# gaps

topic: Agent Resource Management
category: autonomous netops
severity: critical
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
No comprehensive framework for managing computational resources, memory, and processing power across distributed AI agents. Current drafts focus on communication but ignore how agents compete for and share limited resources in multi-agent environments.

evidence:
Real deployments will face resource contention, but no drafts address scheduling, quotas, or fair allocation mechanisms


topic: Cross-Protocol Translation
category: A2A protocols
evidence: Multiple competing A2A protocols with no interoperability framework suggests fragmentation problem
severity: high
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
With 92 A2A protocol drafts and high overlap, there's no standard way for agents using different communication protocols to interoperate. Missing universal translation layer or protocol negotiation mechanism.


topic: Agent Behavior Verification
category: AI safety/alignment
severity: critical
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
No mechanisms to verify that deployed agents actually behave according to their declared policies or specifications. Gap between stated capabilities and runtime behavior validation.

evidence:
Only 36 safety drafts vs 260 total, and no mention of runtime behavior verification in technical ideas


topic: Agent Lifecycle Management
category: agent discovery/reg
evidence: Registration covered but no mention of versioning, updates, or graceful shutdown procedures
severity: high
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
Missing standards for agent deployment, versioning, updates, and retirement. No clear protocols for how agents evolve or get replaced without disrupting dependent services.


topic: Multi-Agent Consensus Mechanisms
category: A2A protocols
evidence: Autonomous netops requires coordination but no consensus mechanisms appear in technical ideas list
severity: high
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
No frameworks for how groups of AI agents reach consensus on conflicting decisions or priorities. Critical for autonomous systems that must coordinate without human intervention.


topic: Agent Error Recovery and Rollback
category: autonomous netops
evidence: Autonomous operations imply unsupervised decisions, but no error recovery mechanisms identified
severity: critical
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
Missing standards for how agents handle and recover from errors, particularly cascading failures across agent networks. No rollback mechanisms for autonomous decisions gone wrong.


topic: Human Override and Intervention
category: human-agent interaction
severity: high
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
Only 22 human-agent interaction drafts but no clear emergency override protocols. Missing standardized ways for humans to intervene in autonomous agent operations during critical situations.

evidence:
Disproportionately low human interaction focus (22 drafts) compared to autonomous operations (60 drafts)


topic: Agent Performance Monitoring
category: autonomous netops
evidence: ML traffic management only has 24 drafts but no performance monitoring in technical ideas
severity: medium
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
No standardized metrics or monitoring frameworks for tracking agent performance, efficiency, or drift over time. Missing observability standards for production agent deployments.


topic: Cross-Domain Security Boundaries
category: agent identity/auth
evidence: Cross-domain identity mentioned but no corresponding security boundary enforcement mechanisms
severity: high
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
While identity management exists, missing frameworks for agents operating across security domains with different trust levels. No clear isolation or privilege escalation prevention.


topic: Agent Explainability Standards
category: AI safety/alignment
evidence: Low safety/alignment focus suggests governance requirements not fully addressed
severity: medium
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
No protocols for agents to explain their decisions or reasoning to other agents or humans. Critical gap for debugging and compliance in regulated environments.


topic: Dynamic Trust and Reputation
category: agent identity/auth
evidence: Certificate authorities mentioned but no dynamic trust or reputation systems in technical ideas
severity: high
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
Missing frameworks for agents to build, assess, and revoke trust relationships dynamically based on behavior history. Static authentication insufficient for long-running autonomous systems.


topic: Agent Data Provenance
category: data formats/interop
evidence: 102 data format drafts but no provenance tracking mechanisms identified in technical ideas
severity: medium
analyzed_at: 2026-02-28T12:14:44.583764+00:00
description:
No standards for tracking data lineage and provenance as information flows between agents. Critical for compliance and debugging in complex agent networks.


