Observability for Delegated Execution in Agentic AI Systems

2026-06-08

AI Summary

This work addresses the challenge that standard observability data in large language model agent systems often fails to distinguish execution traces across different delegation assignments, rendering cross-tool and cross-system delegation behaviors untraceable. To overcome this limitation, the paper proposes an agent-aware observability infrastructure that leverages a lightweight gateway and a unified information model to bind delegation context at runtime. This approach enables, for the first time, precise reconstruction of delegation scopes without relying on heuristic time windows. By supporting fine-grained behavioral forensics and direct forensic queries, the method significantly enhances observability and auditability of delegated executions in heterogeneous multi-agent systems.

Abstract

Delegation-scoped execution is not identifiable from standard observables: audit logs and execution traces can be identical under multiple incompatible delegation assignments. This gap is especially acute in LLM-based agentic systems, where agents dynamically select tools, vary execution sequences across runs for the same instruction, and spawn cooperating sub-agents. These dynamics fragment and interleave traces, making delegation-scoped reconstruction from causal structure alone structurally underdetermined. Although individual actions are authorized and logged, existing audit, tracing, and security schemas lack the semantics to reconstruct what actions occurred under a given delegation across heterogeneous systems. We focus on delegation-scoped attribution and access/share footprint reconstruction, not intent inference or reasoning reconstruction. We present an agent-aware observability substrate consisting of a lightweight gateway and a common information model that binds delegation context at execution time. This enables reliable cross-tool delegation-scoped reconstruction and direct forensic queries without heuristic time-window correlation.

Problem

• delegation-scoped execution
• observability
• agentic AI systems
• audit logs
• execution traces

Innovation

• delegation-scoped observability
• agentic AI systems
• execution tracing
• audit reconstruction
• context binding