The future where AI agents act on your infrastructure

In a future where AI agents act on your infrastructure, observing just logs or traces won’t cut it — you need to see both why and what at once.

AgentSight (Aug 2025) introduces a hybrid observability approach that marries high‑level agent intent (prompts, reasoning) with low‑level system behavior (kernel events) using eBPF and TLS tapping. arXiv Traditional toolsets show “the agent asked X” or “a process executed Y” — but not how those map to each other. With AgentSight, you can detect reasoning loops, spot prompt injection attempts, trace across agent boundaries, and debug coordination failures in multi‑agent systems. For platform engineering and SRE teams building agentic stacks on Kubernetes, this is a foundational leap: you can no longer treat agents as black boxes — you must instrument across the semantic boundary.

This maps exactly to how we think about observability at OpsWorker.ai: our goal is not just to trace infrastructure, but to connect agency and execution. AgentSight’s boundary tracing concept offers one key building block for that integration — the kind of transparency that turns agents into reliable partners, not mystery boxes.