization Requests to allow clients (like AI agents) to request AS-attested user certificates within access tokens. Enables resource servers to obtain trusted user public keys for verifying delegation evidence signed by users.",
  "n": 3,
  "nn": "Useful contribution combining OAuth RAR with certificate attestation for delegation scenarios, particularly relevant for AI agents needing verified user authority",
  "m": 2,
  "mn": "Early sketch stage - introduces concept and basic mechanism but lacks detailed protocol specification, examples, and implementation details",
  "o": 3,
  "on": "Shares concepts with OAuth extensions and certificate-based authentication drafts, but specific combination for AI agent delegation appears less common",
  "mo": 2,
  "mon": "Single revision draft with 2026 date suggests recent submission but no visible working group adoption or community engagement yet",
  "r": 4,
  "rn": "Directly addresses AI agent authentication and authorization needs, specifically tackling how agents can obtain verifiable user delegation authority",
  "c": ["Agent identity/auth", "A2A protocols"]
}
```


This draft defines an OpenID Connect profile for issuing identity tokens to autonomous AI agents, introducing standard claims for agent identity, ownership, capabilities, and trust levels. It enables existing OIDC infrastructure to authenticate and authorize AI agents without core protocol modifications.

Useful adaptation of existing identity standards to AI agents, though the core concept of extending OIDC for non-human entities is not entirely novel

At 2 pages, this appears to be an early sketch outlining the concept rather than a detailed specification with implementation guidance

Some conceptual overlap with general identity federation work, but the specific focus on AI agent identity claims appears relatively unique

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

Directly addresses a core challenge in AI agent deployment - establishing trusted identity and authentication mechanisms for autonomous systems


Proposes a high-speed data express architecture for IP networks to support massive data transmission for AI and supercomputing applications. Introduces a 'one low and three high' technical system for differentiated data express services.

Incremental approach applying existing IP network optimization concepts to AI data transmission needs

Early sketch with high-level architecture and concepts but lacks detailed protocol specifications or implementation details

Shares general concepts with existing high-speed networking and QoS drafts, though specific focus on AI data express is somewhat distinct

Appears to be initial draft with no visible community engagement or working group activity

Partially relevant as it addresses infrastructure needs for AI applications, though not directly about AI agents themselves


RMRP defines a protocol for routing AI inference requests across multiple models with policy governance and audit trails. It provides vendor-agnostic framework for managing routing decisions, cost attribution, and compliance in multi-model AI deployments.

First comprehensive protocol specifically addressing AI model routing with policy governance - novel intersection of network routing concepts with AI infrastructure management

At 37 pages with detailed metadata structures, routing policies, execution semantics, and audit requirements - appears to be a well-developed specification

Some conceptual overlap with general routing protocols and service mesh concepts, but AI model routing with policy governance is largely unexplored territory

Future-dated draft (2026) suggests speculative work without current community development or validation

Directly addresses core AI infrastructure challenge of managing requests across multiple models with governance requirements - highly relevant to AI agent ecosystems

ML traffic mgmt
Policy/governance
Model serving/inference
Data formats/interop


Defines an architectural model for human-anchored agent identity that establishes delegation semantics and provenance structures to ensure agents can be traced back to responsible humans. The framework addresses the critical problem of accountability in autonomous agent systems without defining specific protocols.

Notable originality in proposing human identity roots and explicit delegation chains for agent accountability - addresses a gap not well covered by existing identity frameworks

Early architectural sketch that defines concepts and models but lacks concrete protocols, wire formats, or implementation details

Minor similarities to general identity and delegation frameworks, but the human-anchored agent focus is relatively unique in IETF space

Single revision with future date suggests early stage work - unclear if there's working group interest or broader community engagement

Core AI agent topic addressing fundamental challenges of accountability, delegation, and provenance in autonomous agent ecosystems

Agent identity/auth
AI safety/alignment
Human-agent interaction
Policy/governance


This April 1st RFC draft humorously proposes cryptographic identity and provenance attestation for AI agents communicating via carrier pigeons, extending the classic RFC 1149 IP over Avian Carriers joke. It addresses delegation chains and hallucination propagation across 'feather-based transport layers' with tongue-in-cheek technical rigor.

Genuinely creative fusion of AI agent identity concepts with the classic avian carrier RFCs - unprecedented technical humor territory

April 1st publication with no real development momentum expected or intended

Completely unique approach combining agent identity with avian carriers - no other work remotely similar

Partially relevant as it does address real AI agent concepts like delegation chains and provenance, albeit in humorous context


This draft proposes a vocabulary for three categories of content signals that enable parties to express preferences about how their digital assets are used by automated processing systems. It extends the AIPREF-VOCAB framework to provide granular control over AI system interactions with content.

Incremental extension of existing AIPREF vocabulary work, categorizing content signals in a straightforward manner

Early sketch level - only 5 pages describing categories without detailed mechanisms, examples, or implementation guidance

Significant overlap with existing AIPREF-VOCAB work and other content preference/rights expression efforts

Single revision with October 2025 date suggests minimal development activity so far

Directly relevant to AI systems as it addresses how content owners can signal usage preferences to automated processing systems


This draft proposes using LISP (Locator/Identifier Separation Protocol) as a unified control plane for AI infrastructure networks, enabling scale-up, scale-out, and scale-across deployment patterns. It leverages existing LISP mechanisms like EID-to-RLOC mapping and VPN segmentation to provide scalable bandwidth and low-latency operations for AI training and inference workloads across heterogeneous accelerator fabrics.

Incremental application of existing LISP protocol to AI infrastructure use case

Defines mechanisms and architecture but lacks detailed implementation specifics

Shares networking concepts with other AI infrastructure drafts but takes distinct LISP-based approach

Single revision, unclear WG interest or community engagement

Partially relevant - focuses on network infrastructure for AI rather than AI agents themselves


Proposes a framework for distributed AI data center networks to enable lossless interconnection between multiple data centers for large-scale model training. Focuses on networking challenges for connecting geographically distributed data centers into unified AI training clusters.

Incremental approach applying existing lossless networking concepts to AI data center interconnection without significant technical innovation

Early framework sketch with high-level concepts but lacks detailed protocols, mechanisms, or implementation specifics

Shares networking concepts with existing data center interconnect work but applies them specifically to AI workloads

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

Directly addresses AI infrastructure networking needs for distributed training, which is highly relevant to AI systems